Orthopedics

Total hip arthroplasty (THA) is a successful surgery with positive clinical outcomes and over 95% survivorship at 10-year follow-up and 80% survivorship at 25-year follow-up.^1,2 A hip replacement requires strong osteointegration^3,4 to prevent femoral osteolysis, and correct implant alignment has been shown to correlate with prolonged implant survivorship and reduced dislocation.^5,6 Robotics and computer-assisted navigation have been developed to increase the accuracy of implant placement and reduce outliers with the overall goal of improving long-term results. These technologies have shown significant improvements in implant positioning when compared to conventional techniques.⁷

The first active robotic system for use in orthopedic procedures, Robodoc (Think Surgical, Inc.), was based on a traditional computer-aided design/computer-aided manufacturing system. Currently, only 3 robotic systems for THA have clearance in the US: The Mako System (Stryker), Robodoc, and TSolution One (Think Surgical, Inc.). The TSolution One system is based on the legacy technology developed as Robodoc and currently provides assistance during preparation of the femoral canal as well as guidance and positioning assistance during acetabular cup reaming and implanting. The following is a summary of the author’s (DSD) preferred technique for robotic-assisted THA using TSolution One.

How It Works

The process begins with preoperative planning (Figure 1). A computed tomography (CT) scan is used to create a detailed 3-dimensional (3D) reconstruction of the patient’s pathologic hip anatomy. The CT scan images are uploaded to TPLAN, a preoperative planning station.

In TPLAN, the user creates a 3D template of the surgical plan for both the femoral and acetabular portions of the procedure. The system has an open platform, meaning that the user is not limited to a single implant design or manufacturer. The surgeon can control every aspect of implant positioning: rotation, anteversion, fit and fill on the femoral side and anteversion, inclination/lateral opening, and depth on the acetabular side. Additional features available to the surgeon include accurately defining bony deficits, identifying outlier implant sizes, and checking for excess native version. The system allows the surgeon to determine the native center of hip rotation, which can then be used during templating to give the patient a hip that feels natural because the native muscle tension is restored. Once the desired plan has been achieved, it is uploaded to the robot.The TCAT robot is an active system similar to those used in manufacturing assembly plants (eg, automobiles) in that it follows a predetermined path and can do so in an efficient manner. More specifically, once the user has defined the patient’s anatomy within its workspace, it will proceed with actively milling the femur as planned with sub-millimeter accuracy without the use of navigation. This is in contrast to a haptic system, where the user manually guides the robotic arm within a predefined boundary.

The acetabular portion of the procedure currently uses a standard reamer system and power tools, but the TCAT guides the surgeon to the planned cup orientation, which is maintained during reaming and impaction.

In the Operating Suite

Once in the operating suite, the plan is uploaded into TCAT. Confirmation of the plan and the patient are incorporated into the surgical “time out.” Currently, the system supports patient positioning in standard lateral decubitus using a posterior approach with a standard operating room table. A posterior approach is undertaken to expose and dislocate the hip, with retractors placed to protect the soft tissues and allow the robot its working space.

One procedural difference from the standard THA technique is that the femoral head is initially retained to fixate the femur relative to the robot. A 5-mm Schanz pin is placed in the femoral head and then rigidly attached to the base of the robot. During a process called registration, a series of points on the surface of the exposed bone are collected by the surgeon via a digitizer probe attached to the robot. The TCAT monitor will guide the surgeon through point collection using a map showing the patient’s 3D bone model generated from the CT scan. The software then “finds” the patient’s femur in space and matches it to the 3D CT plan. Milling begins with a burr spinning at 80,000 rpm and saline to irrigate and remove bone debris (Figure 2). The actual milling process takes 5 to 15 minutes, depending on the choice and size of the implant.

A bone motion monitor (BMM) is also attached to the femur, along with recovery markers (RM). The BMM immediately pauses the robot during any active bone milling if it senses femoral motion from the original position. The surgeon then touches the RM with the digitizer to re-register the bone’s position and resume the milling process.

Attention is then turned to the acetabular portion of the procedure. Again, the robot must be rigidly fixed to the patient’s pelvis, along with the RM. Once the surgeon has registered the acetabular position using the digitizer, the robotic arm moves into the preoperatively planned orientation. A universal quick-release allows the surgeon to attach a standard reamer to the robot arm and ream while the robot holds the reamer in place. Once the acetabular preparation is complete, the cup impactor is placed onto the robotic arm and the implant is impacted into the patient. Thereafter, the digitizer can be used to collect points on the surface of the cup and confirm the exact cup placement (Figure 3).

Outcomes

The legacy system, Robodoc, has been used in thousands of clinical cases for both THA and total knee arthroplasty. The Table represents a summary of the THA clinical studies during a time frame in which only the femoral portion of the procedure was available to surgeons.

Bargar and colleagues⁸ describe the first Robodoc clinical trial in the US, along with the first 900 THA procedures performed in Germany. In the US, researchers conducted a prospective, randomized control study with 65 robotic cases and 62 conventional control cases. In terms of functional outcomes, there were no differences between the 2 groups. The robot group had improved radiographic fit and component positioning but significantly increased surgical time and blood loss. There were no femoral fractures in the robot group but 3 cases in the control group. In Germany, they reported on 870 primary THAs and 30 revision THA cases. For the primary cases, Harris hip scores rose from 43.7 preoperatively to 91.5 postoperatively. Complication rates were similar to conventional techniques, except the robot cases had no intraoperative femoral fractures.

Several prospective randomized clinical studies compared use of the Robodoc system with a conventional technique. The group studied by Honl and colleagues⁹ included 61 robotic cases and 80 conventional cases. The robot group had significant improvements in limb-length equality and varus-valgus orientation of the stem. When the revision cases were excluded, the authors found the Harris hip scores, prosthetic alignment, and limb length differentials were better for the robotic group at both 6 and 12 months.

Nakamura and colleagues¹⁰ looked at 75 robotic cases and 71 conventional cases. The results showed that at 2 and 3 years postoperatively, the robotic group had better Japanese Orthopaedic Association (JOA) scores, but by 5 years postoperatively, the differences were no longer significant. The robotic group had a smaller range for leg length inequality (0-12 mm) compared to the conventional group (0-29 mm). The results also showed that at both 2 and 5 years postoperatively, there was more significant stress shielding of the proximal femur, suggesting greater bone loss in the conventional group.

Nishihara and colleagues¹¹ had 78 subjects in each of the robotic and conventional groups and found significantly better Merle d’Aubigné hip scores at 2 years postoperatively in the robotic group. The conventional group suffered 5 intraoperative fractures compared with none in the robotic group, along with greater estimated blood loss, an increased use of undersized stems, higher-than-expected vertical seating, and unexpected femoral anteversion. The robotic cases did, however, take 19 minutes longer than the conventional cases.

Hananouchi and colleagues¹² looked at periprosthetic bone remodeling in 31 robotic hips and 27 conventional hips to determine whether load was effectively transferred from implant to bone after using the Robodoc system to prepare the femoral canal. Using dual energy X-ray absorptiometry (DEXA) to measure bone density, they found significantly less bone loss in the proximal periprosthetic areas in the robotic group compared to the conventional group; however, there were no differences in the Merle d’Aubigné hip scores.

Lim and colleagues¹³ looked specifically at alignment accuracy and clinical outcomes specifically for short femoral stem implants. In a group of 24 robotic cases and 25 conventional cases, they found significantly improved stem alignment and leg length inequality and no differences in Harris Hip score, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score, or complications at 24 months.

In 2004, Nishihara and colleagues¹⁴ evaluated the accuracy of femoral canal preparation using postoperative CT images for 75 cases of THA performed with the original pin-based version of Robodoc. The results showed that the differences between the preoperative plan and the postoperative CT were <5% in terms of canal fill, <1 mm in gap, and <1° in mediolateral and anteroposterior alignment with no reported fractures or complications. They concluded that the Robodoc system resulted in a high degree of accuracy.

Schulz and colleagues¹⁵ reported on 97 of 143 consecutive cases performed from 1997 to 2002. Technical complications were described in 9 cases. Five of the reported complications included the BMM pausing cutting as designed for patient safety, which led to re-registration, and slightly prolonged surgery. The remaining 4 complications included 2 femoral shaft fissures requiring wire cerclage, 1 case of damage to the acetabular rim from the milling device, and 1 defect of the greater trochanter that was milled. In terms of clinical results, they found that the complications, functional outcomes, and radiographic outcomes were comparable to conventional techniques. The rate of femoral shaft fissures, which had been zero in all other studies with Robodoc, was comparable to conventional technique.

Conclusion

The most significant change in hip arthroplasty until now has been the transition from a cemented technique to a press-fit or ingrowth prosthesis.¹⁶ The first robotic surgery was performed in the US in 1992 using the legacy system upon which the current TSolution One was based. Since then, the use of surgical robots has seen a 30% increase annually over the last decade in a variety of surgical fields.¹⁷ In orthopedics, specifically THA, the results have shown that robotics clearly offers benefits in terms of accuracy, precision, and reproducibility. These benefits will likely translate into improved long-term outcomes and increased survivorship in future studies.

Total hip arthroplasty (THA) is a successful surgery with positive clinical outcomes and over 95% survivorship at 10-year follow-up and 80% survivorship at 25-year follow-up.^1,2 A hip replacement requires strong osteointegration^3,4 to prevent femoral osteolysis, and correct implant alignment has been shown to correlate with prolonged implant survivorship and reduced dislocation.^5,6 Robotics and computer-assisted navigation have been developed to increase the accuracy of implant placement and reduce outliers with the overall goal of improving long-term results. These technologies have shown significant improvements in implant positioning when compared to conventional techniques.⁷

The first active robotic system for use in orthopedic procedures, Robodoc (Think Surgical, Inc.), was based on a traditional computer-aided design/computer-aided manufacturing system. Currently, only 3 robotic systems for THA have clearance in the US: The Mako System (Stryker), Robodoc, and TSolution One (Think Surgical, Inc.). The TSolution One system is based on the legacy technology developed as Robodoc and currently provides assistance during preparation of the femoral canal as well as guidance and positioning assistance during acetabular cup reaming and implanting. The following is a summary of the author’s (DSD) preferred technique for robotic-assisted THA using TSolution One.

How It Works

The process begins with preoperative planning (Figure 1). A computed tomography (CT) scan is used to create a detailed 3-dimensional (3D) reconstruction of the patient’s pathologic hip anatomy. The CT scan images are uploaded to TPLAN, a preoperative planning station.

In TPLAN, the user creates a 3D template of the surgical plan for both the femoral and acetabular portions of the procedure. The system has an open platform, meaning that the user is not limited to a single implant design or manufacturer. The surgeon can control every aspect of implant positioning: rotation, anteversion, fit and fill on the femoral side and anteversion, inclination/lateral opening, and depth on the acetabular side. Additional features available to the surgeon include accurately defining bony deficits, identifying outlier implant sizes, and checking for excess native version. The system allows the surgeon to determine the native center of hip rotation, which can then be used during templating to give the patient a hip that feels natural because the native muscle tension is restored. Once the desired plan has been achieved, it is uploaded to the robot.The TCAT robot is an active system similar to those used in manufacturing assembly plants (eg, automobiles) in that it follows a predetermined path and can do so in an efficient manner. More specifically, once the user has defined the patient’s anatomy within its workspace, it will proceed with actively milling the femur as planned with sub-millimeter accuracy without the use of navigation. This is in contrast to a haptic system, where the user manually guides the robotic arm within a predefined boundary.

The acetabular portion of the procedure currently uses a standard reamer system and power tools, but the TCAT guides the surgeon to the planned cup orientation, which is maintained during reaming and impaction.

In the Operating Suite

Once in the operating suite, the plan is uploaded into TCAT. Confirmation of the plan and the patient are incorporated into the surgical “time out.” Currently, the system supports patient positioning in standard lateral decubitus using a posterior approach with a standard operating room table. A posterior approach is undertaken to expose and dislocate the hip, with retractors placed to protect the soft tissues and allow the robot its working space.

One procedural difference from the standard THA technique is that the femoral head is initially retained to fixate the femur relative to the robot. A 5-mm Schanz pin is placed in the femoral head and then rigidly attached to the base of the robot. During a process called registration, a series of points on the surface of the exposed bone are collected by the surgeon via a digitizer probe attached to the robot. The TCAT monitor will guide the surgeon through point collection using a map showing the patient’s 3D bone model generated from the CT scan. The software then “finds” the patient’s femur in space and matches it to the 3D CT plan. Milling begins with a burr spinning at 80,000 rpm and saline to irrigate and remove bone debris (Figure 2). The actual milling process takes 5 to 15 minutes, depending on the choice and size of the implant.

A bone motion monitor (BMM) is also attached to the femur, along with recovery markers (RM). The BMM immediately pauses the robot during any active bone milling if it senses femoral motion from the original position. The surgeon then touches the RM with the digitizer to re-register the bone’s position and resume the milling process.

Attention is then turned to the acetabular portion of the procedure. Again, the robot must be rigidly fixed to the patient’s pelvis, along with the RM. Once the surgeon has registered the acetabular position using the digitizer, the robotic arm moves into the preoperatively planned orientation. A universal quick-release allows the surgeon to attach a standard reamer to the robot arm and ream while the robot holds the reamer in place. Once the acetabular preparation is complete, the cup impactor is placed onto the robotic arm and the implant is impacted into the patient. Thereafter, the digitizer can be used to collect points on the surface of the cup and confirm the exact cup placement (Figure 3).

Outcomes

The legacy system, Robodoc, has been used in thousands of clinical cases for both THA and total knee arthroplasty. The Table represents a summary of the THA clinical studies during a time frame in which only the femoral portion of the procedure was available to surgeons.

Bargar and colleagues⁸ describe the first Robodoc clinical trial in the US, along with the first 900 THA procedures performed in Germany. In the US, researchers conducted a prospective, randomized control study with 65 robotic cases and 62 conventional control cases. In terms of functional outcomes, there were no differences between the 2 groups. The robot group had improved radiographic fit and component positioning but significantly increased surgical time and blood loss. There were no femoral fractures in the robot group but 3 cases in the control group. In Germany, they reported on 870 primary THAs and 30 revision THA cases. For the primary cases, Harris hip scores rose from 43.7 preoperatively to 91.5 postoperatively. Complication rates were similar to conventional techniques, except the robot cases had no intraoperative femoral fractures.

Several prospective randomized clinical studies compared use of the Robodoc system with a conventional technique. The group studied by Honl and colleagues⁹ included 61 robotic cases and 80 conventional cases. The robot group had significant improvements in limb-length equality and varus-valgus orientation of the stem. When the revision cases were excluded, the authors found the Harris hip scores, prosthetic alignment, and limb length differentials were better for the robotic group at both 6 and 12 months.

Nakamura and colleagues¹⁰ looked at 75 robotic cases and 71 conventional cases. The results showed that at 2 and 3 years postoperatively, the robotic group had better Japanese Orthopaedic Association (JOA) scores, but by 5 years postoperatively, the differences were no longer significant. The robotic group had a smaller range for leg length inequality (0-12 mm) compared to the conventional group (0-29 mm). The results also showed that at both 2 and 5 years postoperatively, there was more significant stress shielding of the proximal femur, suggesting greater bone loss in the conventional group.

Nishihara and colleagues¹¹ had 78 subjects in each of the robotic and conventional groups and found significantly better Merle d’Aubigné hip scores at 2 years postoperatively in the robotic group. The conventional group suffered 5 intraoperative fractures compared with none in the robotic group, along with greater estimated blood loss, an increased use of undersized stems, higher-than-expected vertical seating, and unexpected femoral anteversion. The robotic cases did, however, take 19 minutes longer than the conventional cases.

Hananouchi and colleagues¹² looked at periprosthetic bone remodeling in 31 robotic hips and 27 conventional hips to determine whether load was effectively transferred from implant to bone after using the Robodoc system to prepare the femoral canal. Using dual energy X-ray absorptiometry (DEXA) to measure bone density, they found significantly less bone loss in the proximal periprosthetic areas in the robotic group compared to the conventional group; however, there were no differences in the Merle d’Aubigné hip scores.

Lim and colleagues¹³ looked specifically at alignment accuracy and clinical outcomes specifically for short femoral stem implants. In a group of 24 robotic cases and 25 conventional cases, they found significantly improved stem alignment and leg length inequality and no differences in Harris Hip score, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score, or complications at 24 months.

In 2004, Nishihara and colleagues¹⁴ evaluated the accuracy of femoral canal preparation using postoperative CT images for 75 cases of THA performed with the original pin-based version of Robodoc. The results showed that the differences between the preoperative plan and the postoperative CT were <5% in terms of canal fill, <1 mm in gap, and <1° in mediolateral and anteroposterior alignment with no reported fractures or complications. They concluded that the Robodoc system resulted in a high degree of accuracy.

Schulz and colleagues¹⁵ reported on 97 of 143 consecutive cases performed from 1997 to 2002. Technical complications were described in 9 cases. Five of the reported complications included the BMM pausing cutting as designed for patient safety, which led to re-registration, and slightly prolonged surgery. The remaining 4 complications included 2 femoral shaft fissures requiring wire cerclage, 1 case of damage to the acetabular rim from the milling device, and 1 defect of the greater trochanter that was milled. In terms of clinical results, they found that the complications, functional outcomes, and radiographic outcomes were comparable to conventional techniques. The rate of femoral shaft fissures, which had been zero in all other studies with Robodoc, was comparable to conventional technique.

Conclusion

The most significant change in hip arthroplasty until now has been the transition from a cemented technique to a press-fit or ingrowth prosthesis.¹⁶ The first robotic surgery was performed in the US in 1992 using the legacy system upon which the current TSolution One was based. Since then, the use of surgical robots has seen a 30% increase annually over the last decade in a variety of surgical fields.¹⁷ In orthopedics, specifically THA, the results have shown that robotics clearly offers benefits in terms of accuracy, precision, and reproducibility. These benefits will likely translate into improved long-term outcomes and increased survivorship in future studies.

Total hip arthroplasty (THA) is a successful surgery with positive clinical outcomes and over 95% survivorship at 10-year follow-up and 80% survivorship at 25-year follow-up.^1,2 A hip replacement requires strong osteointegration^3,4 to prevent femoral osteolysis, and correct implant alignment has been shown to correlate with prolonged implant survivorship and reduced dislocation.^5,6 Robotics and computer-assisted navigation have been developed to increase the accuracy of implant placement and reduce outliers with the overall goal of improving long-term results. These technologies have shown significant improvements in implant positioning when compared to conventional techniques.⁷

The first active robotic system for use in orthopedic procedures, Robodoc (Think Surgical, Inc.), was based on a traditional computer-aided design/computer-aided manufacturing system. Currently, only 3 robotic systems for THA have clearance in the US: The Mako System (Stryker), Robodoc, and TSolution One (Think Surgical, Inc.). The TSolution One system is based on the legacy technology developed as Robodoc and currently provides assistance during preparation of the femoral canal as well as guidance and positioning assistance during acetabular cup reaming and implanting. The following is a summary of the author’s (DSD) preferred technique for robotic-assisted THA using TSolution One.

How It Works

The process begins with preoperative planning (Figure 1). A computed tomography (CT) scan is used to create a detailed 3-dimensional (3D) reconstruction of the patient’s pathologic hip anatomy. The CT scan images are uploaded to TPLAN, a preoperative planning station.

In TPLAN, the user creates a 3D template of the surgical plan for both the femoral and acetabular portions of the procedure. The system has an open platform, meaning that the user is not limited to a single implant design or manufacturer. The surgeon can control every aspect of implant positioning: rotation, anteversion, fit and fill on the femoral side and anteversion, inclination/lateral opening, and depth on the acetabular side. Additional features available to the surgeon include accurately defining bony deficits, identifying outlier implant sizes, and checking for excess native version. The system allows the surgeon to determine the native center of hip rotation, which can then be used during templating to give the patient a hip that feels natural because the native muscle tension is restored. Once the desired plan has been achieved, it is uploaded to the robot.The TCAT robot is an active system similar to those used in manufacturing assembly plants (eg, automobiles) in that it follows a predetermined path and can do so in an efficient manner. More specifically, once the user has defined the patient’s anatomy within its workspace, it will proceed with actively milling the femur as planned with sub-millimeter accuracy without the use of navigation. This is in contrast to a haptic system, where the user manually guides the robotic arm within a predefined boundary.

The acetabular portion of the procedure currently uses a standard reamer system and power tools, but the TCAT guides the surgeon to the planned cup orientation, which is maintained during reaming and impaction.

In the Operating Suite

Once in the operating suite, the plan is uploaded into TCAT. Confirmation of the plan and the patient are incorporated into the surgical “time out.” Currently, the system supports patient positioning in standard lateral decubitus using a posterior approach with a standard operating room table. A posterior approach is undertaken to expose and dislocate the hip, with retractors placed to protect the soft tissues and allow the robot its working space.

One procedural difference from the standard THA technique is that the femoral head is initially retained to fixate the femur relative to the robot. A 5-mm Schanz pin is placed in the femoral head and then rigidly attached to the base of the robot. During a process called registration, a series of points on the surface of the exposed bone are collected by the surgeon via a digitizer probe attached to the robot. The TCAT monitor will guide the surgeon through point collection using a map showing the patient’s 3D bone model generated from the CT scan. The software then “finds” the patient’s femur in space and matches it to the 3D CT plan. Milling begins with a burr spinning at 80,000 rpm and saline to irrigate and remove bone debris (Figure 2). The actual milling process takes 5 to 15 minutes, depending on the choice and size of the implant.

A bone motion monitor (BMM) is also attached to the femur, along with recovery markers (RM). The BMM immediately pauses the robot during any active bone milling if it senses femoral motion from the original position. The surgeon then touches the RM with the digitizer to re-register the bone’s position and resume the milling process.

Attention is then turned to the acetabular portion of the procedure. Again, the robot must be rigidly fixed to the patient’s pelvis, along with the RM. Once the surgeon has registered the acetabular position using the digitizer, the robotic arm moves into the preoperatively planned orientation. A universal quick-release allows the surgeon to attach a standard reamer to the robot arm and ream while the robot holds the reamer in place. Once the acetabular preparation is complete, the cup impactor is placed onto the robotic arm and the implant is impacted into the patient. Thereafter, the digitizer can be used to collect points on the surface of the cup and confirm the exact cup placement (Figure 3).

Outcomes

The legacy system, Robodoc, has been used in thousands of clinical cases for both THA and total knee arthroplasty. The Table represents a summary of the THA clinical studies during a time frame in which only the femoral portion of the procedure was available to surgeons.

Bargar and colleagues⁸ describe the first Robodoc clinical trial in the US, along with the first 900 THA procedures performed in Germany. In the US, researchers conducted a prospective, randomized control study with 65 robotic cases and 62 conventional control cases. In terms of functional outcomes, there were no differences between the 2 groups. The robot group had improved radiographic fit and component positioning but significantly increased surgical time and blood loss. There were no femoral fractures in the robot group but 3 cases in the control group. In Germany, they reported on 870 primary THAs and 30 revision THA cases. For the primary cases, Harris hip scores rose from 43.7 preoperatively to 91.5 postoperatively. Complication rates were similar to conventional techniques, except the robot cases had no intraoperative femoral fractures.

Several prospective randomized clinical studies compared use of the Robodoc system with a conventional technique. The group studied by Honl and colleagues⁹ included 61 robotic cases and 80 conventional cases. The robot group had significant improvements in limb-length equality and varus-valgus orientation of the stem. When the revision cases were excluded, the authors found the Harris hip scores, prosthetic alignment, and limb length differentials were better for the robotic group at both 6 and 12 months.

Nakamura and colleagues¹⁰ looked at 75 robotic cases and 71 conventional cases. The results showed that at 2 and 3 years postoperatively, the robotic group had better Japanese Orthopaedic Association (JOA) scores, but by 5 years postoperatively, the differences were no longer significant. The robotic group had a smaller range for leg length inequality (0-12 mm) compared to the conventional group (0-29 mm). The results also showed that at both 2 and 5 years postoperatively, there was more significant stress shielding of the proximal femur, suggesting greater bone loss in the conventional group.

Nishihara and colleagues¹¹ had 78 subjects in each of the robotic and conventional groups and found significantly better Merle d’Aubigné hip scores at 2 years postoperatively in the robotic group. The conventional group suffered 5 intraoperative fractures compared with none in the robotic group, along with greater estimated blood loss, an increased use of undersized stems, higher-than-expected vertical seating, and unexpected femoral anteversion. The robotic cases did, however, take 19 minutes longer than the conventional cases.

Hananouchi and colleagues¹² looked at periprosthetic bone remodeling in 31 robotic hips and 27 conventional hips to determine whether load was effectively transferred from implant to bone after using the Robodoc system to prepare the femoral canal. Using dual energy X-ray absorptiometry (DEXA) to measure bone density, they found significantly less bone loss in the proximal periprosthetic areas in the robotic group compared to the conventional group; however, there were no differences in the Merle d’Aubigné hip scores.

Lim and colleagues¹³ looked specifically at alignment accuracy and clinical outcomes specifically for short femoral stem implants. In a group of 24 robotic cases and 25 conventional cases, they found significantly improved stem alignment and leg length inequality and no differences in Harris Hip score, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score, or complications at 24 months.

In 2004, Nishihara and colleagues¹⁴ evaluated the accuracy of femoral canal preparation using postoperative CT images for 75 cases of THA performed with the original pin-based version of Robodoc. The results showed that the differences between the preoperative plan and the postoperative CT were <5% in terms of canal fill, <1 mm in gap, and <1° in mediolateral and anteroposterior alignment with no reported fractures or complications. They concluded that the Robodoc system resulted in a high degree of accuracy.

Schulz and colleagues¹⁵ reported on 97 of 143 consecutive cases performed from 1997 to 2002. Technical complications were described in 9 cases. Five of the reported complications included the BMM pausing cutting as designed for patient safety, which led to re-registration, and slightly prolonged surgery. The remaining 4 complications included 2 femoral shaft fissures requiring wire cerclage, 1 case of damage to the acetabular rim from the milling device, and 1 defect of the greater trochanter that was milled. In terms of clinical results, they found that the complications, functional outcomes, and radiographic outcomes were comparable to conventional techniques. The rate of femoral shaft fissures, which had been zero in all other studies with Robodoc, was comparable to conventional technique.

Conclusion

The most significant change in hip arthroplasty until now has been the transition from a cemented technique to a press-fit or ingrowth prosthesis.¹⁶ The first robotic surgery was performed in the US in 1992 using the legacy system upon which the current TSolution One was based. Since then, the use of surgical robots has seen a 30% increase annually over the last decade in a variety of surgical fields.¹⁷ In orthopedics, specifically THA, the results have shown that robotics clearly offers benefits in terms of accuracy, precision, and reproducibility. These benefits will likely translate into improved long-term outcomes and increased survivorship in future studies.

The concept of robotics is relatively new in medical practice. The term “robot” itself is less than 100 years old, having been first introduced to popular culture in 1917 by Joseph Capek in the science fiction story Opilec.^1,2 Robots eventually transitioned from this initial fictional literary setting to reality in 1958, when General Motors began adding automated machines to its assembly lines.¹ However, it was not until the 1980s that robotics and their exacting efficiencies would be introduced in the medical field, and it would take another decade before they would enter the specialty of orthopedics.^1-4

The first robotic-assisted orthopedic surgery was reportedly performed in 1992, when the Robodoc autonomous system was utilized for total hip arthroplasty.^2-4 A robotic system for total knee arthroplasty (TKA) was first described in 1993, but it would take several more years until a system for unicompartmental knee arthroplasty (UKA) would be commercialized and used clinically.^5,6 The rationale for advancement of robotic technology for isolated medial or lateral knee arthritis stems from the recognition that while UKA is effective and durable when components and limb are well aligned and soft tissues appropriately balanced, they are less forgiving of even slight component malalignment of as little as 2° to 3° and prone to premature loosening or wear in those circumstances.^7-13,14 In the mid 2000s, Cobb and colleagues⁶ reported using a semiautonomous robot for UKA. Since then, emergence of other semiautonomous robotic systems has led to greater market penetration and technology utilization.¹⁵

Currently, an estimated 15% to 20% of UKA surgeries are being performed with robotic assistance.¹⁶ Further, patent activity and peer-reviewed publications related to robotic technology in UKA (which can be considered surrogate measures of interest and evolving development and experience with robotic technologies) have increased dramatically over the past few years.^{2,6,14,17,18-34} To date, while the most dramatic growth of robotic utilization and case volumes has occurred in the subspecialty of UKA, semiautonomous robotic systems have been used with increasing frequency for patellofemoral and bicompartmental knee arthroplasty.^35,36 Robotics have been used sparingly for TKA, and limited to autonomous systems;^37,38 however, it is anticipated that emergence of semiautonomous platforms for TKA will further expand the role of robotics over the next decade, particularly as our focus shifts beyond component and limb alignment in TKA and more towards the role of robotics in soft tissue balancing, reduction in instrumentation and inventory and its attendant cost savings, and surgical efficiencies. One semiautonomous robotic technology first used in 2006 (Mako, Stryker) reported a 130% increase in robotic volume from 2011 to 2012; another, first used in 2013, reported growth of 480% between 2013 and 2014, due to its improved cost structure, ease of use, smaller footprint, image-free platform and applicability in ambulatory surgery centers (Navio, Smith & Nephew; data supplied by manufacturer), demonstrating the growing popularity of robotic technology.^17,39 Further, a recent analysis of potential market penetration over the next decade published by Medical Device and Diagnostic Industry (http://www.mddionline.com) projected that nearly 37% of UKAs and 23% of TKAs will be performed with robotics in 10 years.

Distinction Between Robotic-Assisted Technologies

Autonomous systems involve pre-programming the system with parameters that define the amount and orientation of bone to be removed, after which the system prepares the surfaces independent of surgeon control, other than having access to a “shutdown” switch. There are currently no autonomous robotic tools approved by the US Food and Drug Administration (FDA) for knee arthroplasty.

Semiautonomous systems involve the mapping of condylar landmarks and determination of alignment indices, which also defines the volume and orientation of bone to be removed. While the systems remove bone and cartilage within the pre-established parameters, the robotic tools are controlled and manipulated by the surgeon (Figure 1). The predetermined safe zones modulate and safeguard the surgical actions. These systems also provide real-time quantification of soft tissue balancing, which may contribute to the reported successful clinical and functional outcomes with semiautonomous systems (Figure 2).^2,4,19,22 There are several semiautonomous robotic systems that are approved for use by the FDA.

Each robotic-assisted surgery (RAS) system utilizes some sort of 3-dimensional digital map of the surgical surfaces after a process of surface mapping and landmark registration.² In the case of Mako, this planning process also requires a preoperative computed tomography (CT) scan. Over the past few years, the requirement of a CT scan has proven problematic and costly, as increasingly third-party payers and insurers are denying coverage for additional studies used for preoperative planning, leaving the burden of cost on the patients and/or hospitals. Additionally, in an era in which bundled payment arrangements are commonplace or in which providers are held accountable for costly care, the use of costly preoperative imaging is untenable. Furthermore, there is a growing concern regarding the risk of radiation exposure from CT scans that makes image-free technologies, such as Navio, an alternative for stakeholders.⁴⁰

At this time, the 2 semiautonomous systems in use for UKA employ different methods to safeguard against inadvertent bone preparation: one by providing haptic constraint beyond which movement of the bur is limited (Mako); the other by modulating the exposure or speed of the handheld robotic bur (Navio) (Figure 3).

Outcomes of RAS in UKA

Compared to conventional UKA, robotic assistance has consistently demonstrated improved surgical accuracy, even through minimally invasive incisions (Figures 4, 5).^6,20-28 Several studies have found substantial reduction in variability and error of component positioning with use of semiautonomous robotic tools.^6,21,25 In fact, precision appears to be comparable regardless of whether an image-free system or one requiring a preoperative CT scan is used (Table). Further, in addition to improving component and limb alignment, Plate and colleagues²² demonstrated that RAS-based UKA systems can help the surgeon precisely reproduce plans for soft-tissue balancing. The authors reported ligament balancing to be accurate up to .53 mm compared to the preoperative plan, with approximately 83% of cases balanced within 1 mm of the plan through a full range of flexion.²²

When evaluating advanced and novel technologies, there is undoubtedly concern that there will be increased operative time and a substantial learning curve with those technologies. Karia and colleagues³⁰ found that when inexperienced surgeons performed UKA on synthetic bone models using robotics, the mean compound rotational and translational errors were lower than when conventional techniques were used. Among those using conventional techniques, although surgical times improved during the learning period, positional inaccuracies persisted. On the other hand, robotic assistance enabled surgeons to achieve precision and accuracy when positioning UKA components irrespective of their learning experience.³⁰ Another study, by Coon,³¹ similarly suggested a shorter learning curve and greater accuracy with RAS using the Mako system compared to conventional techniques. A prospective, multicenter, observational study evaluated the operative times of 11 surgeons during their initial clinical cases using Navio robotic technology for medial UKA after a period of training using cadaver knees and sawbones.⁴¹ The learning curve for total surgical time (tracker placement to implant trial phase) indicates that it takes 8 cases to achieve 95% of total learning and maintain a steady state surgical time.

Potential Disadvantages of RAS in UKA

RAS for UKA has several potential disadvantages that must be weighed against their potential benefits. One major barrier to broader use of RAS is the increased cost associated with the technologies.^17,19,27,32 Capital and maintenance costs for these systems can be high, and those that require additional advanced imaging, such as CT scans, further challenge the return on investment.^17,19,32 In a Markov analysis of one robotic system (Mako), Moschetti and colleagues¹⁷ found that if one assumes a system cost of $1.362 million, value can be attained due to slightly better outcomes despite being more expensive than traditional methods. Nonetheless, their analysis of the Mako system estimated that each robot-assisted UKA case cost $19,219, compared to $16,476 with traditional UKA, and was associated with an incremental cost of $47,180 per quality-adjusted life-year. Their analysis further demonstrated that the cost-effectiveness was very sensitive to case volume, with lower costs realized once volumes surpassed 94 cases per year. On the other hand, costs (and thus value) will also obviously vary depending on the capital costs, annual service charges, and avoidance of unnecessary preoperative scans.¹⁹ For instance, assuming a cost of $500,000 for the image-free Navio robotic system, return on investment is achievable within 25 cases annually, roughly one-quarter of the cases necessary with the image-based system.

Another disadvantage of RAS systems in UKA is the unique complications associated with their use. Both RAS and conventional UKA can be complicated by similar problems such as component loosening, polyethylene wear, progressive arthritis, infection, stiffness, instability, and thromboembolism. RAS systems, however, carry the additional risk of specific robot-related issues.^19,27 Perhaps most notably, the pin tracts for the required optical tracking arrays can create a stress riser in the cortical bone,^19,27,33,42 highlighting the importance of inserting these pins in metaphyseal, and not diaphyseal, bone. Soft tissue complications have been reported during bone preparation with autonomous systems in total knee and hip arthroplasty;^37,38 however, the senior author (JHL) has not observed that in 1000 consecutive cases with either semiautonomous surgeon-driven robotic tool.¹⁹

Finally, systems that require a preoperative CT scan pose an increased radiation risk.⁴⁰ Ponzio and Lonner⁴⁰ recently reported that each preoperative CT scan for robotic-assisted knee arthroplasty (using a Mako protocol) is associated with a mean effective dose of radiation of 4.8 mSv, which is approximately equivalent to 48 chest radiographs.³⁴ Further, in that study, at least 25% of patients had been subjected to multiple scans, with some being exposed to cumulative effective doses of up to 103 mSv. This risk should not be considered completely negligible given that 10 mSv may be associated with an increase in the possibility of fatal cancer, and an estimated 29,000 excess cancer cases in the United States annually are reportedly caused by CT scans.^40,43,44 However, this increased radiation risk is not inherent to all RAS systems. Image-free systems, such as Navio, do not require CT scans and are thus not associated with this potential disadvantage.

Conclusion

Robotics has come a long way from its humble conceptual beginnings nearly a century ago. Rapid advances in medical technology over the past 10 years have led to the development and growing popularity of RAS in orthopedic surgery, particularly during UKA. Component placement, quantified soft tissue balance, and radiographic alignment appear to be improved and the incidence of outliers reduced with the use of RAS during UKA. Further assessment is needed to determine whether the improved alignment and balance will impact clinical function and/or durability. Early results are very promising, though, creating optimism that the full benefits of RAS in UKA will be further confirmed with additional time and research.

The concept of robotics is relatively new in medical practice. The term “robot” itself is less than 100 years old, having been first introduced to popular culture in 1917 by Joseph Capek in the science fiction story Opilec.^1,2 Robots eventually transitioned from this initial fictional literary setting to reality in 1958, when General Motors began adding automated machines to its assembly lines.¹ However, it was not until the 1980s that robotics and their exacting efficiencies would be introduced in the medical field, and it would take another decade before they would enter the specialty of orthopedics.^1-4

The first robotic-assisted orthopedic surgery was reportedly performed in 1992, when the Robodoc autonomous system was utilized for total hip arthroplasty.^2-4 A robotic system for total knee arthroplasty (TKA) was first described in 1993, but it would take several more years until a system for unicompartmental knee arthroplasty (UKA) would be commercialized and used clinically.^5,6 The rationale for advancement of robotic technology for isolated medial or lateral knee arthritis stems from the recognition that while UKA is effective and durable when components and limb are well aligned and soft tissues appropriately balanced, they are less forgiving of even slight component malalignment of as little as 2° to 3° and prone to premature loosening or wear in those circumstances.^7-13,14 In the mid 2000s, Cobb and colleagues⁶ reported using a semiautonomous robot for UKA. Since then, emergence of other semiautonomous robotic systems has led to greater market penetration and technology utilization.¹⁵

Currently, an estimated 15% to 20% of UKA surgeries are being performed with robotic assistance.¹⁶ Further, patent activity and peer-reviewed publications related to robotic technology in UKA (which can be considered surrogate measures of interest and evolving development and experience with robotic technologies) have increased dramatically over the past few years.^{2,6,14,17,18-34} To date, while the most dramatic growth of robotic utilization and case volumes has occurred in the subspecialty of UKA, semiautonomous robotic systems have been used with increasing frequency for patellofemoral and bicompartmental knee arthroplasty.^35,36 Robotics have been used sparingly for TKA, and limited to autonomous systems;^37,38 however, it is anticipated that emergence of semiautonomous platforms for TKA will further expand the role of robotics over the next decade, particularly as our focus shifts beyond component and limb alignment in TKA and more towards the role of robotics in soft tissue balancing, reduction in instrumentation and inventory and its attendant cost savings, and surgical efficiencies. One semiautonomous robotic technology first used in 2006 (Mako, Stryker) reported a 130% increase in robotic volume from 2011 to 2012; another, first used in 2013, reported growth of 480% between 2013 and 2014, due to its improved cost structure, ease of use, smaller footprint, image-free platform and applicability in ambulatory surgery centers (Navio, Smith & Nephew; data supplied by manufacturer), demonstrating the growing popularity of robotic technology.^17,39 Further, a recent analysis of potential market penetration over the next decade published by Medical Device and Diagnostic Industry (http://www.mddionline.com) projected that nearly 37% of UKAs and 23% of TKAs will be performed with robotics in 10 years.

Distinction Between Robotic-Assisted Technologies

Autonomous systems involve pre-programming the system with parameters that define the amount and orientation of bone to be removed, after which the system prepares the surfaces independent of surgeon control, other than having access to a “shutdown” switch. There are currently no autonomous robotic tools approved by the US Food and Drug Administration (FDA) for knee arthroplasty.

Semiautonomous systems involve the mapping of condylar landmarks and determination of alignment indices, which also defines the volume and orientation of bone to be removed. While the systems remove bone and cartilage within the pre-established parameters, the robotic tools are controlled and manipulated by the surgeon (Figure 1). The predetermined safe zones modulate and safeguard the surgical actions. These systems also provide real-time quantification of soft tissue balancing, which may contribute to the reported successful clinical and functional outcomes with semiautonomous systems (Figure 2).^2,4,19,22 There are several semiautonomous robotic systems that are approved for use by the FDA.

Each robotic-assisted surgery (RAS) system utilizes some sort of 3-dimensional digital map of the surgical surfaces after a process of surface mapping and landmark registration.² In the case of Mako, this planning process also requires a preoperative computed tomography (CT) scan. Over the past few years, the requirement of a CT scan has proven problematic and costly, as increasingly third-party payers and insurers are denying coverage for additional studies used for preoperative planning, leaving the burden of cost on the patients and/or hospitals. Additionally, in an era in which bundled payment arrangements are commonplace or in which providers are held accountable for costly care, the use of costly preoperative imaging is untenable. Furthermore, there is a growing concern regarding the risk of radiation exposure from CT scans that makes image-free technologies, such as Navio, an alternative for stakeholders.⁴⁰

At this time, the 2 semiautonomous systems in use for UKA employ different methods to safeguard against inadvertent bone preparation: one by providing haptic constraint beyond which movement of the bur is limited (Mako); the other by modulating the exposure or speed of the handheld robotic bur (Navio) (Figure 3).

Outcomes of RAS in UKA

Compared to conventional UKA, robotic assistance has consistently demonstrated improved surgical accuracy, even through minimally invasive incisions (Figures 4, 5).^6,20-28 Several studies have found substantial reduction in variability and error of component positioning with use of semiautonomous robotic tools.^6,21,25 In fact, precision appears to be comparable regardless of whether an image-free system or one requiring a preoperative CT scan is used (Table). Further, in addition to improving component and limb alignment, Plate and colleagues²² demonstrated that RAS-based UKA systems can help the surgeon precisely reproduce plans for soft-tissue balancing. The authors reported ligament balancing to be accurate up to .53 mm compared to the preoperative plan, with approximately 83% of cases balanced within 1 mm of the plan through a full range of flexion.²²

When evaluating advanced and novel technologies, there is undoubtedly concern that there will be increased operative time and a substantial learning curve with those technologies. Karia and colleagues³⁰ found that when inexperienced surgeons performed UKA on synthetic bone models using robotics, the mean compound rotational and translational errors were lower than when conventional techniques were used. Among those using conventional techniques, although surgical times improved during the learning period, positional inaccuracies persisted. On the other hand, robotic assistance enabled surgeons to achieve precision and accuracy when positioning UKA components irrespective of their learning experience.³⁰ Another study, by Coon,³¹ similarly suggested a shorter learning curve and greater accuracy with RAS using the Mako system compared to conventional techniques. A prospective, multicenter, observational study evaluated the operative times of 11 surgeons during their initial clinical cases using Navio robotic technology for medial UKA after a period of training using cadaver knees and sawbones.⁴¹ The learning curve for total surgical time (tracker placement to implant trial phase) indicates that it takes 8 cases to achieve 95% of total learning and maintain a steady state surgical time.

Potential Disadvantages of RAS in UKA

RAS for UKA has several potential disadvantages that must be weighed against their potential benefits. One major barrier to broader use of RAS is the increased cost associated with the technologies.^17,19,27,32 Capital and maintenance costs for these systems can be high, and those that require additional advanced imaging, such as CT scans, further challenge the return on investment.^17,19,32 In a Markov analysis of one robotic system (Mako), Moschetti and colleagues¹⁷ found that if one assumes a system cost of $1.362 million, value can be attained due to slightly better outcomes despite being more expensive than traditional methods. Nonetheless, their analysis of the Mako system estimated that each robot-assisted UKA case cost $19,219, compared to $16,476 with traditional UKA, and was associated with an incremental cost of $47,180 per quality-adjusted life-year. Their analysis further demonstrated that the cost-effectiveness was very sensitive to case volume, with lower costs realized once volumes surpassed 94 cases per year. On the other hand, costs (and thus value) will also obviously vary depending on the capital costs, annual service charges, and avoidance of unnecessary preoperative scans.¹⁹ For instance, assuming a cost of $500,000 for the image-free Navio robotic system, return on investment is achievable within 25 cases annually, roughly one-quarter of the cases necessary with the image-based system.

Another disadvantage of RAS systems in UKA is the unique complications associated with their use. Both RAS and conventional UKA can be complicated by similar problems such as component loosening, polyethylene wear, progressive arthritis, infection, stiffness, instability, and thromboembolism. RAS systems, however, carry the additional risk of specific robot-related issues.^19,27 Perhaps most notably, the pin tracts for the required optical tracking arrays can create a stress riser in the cortical bone,^19,27,33,42 highlighting the importance of inserting these pins in metaphyseal, and not diaphyseal, bone. Soft tissue complications have been reported during bone preparation with autonomous systems in total knee and hip arthroplasty;^37,38 however, the senior author (JHL) has not observed that in 1000 consecutive cases with either semiautonomous surgeon-driven robotic tool.¹⁹

Finally, systems that require a preoperative CT scan pose an increased radiation risk.⁴⁰ Ponzio and Lonner⁴⁰ recently reported that each preoperative CT scan for robotic-assisted knee arthroplasty (using a Mako protocol) is associated with a mean effective dose of radiation of 4.8 mSv, which is approximately equivalent to 48 chest radiographs.³⁴ Further, in that study, at least 25% of patients had been subjected to multiple scans, with some being exposed to cumulative effective doses of up to 103 mSv. This risk should not be considered completely negligible given that 10 mSv may be associated with an increase in the possibility of fatal cancer, and an estimated 29,000 excess cancer cases in the United States annually are reportedly caused by CT scans.^40,43,44 However, this increased radiation risk is not inherent to all RAS systems. Image-free systems, such as Navio, do not require CT scans and are thus not associated with this potential disadvantage.

Conclusion

Robotics has come a long way from its humble conceptual beginnings nearly a century ago. Rapid advances in medical technology over the past 10 years have led to the development and growing popularity of RAS in orthopedic surgery, particularly during UKA. Component placement, quantified soft tissue balance, and radiographic alignment appear to be improved and the incidence of outliers reduced with the use of RAS during UKA. Further assessment is needed to determine whether the improved alignment and balance will impact clinical function and/or durability. Early results are very promising, though, creating optimism that the full benefits of RAS in UKA will be further confirmed with additional time and research.

The concept of robotics is relatively new in medical practice. The term “robot” itself is less than 100 years old, having been first introduced to popular culture in 1917 by Joseph Capek in the science fiction story Opilec.^1,2 Robots eventually transitioned from this initial fictional literary setting to reality in 1958, when General Motors began adding automated machines to its assembly lines.¹ However, it was not until the 1980s that robotics and their exacting efficiencies would be introduced in the medical field, and it would take another decade before they would enter the specialty of orthopedics.^1-4

The first robotic-assisted orthopedic surgery was reportedly performed in 1992, when the Robodoc autonomous system was utilized for total hip arthroplasty.^2-4 A robotic system for total knee arthroplasty (TKA) was first described in 1993, but it would take several more years until a system for unicompartmental knee arthroplasty (UKA) would be commercialized and used clinically.^5,6 The rationale for advancement of robotic technology for isolated medial or lateral knee arthritis stems from the recognition that while UKA is effective and durable when components and limb are well aligned and soft tissues appropriately balanced, they are less forgiving of even slight component malalignment of as little as 2° to 3° and prone to premature loosening or wear in those circumstances.^7-13,14 In the mid 2000s, Cobb and colleagues⁶ reported using a semiautonomous robot for UKA. Since then, emergence of other semiautonomous robotic systems has led to greater market penetration and technology utilization.¹⁵

Currently, an estimated 15% to 20% of UKA surgeries are being performed with robotic assistance.¹⁶ Further, patent activity and peer-reviewed publications related to robotic technology in UKA (which can be considered surrogate measures of interest and evolving development and experience with robotic technologies) have increased dramatically over the past few years.^{2,6,14,17,18-34} To date, while the most dramatic growth of robotic utilization and case volumes has occurred in the subspecialty of UKA, semiautonomous robotic systems have been used with increasing frequency for patellofemoral and bicompartmental knee arthroplasty.^35,36 Robotics have been used sparingly for TKA, and limited to autonomous systems;^37,38 however, it is anticipated that emergence of semiautonomous platforms for TKA will further expand the role of robotics over the next decade, particularly as our focus shifts beyond component and limb alignment in TKA and more towards the role of robotics in soft tissue balancing, reduction in instrumentation and inventory and its attendant cost savings, and surgical efficiencies. One semiautonomous robotic technology first used in 2006 (Mako, Stryker) reported a 130% increase in robotic volume from 2011 to 2012; another, first used in 2013, reported growth of 480% between 2013 and 2014, due to its improved cost structure, ease of use, smaller footprint, image-free platform and applicability in ambulatory surgery centers (Navio, Smith & Nephew; data supplied by manufacturer), demonstrating the growing popularity of robotic technology.^17,39 Further, a recent analysis of potential market penetration over the next decade published by Medical Device and Diagnostic Industry (http://www.mddionline.com) projected that nearly 37% of UKAs and 23% of TKAs will be performed with robotics in 10 years.

Distinction Between Robotic-Assisted Technologies

Autonomous systems involve pre-programming the system with parameters that define the amount and orientation of bone to be removed, after which the system prepares the surfaces independent of surgeon control, other than having access to a “shutdown” switch. There are currently no autonomous robotic tools approved by the US Food and Drug Administration (FDA) for knee arthroplasty.

Semiautonomous systems involve the mapping of condylar landmarks and determination of alignment indices, which also defines the volume and orientation of bone to be removed. While the systems remove bone and cartilage within the pre-established parameters, the robotic tools are controlled and manipulated by the surgeon (Figure 1). The predetermined safe zones modulate and safeguard the surgical actions. These systems also provide real-time quantification of soft tissue balancing, which may contribute to the reported successful clinical and functional outcomes with semiautonomous systems (Figure 2).^2,4,19,22 There are several semiautonomous robotic systems that are approved for use by the FDA.

Each robotic-assisted surgery (RAS) system utilizes some sort of 3-dimensional digital map of the surgical surfaces after a process of surface mapping and landmark registration.² In the case of Mako, this planning process also requires a preoperative computed tomography (CT) scan. Over the past few years, the requirement of a CT scan has proven problematic and costly, as increasingly third-party payers and insurers are denying coverage for additional studies used for preoperative planning, leaving the burden of cost on the patients and/or hospitals. Additionally, in an era in which bundled payment arrangements are commonplace or in which providers are held accountable for costly care, the use of costly preoperative imaging is untenable. Furthermore, there is a growing concern regarding the risk of radiation exposure from CT scans that makes image-free technologies, such as Navio, an alternative for stakeholders.⁴⁰

At this time, the 2 semiautonomous systems in use for UKA employ different methods to safeguard against inadvertent bone preparation: one by providing haptic constraint beyond which movement of the bur is limited (Mako); the other by modulating the exposure or speed of the handheld robotic bur (Navio) (Figure 3).

Outcomes of RAS in UKA

Compared to conventional UKA, robotic assistance has consistently demonstrated improved surgical accuracy, even through minimally invasive incisions (Figures 4, 5).^6,20-28 Several studies have found substantial reduction in variability and error of component positioning with use of semiautonomous robotic tools.^6,21,25 In fact, precision appears to be comparable regardless of whether an image-free system or one requiring a preoperative CT scan is used (Table). Further, in addition to improving component and limb alignment, Plate and colleagues²² demonstrated that RAS-based UKA systems can help the surgeon precisely reproduce plans for soft-tissue balancing. The authors reported ligament balancing to be accurate up to .53 mm compared to the preoperative plan, with approximately 83% of cases balanced within 1 mm of the plan through a full range of flexion.²²

When evaluating advanced and novel technologies, there is undoubtedly concern that there will be increased operative time and a substantial learning curve with those technologies. Karia and colleagues³⁰ found that when inexperienced surgeons performed UKA on synthetic bone models using robotics, the mean compound rotational and translational errors were lower than when conventional techniques were used. Among those using conventional techniques, although surgical times improved during the learning period, positional inaccuracies persisted. On the other hand, robotic assistance enabled surgeons to achieve precision and accuracy when positioning UKA components irrespective of their learning experience.³⁰ Another study, by Coon,³¹ similarly suggested a shorter learning curve and greater accuracy with RAS using the Mako system compared to conventional techniques. A prospective, multicenter, observational study evaluated the operative times of 11 surgeons during their initial clinical cases using Navio robotic technology for medial UKA after a period of training using cadaver knees and sawbones.⁴¹ The learning curve for total surgical time (tracker placement to implant trial phase) indicates that it takes 8 cases to achieve 95% of total learning and maintain a steady state surgical time.

Potential Disadvantages of RAS in UKA

RAS for UKA has several potential disadvantages that must be weighed against their potential benefits. One major barrier to broader use of RAS is the increased cost associated with the technologies.^17,19,27,32 Capital and maintenance costs for these systems can be high, and those that require additional advanced imaging, such as CT scans, further challenge the return on investment.^17,19,32 In a Markov analysis of one robotic system (Mako), Moschetti and colleagues¹⁷ found that if one assumes a system cost of $1.362 million, value can be attained due to slightly better outcomes despite being more expensive than traditional methods. Nonetheless, their analysis of the Mako system estimated that each robot-assisted UKA case cost $19,219, compared to $16,476 with traditional UKA, and was associated with an incremental cost of $47,180 per quality-adjusted life-year. Their analysis further demonstrated that the cost-effectiveness was very sensitive to case volume, with lower costs realized once volumes surpassed 94 cases per year. On the other hand, costs (and thus value) will also obviously vary depending on the capital costs, annual service charges, and avoidance of unnecessary preoperative scans.¹⁹ For instance, assuming a cost of $500,000 for the image-free Navio robotic system, return on investment is achievable within 25 cases annually, roughly one-quarter of the cases necessary with the image-based system.

Another disadvantage of RAS systems in UKA is the unique complications associated with their use. Both RAS and conventional UKA can be complicated by similar problems such as component loosening, polyethylene wear, progressive arthritis, infection, stiffness, instability, and thromboembolism. RAS systems, however, carry the additional risk of specific robot-related issues.^19,27 Perhaps most notably, the pin tracts for the required optical tracking arrays can create a stress riser in the cortical bone,^19,27,33,42 highlighting the importance of inserting these pins in metaphyseal, and not diaphyseal, bone. Soft tissue complications have been reported during bone preparation with autonomous systems in total knee and hip arthroplasty;^37,38 however, the senior author (JHL) has not observed that in 1000 consecutive cases with either semiautonomous surgeon-driven robotic tool.¹⁹

Finally, systems that require a preoperative CT scan pose an increased radiation risk.⁴⁰ Ponzio and Lonner⁴⁰ recently reported that each preoperative CT scan for robotic-assisted knee arthroplasty (using a Mako protocol) is associated with a mean effective dose of radiation of 4.8 mSv, which is approximately equivalent to 48 chest radiographs.³⁴ Further, in that study, at least 25% of patients had been subjected to multiple scans, with some being exposed to cumulative effective doses of up to 103 mSv. This risk should not be considered completely negligible given that 10 mSv may be associated with an increase in the possibility of fatal cancer, and an estimated 29,000 excess cancer cases in the United States annually are reportedly caused by CT scans.^40,43,44 However, this increased radiation risk is not inherent to all RAS systems. Image-free systems, such as Navio, do not require CT scans and are thus not associated with this potential disadvantage.

Conclusion

Robotics has come a long way from its humble conceptual beginnings nearly a century ago. Rapid advances in medical technology over the past 10 years have led to the development and growing popularity of RAS in orthopedic surgery, particularly during UKA. Component placement, quantified soft tissue balance, and radiographic alignment appear to be improved and the incidence of outliers reduced with the use of RAS during UKA. Further assessment is needed to determine whether the improved alignment and balance will impact clinical function and/or durability. Early results are very promising, though, creating optimism that the full benefits of RAS in UKA will be further confirmed with additional time and research.

Total knee arthroplasty (TKA) continues to be a widely utilized treatment option for end-stage knee osteoarthritis, and the number of patients undergoing TKA is projected to continually increase over the next decade.¹ Although TKA is highly successful for many patients, studies continue to report that approximately 20% of patients are dissatisfied after undergoing TKA, and nearly 25% of knee revisions are performed for instability or malalignment.^2,3 Technological advances have been developed to help improve clinical outcomes and implant survivorship. Over the past decade, computer navigation and intraoperative guides have been introduced to help control surgical variables and overcome the limitations and inaccuracies of traditional mechanical instrumentation. Currently, there are a variety of technologies available to assist surgeons with component alignment, including extramedullary devices, computer-assisted navigation systems (CAS), and patient-specific instrumentation (PSI) that help achieve desired alignment goals.^4,5

Computer-assisted navigation tools were introduced in an effort to improve implant alignment and clinical outcomes compared to traditional mechanical guides. Some argue that the use of computer-assisted surgery has a steep learning curve and successful use is dependent on the user’s experience; however, studies have suggested computer-assisted surgery may allow less experienced surgeons to reliably achieve anticipated intraoperative alignment goals with a low complication rate.^6,7 Various studies have looked at computer-assisted TKA at short to mid-term follow-up, but few studies have reported long-term outcomes.^6-9 de Steiger and colleagues¹⁰ recently found that computer-assisted TKA reduced the overall revision rate for aseptic loosening following TKA in patients younger than age 65 years, which suggests benefit of CAS for younger patients. Short-term follow-up has also shown the benefit of CAS TKA in patients with severe extra-articular deformity, where traditional instrumentation cannot be utilized.¹¹ Currently, there is no consensus that computer-assisted TKA leads to improved postoperative patient reported outcomes, because many studies are limited by study design or small cohorts; however, current literature does show an improvement in component alignment as compared to mechanical instrumentation.^9,12,13 As future implant and position targets are defined to improve implant survivorship and clinical outcomes in total joint arthroplasty, computer-assisted devices will be useful to help achieve more precise and accurate component positioning.

In addition to CAS devices, some companies have sought to improve TKA surgery by introducing PSI. PSI was introduced to improve component alignment in TKA, with the purported advantages of a shorter surgical time, decrease in the number of instruments needed, and improved clinical outcomes. PSI accuracy remains variable, which may be attributed to the various systems and implant designs in each study.^14-17 In addition, advanced preoperative imaging is necessary, which further adds to the overall cost.¹⁷ While the recent advancement in technology may provide decreased costs at the time of surgery, the increased cost and time incurred by the patient preoperatively has not resulted in significantly better clinical outcomes.^18,19 Additionally, recent work has not shown PSI to have superior accuracy as compared to currently available CAS devices.¹⁴ These findings suggest that the additional cost and time incurred by patients may limit the widespread use of PSI.

Although computer navigation has been shown to be more accurate than conventional instrumentation and PSI, the lack of improvement in long-term clinical outcome data has limited its use. In a meta-analysis, Bauwens and colleagues²⁰ suggested that while navigated TKAs have improved component alignment outcomes as compared to conventional surgery, the clinical benefit remains unclear. Less than 5% of surgeons are currently using navigation systems due to the perceived learning curve, cost, additional surgical time, and imaging required to utilize these systems. Certain navigation systems can be seemingly cumbersome, with large consoles, increased number of instruments required, and optical instruments with line-of-sight issues. Recent technological advances have worked to decrease this challenge by using accelerometer- and gyroscope-based electronic components, which combine the accuracy of computer-assisted technology with the ease of use of mechanical guides.

Accelerometer and gyroscope technology systems, such as the iAssist system, are portable devices that do not require a large computer console or navigation arrays. This technology relies on accelerator-based navigation without additional preoperative imaging. A recent study demonstrated the iAssist had reproducible accuracy in component alignment that could be easily incorporated into the operating room without optical trackers.²¹ The use of portable computer-assisted devices provides a more compact and easily accessible technology that can be used to achieve accurate component alignment without additional large equipment in the operating room.²² These new handheld intraoperative tools have been introduced to place implants according to a preoperative plan in order to minimize failure due to preoperative extra-articular deformity or intraoperative technical miscues.²³ Nam and colleagues²⁴ used an accelerometer-based surgical navigation system to perform tibial resections in cadaveric models, and found that the accelerometer-based guide was accurate for tibial resection in both the coronal and sagittal planes. In a prospective randomized controlled trial evaluating 100 patients undergoing a TKA using either an accelerometer-based guide or conventional alignment methods, the authors showed that the accelerometer-based guide decreased outliers in tibial component alignment compared to conventional guides.²⁵ In the accelerometer-based guide cohort, 95.7% of tibial components were within 2° of perpendicular to the tibial mechanical axis, compared to 68.1% in the conventional group (P < .001). These results suggested that portable accelerometer-based navigation allows surgeons to achieve satisfactory tibial component alignment with a decrease in the number of potential outliers.^24,25 Similarly, Bugbee and colleagues²⁶ found that accelerometer-based handheld navigation was accurate for tibial coronal and sagittal alignment and no additional surgical time was required compared to conventional techniques.

The relationship between knee alignment and clinical outcomes for TKA remains controversial. Regardless of the surgeon’s alignment preference, it is important to reliably and accurately execute the preoperative plan in a reproducible fashion. Advances in technology that assist with intraoperative component alignment can be useful, and may help decrease the incidence of implant malalignment in clinical practice.

Preoperative Planning and Intraoperative Technique

Preoperative planning is carried out in a manner identical to the use of conventional mechanical guides. Long leg films are taken for evaluation of overall limb alignment, and calibrated lateral images are taken for templating implant sizes. Lines are drawn on the images to determine the difference between the mechanical and anatomic axis of the femur, and a line drawn perpendicular to the mechanical axis is placed to show the expected bone cut. In similar fashion a perpendicular line to the tibial mechanical axis is also drawn to show the expected tibial resection. This preoperative plan allows the surgeon to have an additional intraoperative guide to ensure accuracy of the computer-assisted device.

After standard exposure, the distal femoral or proximal tibial cut can be made based on surgeon preference. The system being demonstrated in the accompanying photos is the KneeAlign 2 system (OrthAlign).

Distal Femoral Cut

The KneeAlign 2 femoral cutting guide is attached to the distal femur with a central pin that is placed in the middle of the distal femur measured from medial to lateral, and 1 cm anterior to the intercondylar notch. It is important to note that this spot is often more medial than traditionally used for insertion of an intramedullary rod. This central point sets the distal point of the femoral mechanical axis. The device is then held in place with 2 oblique pins, and is solidly fixed to the bone. Using a rotating motion, the femur is rotated around the hip joint. The accelerometer and gyroscope in the unit are able to determine the center of the hip joint from this motion, creating the proximal point of the mechanical axis of the femur. Once the mechanical axis of the femur is determined, varus/valgus and flexion/extension can be adjusted on the guide. One adjustment screw is available for varus/valgus, and a second is available for flexion/extension. Numbers on the device screen show real-time alignment, and are easily adjusted to set the desired alignment (Figure 1). Once alignment is obtained, a mechanical stylus is used to determine depth of resection, and the distal femoral cutting block is pinned. After pinning the block, the 3 pins in the device are removed, and the device is removed from the bone. This leaves only the distal femoral cutting block in place. In experienced hands, this part of the procedure takes less than 3 minutes.

Proximal Tibial Cut

The KneeAlign 2 proximal tibial guide is similar in appearance to a standard mechanical tibial cutting guide. It is attached to the proximal tibia with a spring around the calf and 2 pins that hold the device aligned with the medial third of the tibial tubercle. A stylus is then centered on the anterior cruciate ligament (ACL) footprint, which sets the proximal mechanical axis point of the tibia (Figure 2). An offset number is read off the stylus on the ACL footprint, and this number is matched on the ankle offset portion of the guide. The device has 2 sensors. One sensor is on the chassis of the device, and the other is on a mobile arm. Movements between the 2 are monitored by the accelerometers, allowing for accurate maintenance of alignment position even with motion in the leg. A point is taken from the lateral malleolus and then a second point is taken from the medial malleolus. These points are used to determine the center of the ankle joint, which sets the distal mechanical axis point. Once mechanical axis of the tibia is determined, the tibial cutting guide is pinned in place, and can be adjusted with real-time guidance of the varus/valgus and posterior slope values seen on the device (Figure 3). Cut depth is once again determined with a mechanical stylus.

Limitations

Although these devices have proven to be very accurate, surgeons must continue to recognize that all tools can have errors. With computerized guides of any sort, these errors are usually user errors that cannot be detected by the device. Surgeons need to be able to recognize this and always double-check bone cuts for accuracy. Templating the bone cuts prior to surgery is an effective double-check. In addition, many handheld accelerometer devices do not currently assist with the rotational alignment of the femoral component. This is still performed using the surgeon’s preferred technique, and is a limitation of these systems.

Discussion

Currently, TKA provides satisfactory 10-year results with modern implant designs and survival rates as high as 90% to 95%.^27,28 Even with good survival rates, a percentage of patients fail within the first 5 years.³ At a single institution, 50% of revision TKAs were related to instability, malalignment, or failure of fixation that occurred less than 2 years after the index procedure.²⁹ In general, TKA with mechanical instrumentation provides satisfactory pain relief and postoperative knee function; however, studies have consistently shown that the use of advanced technology decreases the risk of implant malalignment, which may decrease early implant failure rates as compared to mechanical and some PSI.^13,14,22 While there is a paucity of literature that has shown better clinical outcomes with the use of advanced technology, there are studies supporting the notion that proper limb alignment and component positioning improves implant survivorship.^23,30

CAS may have additional advantages if the surgeon chooses to place the TKA in an alignment other than a neutral mechanical axis. Kinematic alignment for TKA has gained increasing popularity, where the target of a neutral mechanical axis alignment is not always the goal.^31,32 The reported benefit is a more natural ligament tension with the hope of improving patient satisfaction. One concern with this technique is that it is a departure from the long-held teaching that a TKA aligned to a neutral mechanical axis is necessary for long-term implant survivorship.^33,34 In addition, if the goal of surgery is to cut the tibia and femur at a specific varus/valgus cut, standard instrumentation may not allow for this level of accuracy. This in turn increases the risk of having a tibial or femoral cut that is outside the commonly accepted standards of alignment, which may lead to early implant failure. If further research suggests alignment is a variable that differs from patient to patient, the use of precise tools to ensure accuracy of executing the preoperatively templated alignment becomes even more important.

As the number of TKAs continues to rise each year, even a small percentage of malaligned knees that go on to revision surgery will create a large burden on the healthcare system.^1,3 Although the short-term clinical benefits of CAS have not shown substantial differences as compared to conventional TKA, the number of knees aligned outside of a desired neutral mechanical axis alignment has been shown in multiple studies to be decreased with the use of advanced technology.^7,12,34 Although CAS is an additional cost to a primary TKA, if the orthopedic community can decrease the number of TKA revisions due to malalignment from 6.6% to nearly zero, this may decrease the revision burden and overall cost to the healthcare system.^1,3

TKA technology continues to evolve, and we must continue to assess each new advance not only to understand how it works, but also to ensure it addresses a specific clinical problem, and to be aware of the costs associated before incorporating it into routine practice. Some argue that the use of advanced technology requires increased surgical time, which in turn ultimately increases costs; however, one study has documented no increase in surgical time with handheld navigation while maintaining the accuracy of the device.³⁴ In addition, no significant radiographic or clinical differences have been found between handheld navigation and larger console CAS systems, but large console systems have been associated with increased surgical times.²² The use of handheld accelerometer- and gyroscope-based guides has proven to provide reliable coronal and sagittal implant alignment that can easily be incorporated into the operating room. More widespread use of such technology will help decrease alignment outliers for TKA, and future long-term clinical outcome studies will be necessary to assess functional outcomes.

Conclusion

Advanced computer based technology offers an additional tool to the surgeon for reliably improving component positioning during TKA. The use of handheld accelerometer- and gyroscope-based guides increases the accuracy of component placement while decreasing the incidence of outliers compared to standard mechanical guides, without the need for a large computer console. Long-term radiographic and patient-reported outcomes are necessary to further validate these devices.

Total knee arthroplasty (TKA) continues to be a widely utilized treatment option for end-stage knee osteoarthritis, and the number of patients undergoing TKA is projected to continually increase over the next decade.¹ Although TKA is highly successful for many patients, studies continue to report that approximately 20% of patients are dissatisfied after undergoing TKA, and nearly 25% of knee revisions are performed for instability or malalignment.^2,3 Technological advances have been developed to help improve clinical outcomes and implant survivorship. Over the past decade, computer navigation and intraoperative guides have been introduced to help control surgical variables and overcome the limitations and inaccuracies of traditional mechanical instrumentation. Currently, there are a variety of technologies available to assist surgeons with component alignment, including extramedullary devices, computer-assisted navigation systems (CAS), and patient-specific instrumentation (PSI) that help achieve desired alignment goals.^4,5

Computer-assisted navigation tools were introduced in an effort to improve implant alignment and clinical outcomes compared to traditional mechanical guides. Some argue that the use of computer-assisted surgery has a steep learning curve and successful use is dependent on the user’s experience; however, studies have suggested computer-assisted surgery may allow less experienced surgeons to reliably achieve anticipated intraoperative alignment goals with a low complication rate.^6,7 Various studies have looked at computer-assisted TKA at short to mid-term follow-up, but few studies have reported long-term outcomes.^6-9 de Steiger and colleagues¹⁰ recently found that computer-assisted TKA reduced the overall revision rate for aseptic loosening following TKA in patients younger than age 65 years, which suggests benefit of CAS for younger patients. Short-term follow-up has also shown the benefit of CAS TKA in patients with severe extra-articular deformity, where traditional instrumentation cannot be utilized.¹¹ Currently, there is no consensus that computer-assisted TKA leads to improved postoperative patient reported outcomes, because many studies are limited by study design or small cohorts; however, current literature does show an improvement in component alignment as compared to mechanical instrumentation.^9,12,13 As future implant and position targets are defined to improve implant survivorship and clinical outcomes in total joint arthroplasty, computer-assisted devices will be useful to help achieve more precise and accurate component positioning.

In addition to CAS devices, some companies have sought to improve TKA surgery by introducing PSI. PSI was introduced to improve component alignment in TKA, with the purported advantages of a shorter surgical time, decrease in the number of instruments needed, and improved clinical outcomes. PSI accuracy remains variable, which may be attributed to the various systems and implant designs in each study.^14-17 In addition, advanced preoperative imaging is necessary, which further adds to the overall cost.¹⁷ While the recent advancement in technology may provide decreased costs at the time of surgery, the increased cost and time incurred by the patient preoperatively has not resulted in significantly better clinical outcomes.^18,19 Additionally, recent work has not shown PSI to have superior accuracy as compared to currently available CAS devices.¹⁴ These findings suggest that the additional cost and time incurred by patients may limit the widespread use of PSI.

Although computer navigation has been shown to be more accurate than conventional instrumentation and PSI, the lack of improvement in long-term clinical outcome data has limited its use. In a meta-analysis, Bauwens and colleagues²⁰ suggested that while navigated TKAs have improved component alignment outcomes as compared to conventional surgery, the clinical benefit remains unclear. Less than 5% of surgeons are currently using navigation systems due to the perceived learning curve, cost, additional surgical time, and imaging required to utilize these systems. Certain navigation systems can be seemingly cumbersome, with large consoles, increased number of instruments required, and optical instruments with line-of-sight issues. Recent technological advances have worked to decrease this challenge by using accelerometer- and gyroscope-based electronic components, which combine the accuracy of computer-assisted technology with the ease of use of mechanical guides.

Accelerometer and gyroscope technology systems, such as the iAssist system, are portable devices that do not require a large computer console or navigation arrays. This technology relies on accelerator-based navigation without additional preoperative imaging. A recent study demonstrated the iAssist had reproducible accuracy in component alignment that could be easily incorporated into the operating room without optical trackers.²¹ The use of portable computer-assisted devices provides a more compact and easily accessible technology that can be used to achieve accurate component alignment without additional large equipment in the operating room.²² These new handheld intraoperative tools have been introduced to place implants according to a preoperative plan in order to minimize failure due to preoperative extra-articular deformity or intraoperative technical miscues.²³ Nam and colleagues²⁴ used an accelerometer-based surgical navigation system to perform tibial resections in cadaveric models, and found that the accelerometer-based guide was accurate for tibial resection in both the coronal and sagittal planes. In a prospective randomized controlled trial evaluating 100 patients undergoing a TKA using either an accelerometer-based guide or conventional alignment methods, the authors showed that the accelerometer-based guide decreased outliers in tibial component alignment compared to conventional guides.²⁵ In the accelerometer-based guide cohort, 95.7% of tibial components were within 2° of perpendicular to the tibial mechanical axis, compared to 68.1% in the conventional group (P < .001). These results suggested that portable accelerometer-based navigation allows surgeons to achieve satisfactory tibial component alignment with a decrease in the number of potential outliers.^24,25 Similarly, Bugbee and colleagues²⁶ found that accelerometer-based handheld navigation was accurate for tibial coronal and sagittal alignment and no additional surgical time was required compared to conventional techniques.

The relationship between knee alignment and clinical outcomes for TKA remains controversial. Regardless of the surgeon’s alignment preference, it is important to reliably and accurately execute the preoperative plan in a reproducible fashion. Advances in technology that assist with intraoperative component alignment can be useful, and may help decrease the incidence of implant malalignment in clinical practice.

Preoperative Planning and Intraoperative Technique

Preoperative planning is carried out in a manner identical to the use of conventional mechanical guides. Long leg films are taken for evaluation of overall limb alignment, and calibrated lateral images are taken for templating implant sizes. Lines are drawn on the images to determine the difference between the mechanical and anatomic axis of the femur, and a line drawn perpendicular to the mechanical axis is placed to show the expected bone cut. In similar fashion a perpendicular line to the tibial mechanical axis is also drawn to show the expected tibial resection. This preoperative plan allows the surgeon to have an additional intraoperative guide to ensure accuracy of the computer-assisted device.

After standard exposure, the distal femoral or proximal tibial cut can be made based on surgeon preference. The system being demonstrated in the accompanying photos is the KneeAlign 2 system (OrthAlign).

Distal Femoral Cut

The KneeAlign 2 femoral cutting guide is attached to the distal femur with a central pin that is placed in the middle of the distal femur measured from medial to lateral, and 1 cm anterior to the intercondylar notch. It is important to note that this spot is often more medial than traditionally used for insertion of an intramedullary rod. This central point sets the distal point of the femoral mechanical axis. The device is then held in place with 2 oblique pins, and is solidly fixed to the bone. Using a rotating motion, the femur is rotated around the hip joint. The accelerometer and gyroscope in the unit are able to determine the center of the hip joint from this motion, creating the proximal point of the mechanical axis of the femur. Once the mechanical axis of the femur is determined, varus/valgus and flexion/extension can be adjusted on the guide. One adjustment screw is available for varus/valgus, and a second is available for flexion/extension. Numbers on the device screen show real-time alignment, and are easily adjusted to set the desired alignment (Figure 1). Once alignment is obtained, a mechanical stylus is used to determine depth of resection, and the distal femoral cutting block is pinned. After pinning the block, the 3 pins in the device are removed, and the device is removed from the bone. This leaves only the distal femoral cutting block in place. In experienced hands, this part of the procedure takes less than 3 minutes.

Proximal Tibial Cut

The KneeAlign 2 proximal tibial guide is similar in appearance to a standard mechanical tibial cutting guide. It is attached to the proximal tibia with a spring around the calf and 2 pins that hold the device aligned with the medial third of the tibial tubercle. A stylus is then centered on the anterior cruciate ligament (ACL) footprint, which sets the proximal mechanical axis point of the tibia (Figure 2). An offset number is read off the stylus on the ACL footprint, and this number is matched on the ankle offset portion of the guide. The device has 2 sensors. One sensor is on the chassis of the device, and the other is on a mobile arm. Movements between the 2 are monitored by the accelerometers, allowing for accurate maintenance of alignment position even with motion in the leg. A point is taken from the lateral malleolus and then a second point is taken from the medial malleolus. These points are used to determine the center of the ankle joint, which sets the distal mechanical axis point. Once mechanical axis of the tibia is determined, the tibial cutting guide is pinned in place, and can be adjusted with real-time guidance of the varus/valgus and posterior slope values seen on the device (Figure 3). Cut depth is once again determined with a mechanical stylus.

Limitations

Although these devices have proven to be very accurate, surgeons must continue to recognize that all tools can have errors. With computerized guides of any sort, these errors are usually user errors that cannot be detected by the device. Surgeons need to be able to recognize this and always double-check bone cuts for accuracy. Templating the bone cuts prior to surgery is an effective double-check. In addition, many handheld accelerometer devices do not currently assist with the rotational alignment of the femoral component. This is still performed using the surgeon’s preferred technique, and is a limitation of these systems.

Discussion

Currently, TKA provides satisfactory 10-year results with modern implant designs and survival rates as high as 90% to 95%.^27,28 Even with good survival rates, a percentage of patients fail within the first 5 years.³ At a single institution, 50% of revision TKAs were related to instability, malalignment, or failure of fixation that occurred less than 2 years after the index procedure.²⁹ In general, TKA with mechanical instrumentation provides satisfactory pain relief and postoperative knee function; however, studies have consistently shown that the use of advanced technology decreases the risk of implant malalignment, which may decrease early implant failure rates as compared to mechanical and some PSI.^13,14,22 While there is a paucity of literature that has shown better clinical outcomes with the use of advanced technology, there are studies supporting the notion that proper limb alignment and component positioning improves implant survivorship.^23,30

CAS may have additional advantages if the surgeon chooses to place the TKA in an alignment other than a neutral mechanical axis. Kinematic alignment for TKA has gained increasing popularity, where the target of a neutral mechanical axis alignment is not always the goal.^31,32 The reported benefit is a more natural ligament tension with the hope of improving patient satisfaction. One concern with this technique is that it is a departure from the long-held teaching that a TKA aligned to a neutral mechanical axis is necessary for long-term implant survivorship.^33,34 In addition, if the goal of surgery is to cut the tibia and femur at a specific varus/valgus cut, standard instrumentation may not allow for this level of accuracy. This in turn increases the risk of having a tibial or femoral cut that is outside the commonly accepted standards of alignment, which may lead to early implant failure. If further research suggests alignment is a variable that differs from patient to patient, the use of precise tools to ensure accuracy of executing the preoperatively templated alignment becomes even more important.

As the number of TKAs continues to rise each year, even a small percentage of malaligned knees that go on to revision surgery will create a large burden on the healthcare system.^1,3 Although the short-term clinical benefits of CAS have not shown substantial differences as compared to conventional TKA, the number of knees aligned outside of a desired neutral mechanical axis alignment has been shown in multiple studies to be decreased with the use of advanced technology.^7,12,34 Although CAS is an additional cost to a primary TKA, if the orthopedic community can decrease the number of TKA revisions due to malalignment from 6.6% to nearly zero, this may decrease the revision burden and overall cost to the healthcare system.^1,3

TKA technology continues to evolve, and we must continue to assess each new advance not only to understand how it works, but also to ensure it addresses a specific clinical problem, and to be aware of the costs associated before incorporating it into routine practice. Some argue that the use of advanced technology requires increased surgical time, which in turn ultimately increases costs; however, one study has documented no increase in surgical time with handheld navigation while maintaining the accuracy of the device.³⁴ In addition, no significant radiographic or clinical differences have been found between handheld navigation and larger console CAS systems, but large console systems have been associated with increased surgical times.²² The use of handheld accelerometer- and gyroscope-based guides has proven to provide reliable coronal and sagittal implant alignment that can easily be incorporated into the operating room. More widespread use of such technology will help decrease alignment outliers for TKA, and future long-term clinical outcome studies will be necessary to assess functional outcomes.

Conclusion

Advanced computer based technology offers an additional tool to the surgeon for reliably improving component positioning during TKA. The use of handheld accelerometer- and gyroscope-based guides increases the accuracy of component placement while decreasing the incidence of outliers compared to standard mechanical guides, without the need for a large computer console. Long-term radiographic and patient-reported outcomes are necessary to further validate these devices.

Total knee arthroplasty (TKA) continues to be a widely utilized treatment option for end-stage knee osteoarthritis, and the number of patients undergoing TKA is projected to continually increase over the next decade.¹ Although TKA is highly successful for many patients, studies continue to report that approximately 20% of patients are dissatisfied after undergoing TKA, and nearly 25% of knee revisions are performed for instability or malalignment.^2,3 Technological advances have been developed to help improve clinical outcomes and implant survivorship. Over the past decade, computer navigation and intraoperative guides have been introduced to help control surgical variables and overcome the limitations and inaccuracies of traditional mechanical instrumentation. Currently, there are a variety of technologies available to assist surgeons with component alignment, including extramedullary devices, computer-assisted navigation systems (CAS), and patient-specific instrumentation (PSI) that help achieve desired alignment goals.^4,5

Computer-assisted navigation tools were introduced in an effort to improve implant alignment and clinical outcomes compared to traditional mechanical guides. Some argue that the use of computer-assisted surgery has a steep learning curve and successful use is dependent on the user’s experience; however, studies have suggested computer-assisted surgery may allow less experienced surgeons to reliably achieve anticipated intraoperative alignment goals with a low complication rate.^6,7 Various studies have looked at computer-assisted TKA at short to mid-term follow-up, but few studies have reported long-term outcomes.^6-9 de Steiger and colleagues¹⁰ recently found that computer-assisted TKA reduced the overall revision rate for aseptic loosening following TKA in patients younger than age 65 years, which suggests benefit of CAS for younger patients. Short-term follow-up has also shown the benefit of CAS TKA in patients with severe extra-articular deformity, where traditional instrumentation cannot be utilized.¹¹ Currently, there is no consensus that computer-assisted TKA leads to improved postoperative patient reported outcomes, because many studies are limited by study design or small cohorts; however, current literature does show an improvement in component alignment as compared to mechanical instrumentation.^9,12,13 As future implant and position targets are defined to improve implant survivorship and clinical outcomes in total joint arthroplasty, computer-assisted devices will be useful to help achieve more precise and accurate component positioning.

In addition to CAS devices, some companies have sought to improve TKA surgery by introducing PSI. PSI was introduced to improve component alignment in TKA, with the purported advantages of a shorter surgical time, decrease in the number of instruments needed, and improved clinical outcomes. PSI accuracy remains variable, which may be attributed to the various systems and implant designs in each study.^14-17 In addition, advanced preoperative imaging is necessary, which further adds to the overall cost.¹⁷ While the recent advancement in technology may provide decreased costs at the time of surgery, the increased cost and time incurred by the patient preoperatively has not resulted in significantly better clinical outcomes.^18,19 Additionally, recent work has not shown PSI to have superior accuracy as compared to currently available CAS devices.¹⁴ These findings suggest that the additional cost and time incurred by patients may limit the widespread use of PSI.

Although computer navigation has been shown to be more accurate than conventional instrumentation and PSI, the lack of improvement in long-term clinical outcome data has limited its use. In a meta-analysis, Bauwens and colleagues²⁰ suggested that while navigated TKAs have improved component alignment outcomes as compared to conventional surgery, the clinical benefit remains unclear. Less than 5% of surgeons are currently using navigation systems due to the perceived learning curve, cost, additional surgical time, and imaging required to utilize these systems. Certain navigation systems can be seemingly cumbersome, with large consoles, increased number of instruments required, and optical instruments with line-of-sight issues. Recent technological advances have worked to decrease this challenge by using accelerometer- and gyroscope-based electronic components, which combine the accuracy of computer-assisted technology with the ease of use of mechanical guides.

Accelerometer and gyroscope technology systems, such as the iAssist system, are portable devices that do not require a large computer console or navigation arrays. This technology relies on accelerator-based navigation without additional preoperative imaging. A recent study demonstrated the iAssist had reproducible accuracy in component alignment that could be easily incorporated into the operating room without optical trackers.²¹ The use of portable computer-assisted devices provides a more compact and easily accessible technology that can be used to achieve accurate component alignment without additional large equipment in the operating room.²² These new handheld intraoperative tools have been introduced to place implants according to a preoperative plan in order to minimize failure due to preoperative extra-articular deformity or intraoperative technical miscues.²³ Nam and colleagues²⁴ used an accelerometer-based surgical navigation system to perform tibial resections in cadaveric models, and found that the accelerometer-based guide was accurate for tibial resection in both the coronal and sagittal planes. In a prospective randomized controlled trial evaluating 100 patients undergoing a TKA using either an accelerometer-based guide or conventional alignment methods, the authors showed that the accelerometer-based guide decreased outliers in tibial component alignment compared to conventional guides.²⁵ In the accelerometer-based guide cohort, 95.7% of tibial components were within 2° of perpendicular to the tibial mechanical axis, compared to 68.1% in the conventional group (P < .001). These results suggested that portable accelerometer-based navigation allows surgeons to achieve satisfactory tibial component alignment with a decrease in the number of potential outliers.^24,25 Similarly, Bugbee and colleagues²⁶ found that accelerometer-based handheld navigation was accurate for tibial coronal and sagittal alignment and no additional surgical time was required compared to conventional techniques.

The relationship between knee alignment and clinical outcomes for TKA remains controversial. Regardless of the surgeon’s alignment preference, it is important to reliably and accurately execute the preoperative plan in a reproducible fashion. Advances in technology that assist with intraoperative component alignment can be useful, and may help decrease the incidence of implant malalignment in clinical practice.

Preoperative Planning and Intraoperative Technique

Preoperative planning is carried out in a manner identical to the use of conventional mechanical guides. Long leg films are taken for evaluation of overall limb alignment, and calibrated lateral images are taken for templating implant sizes. Lines are drawn on the images to determine the difference between the mechanical and anatomic axis of the femur, and a line drawn perpendicular to the mechanical axis is placed to show the expected bone cut. In similar fashion a perpendicular line to the tibial mechanical axis is also drawn to show the expected tibial resection. This preoperative plan allows the surgeon to have an additional intraoperative guide to ensure accuracy of the computer-assisted device.

After standard exposure, the distal femoral or proximal tibial cut can be made based on surgeon preference. The system being demonstrated in the accompanying photos is the KneeAlign 2 system (OrthAlign).

Distal Femoral Cut

The KneeAlign 2 femoral cutting guide is attached to the distal femur with a central pin that is placed in the middle of the distal femur measured from medial to lateral, and 1 cm anterior to the intercondylar notch. It is important to note that this spot is often more medial than traditionally used for insertion of an intramedullary rod. This central point sets the distal point of the femoral mechanical axis. The device is then held in place with 2 oblique pins, and is solidly fixed to the bone. Using a rotating motion, the femur is rotated around the hip joint. The accelerometer and gyroscope in the unit are able to determine the center of the hip joint from this motion, creating the proximal point of the mechanical axis of the femur. Once the mechanical axis of the femur is determined, varus/valgus and flexion/extension can be adjusted on the guide. One adjustment screw is available for varus/valgus, and a second is available for flexion/extension. Numbers on the device screen show real-time alignment, and are easily adjusted to set the desired alignment (Figure 1). Once alignment is obtained, a mechanical stylus is used to determine depth of resection, and the distal femoral cutting block is pinned. After pinning the block, the 3 pins in the device are removed, and the device is removed from the bone. This leaves only the distal femoral cutting block in place. In experienced hands, this part of the procedure takes less than 3 minutes.

Proximal Tibial Cut

The KneeAlign 2 proximal tibial guide is similar in appearance to a standard mechanical tibial cutting guide. It is attached to the proximal tibia with a spring around the calf and 2 pins that hold the device aligned with the medial third of the tibial tubercle. A stylus is then centered on the anterior cruciate ligament (ACL) footprint, which sets the proximal mechanical axis point of the tibia (Figure 2). An offset number is read off the stylus on the ACL footprint, and this number is matched on the ankle offset portion of the guide. The device has 2 sensors. One sensor is on the chassis of the device, and the other is on a mobile arm. Movements between the 2 are monitored by the accelerometers, allowing for accurate maintenance of alignment position even with motion in the leg. A point is taken from the lateral malleolus and then a second point is taken from the medial malleolus. These points are used to determine the center of the ankle joint, which sets the distal mechanical axis point. Once mechanical axis of the tibia is determined, the tibial cutting guide is pinned in place, and can be adjusted with real-time guidance of the varus/valgus and posterior slope values seen on the device (Figure 3). Cut depth is once again determined with a mechanical stylus.

Limitations

Although these devices have proven to be very accurate, surgeons must continue to recognize that all tools can have errors. With computerized guides of any sort, these errors are usually user errors that cannot be detected by the device. Surgeons need to be able to recognize this and always double-check bone cuts for accuracy. Templating the bone cuts prior to surgery is an effective double-check. In addition, many handheld accelerometer devices do not currently assist with the rotational alignment of the femoral component. This is still performed using the surgeon’s preferred technique, and is a limitation of these systems.

Discussion

Currently, TKA provides satisfactory 10-year results with modern implant designs and survival rates as high as 90% to 95%.^27,28 Even with good survival rates, a percentage of patients fail within the first 5 years.³ At a single institution, 50% of revision TKAs were related to instability, malalignment, or failure of fixation that occurred less than 2 years after the index procedure.²⁹ In general, TKA with mechanical instrumentation provides satisfactory pain relief and postoperative knee function; however, studies have consistently shown that the use of advanced technology decreases the risk of implant malalignment, which may decrease early implant failure rates as compared to mechanical and some PSI.^13,14,22 While there is a paucity of literature that has shown better clinical outcomes with the use of advanced technology, there are studies supporting the notion that proper limb alignment and component positioning improves implant survivorship.^23,30

CAS may have additional advantages if the surgeon chooses to place the TKA in an alignment other than a neutral mechanical axis. Kinematic alignment for TKA has gained increasing popularity, where the target of a neutral mechanical axis alignment is not always the goal.^31,32 The reported benefit is a more natural ligament tension with the hope of improving patient satisfaction. One concern with this technique is that it is a departure from the long-held teaching that a TKA aligned to a neutral mechanical axis is necessary for long-term implant survivorship.^33,34 In addition, if the goal of surgery is to cut the tibia and femur at a specific varus/valgus cut, standard instrumentation may not allow for this level of accuracy. This in turn increases the risk of having a tibial or femoral cut that is outside the commonly accepted standards of alignment, which may lead to early implant failure. If further research suggests alignment is a variable that differs from patient to patient, the use of precise tools to ensure accuracy of executing the preoperatively templated alignment becomes even more important.

As the number of TKAs continues to rise each year, even a small percentage of malaligned knees that go on to revision surgery will create a large burden on the healthcare system.^1,3 Although the short-term clinical benefits of CAS have not shown substantial differences as compared to conventional TKA, the number of knees aligned outside of a desired neutral mechanical axis alignment has been shown in multiple studies to be decreased with the use of advanced technology.^7,12,34 Although CAS is an additional cost to a primary TKA, if the orthopedic community can decrease the number of TKA revisions due to malalignment from 6.6% to nearly zero, this may decrease the revision burden and overall cost to the healthcare system.^1,3

TKA technology continues to evolve, and we must continue to assess each new advance not only to understand how it works, but also to ensure it addresses a specific clinical problem, and to be aware of the costs associated before incorporating it into routine practice. Some argue that the use of advanced technology requires increased surgical time, which in turn ultimately increases costs; however, one study has documented no increase in surgical time with handheld navigation while maintaining the accuracy of the device.³⁴ In addition, no significant radiographic or clinical differences have been found between handheld navigation and larger console CAS systems, but large console systems have been associated with increased surgical times.²² The use of handheld accelerometer- and gyroscope-based guides has proven to provide reliable coronal and sagittal implant alignment that can easily be incorporated into the operating room. More widespread use of such technology will help decrease alignment outliers for TKA, and future long-term clinical outcome studies will be necessary to assess functional outcomes.

Conclusion

Advanced computer based technology offers an additional tool to the surgeon for reliably improving component positioning during TKA. The use of handheld accelerometer- and gyroscope-based guides increases the accuracy of component placement while decreasing the incidence of outliers compared to standard mechanical guides, without the need for a large computer console. Long-term radiographic and patient-reported outcomes are necessary to further validate these devices.

A transition is underway at AJO. As we discuss the future of the “new journal,” I often think about the future of orthopedics. I’ve decided my vision of the future is centered on 3 components. First, there will be a change in our training paradigm from an apprenticeship model to standardized training, where core competencies must be demonstrated for certification. Second, robots and computers will improve our diagnostic accuracy and will allow us to perform surgery with improved component positioning, while biologics and genetic analysis will accelerate nature’s ability to heal, and perhaps regenerate, injured tissue. Finally, computerized algorithms and technologically improved surgical outcomes will allow us to deliver high-quality healthcare at a lower cost, producing the value our current health systems are striving for, and leveling the playing field between high-volume centers and rural institutions forced to offer complete service lines.

In this issue, we examine robotic-assisted arthroplasty and its role in modern healthcare. I think the best argument for robots in the operating room might come from the airline industry. I’m sitting on a plane as I write this, without once thinking about how much experience my pilot has in the cockpit. I know our pilot has demonstrated the core competencies required to safely operate the plane, trained on emergency simulations, and logged the necessary hours before being handed the controls. I also know that the instrumentation is so good that the plane can essentially fly itself, making pilot skill and experience less relevant. In short, technology has, in all but rare circumstances, made our pilots virtually interchangeable.

Unfortunately, none of the above is true in orthopedics. Our residents are not required to demonstrate their skills before any licensing authority, simulator training is not available in all programs, and we’ve limited resident work hours. Yet it’s that same interchangeability that most healthcare models assume. No one argues that high-volume centers have better results when it comes to arthroplasty, but only a small percentage of total joints are currently performed at these centers. Surgeon training remains a virtual apprenticeship, lacking standardization, and resulting in a wide variation in skill and experience. Surgical residencies are not awarded based on dexterity, and work hour restrictions, Relative Value Unit-based academic contracts, patient expectations, and staffing pressures can lead to reduced hands-on experience for trainees. The results: an entire generation of surgeons with decreased repetitions in the operating room when compared to their predecessors.

That’s why I believe we are on the cusp of a transition in the operating room, and that computer-assisted surgery is here to stay. While studies exist showing robots have tighter control over virtually every identifiable metric, little data currently exists supporting enhanced long-term outcomes. But as long as component malposition remains a leading cause of early failure, there will be a place for technologies that enhance accuracy of component placement. At odds with the drive for increased technology is the necessity of cost containment, leading us to question the value of robotic-assisted surgery, and whether the improved metrics are clinically important and the additional potential complications are worth the risk.

In the articles in this issue, we will take a critical look at the benefits and drawbacks of robotic surgery. As you read, think about the future of orthopedics and how you will implement new technology into your practice. A transition is coming, and I invite each of you to consider leading it.

A transition is underway at AJO. As we discuss the future of the “new journal,” I often think about the future of orthopedics. I’ve decided my vision of the future is centered on 3 components. First, there will be a change in our training paradigm from an apprenticeship model to standardized training, where core competencies must be demonstrated for certification. Second, robots and computers will improve our diagnostic accuracy and will allow us to perform surgery with improved component positioning, while biologics and genetic analysis will accelerate nature’s ability to heal, and perhaps regenerate, injured tissue. Finally, computerized algorithms and technologically improved surgical outcomes will allow us to deliver high-quality healthcare at a lower cost, producing the value our current health systems are striving for, and leveling the playing field between high-volume centers and rural institutions forced to offer complete service lines.

In this issue, we examine robotic-assisted arthroplasty and its role in modern healthcare. I think the best argument for robots in the operating room might come from the airline industry. I’m sitting on a plane as I write this, without once thinking about how much experience my pilot has in the cockpit. I know our pilot has demonstrated the core competencies required to safely operate the plane, trained on emergency simulations, and logged the necessary hours before being handed the controls. I also know that the instrumentation is so good that the plane can essentially fly itself, making pilot skill and experience less relevant. In short, technology has, in all but rare circumstances, made our pilots virtually interchangeable.

Unfortunately, none of the above is true in orthopedics. Our residents are not required to demonstrate their skills before any licensing authority, simulator training is not available in all programs, and we’ve limited resident work hours. Yet it’s that same interchangeability that most healthcare models assume. No one argues that high-volume centers have better results when it comes to arthroplasty, but only a small percentage of total joints are currently performed at these centers. Surgeon training remains a virtual apprenticeship, lacking standardization, and resulting in a wide variation in skill and experience. Surgical residencies are not awarded based on dexterity, and work hour restrictions, Relative Value Unit-based academic contracts, patient expectations, and staffing pressures can lead to reduced hands-on experience for trainees. The results: an entire generation of surgeons with decreased repetitions in the operating room when compared to their predecessors.

That’s why I believe we are on the cusp of a transition in the operating room, and that computer-assisted surgery is here to stay. While studies exist showing robots have tighter control over virtually every identifiable metric, little data currently exists supporting enhanced long-term outcomes. But as long as component malposition remains a leading cause of early failure, there will be a place for technologies that enhance accuracy of component placement. At odds with the drive for increased technology is the necessity of cost containment, leading us to question the value of robotic-assisted surgery, and whether the improved metrics are clinically important and the additional potential complications are worth the risk.

In the articles in this issue, we will take a critical look at the benefits and drawbacks of robotic surgery. As you read, think about the future of orthopedics and how you will implement new technology into your practice. A transition is coming, and I invite each of you to consider leading it.

A transition is underway at AJO. As we discuss the future of the “new journal,” I often think about the future of orthopedics. I’ve decided my vision of the future is centered on 3 components. First, there will be a change in our training paradigm from an apprenticeship model to standardized training, where core competencies must be demonstrated for certification. Second, robots and computers will improve our diagnostic accuracy and will allow us to perform surgery with improved component positioning, while biologics and genetic analysis will accelerate nature’s ability to heal, and perhaps regenerate, injured tissue. Finally, computerized algorithms and technologically improved surgical outcomes will allow us to deliver high-quality healthcare at a lower cost, producing the value our current health systems are striving for, and leveling the playing field between high-volume centers and rural institutions forced to offer complete service lines.

In this issue, we examine robotic-assisted arthroplasty and its role in modern healthcare. I think the best argument for robots in the operating room might come from the airline industry. I’m sitting on a plane as I write this, without once thinking about how much experience my pilot has in the cockpit. I know our pilot has demonstrated the core competencies required to safely operate the plane, trained on emergency simulations, and logged the necessary hours before being handed the controls. I also know that the instrumentation is so good that the plane can essentially fly itself, making pilot skill and experience less relevant. In short, technology has, in all but rare circumstances, made our pilots virtually interchangeable.

Unfortunately, none of the above is true in orthopedics. Our residents are not required to demonstrate their skills before any licensing authority, simulator training is not available in all programs, and we’ve limited resident work hours. Yet it’s that same interchangeability that most healthcare models assume. No one argues that high-volume centers have better results when it comes to arthroplasty, but only a small percentage of total joints are currently performed at these centers. Surgeon training remains a virtual apprenticeship, lacking standardization, and resulting in a wide variation in skill and experience. Surgical residencies are not awarded based on dexterity, and work hour restrictions, Relative Value Unit-based academic contracts, patient expectations, and staffing pressures can lead to reduced hands-on experience for trainees. The results: an entire generation of surgeons with decreased repetitions in the operating room when compared to their predecessors.

That’s why I believe we are on the cusp of a transition in the operating room, and that computer-assisted surgery is here to stay. While studies exist showing robots have tighter control over virtually every identifiable metric, little data currently exists supporting enhanced long-term outcomes. But as long as component malposition remains a leading cause of early failure, there will be a place for technologies that enhance accuracy of component placement. At odds with the drive for increased technology is the necessity of cost containment, leading us to question the value of robotic-assisted surgery, and whether the improved metrics are clinically important and the additional potential complications are worth the risk.

In the articles in this issue, we will take a critical look at the benefits and drawbacks of robotic surgery. As you read, think about the future of orthopedics and how you will implement new technology into your practice. A transition is coming, and I invite each of you to consider leading it.

Unicompartmental knee arthroplasty (UKA) and total knee arthroplasty (TKA) are 2 reliable treatment options for patients with primary osteoarthritis. Recently published systematic reviews of cohort studies have shown that 10-year survivorship of medial and lateral UKA is 92% and 91%, respectively,¹ while 10-year survivorship of TKA in cohort studies is 95%.² National and annual registries show a similar trend, although the reported survivorship is lower.^1,3-7

In order to improve these survivorship rates, the surgical variables that can intraoperatively be controlled by the orthopedic surgeon have been evaluated. These variables include lower leg alignment, soft tissue balance, joint line maintenance, and alignment, size, and fixation of the tibial and femoral component. Several studies have shown that tight control of lower leg alignment,^8-14 balancing of the soft tissues,^15-19 joint line maintenance,^20-23 component alignment,^24-28 component size,^29-34 and component fixation^35-40 can improve the outcomes of UKA and TKA. As a result, over the past 2 decades, several computer-assisted surgery systems have been developed with the goal of more accurate and reliable control of these factors, and thus improved outcomes of knee arthroplasty.

These systems differ with regard to the number and type of variables they control. Computer navigation systems aim to control one or more of these surgical variables, and several meta-analyses have shown that these systems, when compared to conventional surgery, improve mechanical axis accuracy, decrease the risk for mechanical axis outliers, and improve component positioning in TKA^41-49 and UKA surgery.^50,51 Interestingly, however, meta-analyses have failed to show the expected superiority in clinical outcomes following computer navigation compared to conventional knee arthroplasty.^48,52-55 Furthermore, authors have shown that, despite the fact that computer-navigated surgery increases the accuracy of mechanical alignment and surgical cutting, there is still room for improvement.⁵⁶ As a consequence, robotic-assisted systems have been developed.

Similar to computer navigation, these robotic-assisted systems aim to control the surgical variables; in addition, they aim to improve the surgical precision of the procedure. Interestingly, 2 recent studies have shown that robotic-assisted systems are superior to computer navigation systems with regard to less cutting time and less resection deviations in coronal and sagittal plane in a cadaveric study,⁵⁷ and shorter total surgery time, more accurate mechanical axis, and shorter hospital stay in a clinical study.⁵⁸ Although these results are promising, the exact role of robotic surgery in knee arthroplasty remains unclear. In this review, we aim to report the current state of robotic-assisted knee arthroplasty by discussing (1) the different robotic-assisted knee arthroplasty systems that are available for UKA and TKA surgery, (2) studies that assessed the role of robotic-assisted knee arthroplasty in controlling the aforementioned surgical variables, (3) cadaveric and clinical comparative studies that compared how accurate robotic-assisted and conventional knee surgery control these surgical variables, and (4) studies that assessed the cost-effectiveness of robotic-assisted knee arthroplasty surgery.

Robotic-Assisted Knee Arthroplasty Systems

Several systems have been developed over the years for knee arthroplasty, and these are usually defined as active, semi-active, or passive.⁵⁹ Active systems are capable of performing tasks or processes autonomously under the watchful eye of the surgeon, while passive systems do not perform actions independently but provide the surgeon with information. In semi-active systems, the surgical action is physically constrained in order to follow a predefined strategy.

In the United States, 3 robotic systems are FDA-approved for knee arthroplasty. The Stryker/Mako haptic guided robot (Mako Surgical Corp.) was introduced in 2005 and has been used for over 50,000 UKA procedures (Figure 1). There are nearly 300 robotic systems used nationally, as it has 20% of the market share for UKA in the United States. The Mako system is a semi-active tactile robotic system that requires preoperative imaging, after which a preoperative planning is performed. Intraoperatively, the robotic arm is under direct surgeon control and gives real-time tactile feedback during the procedure (Figure 2).

Furthermore, the surgeon can intraoperatively virtually adjust component positioning and alignment and move the knee through the range of motion, after which the system can provide information on alignment, component position, and balance of the soft tissue (eg, if the knee is overtight or lax through the flexion-arch).⁶⁰ This system has a burr that resects the bone and when the surgeon directs the burr outside the preplanned area, the burr stops and prevents unnecessary and unwanted resections (Figure 3).

The Navio Precision Free-Hand Sculptor (PFS) system (Blue Belt Technologies) has been used for 1500 UKA procedures, with 50 robots in use in the United States (Figure 4). This system is an image-free semi-active robotic system and has the same characteristics as the aforementioned Mako system.⁶¹ Finally, the OmniBotic robotic system (Omnilife Science) has been released for TKA and has been used for over 7300 procedures (Figure 5). This system has an automated cutting-guide technique in which the surgeon designs a virtual plan on the computer system. After this, the cutting-guides are placed by the robotic system at the planned location for all 5 femoral cuts (ie, distal, anterior chamfer, anterior, posterior chamfer, and posterior) and the surgeon then makes the final cuts.^57,62

Three robotic systems for knee arthroplasty surgery have been used in Europe. The Caspar system (URS Ortho) is an active robotic system in which a computed tomography (CT) scan is performed preoperatively, after which a virtual implantation is performed on the screen. The surgeon can then obtain information on lower leg alignment, gap balancing, and component positioning, and after an operative plan is made, the surgical resections are performed by the robot. Reflective markers are attached to the leg and all robotic movements are monitored using an infrared camera system. Any undesired motion will be detected by this camera system and will stop all movements.⁶³ A second and more frequently reported system in the literature is the active Robodoc surgical system (Curexo Technology Corporation). This system is designed for TKA and total hip arthroplasty (THA) surgery. Although initial studies reported a high incidence of system-related complications in THA,⁶⁴ the use of this system for TKA has frequently been reported in the literature.^56,63,65-69 A third robotic system that has been used in Europe is the Acrobot surgical system (Acrobot Company Ltd), which is an image-based semi-active robotic system⁷⁰ used for both UKA and TKA surgery.^70,71

Accuracy of Controlling Surgical Variables in Robotic-Assisted Knee Arthroplasty

Several studies have assessed the accuracy of robotic-assisted surgery in UKA surgery with regard to control of the aforementioned surgical variables. Pearle and colleagues⁷² assessed the mechanical axis accuracy of the Mako system in 10 patients undergoing medial UKA robotic-assisted surgery. They reported that the intraoperative registration lasted 7.5 minutes and the duration of time needed for robotic-assisted burring was 34.8 minutes. They compared the actual postoperative alignment at 6 weeks follow-up with the planned lower leg alignment and found that all measurements were within 1.6° of the planned lower leg alignment. Dunbar and colleagues⁷³ assessed the accuracy of component positioning of the Mako system in 20 patients undergoing medial UKA surgery by comparing preoperative and postoperative 3-dimensional CT scans. They found that the femoral component was within 0.8 mm and 0.9° in all directions and that the tibial component was within 0.9 mm and 1.7° in all directions. They concluded that the accuracy of component positioning with the Mako system was excellent. Finally, Plate and colleagues¹⁷ assessed the accuracy of soft tissue balancing in the Mako system in 52 patients undergoing medial UKA surgery. They compared the balance plan with the soft tissue balance after implantation and the Mako system quantified soft tissue balance as the amount of mm of the knee being tight or loose at 0°, 30°, 60°, 90°, and 110° of flexion. They found that at all flexion angles the ligament balancing was accurate up to 0.53 mm of the original plan. Furthermore, they noted that in 83% of cases the accuracy was within 1 mm at all flexion angles.

For the Navio system, Smith and colleagues⁷⁴ assessed the accuracy of component positioning using 20 synthetic femurs and tibia. They reported a maximum rotational error of 3.2°, an angular error of 1.46° in all orientations, and a maximum translational error of 1.18 mm for both the tibial and femoral implants. Lonner and colleagues⁷⁵ assessed the accuracy of component positioning in 25 cadaveric specimens. They found similar results as were found in the study of Smith and colleagues⁷⁴ and concluded that these results were similar to other semi-active robotic systems designed for UKA.

For TKA surgery, Ponder and colleagues⁷⁶ assessed the accuracy of the OmniBotic system and found that the average error in the anterior-posterior dimension between the targeted and measured cuts was -0.14 mm, and that the standard deviation in guide positioning for the distal, anterior chamfer, and posterior chamfer resections was 0.03° and 0.17 mm. Koenig and colleagues⁶² assessed the accuracy of the OmniBotic system in the first 100 cases and found that 98% of the cases were within 3° of the neutral mechanical axis. Furthermore, they found a learning curve with regard to tourniquet time between the first and second 10 patients in which they performed robotic-assisted TKA surgery. Siebert and colleagues⁶³ assessed the accuracy of mechanical alignment in the Caspar system in 70 patients treated with the robotic system. They found that the difference between preoperatively planned and postoperatively achieved mechanical alignment was 0.8°. Similarly, Bellemans and colleagues⁷⁷ assessed mechanical alignment and the positioning and rotation of the tibial and femoral components in a clinical study of 25 cases using the Caspar system. They noted that none of the patients had mechanical alignment, tibial or femoral component positioning, or rotation beyond 1° of the neutral axis. Liow and colleagues⁵⁶ assessed the accuracy of mechanical axis alignment and component sizing accuracy using the Robodoc system in 25 patients. They reported that the mean postoperative alignment was 0.4° valgus and that all cases were within 3° of the neutral mechanical axis. Furthermore, they reported a mean surgical time of 96 minutes and reported that preoperative planning yielded femoral and tibial component size accuracy of 100%.

These studies have shown that robotic systems for UKA and TKA are accurate in the surgical variables they aim to control. These studies validated tight control of mechanical axis alignment, decrease for outliers, and component positioning and rotation, and also found that the balancing of soft tissues was improved using robotic-assisted surgery.

Robotic-Assisted vs Conventional Knee Arthroplasty

Despite the fact that these systems are accurate in the variables they aim to control, these systems have to be compared to the gold standard of conventional knee arthroplasty. For UKA, Cobb and colleagues⁷⁰ performed a randomized clinical trial for patients treated undergoing UKA with robotic-assistance of the Acrobot systems compared to conventional UKA and assessed differences in mechanical accuracy. A total of 27 patients were randomly assigned to one of both treatments. They found that in the group of robotic-assisted surgery, 100% of the patients had a mechanical axis within 2° of neutral, while this was only 40% in the conventional UKA groups (difference P < .001). They also assessed the increase in functional outcomes and noted a trend towards improvement in performance with increasing accuracy at 6 weeks and 3 months postoperatively. Lonner and colleagues⁷⁸ also compared the tibial component positioning between robotic-assisted UKA surgery using the Mako system and conventional UKA surgery. The authors found that the variance in tibial slope, in coronal plane of the tibial component, and varus/valgus alignment were all larger with conventional UKA when compared to robotic-assisted UKA. Citak and colleagues⁷⁹ compared the accuracy of tibial and femoral implant positioning between robotic-assisted surgery using the Mako system and conventional UKA in a cadaveric study. They reported that the root mean square (RMS) error of femoral component was 1.9 mm and 3.7° in robotic-assisted surgery and 5.4 mm and 10.2° for conventional UKA, while the RMS error for tibial component were 1.4 mm and 5.0° for robotic-assisted surgery and 5.7 mm and 19.2° for conventional UKA surgery. MacCallum and colleagues⁸⁰ compared the tibial base plate position in a prospective clinical study of 177 patients treated with conventional UKA and 87 patients treated with robotic-assisted surgery using the Mako system. They found that surgery with robotic-assistance was more precise in the coronal and sagittal plane and was more accurate in coronal alignment when compared to conventional UKA. Finally, the first results of robotic-assisted UKA surgery have been presented. Coon and colleagues⁸¹ reported the preliminary results of a multicenter study of 854 patients and found a survivorship of 98.9% and satisfaction rate of 92% at minimum 2-year follow-up. Comparing these results to other large conventional UKA cohorts^82,83 suggests that robotic-assisted surgery may improve survivorship at short-term follow-up. However, comparative studies and studies with longer follow-up are necessary to assess the additional value of robotic-assisted UKA surgery. Due to the relatively new concept of robotic-assisted surgery, these studies have not been performed or published yet.

For TKA, several studies also have compared how these robotic-systems control the surgical variables compared to conventional TKA surgery. Siebert and colleagues⁶³ assessed mechanical axis accuracy and mechanical outliers following robotic-assisted TKA surgery using the Caspar system and conventional TKA surgery. They reported the difference between preoperative planned and postoperative achieved alignment was 0.8° for robotic-assisted surgery and 2.6° for conventional TKA surgery. Furthermore, they showed that 1 patient in the robotic-assisted group (1.4%) and 18 patients in the conventional TKA group (35%) had mechanical alignment greater than 3° from the neutral mechanical axis. Liow and colleagues⁵⁶ found similar differences in their prospective randomized study in which they reported that 0% outliers greater than 3° from the neutral mechanical axis were found in the robotic-assisted group while 19.4% of the patients in the conventional TKA group had mechanical axis outliers. They also assessed the joint-line outliers in both procedures and found that 3.2% had joint-line outliers greater than 5 mm in the robotic-assisted group compared to 20.6% in the conventional TKA group. Kim and colleagues⁶⁵ assessed implant accuracy in robotic-assisted surgery using the ROBODOC system and in conventional surgery and reported higher implant accuracy and fewer outliers using robotic-assisted surgery. Moon and colleagues⁶⁶ compared robotic-assisted TKA surgery using the Robodoc system with conventional TKA surgery in 10 cadavers. They found that robotic-assisted surgery had excellent precision in all planes and had better accuracy in femoral rotation alignment compared to conventional TKA surgery. Park and Lee⁶⁷ compared Robodoc robotic-assisted TKA surgery with conventional TKA surgery in a randomized clinical trial of 72 patients. They found that robotic-assisted surgery had definitive advantages in preoperative planning, accuracy of the procedure, and postoperative follow-up regarding femoral and tibial component flexion angles. Finally, Song and colleagues^68,69 performed 2 randomized clinical trials in which they compared mechanical axis alignment, component positioning, soft tissue balancing, and patient preference between conventional TKA surgery and robotic-assisted surgery using the Robodoc system. In the first study,⁶⁸ they simultaneously performed robotic-assisted surgery in one leg and conventional TKA surgery in the other leg. They found that robotic-assisted surgery resulted in less outlier in mechanical axis and component positioning. Furthermore, they found at latest follow-up of 2 years that 12 patients preferred the leg treated with robotic-assisted surgery while 6 preferred the conventional leg. Despite this finding, no significant differences in functional outcome scores were detected between both treatment options. Furthermore, they found that flexion-extension balance was achieved in 92% of patients treated with robotic-assisted TKA surgery and in 77% of patients treated with conventional TKA surgery. In the other study,⁶⁹ the authors found that more patients treated with robotic-assisted surgery had <2 mm flexion-extension gap and more satisfactory posterior cruciate ligament tension when compared to conventional surgery.

These studies have shown that robotic-assisted surgery is accurate in controlling surgical variables, such as mechanical lower leg alignment, maintaining joint-line, implant positioning, and soft tissue balancing. Furthermore, these studies have shown that controlling these variables is better than the current gold standard of manual knee arthroplasty. Until now, not many studies have assessed survivorship of robotic-assisted surgery. Furthermore, no studies have, to our knowledge, compared survivorship of robotic-assisted with conventional knee replacement surgery. Finally, studies comparing functional outcomes following robotic-assisted surgery and conventional knee arthroplasty surgery are frequently underpowered due to their small sample sizes.^68,70 Since many studies have shown that the surgical variables are more tightly controlled using robotic-assisted surgery when compared to conventional surgery, large comparative studies are necessary to assess the role of robotic-assisted surgery in functional outcomes and survivorship of UKA and TKA.

Cost-Effectiveness of Robotic-Assisted Surgery

High initial capital costs of robotic-assisted surgery is one of the factors that constitute a barrier to the widespread implementation of this technique. Multiple authors have suggested that improved implant survivorship afforded by robotic-assisted surgery may justify the expenditure from both societal and provider perspective.^84-86 Two studies have performed a cost-effectiveness analysis for UKA surgery. Swank and colleagues⁸⁴ reviewed the hospital expenditures and profits associated with robot-assisted knee arthroplasty, citing upfront costs of approximately $800,000. The authors estimated a mean per-case contribution profit of $5790 for robotic-assisted UKA, assuming an inpatient-to-outpatient ratio of 1 to 3. Based on this data, Swank and colleagues84 proposed that the capital costs of robotic-assisted UKA may be recovered in as little as 2 years when in the first 3 consecutive years 50, 70, and 90 cases were performed using robotic-assisted UKA. Moschetti and colleagues⁸⁵ recently published the first formal cost-effectiveness analysis of robotic-assisted compared to manual UKA. The authors used an annual revision risk of 0.55% for the first 2 years following robot-assisted UKA, based on the aforementioned presented data by Coon and colleagues.⁸¹ They based their data on the Mako system and assumed an initial capital expenditure of $934,728 with annual servicing costs of 10% (discounted annually) for 4 years thereafter, resulting in a total cost of the robotic system of $1.362 million. These costs were divided by the number of patients estimated to undergo robotic-assisted UKA per year, which was varied to estimate the effect of case volume on cost-effectiveness. The authors reported that robotic-assisted UKA was associated with higher lifetime costs and net utilities compared to manual UKA, at an incremental cost-effectiveness ratio of $47,180 per quality-adjusted life year (QALY) in a high-volume center. This falls well within the societal willingness-to-pay threshold of $100,000/QALY. Sensitivity analysis showed that robotic-assisted UKA is cost-effective under the following conditions: (1) centers performing at least 94 cases annually, (2) in patients younger than age 67 years, and (3) 2-year revision rate does not exceed 1.2%. While the results of this initial analysis are promising, follow-up cost-effectiveness analysis studies will be required as long-term survivorship data become available.

Conclusion

Tighter control of intraoperative surgical variables, such as lower leg alignment, soft tissue balance, joint-line maintenance, and component alignment and positioning, have been associated with improved survivorship and functional outcomes. Upon reviewing the available literature on robotic-assisted surgery, it becomes clear that this technique can improve the accuracy of these surgical variables and is superior to conventional manual UKA and TKA. Although larger and comparative survivorship studies are necessary to compare robotic-assisted knee arthroplasty to conventional techniques, the early results and cost-effectiveness analysis seem promising.

Unicompartmental knee arthroplasty (UKA) and total knee arthroplasty (TKA) are 2 reliable treatment options for patients with primary osteoarthritis. Recently published systematic reviews of cohort studies have shown that 10-year survivorship of medial and lateral UKA is 92% and 91%, respectively,¹ while 10-year survivorship of TKA in cohort studies is 95%.² National and annual registries show a similar trend, although the reported survivorship is lower.^1,3-7

In order to improve these survivorship rates, the surgical variables that can intraoperatively be controlled by the orthopedic surgeon have been evaluated. These variables include lower leg alignment, soft tissue balance, joint line maintenance, and alignment, size, and fixation of the tibial and femoral component. Several studies have shown that tight control of lower leg alignment,^8-14 balancing of the soft tissues,^15-19 joint line maintenance,^20-23 component alignment,^24-28 component size,^29-34 and component fixation^35-40 can improve the outcomes of UKA and TKA. As a result, over the past 2 decades, several computer-assisted surgery systems have been developed with the goal of more accurate and reliable control of these factors, and thus improved outcomes of knee arthroplasty.

These systems differ with regard to the number and type of variables they control. Computer navigation systems aim to control one or more of these surgical variables, and several meta-analyses have shown that these systems, when compared to conventional surgery, improve mechanical axis accuracy, decrease the risk for mechanical axis outliers, and improve component positioning in TKA^41-49 and UKA surgery.^50,51 Interestingly, however, meta-analyses have failed to show the expected superiority in clinical outcomes following computer navigation compared to conventional knee arthroplasty.^48,52-55 Furthermore, authors have shown that, despite the fact that computer-navigated surgery increases the accuracy of mechanical alignment and surgical cutting, there is still room for improvement.⁵⁶ As a consequence, robotic-assisted systems have been developed.

Similar to computer navigation, these robotic-assisted systems aim to control the surgical variables; in addition, they aim to improve the surgical precision of the procedure. Interestingly, 2 recent studies have shown that robotic-assisted systems are superior to computer navigation systems with regard to less cutting time and less resection deviations in coronal and sagittal plane in a cadaveric study,⁵⁷ and shorter total surgery time, more accurate mechanical axis, and shorter hospital stay in a clinical study.⁵⁸ Although these results are promising, the exact role of robotic surgery in knee arthroplasty remains unclear. In this review, we aim to report the current state of robotic-assisted knee arthroplasty by discussing (1) the different robotic-assisted knee arthroplasty systems that are available for UKA and TKA surgery, (2) studies that assessed the role of robotic-assisted knee arthroplasty in controlling the aforementioned surgical variables, (3) cadaveric and clinical comparative studies that compared how accurate robotic-assisted and conventional knee surgery control these surgical variables, and (4) studies that assessed the cost-effectiveness of robotic-assisted knee arthroplasty surgery.

Robotic-Assisted Knee Arthroplasty Systems

Several systems have been developed over the years for knee arthroplasty, and these are usually defined as active, semi-active, or passive.⁵⁹ Active systems are capable of performing tasks or processes autonomously under the watchful eye of the surgeon, while passive systems do not perform actions independently but provide the surgeon with information. In semi-active systems, the surgical action is physically constrained in order to follow a predefined strategy.

In the United States, 3 robotic systems are FDA-approved for knee arthroplasty. The Stryker/Mako haptic guided robot (Mako Surgical Corp.) was introduced in 2005 and has been used for over 50,000 UKA procedures (Figure 1). There are nearly 300 robotic systems used nationally, as it has 20% of the market share for UKA in the United States. The Mako system is a semi-active tactile robotic system that requires preoperative imaging, after which a preoperative planning is performed. Intraoperatively, the robotic arm is under direct surgeon control and gives real-time tactile feedback during the procedure (Figure 2).

Furthermore, the surgeon can intraoperatively virtually adjust component positioning and alignment and move the knee through the range of motion, after which the system can provide information on alignment, component position, and balance of the soft tissue (eg, if the knee is overtight or lax through the flexion-arch).⁶⁰ This system has a burr that resects the bone and when the surgeon directs the burr outside the preplanned area, the burr stops and prevents unnecessary and unwanted resections (Figure 3).

The Navio Precision Free-Hand Sculptor (PFS) system (Blue Belt Technologies) has been used for 1500 UKA procedures, with 50 robots in use in the United States (Figure 4). This system is an image-free semi-active robotic system and has the same characteristics as the aforementioned Mako system.⁶¹ Finally, the OmniBotic robotic system (Omnilife Science) has been released for TKA and has been used for over 7300 procedures (Figure 5). This system has an automated cutting-guide technique in which the surgeon designs a virtual plan on the computer system. After this, the cutting-guides are placed by the robotic system at the planned location for all 5 femoral cuts (ie, distal, anterior chamfer, anterior, posterior chamfer, and posterior) and the surgeon then makes the final cuts.^57,62

Three robotic systems for knee arthroplasty surgery have been used in Europe. The Caspar system (URS Ortho) is an active robotic system in which a computed tomography (CT) scan is performed preoperatively, after which a virtual implantation is performed on the screen. The surgeon can then obtain information on lower leg alignment, gap balancing, and component positioning, and after an operative plan is made, the surgical resections are performed by the robot. Reflective markers are attached to the leg and all robotic movements are monitored using an infrared camera system. Any undesired motion will be detected by this camera system and will stop all movements.⁶³ A second and more frequently reported system in the literature is the active Robodoc surgical system (Curexo Technology Corporation). This system is designed for TKA and total hip arthroplasty (THA) surgery. Although initial studies reported a high incidence of system-related complications in THA,⁶⁴ the use of this system for TKA has frequently been reported in the literature.^56,63,65-69 A third robotic system that has been used in Europe is the Acrobot surgical system (Acrobot Company Ltd), which is an image-based semi-active robotic system⁷⁰ used for both UKA and TKA surgery.^70,71

Accuracy of Controlling Surgical Variables in Robotic-Assisted Knee Arthroplasty

Several studies have assessed the accuracy of robotic-assisted surgery in UKA surgery with regard to control of the aforementioned surgical variables. Pearle and colleagues⁷² assessed the mechanical axis accuracy of the Mako system in 10 patients undergoing medial UKA robotic-assisted surgery. They reported that the intraoperative registration lasted 7.5 minutes and the duration of time needed for robotic-assisted burring was 34.8 minutes. They compared the actual postoperative alignment at 6 weeks follow-up with the planned lower leg alignment and found that all measurements were within 1.6° of the planned lower leg alignment. Dunbar and colleagues⁷³ assessed the accuracy of component positioning of the Mako system in 20 patients undergoing medial UKA surgery by comparing preoperative and postoperative 3-dimensional CT scans. They found that the femoral component was within 0.8 mm and 0.9° in all directions and that the tibial component was within 0.9 mm and 1.7° in all directions. They concluded that the accuracy of component positioning with the Mako system was excellent. Finally, Plate and colleagues¹⁷ assessed the accuracy of soft tissue balancing in the Mako system in 52 patients undergoing medial UKA surgery. They compared the balance plan with the soft tissue balance after implantation and the Mako system quantified soft tissue balance as the amount of mm of the knee being tight or loose at 0°, 30°, 60°, 90°, and 110° of flexion. They found that at all flexion angles the ligament balancing was accurate up to 0.53 mm of the original plan. Furthermore, they noted that in 83% of cases the accuracy was within 1 mm at all flexion angles.

For the Navio system, Smith and colleagues⁷⁴ assessed the accuracy of component positioning using 20 synthetic femurs and tibia. They reported a maximum rotational error of 3.2°, an angular error of 1.46° in all orientations, and a maximum translational error of 1.18 mm for both the tibial and femoral implants. Lonner and colleagues⁷⁵ assessed the accuracy of component positioning in 25 cadaveric specimens. They found similar results as were found in the study of Smith and colleagues⁷⁴ and concluded that these results were similar to other semi-active robotic systems designed for UKA.

For TKA surgery, Ponder and colleagues⁷⁶ assessed the accuracy of the OmniBotic system and found that the average error in the anterior-posterior dimension between the targeted and measured cuts was -0.14 mm, and that the standard deviation in guide positioning for the distal, anterior chamfer, and posterior chamfer resections was 0.03° and 0.17 mm. Koenig and colleagues⁶² assessed the accuracy of the OmniBotic system in the first 100 cases and found that 98% of the cases were within 3° of the neutral mechanical axis. Furthermore, they found a learning curve with regard to tourniquet time between the first and second 10 patients in which they performed robotic-assisted TKA surgery. Siebert and colleagues⁶³ assessed the accuracy of mechanical alignment in the Caspar system in 70 patients treated with the robotic system. They found that the difference between preoperatively planned and postoperatively achieved mechanical alignment was 0.8°. Similarly, Bellemans and colleagues⁷⁷ assessed mechanical alignment and the positioning and rotation of the tibial and femoral components in a clinical study of 25 cases using the Caspar system. They noted that none of the patients had mechanical alignment, tibial or femoral component positioning, or rotation beyond 1° of the neutral axis. Liow and colleagues⁵⁶ assessed the accuracy of mechanical axis alignment and component sizing accuracy using the Robodoc system in 25 patients. They reported that the mean postoperative alignment was 0.4° valgus and that all cases were within 3° of the neutral mechanical axis. Furthermore, they reported a mean surgical time of 96 minutes and reported that preoperative planning yielded femoral and tibial component size accuracy of 100%.

These studies have shown that robotic systems for UKA and TKA are accurate in the surgical variables they aim to control. These studies validated tight control of mechanical axis alignment, decrease for outliers, and component positioning and rotation, and also found that the balancing of soft tissues was improved using robotic-assisted surgery.

Robotic-Assisted vs Conventional Knee Arthroplasty

Despite the fact that these systems are accurate in the variables they aim to control, these systems have to be compared to the gold standard of conventional knee arthroplasty. For UKA, Cobb and colleagues⁷⁰ performed a randomized clinical trial for patients treated undergoing UKA with robotic-assistance of the Acrobot systems compared to conventional UKA and assessed differences in mechanical accuracy. A total of 27 patients were randomly assigned to one of both treatments. They found that in the group of robotic-assisted surgery, 100% of the patients had a mechanical axis within 2° of neutral, while this was only 40% in the conventional UKA groups (difference P < .001). They also assessed the increase in functional outcomes and noted a trend towards improvement in performance with increasing accuracy at 6 weeks and 3 months postoperatively. Lonner and colleagues⁷⁸ also compared the tibial component positioning between robotic-assisted UKA surgery using the Mako system and conventional UKA surgery. The authors found that the variance in tibial slope, in coronal plane of the tibial component, and varus/valgus alignment were all larger with conventional UKA when compared to robotic-assisted UKA. Citak and colleagues⁷⁹ compared the accuracy of tibial and femoral implant positioning between robotic-assisted surgery using the Mako system and conventional UKA in a cadaveric study. They reported that the root mean square (RMS) error of femoral component was 1.9 mm and 3.7° in robotic-assisted surgery and 5.4 mm and 10.2° for conventional UKA, while the RMS error for tibial component were 1.4 mm and 5.0° for robotic-assisted surgery and 5.7 mm and 19.2° for conventional UKA surgery. MacCallum and colleagues⁸⁰ compared the tibial base plate position in a prospective clinical study of 177 patients treated with conventional UKA and 87 patients treated with robotic-assisted surgery using the Mako system. They found that surgery with robotic-assistance was more precise in the coronal and sagittal plane and was more accurate in coronal alignment when compared to conventional UKA. Finally, the first results of robotic-assisted UKA surgery have been presented. Coon and colleagues⁸¹ reported the preliminary results of a multicenter study of 854 patients and found a survivorship of 98.9% and satisfaction rate of 92% at minimum 2-year follow-up. Comparing these results to other large conventional UKA cohorts^82,83 suggests that robotic-assisted surgery may improve survivorship at short-term follow-up. However, comparative studies and studies with longer follow-up are necessary to assess the additional value of robotic-assisted UKA surgery. Due to the relatively new concept of robotic-assisted surgery, these studies have not been performed or published yet.

For TKA, several studies also have compared how these robotic-systems control the surgical variables compared to conventional TKA surgery. Siebert and colleagues⁶³ assessed mechanical axis accuracy and mechanical outliers following robotic-assisted TKA surgery using the Caspar system and conventional TKA surgery. They reported the difference between preoperative planned and postoperative achieved alignment was 0.8° for robotic-assisted surgery and 2.6° for conventional TKA surgery. Furthermore, they showed that 1 patient in the robotic-assisted group (1.4%) and 18 patients in the conventional TKA group (35%) had mechanical alignment greater than 3° from the neutral mechanical axis. Liow and colleagues⁵⁶ found similar differences in their prospective randomized study in which they reported that 0% outliers greater than 3° from the neutral mechanical axis were found in the robotic-assisted group while 19.4% of the patients in the conventional TKA group had mechanical axis outliers. They also assessed the joint-line outliers in both procedures and found that 3.2% had joint-line outliers greater than 5 mm in the robotic-assisted group compared to 20.6% in the conventional TKA group. Kim and colleagues⁶⁵ assessed implant accuracy in robotic-assisted surgery using the ROBODOC system and in conventional surgery and reported higher implant accuracy and fewer outliers using robotic-assisted surgery. Moon and colleagues⁶⁶ compared robotic-assisted TKA surgery using the Robodoc system with conventional TKA surgery in 10 cadavers. They found that robotic-assisted surgery had excellent precision in all planes and had better accuracy in femoral rotation alignment compared to conventional TKA surgery. Park and Lee⁶⁷ compared Robodoc robotic-assisted TKA surgery with conventional TKA surgery in a randomized clinical trial of 72 patients. They found that robotic-assisted surgery had definitive advantages in preoperative planning, accuracy of the procedure, and postoperative follow-up regarding femoral and tibial component flexion angles. Finally, Song and colleagues^68,69 performed 2 randomized clinical trials in which they compared mechanical axis alignment, component positioning, soft tissue balancing, and patient preference between conventional TKA surgery and robotic-assisted surgery using the Robodoc system. In the first study,⁶⁸ they simultaneously performed robotic-assisted surgery in one leg and conventional TKA surgery in the other leg. They found that robotic-assisted surgery resulted in less outlier in mechanical axis and component positioning. Furthermore, they found at latest follow-up of 2 years that 12 patients preferred the leg treated with robotic-assisted surgery while 6 preferred the conventional leg. Despite this finding, no significant differences in functional outcome scores were detected between both treatment options. Furthermore, they found that flexion-extension balance was achieved in 92% of patients treated with robotic-assisted TKA surgery and in 77% of patients treated with conventional TKA surgery. In the other study,⁶⁹ the authors found that more patients treated with robotic-assisted surgery had <2 mm flexion-extension gap and more satisfactory posterior cruciate ligament tension when compared to conventional surgery.

These studies have shown that robotic-assisted surgery is accurate in controlling surgical variables, such as mechanical lower leg alignment, maintaining joint-line, implant positioning, and soft tissue balancing. Furthermore, these studies have shown that controlling these variables is better than the current gold standard of manual knee arthroplasty. Until now, not many studies have assessed survivorship of robotic-assisted surgery. Furthermore, no studies have, to our knowledge, compared survivorship of robotic-assisted with conventional knee replacement surgery. Finally, studies comparing functional outcomes following robotic-assisted surgery and conventional knee arthroplasty surgery are frequently underpowered due to their small sample sizes.^68,70 Since many studies have shown that the surgical variables are more tightly controlled using robotic-assisted surgery when compared to conventional surgery, large comparative studies are necessary to assess the role of robotic-assisted surgery in functional outcomes and survivorship of UKA and TKA.

Cost-Effectiveness of Robotic-Assisted Surgery

High initial capital costs of robotic-assisted surgery is one of the factors that constitute a barrier to the widespread implementation of this technique. Multiple authors have suggested that improved implant survivorship afforded by robotic-assisted surgery may justify the expenditure from both societal and provider perspective.^84-86 Two studies have performed a cost-effectiveness analysis for UKA surgery. Swank and colleagues⁸⁴ reviewed the hospital expenditures and profits associated with robot-assisted knee arthroplasty, citing upfront costs of approximately $800,000. The authors estimated a mean per-case contribution profit of $5790 for robotic-assisted UKA, assuming an inpatient-to-outpatient ratio of 1 to 3. Based on this data, Swank and colleagues84 proposed that the capital costs of robotic-assisted UKA may be recovered in as little as 2 years when in the first 3 consecutive years 50, 70, and 90 cases were performed using robotic-assisted UKA. Moschetti and colleagues⁸⁵ recently published the first formal cost-effectiveness analysis of robotic-assisted compared to manual UKA. The authors used an annual revision risk of 0.55% for the first 2 years following robot-assisted UKA, based on the aforementioned presented data by Coon and colleagues.⁸¹ They based their data on the Mako system and assumed an initial capital expenditure of $934,728 with annual servicing costs of 10% (discounted annually) for 4 years thereafter, resulting in a total cost of the robotic system of $1.362 million. These costs were divided by the number of patients estimated to undergo robotic-assisted UKA per year, which was varied to estimate the effect of case volume on cost-effectiveness. The authors reported that robotic-assisted UKA was associated with higher lifetime costs and net utilities compared to manual UKA, at an incremental cost-effectiveness ratio of $47,180 per quality-adjusted life year (QALY) in a high-volume center. This falls well within the societal willingness-to-pay threshold of $100,000/QALY. Sensitivity analysis showed that robotic-assisted UKA is cost-effective under the following conditions: (1) centers performing at least 94 cases annually, (2) in patients younger than age 67 years, and (3) 2-year revision rate does not exceed 1.2%. While the results of this initial analysis are promising, follow-up cost-effectiveness analysis studies will be required as long-term survivorship data become available.

Conclusion

Tighter control of intraoperative surgical variables, such as lower leg alignment, soft tissue balance, joint-line maintenance, and component alignment and positioning, have been associated with improved survivorship and functional outcomes. Upon reviewing the available literature on robotic-assisted surgery, it becomes clear that this technique can improve the accuracy of these surgical variables and is superior to conventional manual UKA and TKA. Although larger and comparative survivorship studies are necessary to compare robotic-assisted knee arthroplasty to conventional techniques, the early results and cost-effectiveness analysis seem promising.

Unicompartmental knee arthroplasty (UKA) and total knee arthroplasty (TKA) are 2 reliable treatment options for patients with primary osteoarthritis. Recently published systematic reviews of cohort studies have shown that 10-year survivorship of medial and lateral UKA is 92% and 91%, respectively,¹ while 10-year survivorship of TKA in cohort studies is 95%.² National and annual registries show a similar trend, although the reported survivorship is lower.^1,3-7

In order to improve these survivorship rates, the surgical variables that can intraoperatively be controlled by the orthopedic surgeon have been evaluated. These variables include lower leg alignment, soft tissue balance, joint line maintenance, and alignment, size, and fixation of the tibial and femoral component. Several studies have shown that tight control of lower leg alignment,^8-14 balancing of the soft tissues,^15-19 joint line maintenance,^20-23 component alignment,^24-28 component size,^29-34 and component fixation^35-40 can improve the outcomes of UKA and TKA. As a result, over the past 2 decades, several computer-assisted surgery systems have been developed with the goal of more accurate and reliable control of these factors, and thus improved outcomes of knee arthroplasty.

These systems differ with regard to the number and type of variables they control. Computer navigation systems aim to control one or more of these surgical variables, and several meta-analyses have shown that these systems, when compared to conventional surgery, improve mechanical axis accuracy, decrease the risk for mechanical axis outliers, and improve component positioning in TKA^41-49 and UKA surgery.^50,51 Interestingly, however, meta-analyses have failed to show the expected superiority in clinical outcomes following computer navigation compared to conventional knee arthroplasty.^48,52-55 Furthermore, authors have shown that, despite the fact that computer-navigated surgery increases the accuracy of mechanical alignment and surgical cutting, there is still room for improvement.⁵⁶ As a consequence, robotic-assisted systems have been developed.

Similar to computer navigation, these robotic-assisted systems aim to control the surgical variables; in addition, they aim to improve the surgical precision of the procedure. Interestingly, 2 recent studies have shown that robotic-assisted systems are superior to computer navigation systems with regard to less cutting time and less resection deviations in coronal and sagittal plane in a cadaveric study,⁵⁷ and shorter total surgery time, more accurate mechanical axis, and shorter hospital stay in a clinical study.⁵⁸ Although these results are promising, the exact role of robotic surgery in knee arthroplasty remains unclear. In this review, we aim to report the current state of robotic-assisted knee arthroplasty by discussing (1) the different robotic-assisted knee arthroplasty systems that are available for UKA and TKA surgery, (2) studies that assessed the role of robotic-assisted knee arthroplasty in controlling the aforementioned surgical variables, (3) cadaveric and clinical comparative studies that compared how accurate robotic-assisted and conventional knee surgery control these surgical variables, and (4) studies that assessed the cost-effectiveness of robotic-assisted knee arthroplasty surgery.

Robotic-Assisted Knee Arthroplasty Systems

Several systems have been developed over the years for knee arthroplasty, and these are usually defined as active, semi-active, or passive.⁵⁹ Active systems are capable of performing tasks or processes autonomously under the watchful eye of the surgeon, while passive systems do not perform actions independently but provide the surgeon with information. In semi-active systems, the surgical action is physically constrained in order to follow a predefined strategy.

In the United States, 3 robotic systems are FDA-approved for knee arthroplasty. The Stryker/Mako haptic guided robot (Mako Surgical Corp.) was introduced in 2005 and has been used for over 50,000 UKA procedures (Figure 1). There are nearly 300 robotic systems used nationally, as it has 20% of the market share for UKA in the United States. The Mako system is a semi-active tactile robotic system that requires preoperative imaging, after which a preoperative planning is performed. Intraoperatively, the robotic arm is under direct surgeon control and gives real-time tactile feedback during the procedure (Figure 2).

Furthermore, the surgeon can intraoperatively virtually adjust component positioning and alignment and move the knee through the range of motion, after which the system can provide information on alignment, component position, and balance of the soft tissue (eg, if the knee is overtight or lax through the flexion-arch).⁶⁰ This system has a burr that resects the bone and when the surgeon directs the burr outside the preplanned area, the burr stops and prevents unnecessary and unwanted resections (Figure 3).

The Navio Precision Free-Hand Sculptor (PFS) system (Blue Belt Technologies) has been used for 1500 UKA procedures, with 50 robots in use in the United States (Figure 4). This system is an image-free semi-active robotic system and has the same characteristics as the aforementioned Mako system.⁶¹ Finally, the OmniBotic robotic system (Omnilife Science) has been released for TKA and has been used for over 7300 procedures (Figure 5). This system has an automated cutting-guide technique in which the surgeon designs a virtual plan on the computer system. After this, the cutting-guides are placed by the robotic system at the planned location for all 5 femoral cuts (ie, distal, anterior chamfer, anterior, posterior chamfer, and posterior) and the surgeon then makes the final cuts.^57,62

Three robotic systems for knee arthroplasty surgery have been used in Europe. The Caspar system (URS Ortho) is an active robotic system in which a computed tomography (CT) scan is performed preoperatively, after which a virtual implantation is performed on the screen. The surgeon can then obtain information on lower leg alignment, gap balancing, and component positioning, and after an operative plan is made, the surgical resections are performed by the robot. Reflective markers are attached to the leg and all robotic movements are monitored using an infrared camera system. Any undesired motion will be detected by this camera system and will stop all movements.⁶³ A second and more frequently reported system in the literature is the active Robodoc surgical system (Curexo Technology Corporation). This system is designed for TKA and total hip arthroplasty (THA) surgery. Although initial studies reported a high incidence of system-related complications in THA,⁶⁴ the use of this system for TKA has frequently been reported in the literature.^56,63,65-69 A third robotic system that has been used in Europe is the Acrobot surgical system (Acrobot Company Ltd), which is an image-based semi-active robotic system⁷⁰ used for both UKA and TKA surgery.^70,71

Accuracy of Controlling Surgical Variables in Robotic-Assisted Knee Arthroplasty

Several studies have assessed the accuracy of robotic-assisted surgery in UKA surgery with regard to control of the aforementioned surgical variables. Pearle and colleagues⁷² assessed the mechanical axis accuracy of the Mako system in 10 patients undergoing medial UKA robotic-assisted surgery. They reported that the intraoperative registration lasted 7.5 minutes and the duration of time needed for robotic-assisted burring was 34.8 minutes. They compared the actual postoperative alignment at 6 weeks follow-up with the planned lower leg alignment and found that all measurements were within 1.6° of the planned lower leg alignment. Dunbar and colleagues⁷³ assessed the accuracy of component positioning of the Mako system in 20 patients undergoing medial UKA surgery by comparing preoperative and postoperative 3-dimensional CT scans. They found that the femoral component was within 0.8 mm and 0.9° in all directions and that the tibial component was within 0.9 mm and 1.7° in all directions. They concluded that the accuracy of component positioning with the Mako system was excellent. Finally, Plate and colleagues¹⁷ assessed the accuracy of soft tissue balancing in the Mako system in 52 patients undergoing medial UKA surgery. They compared the balance plan with the soft tissue balance after implantation and the Mako system quantified soft tissue balance as the amount of mm of the knee being tight or loose at 0°, 30°, 60°, 90°, and 110° of flexion. They found that at all flexion angles the ligament balancing was accurate up to 0.53 mm of the original plan. Furthermore, they noted that in 83% of cases the accuracy was within 1 mm at all flexion angles.

For the Navio system, Smith and colleagues⁷⁴ assessed the accuracy of component positioning using 20 synthetic femurs and tibia. They reported a maximum rotational error of 3.2°, an angular error of 1.46° in all orientations, and a maximum translational error of 1.18 mm for both the tibial and femoral implants. Lonner and colleagues⁷⁵ assessed the accuracy of component positioning in 25 cadaveric specimens. They found similar results as were found in the study of Smith and colleagues⁷⁴ and concluded that these results were similar to other semi-active robotic systems designed for UKA.

For TKA surgery, Ponder and colleagues⁷⁶ assessed the accuracy of the OmniBotic system and found that the average error in the anterior-posterior dimension between the targeted and measured cuts was -0.14 mm, and that the standard deviation in guide positioning for the distal, anterior chamfer, and posterior chamfer resections was 0.03° and 0.17 mm. Koenig and colleagues⁶² assessed the accuracy of the OmniBotic system in the first 100 cases and found that 98% of the cases were within 3° of the neutral mechanical axis. Furthermore, they found a learning curve with regard to tourniquet time between the first and second 10 patients in which they performed robotic-assisted TKA surgery. Siebert and colleagues⁶³ assessed the accuracy of mechanical alignment in the Caspar system in 70 patients treated with the robotic system. They found that the difference between preoperatively planned and postoperatively achieved mechanical alignment was 0.8°. Similarly, Bellemans and colleagues⁷⁷ assessed mechanical alignment and the positioning and rotation of the tibial and femoral components in a clinical study of 25 cases using the Caspar system. They noted that none of the patients had mechanical alignment, tibial or femoral component positioning, or rotation beyond 1° of the neutral axis. Liow and colleagues⁵⁶ assessed the accuracy of mechanical axis alignment and component sizing accuracy using the Robodoc system in 25 patients. They reported that the mean postoperative alignment was 0.4° valgus and that all cases were within 3° of the neutral mechanical axis. Furthermore, they reported a mean surgical time of 96 minutes and reported that preoperative planning yielded femoral and tibial component size accuracy of 100%.

These studies have shown that robotic systems for UKA and TKA are accurate in the surgical variables they aim to control. These studies validated tight control of mechanical axis alignment, decrease for outliers, and component positioning and rotation, and also found that the balancing of soft tissues was improved using robotic-assisted surgery.

Robotic-Assisted vs Conventional Knee Arthroplasty

Despite the fact that these systems are accurate in the variables they aim to control, these systems have to be compared to the gold standard of conventional knee arthroplasty. For UKA, Cobb and colleagues⁷⁰ performed a randomized clinical trial for patients treated undergoing UKA with robotic-assistance of the Acrobot systems compared to conventional UKA and assessed differences in mechanical accuracy. A total of 27 patients were randomly assigned to one of both treatments. They found that in the group of robotic-assisted surgery, 100% of the patients had a mechanical axis within 2° of neutral, while this was only 40% in the conventional UKA groups (difference P < .001). They also assessed the increase in functional outcomes and noted a trend towards improvement in performance with increasing accuracy at 6 weeks and 3 months postoperatively. Lonner and colleagues⁷⁸ also compared the tibial component positioning between robotic-assisted UKA surgery using the Mako system and conventional UKA surgery. The authors found that the variance in tibial slope, in coronal plane of the tibial component, and varus/valgus alignment were all larger with conventional UKA when compared to robotic-assisted UKA. Citak and colleagues⁷⁹ compared the accuracy of tibial and femoral implant positioning between robotic-assisted surgery using the Mako system and conventional UKA in a cadaveric study. They reported that the root mean square (RMS) error of femoral component was 1.9 mm and 3.7° in robotic-assisted surgery and 5.4 mm and 10.2° for conventional UKA, while the RMS error for tibial component were 1.4 mm and 5.0° for robotic-assisted surgery and 5.7 mm and 19.2° for conventional UKA surgery. MacCallum and colleagues⁸⁰ compared the tibial base plate position in a prospective clinical study of 177 patients treated with conventional UKA and 87 patients treated with robotic-assisted surgery using the Mako system. They found that surgery with robotic-assistance was more precise in the coronal and sagittal plane and was more accurate in coronal alignment when compared to conventional UKA. Finally, the first results of robotic-assisted UKA surgery have been presented. Coon and colleagues⁸¹ reported the preliminary results of a multicenter study of 854 patients and found a survivorship of 98.9% and satisfaction rate of 92% at minimum 2-year follow-up. Comparing these results to other large conventional UKA cohorts^82,83 suggests that robotic-assisted surgery may improve survivorship at short-term follow-up. However, comparative studies and studies with longer follow-up are necessary to assess the additional value of robotic-assisted UKA surgery. Due to the relatively new concept of robotic-assisted surgery, these studies have not been performed or published yet.

For TKA, several studies also have compared how these robotic-systems control the surgical variables compared to conventional TKA surgery. Siebert and colleagues⁶³ assessed mechanical axis accuracy and mechanical outliers following robotic-assisted TKA surgery using the Caspar system and conventional TKA surgery. They reported the difference between preoperative planned and postoperative achieved alignment was 0.8° for robotic-assisted surgery and 2.6° for conventional TKA surgery. Furthermore, they showed that 1 patient in the robotic-assisted group (1.4%) and 18 patients in the conventional TKA group (35%) had mechanical alignment greater than 3° from the neutral mechanical axis. Liow and colleagues⁵⁶ found similar differences in their prospective randomized study in which they reported that 0% outliers greater than 3° from the neutral mechanical axis were found in the robotic-assisted group while 19.4% of the patients in the conventional TKA group had mechanical axis outliers. They also assessed the joint-line outliers in both procedures and found that 3.2% had joint-line outliers greater than 5 mm in the robotic-assisted group compared to 20.6% in the conventional TKA group. Kim and colleagues⁶⁵ assessed implant accuracy in robotic-assisted surgery using the ROBODOC system and in conventional surgery and reported higher implant accuracy and fewer outliers using robotic-assisted surgery. Moon and colleagues⁶⁶ compared robotic-assisted TKA surgery using the Robodoc system with conventional TKA surgery in 10 cadavers. They found that robotic-assisted surgery had excellent precision in all planes and had better accuracy in femoral rotation alignment compared to conventional TKA surgery. Park and Lee⁶⁷ compared Robodoc robotic-assisted TKA surgery with conventional TKA surgery in a randomized clinical trial of 72 patients. They found that robotic-assisted surgery had definitive advantages in preoperative planning, accuracy of the procedure, and postoperative follow-up regarding femoral and tibial component flexion angles. Finally, Song and colleagues^68,69 performed 2 randomized clinical trials in which they compared mechanical axis alignment, component positioning, soft tissue balancing, and patient preference between conventional TKA surgery and robotic-assisted surgery using the Robodoc system. In the first study,⁶⁸ they simultaneously performed robotic-assisted surgery in one leg and conventional TKA surgery in the other leg. They found that robotic-assisted surgery resulted in less outlier in mechanical axis and component positioning. Furthermore, they found at latest follow-up of 2 years that 12 patients preferred the leg treated with robotic-assisted surgery while 6 preferred the conventional leg. Despite this finding, no significant differences in functional outcome scores were detected between both treatment options. Furthermore, they found that flexion-extension balance was achieved in 92% of patients treated with robotic-assisted TKA surgery and in 77% of patients treated with conventional TKA surgery. In the other study,⁶⁹ the authors found that more patients treated with robotic-assisted surgery had <2 mm flexion-extension gap and more satisfactory posterior cruciate ligament tension when compared to conventional surgery.

These studies have shown that robotic-assisted surgery is accurate in controlling surgical variables, such as mechanical lower leg alignment, maintaining joint-line, implant positioning, and soft tissue balancing. Furthermore, these studies have shown that controlling these variables is better than the current gold standard of manual knee arthroplasty. Until now, not many studies have assessed survivorship of robotic-assisted surgery. Furthermore, no studies have, to our knowledge, compared survivorship of robotic-assisted with conventional knee replacement surgery. Finally, studies comparing functional outcomes following robotic-assisted surgery and conventional knee arthroplasty surgery are frequently underpowered due to their small sample sizes.^68,70 Since many studies have shown that the surgical variables are more tightly controlled using robotic-assisted surgery when compared to conventional surgery, large comparative studies are necessary to assess the role of robotic-assisted surgery in functional outcomes and survivorship of UKA and TKA.

Cost-Effectiveness of Robotic-Assisted Surgery

High initial capital costs of robotic-assisted surgery is one of the factors that constitute a barrier to the widespread implementation of this technique. Multiple authors have suggested that improved implant survivorship afforded by robotic-assisted surgery may justify the expenditure from both societal and provider perspective.^84-86 Two studies have performed a cost-effectiveness analysis for UKA surgery. Swank and colleagues⁸⁴ reviewed the hospital expenditures and profits associated with robot-assisted knee arthroplasty, citing upfront costs of approximately $800,000. The authors estimated a mean per-case contribution profit of $5790 for robotic-assisted UKA, assuming an inpatient-to-outpatient ratio of 1 to 3. Based on this data, Swank and colleagues84 proposed that the capital costs of robotic-assisted UKA may be recovered in as little as 2 years when in the first 3 consecutive years 50, 70, and 90 cases were performed using robotic-assisted UKA. Moschetti and colleagues⁸⁵ recently published the first formal cost-effectiveness analysis of robotic-assisted compared to manual UKA. The authors used an annual revision risk of 0.55% for the first 2 years following robot-assisted UKA, based on the aforementioned presented data by Coon and colleagues.⁸¹ They based their data on the Mako system and assumed an initial capital expenditure of $934,728 with annual servicing costs of 10% (discounted annually) for 4 years thereafter, resulting in a total cost of the robotic system of $1.362 million. These costs were divided by the number of patients estimated to undergo robotic-assisted UKA per year, which was varied to estimate the effect of case volume on cost-effectiveness. The authors reported that robotic-assisted UKA was associated with higher lifetime costs and net utilities compared to manual UKA, at an incremental cost-effectiveness ratio of $47,180 per quality-adjusted life year (QALY) in a high-volume center. This falls well within the societal willingness-to-pay threshold of $100,000/QALY. Sensitivity analysis showed that robotic-assisted UKA is cost-effective under the following conditions: (1) centers performing at least 94 cases annually, (2) in patients younger than age 67 years, and (3) 2-year revision rate does not exceed 1.2%. While the results of this initial analysis are promising, follow-up cost-effectiveness analysis studies will be required as long-term survivorship data become available.

Conclusion

Tighter control of intraoperative surgical variables, such as lower leg alignment, soft tissue balance, joint-line maintenance, and component alignment and positioning, have been associated with improved survivorship and functional outcomes. Upon reviewing the available literature on robotic-assisted surgery, it becomes clear that this technique can improve the accuracy of these surgical variables and is superior to conventional manual UKA and TKA. Although larger and comparative survivorship studies are necessary to compare robotic-assisted knee arthroplasty to conventional techniques, the early results and cost-effectiveness analysis seem promising.

AMSTERDAM – Further evidence that acetaminophen has limited benefits in patients with osteoarthritis was presented at the World Congress on Osteoarthritis, with authors of a systematic review calling for reconsideration of guidelines recommending the common analgesic as a first-line option.

“[Acetaminophen] provides minimal short-term benefits for people with hip or knee OA,” said presenting author and rheumatologist Dr. David J. Hunter of the University of Sydney. The treatment effects for both pain relief and for improving physical function were smallest in people with knee OA, he said. “In general, the small effect sizes are unlikely to be clinically relevant,” Dr. Hunter observed.

“These are mean differences across large populations in the clinical trials, and there may be certain individuals with knee or hip osteoarthritis that this may not necessarily apply to,” he conceded during a discussion following his presentation, “but I think from the perspective of the recommendations that come from guidelines, we have got to think about what would be do-able in the general population.”

The findings come shortly after the publication of a large meta-analysis of 74 trials evaluating pain-relieving medications that highlighted the ineffectiveness of acetaminophen for OA pain, particularly when compared against diclofenac and other nonsteroidal anti-inflammatory drugs (Lancet. 2016 Mar 17. doi: 10.1016/S0140-6736(16)30002-2).

Dr. Hunter and coworkers searched clinical trial and medical databases from inception to September 2015 for records relating to acetaminophen use in patients with hip or knee OA. Only placebo-controlled, randomized trials were included, and nine records were found that reported 10 trials involving 3,541 patients. Part of the analysis was published in the BMJ last year (BMJ. 2015;350:h1225. doi: 10.1136/bmj.h1225). The last prior systematic review on the topic was published in 2004 (Ann Rheum Dis. 2004;Aug;63[8]:901–7).

Pain scores were converted to a common 0-100 scale with 0 signifying no pain or disability and 100 the worst possible pain or disability and then expressed as a mean difference between the acetaminophen and placebo groups. Physical function scores were pooled to give a standardized mean difference.

There was high-quality evidence that acetaminophen given at a dose of 3-4 g per day had a significant effect on pain and physical function during a short period of more than 2 weeks to less than 3 months and a more immediate time frame of 2 weeks or less, but it was unlikely to be clinically significant, with a mean difference of just –3.14 for pain and a standardized mean difference of –0.12 to –0.15 for physical function. Differences would need to be at least 9 points for pain and greater than 0.2 for physical function to be clinically significant, Dr. Hunter explained.

Four of the trials considered knee OA only. The mean and standardized mean differences between the acetaminophen and placebo groups in those trials was just –1.09 for pain and –0.06 for physical function.

Similar numbers of patients reported being adherent to their assigned treatment group, with less rescue analgesic use in the acetaminophen-treated patients. Although no differences in adverse events, serious adverse events, or withdrawals because of adverse events were seen, there was a higher risk of liver function test (LFT) abnormalities in the acetaminophen-treated patients. The relative risk for abnormal LFTs was 3.79, but the clinical significance of this is uncertain according to the review’s authors.

“Current guidelines consistently recommend [acetaminophen] as the first line of analgesic medication for this condition,” Dr. Hunter said at the meeting, sponsored by the Osteoarthritis Research Society International. “But these results call for reconsideration of these recommendations.”

The results highlight the importance of using other, nonpharmacologic means to manage pain and physical function, the authors conclude, such as lifestyle changes, weight control, and regular physical exercise.

Dr. Hunter had no disclosures relevant to his comments.

AMSTERDAM – Further evidence that acetaminophen has limited benefits in patients with osteoarthritis was presented at the World Congress on Osteoarthritis, with authors of a systematic review calling for reconsideration of guidelines recommending the common analgesic as a first-line option.

“[Acetaminophen] provides minimal short-term benefits for people with hip or knee OA,” said presenting author and rheumatologist Dr. David J. Hunter of the University of Sydney. The treatment effects for both pain relief and for improving physical function were smallest in people with knee OA, he said. “In general, the small effect sizes are unlikely to be clinically relevant,” Dr. Hunter observed.

“These are mean differences across large populations in the clinical trials, and there may be certain individuals with knee or hip osteoarthritis that this may not necessarily apply to,” he conceded during a discussion following his presentation, “but I think from the perspective of the recommendations that come from guidelines, we have got to think about what would be do-able in the general population.”

The findings come shortly after the publication of a large meta-analysis of 74 trials evaluating pain-relieving medications that highlighted the ineffectiveness of acetaminophen for OA pain, particularly when compared against diclofenac and other nonsteroidal anti-inflammatory drugs (Lancet. 2016 Mar 17. doi: 10.1016/S0140-6736(16)30002-2).

Dr. Hunter and coworkers searched clinical trial and medical databases from inception to September 2015 for records relating to acetaminophen use in patients with hip or knee OA. Only placebo-controlled, randomized trials were included, and nine records were found that reported 10 trials involving 3,541 patients. Part of the analysis was published in the BMJ last year (BMJ. 2015;350:h1225. doi: 10.1136/bmj.h1225). The last prior systematic review on the topic was published in 2004 (Ann Rheum Dis. 2004;Aug;63[8]:901–7).

Pain scores were converted to a common 0-100 scale with 0 signifying no pain or disability and 100 the worst possible pain or disability and then expressed as a mean difference between the acetaminophen and placebo groups. Physical function scores were pooled to give a standardized mean difference.

There was high-quality evidence that acetaminophen given at a dose of 3-4 g per day had a significant effect on pain and physical function during a short period of more than 2 weeks to less than 3 months and a more immediate time frame of 2 weeks or less, but it was unlikely to be clinically significant, with a mean difference of just –3.14 for pain and a standardized mean difference of –0.12 to –0.15 for physical function. Differences would need to be at least 9 points for pain and greater than 0.2 for physical function to be clinically significant, Dr. Hunter explained.

Four of the trials considered knee OA only. The mean and standardized mean differences between the acetaminophen and placebo groups in those trials was just –1.09 for pain and –0.06 for physical function.

Similar numbers of patients reported being adherent to their assigned treatment group, with less rescue analgesic use in the acetaminophen-treated patients. Although no differences in adverse events, serious adverse events, or withdrawals because of adverse events were seen, there was a higher risk of liver function test (LFT) abnormalities in the acetaminophen-treated patients. The relative risk for abnormal LFTs was 3.79, but the clinical significance of this is uncertain according to the review’s authors.

“Current guidelines consistently recommend [acetaminophen] as the first line of analgesic medication for this condition,” Dr. Hunter said at the meeting, sponsored by the Osteoarthritis Research Society International. “But these results call for reconsideration of these recommendations.”

The results highlight the importance of using other, nonpharmacologic means to manage pain and physical function, the authors conclude, such as lifestyle changes, weight control, and regular physical exercise.

Dr. Hunter had no disclosures relevant to his comments.

AMSTERDAM – Further evidence that acetaminophen has limited benefits in patients with osteoarthritis was presented at the World Congress on Osteoarthritis, with authors of a systematic review calling for reconsideration of guidelines recommending the common analgesic as a first-line option.

“[Acetaminophen] provides minimal short-term benefits for people with hip or knee OA,” said presenting author and rheumatologist Dr. David J. Hunter of the University of Sydney. The treatment effects for both pain relief and for improving physical function were smallest in people with knee OA, he said. “In general, the small effect sizes are unlikely to be clinically relevant,” Dr. Hunter observed.

“These are mean differences across large populations in the clinical trials, and there may be certain individuals with knee or hip osteoarthritis that this may not necessarily apply to,” he conceded during a discussion following his presentation, “but I think from the perspective of the recommendations that come from guidelines, we have got to think about what would be do-able in the general population.”

The findings come shortly after the publication of a large meta-analysis of 74 trials evaluating pain-relieving medications that highlighted the ineffectiveness of acetaminophen for OA pain, particularly when compared against diclofenac and other nonsteroidal anti-inflammatory drugs (Lancet. 2016 Mar 17. doi: 10.1016/S0140-6736(16)30002-2).

Dr. Hunter and coworkers searched clinical trial and medical databases from inception to September 2015 for records relating to acetaminophen use in patients with hip or knee OA. Only placebo-controlled, randomized trials were included, and nine records were found that reported 10 trials involving 3,541 patients. Part of the analysis was published in the BMJ last year (BMJ. 2015;350:h1225. doi: 10.1136/bmj.h1225). The last prior systematic review on the topic was published in 2004 (Ann Rheum Dis. 2004;Aug;63[8]:901–7).

Pain scores were converted to a common 0-100 scale with 0 signifying no pain or disability and 100 the worst possible pain or disability and then expressed as a mean difference between the acetaminophen and placebo groups. Physical function scores were pooled to give a standardized mean difference.

There was high-quality evidence that acetaminophen given at a dose of 3-4 g per day had a significant effect on pain and physical function during a short period of more than 2 weeks to less than 3 months and a more immediate time frame of 2 weeks or less, but it was unlikely to be clinically significant, with a mean difference of just –3.14 for pain and a standardized mean difference of –0.12 to –0.15 for physical function. Differences would need to be at least 9 points for pain and greater than 0.2 for physical function to be clinically significant, Dr. Hunter explained.

Four of the trials considered knee OA only. The mean and standardized mean differences between the acetaminophen and placebo groups in those trials was just –1.09 for pain and –0.06 for physical function.

Similar numbers of patients reported being adherent to their assigned treatment group, with less rescue analgesic use in the acetaminophen-treated patients. Although no differences in adverse events, serious adverse events, or withdrawals because of adverse events were seen, there was a higher risk of liver function test (LFT) abnormalities in the acetaminophen-treated patients. The relative risk for abnormal LFTs was 3.79, but the clinical significance of this is uncertain according to the review’s authors.

“Current guidelines consistently recommend [acetaminophen] as the first line of analgesic medication for this condition,” Dr. Hunter said at the meeting, sponsored by the Osteoarthritis Research Society International. “But these results call for reconsideration of these recommendations.”

The results highlight the importance of using other, nonpharmacologic means to manage pain and physical function, the authors conclude, such as lifestyle changes, weight control, and regular physical exercise.

Dr. Hunter had no disclosures relevant to his comments.

The benefit of adding lumbar fusion surgery to decompression surgery for spinal stenosis was nonexistent in one large clinical trial and very modest in another, according to separate reports published online April 13 in the New England Journal of Medicine.

Both studies indicated that, given the considerable cost and the potential complications associated with lumbar fusion, it may not be worthwhile to add it to decompression surgery for spinal stenosis. “The goal of surgery in lumbar spinal stenosis is to improve walking distance and to relieve pain by decompression of the nerve roots. The addition of instrumented fusion – ‘just to be sure’ – for the treatment of the most frequent forms of lumbar spinal stenosis does not create any added value for patients and might be regarded as an overcautious and unnecessary treatment,” Dr. Wilco C. Peul and Dr. Wouter A. Moojen said in an editorial accompanying the two reports.

Surgical decompression of spinal stenosis using laminectomy is increasingly being supplemented with lumbar fusion, which is thought to firm up spinal instability and minimize the risk of future deformity. In the United States, approximately half of patients who have surgery for spinal stenosis undergo fusion procedures. Of those who also show degenerative spondylolisthesis on preoperative imaging studies, 96% undergo fusion procedures because many spine surgeons see this as a sign of instability and a mandatory indication for fusion. However, the evidence supporting the use of fusion plus decompression, as opposed to decompression alone, is weak, according to the investigators who conducted the Swedish Spinal Stenosis Study. The other study in the New England Journal of Medicine, the Spinal Laminectomy Versus Instrumented Pedicle Screw (SLIP) trial, was conducted in the United States.

Both of those clinical trials were performed to shed further light on the issue.

In the Swedish Spinal Stenosis Study, the investigators assessed outcomes in 247 patients aged 50-80 years who were treated at seven Swedish hospitals over the course of 6 years. This open-label, superiority trial randomly assigned 124 patients to decompression surgery alone and 123 to decompression plus fusion. The primary outcome measure was score on the Oswestry Disability Index (ODI), which measures disability and quality of life in patients with low-back pain, 2 years after surgery. The ODI scale runs from 0 to 100, with higher scores indicating more severe disability, said Dr. Peter Försth of the department of surgical sciences at Uppsala (Sweden) University and the Stockholm Spine Center and his associates.

At 2 years, there was no significant difference between the two study groups; the decompression-only group had a mean ODI score of 24, and the fusion group had a mean score of 27. The ODI scores in both groups had improved from baseline to a similar degree: by 17 points with decompression alone and by 15 points with fusion. In addition, fusion surgery was not superior to decompression alone regardless of whether patients had any degree of spondylolisthesis and regardless of whether they had severe spondylolisthesis involving a vertebral slip of 7.4 mm or more, the investigators reported (N Engl J Med. 2016 April 13. doi: 10.1056/NEJMoa1513721).The two study groups also showed no significant differences in secondary outcome measures, including performance on the 6-minute walk test and subjective patient assessment of improvement in walking ability. Moreover, these results persisted in the 144 patients who were assessed at 5-year follow-up.

In contrast, decompression alone was associated with fewer complications than decompression plus fusion. Postoperative wound infection developed in only 4% of the decompression-only group, compared with 10% of the fusion group. Although this study wasn’t adequately powered to draw firm conclusions regarding complications, a previous analysis of registry data reported that adding fusion surgery to decompression surgery doubles the risk of severe adverse events in older patients, Dr. Försth and his associates said.

Decompression alone also was markedly less expensive than fusion surgery. Mean direct costs were $6,800 higher for fusion than for decompression alone, because of the additional operating time needed, the extended hospital stay, and the cost of the implant.

In the SLIP trial, the researchers compared outcomes in 66 patients aged 50-80 years who all had spinal stenosis with grade 1 degenerative spondylolisthesis. The participants were randomly assigned to undergo decompression alone (35 patients) or decompression plus fusion (31 patients) at five U.S. medical centers, said Dr. Zoher Ghogawala of the Alan and Jacqueline B. Stuart Spine Research Center in the department of neurosurgery at Lahey Hospital and Medical Center, Burlington, Mass., and his associates.

The primary outcome measure was the physical-component summary score on the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) 2 years after surgery. This scale also runs from 0 to 100, but higher scores indicate better physical health. Five points was prespecified as the minimal clinically important difference on the SF-36.

At 2 years, patients in the fusion group showed a small but significant advantage of 5.7 points on the SF-36, with a mean score of 15.2, compared with patients in the decompression-only group (mean score, 9.5). However, the ODI scores, a secondary outcome measure in this study, were not significantly different between the two study groups, Dr. Ghogawala and his associates reported (N Engl J Med. 2016 April 13. doi: 10.1056/NEJMoa1508788).Surgical complications, blood loss, and length of stay all were significantly greater with fusion than with decompression alone.

Dr. Försth’s study was supported by Uppsala University, Uppsala County Council, the Stockholm Spine Center, and Johnson & Johnson. Two of his associates reported ties to Medtronic and Quantify Research. Dr. Ghogawala’s study was supported by the Jean and David Wallace Foundation, the Greenwich Lumbar Stenosis SLIP Study Fund. His associates reported ties to numerous industry sources.

The benefit of adding lumbar fusion surgery to decompression surgery for spinal stenosis was nonexistent in one large clinical trial and very modest in another, according to separate reports published online April 13 in the New England Journal of Medicine.

Both studies indicated that, given the considerable cost and the potential complications associated with lumbar fusion, it may not be worthwhile to add it to decompression surgery for spinal stenosis. “The goal of surgery in lumbar spinal stenosis is to improve walking distance and to relieve pain by decompression of the nerve roots. The addition of instrumented fusion – ‘just to be sure’ – for the treatment of the most frequent forms of lumbar spinal stenosis does not create any added value for patients and might be regarded as an overcautious and unnecessary treatment,” Dr. Wilco C. Peul and Dr. Wouter A. Moojen said in an editorial accompanying the two reports.

Surgical decompression of spinal stenosis using laminectomy is increasingly being supplemented with lumbar fusion, which is thought to firm up spinal instability and minimize the risk of future deformity. In the United States, approximately half of patients who have surgery for spinal stenosis undergo fusion procedures. Of those who also show degenerative spondylolisthesis on preoperative imaging studies, 96% undergo fusion procedures because many spine surgeons see this as a sign of instability and a mandatory indication for fusion. However, the evidence supporting the use of fusion plus decompression, as opposed to decompression alone, is weak, according to the investigators who conducted the Swedish Spinal Stenosis Study. The other study in the New England Journal of Medicine, the Spinal Laminectomy Versus Instrumented Pedicle Screw (SLIP) trial, was conducted in the United States.

Both of those clinical trials were performed to shed further light on the issue.

In the Swedish Spinal Stenosis Study, the investigators assessed outcomes in 247 patients aged 50-80 years who were treated at seven Swedish hospitals over the course of 6 years. This open-label, superiority trial randomly assigned 124 patients to decompression surgery alone and 123 to decompression plus fusion. The primary outcome measure was score on the Oswestry Disability Index (ODI), which measures disability and quality of life in patients with low-back pain, 2 years after surgery. The ODI scale runs from 0 to 100, with higher scores indicating more severe disability, said Dr. Peter Försth of the department of surgical sciences at Uppsala (Sweden) University and the Stockholm Spine Center and his associates.

At 2 years, there was no significant difference between the two study groups; the decompression-only group had a mean ODI score of 24, and the fusion group had a mean score of 27. The ODI scores in both groups had improved from baseline to a similar degree: by 17 points with decompression alone and by 15 points with fusion. In addition, fusion surgery was not superior to decompression alone regardless of whether patients had any degree of spondylolisthesis and regardless of whether they had severe spondylolisthesis involving a vertebral slip of 7.4 mm or more, the investigators reported (N Engl J Med. 2016 April 13. doi: 10.1056/NEJMoa1513721).The two study groups also showed no significant differences in secondary outcome measures, including performance on the 6-minute walk test and subjective patient assessment of improvement in walking ability. Moreover, these results persisted in the 144 patients who were assessed at 5-year follow-up.

In contrast, decompression alone was associated with fewer complications than decompression plus fusion. Postoperative wound infection developed in only 4% of the decompression-only group, compared with 10% of the fusion group. Although this study wasn’t adequately powered to draw firm conclusions regarding complications, a previous analysis of registry data reported that adding fusion surgery to decompression surgery doubles the risk of severe adverse events in older patients, Dr. Försth and his associates said.

Decompression alone also was markedly less expensive than fusion surgery. Mean direct costs were $6,800 higher for fusion than for decompression alone, because of the additional operating time needed, the extended hospital stay, and the cost of the implant.

In the SLIP trial, the researchers compared outcomes in 66 patients aged 50-80 years who all had spinal stenosis with grade 1 degenerative spondylolisthesis. The participants were randomly assigned to undergo decompression alone (35 patients) or decompression plus fusion (31 patients) at five U.S. medical centers, said Dr. Zoher Ghogawala of the Alan and Jacqueline B. Stuart Spine Research Center in the department of neurosurgery at Lahey Hospital and Medical Center, Burlington, Mass., and his associates.

The primary outcome measure was the physical-component summary score on the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) 2 years after surgery. This scale also runs from 0 to 100, but higher scores indicate better physical health. Five points was prespecified as the minimal clinically important difference on the SF-36.

At 2 years, patients in the fusion group showed a small but significant advantage of 5.7 points on the SF-36, with a mean score of 15.2, compared with patients in the decompression-only group (mean score, 9.5). However, the ODI scores, a secondary outcome measure in this study, were not significantly different between the two study groups, Dr. Ghogawala and his associates reported (N Engl J Med. 2016 April 13. doi: 10.1056/NEJMoa1508788).Surgical complications, blood loss, and length of stay all were significantly greater with fusion than with decompression alone.

Dr. Försth’s study was supported by Uppsala University, Uppsala County Council, the Stockholm Spine Center, and Johnson & Johnson. Two of his associates reported ties to Medtronic and Quantify Research. Dr. Ghogawala’s study was supported by the Jean and David Wallace Foundation, the Greenwich Lumbar Stenosis SLIP Study Fund. His associates reported ties to numerous industry sources.

The benefit of adding lumbar fusion surgery to decompression surgery for spinal stenosis was nonexistent in one large clinical trial and very modest in another, according to separate reports published online April 13 in the New England Journal of Medicine.

Both studies indicated that, given the considerable cost and the potential complications associated with lumbar fusion, it may not be worthwhile to add it to decompression surgery for spinal stenosis. “The goal of surgery in lumbar spinal stenosis is to improve walking distance and to relieve pain by decompression of the nerve roots. The addition of instrumented fusion – ‘just to be sure’ – for the treatment of the most frequent forms of lumbar spinal stenosis does not create any added value for patients and might be regarded as an overcautious and unnecessary treatment,” Dr. Wilco C. Peul and Dr. Wouter A. Moojen said in an editorial accompanying the two reports.

Surgical decompression of spinal stenosis using laminectomy is increasingly being supplemented with lumbar fusion, which is thought to firm up spinal instability and minimize the risk of future deformity. In the United States, approximately half of patients who have surgery for spinal stenosis undergo fusion procedures. Of those who also show degenerative spondylolisthesis on preoperative imaging studies, 96% undergo fusion procedures because many spine surgeons see this as a sign of instability and a mandatory indication for fusion. However, the evidence supporting the use of fusion plus decompression, as opposed to decompression alone, is weak, according to the investigators who conducted the Swedish Spinal Stenosis Study. The other study in the New England Journal of Medicine, the Spinal Laminectomy Versus Instrumented Pedicle Screw (SLIP) trial, was conducted in the United States.

Both of those clinical trials were performed to shed further light on the issue.

In the Swedish Spinal Stenosis Study, the investigators assessed outcomes in 247 patients aged 50-80 years who were treated at seven Swedish hospitals over the course of 6 years. This open-label, superiority trial randomly assigned 124 patients to decompression surgery alone and 123 to decompression plus fusion. The primary outcome measure was score on the Oswestry Disability Index (ODI), which measures disability and quality of life in patients with low-back pain, 2 years after surgery. The ODI scale runs from 0 to 100, with higher scores indicating more severe disability, said Dr. Peter Försth of the department of surgical sciences at Uppsala (Sweden) University and the Stockholm Spine Center and his associates.

At 2 years, there was no significant difference between the two study groups; the decompression-only group had a mean ODI score of 24, and the fusion group had a mean score of 27. The ODI scores in both groups had improved from baseline to a similar degree: by 17 points with decompression alone and by 15 points with fusion. In addition, fusion surgery was not superior to decompression alone regardless of whether patients had any degree of spondylolisthesis and regardless of whether they had severe spondylolisthesis involving a vertebral slip of 7.4 mm or more, the investigators reported (N Engl J Med. 2016 April 13. doi: 10.1056/NEJMoa1513721).The two study groups also showed no significant differences in secondary outcome measures, including performance on the 6-minute walk test and subjective patient assessment of improvement in walking ability. Moreover, these results persisted in the 144 patients who were assessed at 5-year follow-up.

In contrast, decompression alone was associated with fewer complications than decompression plus fusion. Postoperative wound infection developed in only 4% of the decompression-only group, compared with 10% of the fusion group. Although this study wasn’t adequately powered to draw firm conclusions regarding complications, a previous analysis of registry data reported that adding fusion surgery to decompression surgery doubles the risk of severe adverse events in older patients, Dr. Försth and his associates said.

Decompression alone also was markedly less expensive than fusion surgery. Mean direct costs were $6,800 higher for fusion than for decompression alone, because of the additional operating time needed, the extended hospital stay, and the cost of the implant.

In the SLIP trial, the researchers compared outcomes in 66 patients aged 50-80 years who all had spinal stenosis with grade 1 degenerative spondylolisthesis. The participants were randomly assigned to undergo decompression alone (35 patients) or decompression plus fusion (31 patients) at five U.S. medical centers, said Dr. Zoher Ghogawala of the Alan and Jacqueline B. Stuart Spine Research Center in the department of neurosurgery at Lahey Hospital and Medical Center, Burlington, Mass., and his associates.

The primary outcome measure was the physical-component summary score on the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) 2 years after surgery. This scale also runs from 0 to 100, but higher scores indicate better physical health. Five points was prespecified as the minimal clinically important difference on the SF-36.

At 2 years, patients in the fusion group showed a small but significant advantage of 5.7 points on the SF-36, with a mean score of 15.2, compared with patients in the decompression-only group (mean score, 9.5). However, the ODI scores, a secondary outcome measure in this study, were not significantly different between the two study groups, Dr. Ghogawala and his associates reported (N Engl J Med. 2016 April 13. doi: 10.1056/NEJMoa1508788).Surgical complications, blood loss, and length of stay all were significantly greater with fusion than with decompression alone.

Dr. Försth’s study was supported by Uppsala University, Uppsala County Council, the Stockholm Spine Center, and Johnson & Johnson. Two of his associates reported ties to Medtronic and Quantify Research. Dr. Ghogawala’s study was supported by the Jean and David Wallace Foundation, the Greenwich Lumbar Stenosis SLIP Study Fund. His associates reported ties to numerous industry sources.

AMSTERDAM – Patients with milder knee osteoarthritis symptoms or better quality of life before undergoing total knee replacement surgery gained less benefit from the surgery than did those who had more severe symptoms in two separate analyses of British and U.S. patients.

Additional evidence from total knee replacements (TKRs) performed on U.S. participants of the Osteoarthritis Initiative also suggest that as the use of TKR has increased to include less symptomatic patients, the overall cost-effectiveness of the procedure has declined.

©pixologicstudio/ thinkstockphotos.com

“Knee replacements are one of those interventions that are known to be very effective and very cost-effective,” Rafael Pinedo-Villanueva, Ph.D., of the University of Oxford (England) said during his presentation of National Health Service data from England at the World Congress on Osteoarthritis. Indeed, knee replacements are associated with significant improvements in pain, function, and quality of life, he said, but that is if you look at the mean values.

As the deciles for baseline knee pain and function decrease in severity, there are diminishing mean improvements and an increasing proportion of patients who do worse after the operation, he reported. Up to 17% of patients had unchanged or improved knee pain scores and up to 27% had lower quality of life scores. If minimally important differences were considered, these percentages rose to 40% and 48% of patients being worse off, respectively.

“The significant improvements seem to be overshadowing what happens to those patients who are doing worse,” Dr. Pinedo-Villanueva suggested. “So essentially cost-effectiveness is being driven by the magnitude of the change in those who do improve, and we don’t really see much about what is happening to those who are doing worse.”

Of over 215,000 records of knee replacement collected from all patients undergoing TKR in England during 2008-2012, Dr. Pinedo-Villanueva and his study coauthors found 117,844 had data on pre- and post-operative knee pain assessed using the Oxford Knee Score (OKS) and quality of life measured with the EQ-5D instrument. The majority of replacements were in women (55%) and almost three quarters of patients had one or no comorbidities. Overall, the mean change in OKS was 15 points, improving from 19 to 34 (the higher the score the lesser the knee pain). EQ-5D scores also improved by a mean difference of 0.30 (from 0.41 to 0.70 where 1.0 is perfect health). Although the vast majority of patients had improved OKS and EQ-5D scores after surgery, unchanged or decreased scores were seen in 8% and 22% of patients, respectively.

“As we breakdown these data by deciles of baseline pain and function we see clearly that those starting at the lower decile improved the most, and that’s to be expected; they’ve a lot more to improve than the ones that came into the operation at the higher decile,” Dr. Pinedo-Villanueva said at the Congress, sponsored by the Osteoarthritis Research Society International. But there were patients who fared worse at every decile, he noted.

Dr. Pinedo-Villanueva concluded that outcome prediction models were needed to try to reduce the number of patients who are apparently worse off after knee replacement and improve the efficiency of resource allocation.

The value of TKR in a contemporary U.S. population was the focus of a separate presentation by Dr. Bart Ferket of Mount Sinai Hospital in New York. Dr. Ferket reported the results of a study looking at the impact of TKR on patients’ quality of life, lifetime costs, and quality-adjusted life years (QALYs) while varying the use of TKR by patients’ functional status at baseline.

“In the United States, the rate at which total knee replacement is performed has doubled in the last two decades,” Dr. Ferket observed. This “disproportionate” increase has been attributed to expanding the eligibility criteria to include less symptomatic patients.

Using data collected over an 8-year period on 1,327 participants from the Osteoarthritis Initiative, Dr. Ferket and his associates at Mount Sinai and Erasmus University Medical Center in Rotterdam (The Netherlands) discovered that the increased uptake of TKR might have affected the likely benefit and reduced the overall cost-effectiveness of the procedure.

At baseline, 17% of the participants, who all had knee osteoarthritis, had had a prior knee replacement.

Quality of life measured on the physical component scores (PCS) of the 12-item Short Form (SF-12) were generally improved after TKR but decreased in those who did not have a knee replaced. The effect on the mental component of the SF-12 was less clear, with possibly a decrease seen in some patients. Changes on the Western Ontario and McMaster Universities Arthritis Index (WOMAC) and Knee injury and Osteoarthritis Outcome Score (KOOS) showed a considerable benefit for knee replacement and there was a general decrease in pain medication over time in those who had surgery. The overall effect was more pronounced if patients with greater baseline symptoms were considered.

Cost-effectiveness modeling showed that reserving TKR for more seriously affected patients may make it more economically attractive. The QALYs gained from TKR was about 11 but as the number of QALYs increased, so did the relative lifetime cost, with increasing incremental cost-effectiveness ratios (ICERs) as SF-12 PCS rose. ICERs were around $143,000, $160,000, $217,000, $385,000, and $1,175,000 considering patients with SF-12 PCS of less than 30, 35, 40, 45, and 50, respectively.

“The more lenient the eligibility criteria are, the higher the effectiveness, but also the higher the costs,” Dr. Ferket said. “The most cost-effective scenarios are actually more restrictive that what is currently seen in current practice in the U.S.”

Dr. Pinedo-Villanueva and Dr. Ferket reported having no financial disclosures.

AMSTERDAM – Patients with milder knee osteoarthritis symptoms or better quality of life before undergoing total knee replacement surgery gained less benefit from the surgery than did those who had more severe symptoms in two separate analyses of British and U.S. patients.

Additional evidence from total knee replacements (TKRs) performed on U.S. participants of the Osteoarthritis Initiative also suggest that as the use of TKR has increased to include less symptomatic patients, the overall cost-effectiveness of the procedure has declined.

©pixologicstudio/ thinkstockphotos.com

“Knee replacements are one of those interventions that are known to be very effective and very cost-effective,” Rafael Pinedo-Villanueva, Ph.D., of the University of Oxford (England) said during his presentation of National Health Service data from England at the World Congress on Osteoarthritis. Indeed, knee replacements are associated with significant improvements in pain, function, and quality of life, he said, but that is if you look at the mean values.

As the deciles for baseline knee pain and function decrease in severity, there are diminishing mean improvements and an increasing proportion of patients who do worse after the operation, he reported. Up to 17% of patients had unchanged or improved knee pain scores and up to 27% had lower quality of life scores. If minimally important differences were considered, these percentages rose to 40% and 48% of patients being worse off, respectively.

“The significant improvements seem to be overshadowing what happens to those patients who are doing worse,” Dr. Pinedo-Villanueva suggested. “So essentially cost-effectiveness is being driven by the magnitude of the change in those who do improve, and we don’t really see much about what is happening to those who are doing worse.”

Of over 215,000 records of knee replacement collected from all patients undergoing TKR in England during 2008-2012, Dr. Pinedo-Villanueva and his study coauthors found 117,844 had data on pre- and post-operative knee pain assessed using the Oxford Knee Score (OKS) and quality of life measured with the EQ-5D instrument. The majority of replacements were in women (55%) and almost three quarters of patients had one or no comorbidities. Overall, the mean change in OKS was 15 points, improving from 19 to 34 (the higher the score the lesser the knee pain). EQ-5D scores also improved by a mean difference of 0.30 (from 0.41 to 0.70 where 1.0 is perfect health). Although the vast majority of patients had improved OKS and EQ-5D scores after surgery, unchanged or decreased scores were seen in 8% and 22% of patients, respectively.

“As we breakdown these data by deciles of baseline pain and function we see clearly that those starting at the lower decile improved the most, and that’s to be expected; they’ve a lot more to improve than the ones that came into the operation at the higher decile,” Dr. Pinedo-Villanueva said at the Congress, sponsored by the Osteoarthritis Research Society International. But there were patients who fared worse at every decile, he noted.

Dr. Pinedo-Villanueva concluded that outcome prediction models were needed to try to reduce the number of patients who are apparently worse off after knee replacement and improve the efficiency of resource allocation.

The value of TKR in a contemporary U.S. population was the focus of a separate presentation by Dr. Bart Ferket of Mount Sinai Hospital in New York. Dr. Ferket reported the results of a study looking at the impact of TKR on patients’ quality of life, lifetime costs, and quality-adjusted life years (QALYs) while varying the use of TKR by patients’ functional status at baseline.

“In the United States, the rate at which total knee replacement is performed has doubled in the last two decades,” Dr. Ferket observed. This “disproportionate” increase has been attributed to expanding the eligibility criteria to include less symptomatic patients.

Using data collected over an 8-year period on 1,327 participants from the Osteoarthritis Initiative, Dr. Ferket and his associates at Mount Sinai and Erasmus University Medical Center in Rotterdam (The Netherlands) discovered that the increased uptake of TKR might have affected the likely benefit and reduced the overall cost-effectiveness of the procedure.

At baseline, 17% of the participants, who all had knee osteoarthritis, had had a prior knee replacement.

Quality of life measured on the physical component scores (PCS) of the 12-item Short Form (SF-12) were generally improved after TKR but decreased in those who did not have a knee replaced. The effect on the mental component of the SF-12 was less clear, with possibly a decrease seen in some patients. Changes on the Western Ontario and McMaster Universities Arthritis Index (WOMAC) and Knee injury and Osteoarthritis Outcome Score (KOOS) showed a considerable benefit for knee replacement and there was a general decrease in pain medication over time in those who had surgery. The overall effect was more pronounced if patients with greater baseline symptoms were considered.

Cost-effectiveness modeling showed that reserving TKR for more seriously affected patients may make it more economically attractive. The QALYs gained from TKR was about 11 but as the number of QALYs increased, so did the relative lifetime cost, with increasing incremental cost-effectiveness ratios (ICERs) as SF-12 PCS rose. ICERs were around $143,000, $160,000, $217,000, $385,000, and $1,175,000 considering patients with SF-12 PCS of less than 30, 35, 40, 45, and 50, respectively.

“The more lenient the eligibility criteria are, the higher the effectiveness, but also the higher the costs,” Dr. Ferket said. “The most cost-effective scenarios are actually more restrictive that what is currently seen in current practice in the U.S.”

Dr. Pinedo-Villanueva and Dr. Ferket reported having no financial disclosures.

AMSTERDAM – Patients with milder knee osteoarthritis symptoms or better quality of life before undergoing total knee replacement surgery gained less benefit from the surgery than did those who had more severe symptoms in two separate analyses of British and U.S. patients.

Additional evidence from total knee replacements (TKRs) performed on U.S. participants of the Osteoarthritis Initiative also suggest that as the use of TKR has increased to include less symptomatic patients, the overall cost-effectiveness of the procedure has declined.

©pixologicstudio/ thinkstockphotos.com

“Knee replacements are one of those interventions that are known to be very effective and very cost-effective,” Rafael Pinedo-Villanueva, Ph.D., of the University of Oxford (England) said during his presentation of National Health Service data from England at the World Congress on Osteoarthritis. Indeed, knee replacements are associated with significant improvements in pain, function, and quality of life, he said, but that is if you look at the mean values.

As the deciles for baseline knee pain and function decrease in severity, there are diminishing mean improvements and an increasing proportion of patients who do worse after the operation, he reported. Up to 17% of patients had unchanged or improved knee pain scores and up to 27% had lower quality of life scores. If minimally important differences were considered, these percentages rose to 40% and 48% of patients being worse off, respectively.

“The significant improvements seem to be overshadowing what happens to those patients who are doing worse,” Dr. Pinedo-Villanueva suggested. “So essentially cost-effectiveness is being driven by the magnitude of the change in those who do improve, and we don’t really see much about what is happening to those who are doing worse.”

Of over 215,000 records of knee replacement collected from all patients undergoing TKR in England during 2008-2012, Dr. Pinedo-Villanueva and his study coauthors found 117,844 had data on pre- and post-operative knee pain assessed using the Oxford Knee Score (OKS) and quality of life measured with the EQ-5D instrument. The majority of replacements were in women (55%) and almost three quarters of patients had one or no comorbidities. Overall, the mean change in OKS was 15 points, improving from 19 to 34 (the higher the score the lesser the knee pain). EQ-5D scores also improved by a mean difference of 0.30 (from 0.41 to 0.70 where 1.0 is perfect health). Although the vast majority of patients had improved OKS and EQ-5D scores after surgery, unchanged or decreased scores were seen in 8% and 22% of patients, respectively.

“As we breakdown these data by deciles of baseline pain and function we see clearly that those starting at the lower decile improved the most, and that’s to be expected; they’ve a lot more to improve than the ones that came into the operation at the higher decile,” Dr. Pinedo-Villanueva said at the Congress, sponsored by the Osteoarthritis Research Society International. But there were patients who fared worse at every decile, he noted.

Dr. Pinedo-Villanueva concluded that outcome prediction models were needed to try to reduce the number of patients who are apparently worse off after knee replacement and improve the efficiency of resource allocation.

The value of TKR in a contemporary U.S. population was the focus of a separate presentation by Dr. Bart Ferket of Mount Sinai Hospital in New York. Dr. Ferket reported the results of a study looking at the impact of TKR on patients’ quality of life, lifetime costs, and quality-adjusted life years (QALYs) while varying the use of TKR by patients’ functional status at baseline.

“In the United States, the rate at which total knee replacement is performed has doubled in the last two decades,” Dr. Ferket observed. This “disproportionate” increase has been attributed to expanding the eligibility criteria to include less symptomatic patients.

Using data collected over an 8-year period on 1,327 participants from the Osteoarthritis Initiative, Dr. Ferket and his associates at Mount Sinai and Erasmus University Medical Center in Rotterdam (The Netherlands) discovered that the increased uptake of TKR might have affected the likely benefit and reduced the overall cost-effectiveness of the procedure.

At baseline, 17% of the participants, who all had knee osteoarthritis, had had a prior knee replacement.

Quality of life measured on the physical component scores (PCS) of the 12-item Short Form (SF-12) were generally improved after TKR but decreased in those who did not have a knee replaced. The effect on the mental component of the SF-12 was less clear, with possibly a decrease seen in some patients. Changes on the Western Ontario and McMaster Universities Arthritis Index (WOMAC) and Knee injury and Osteoarthritis Outcome Score (KOOS) showed a considerable benefit for knee replacement and there was a general decrease in pain medication over time in those who had surgery. The overall effect was more pronounced if patients with greater baseline symptoms were considered.

Cost-effectiveness modeling showed that reserving TKR for more seriously affected patients may make it more economically attractive. The QALYs gained from TKR was about 11 but as the number of QALYs increased, so did the relative lifetime cost, with increasing incremental cost-effectiveness ratios (ICERs) as SF-12 PCS rose. ICERs were around $143,000, $160,000, $217,000, $385,000, and $1,175,000 considering patients with SF-12 PCS of less than 30, 35, 40, 45, and 50, respectively.

“The more lenient the eligibility criteria are, the higher the effectiveness, but also the higher the costs,” Dr. Ferket said. “The most cost-effective scenarios are actually more restrictive that what is currently seen in current practice in the U.S.”

Dr. Pinedo-Villanueva and Dr. Ferket reported having no financial disclosures.

The American Academy of Orthopaedic Surgeons has adopted clinical practice guidelines that assign evidence-based ratings for common strategies used to diagnose and treat carpal tunnel syndrome (CTS).

The 982-page comprehensive guidelines have been endorsed by the American Society for the Surgery of the Hand and the American College of Radiology. The guidelines address the burden of CTS, the second most common cause of sick days from work, according to AAOS, and its etiology, risk factors, emotional and physical impact, potential benefits, harms, contraindications, and future research. The document is available on the OrthoGuidelines Web-based app at orthoguidelines.org.

©nebari/Thinkstock.com

The assessments of evidence are based upon a systematic review of the current scientific and clinical information and accepted approaches to treatment and/or diagnosis of carpal tunnel syndrome. In addition to a concise summary, the report includes an exhaustive list of studies used to establish levels of evidence and a summary of the evidence in each. Also included is a list of studies not included, many because of poor study design or very small samples.

The guidelines make recommendations on practices to diagnose and manage CTS based on four levels of evidence:

• Strong: Supported by two or more “high-quality” studies with consistent findings.

• Moderate: Supported by two or more “moderate-quality” studies or one “high-quality” study.

• Limited: Supported by two or more “low-quality” studies or one “moderate-quality” study, or the evidence is considered insufficient or conflicting.

• Consensus: No supporting evidence but the guidelines development group made a recommendation based on clinical opinion.

Diagnosis and risk evidence

For diagnosis of CTS, the guidelines rate the evidence for the value of both observation and physical signs as strong, but assign ratings of moderate to MRI and limited to ultrasound. Evidence is strong for thenar atrophy, or diminished thumb muscle mass, being associated with CTS, but a lack of thenar atrophy is not enough to rule out a diagnosis. Common evaluation tools such the Phalen test, Tinel sign, Flick sign, or Upper-Limb Neurodynamic/Nerve Tension test (ULNT) are weakly supported as independent physical examination maneuvers to rule in or rule out carpal tunnel and the guidelines suggest that they not be used as sole diagnostic tools.

Moderate evidence supports exercise and physical activity to reduce the risk of developing CTS. The guidelines consider obesity a strong risk factor for CTS, but assign moderate ratings to evidence for a host of other factors, perimenopausal status, wrist ratio/index, rheumatoid arthritis, psychosocial factors, and activities such as gardening and computer use among them.  

Treatment evidence

For treatment, the guidelines evaluate evidence for both surgical and nonsurgical strategies. In general, evidence for the efficacy of splinting, steroids (oral or injection), the use of ketoprofen phonophoresis gel, and magnetic therapy is strong. But therapeutic ultrasound and laser therapy are backed up with only limited evidence from the literature.

As might be expected, the evidence is strong for the efficacy of surgery to release the transverse carpal ligament. “Strong evidence supports that surgical treatment of carpal tunnel syndrome should have a greater treatment benefit at 6 and 12 months as compared to splinting, NSAIDs/therapy, and a single steroid injection.” But the value of adjunctive techniques such as epineurotomy, neurolysis, flexor tenosynovectomy, and lengthening/reconstruction of the flexor retinaculum (transverse carpal ligament) is not supported with strong evidence at this point. And the superiority of the endoscopic surgical approach is supported with only limited evidence.

“The impetus for this came from trying to help physicians cull through literally thousands and thousands of published research papers concerning various diagnoses,” said Dr. Allan E. Peljovich, vice-chair of the Guideline Work Group and AAOS representative to the group. It’s a tool to help orthopedic surgeons and other practitioners “understand what our best evidence tells us about diagnosing and treating a variety of conditions,” he said.

The effort to develop the CTS guidelines started February 2013 and involved the Guideline Work Group formulating a set of questions that, as Dr. Peljovich explained, were “the most pertinent questions that anybody interested in a particular diagnosis would want to have answered.” Then a team of statisticians and epidemiologists culled through the “incredible expanse of English language literature” to correlate data to answer those questions.

In May 2015 the work group then met to review the evidence and draft final recommendations. After a period of editing, the draft was submitted for peer review in September. The AAOS board of directors adopted the guidelines in February.

“The guidelines are not intended to be a cookbook on how to treat a condition,” Dr. Peljovich said. “They are really designed to tell you what the best evidence says about a particular set of questions. It helps you to be as updated as you want to be; it’s not designed to tell you this is the only way to do anything. ... It’s an educational tool.”

Members of the Guideline Work Group, AAOS staff, and contributing members submitted their disclosures to the AAOS.

The American Academy of Orthopaedic Surgeons has adopted clinical practice guidelines that assign evidence-based ratings for common strategies used to diagnose and treat carpal tunnel syndrome (CTS).

The 982-page comprehensive guidelines have been endorsed by the American Society for the Surgery of the Hand and the American College of Radiology. The guidelines address the burden of CTS, the second most common cause of sick days from work, according to AAOS, and its etiology, risk factors, emotional and physical impact, potential benefits, harms, contraindications, and future research. The document is available on the OrthoGuidelines Web-based app at orthoguidelines.org.

©nebari/Thinkstock.com

The assessments of evidence are based upon a systematic review of the current scientific and clinical information and accepted approaches to treatment and/or diagnosis of carpal tunnel syndrome. In addition to a concise summary, the report includes an exhaustive list of studies used to establish levels of evidence and a summary of the evidence in each. Also included is a list of studies not included, many because of poor study design or very small samples.

The guidelines make recommendations on practices to diagnose and manage CTS based on four levels of evidence:

• Strong: Supported by two or more “high-quality” studies with consistent findings.

• Moderate: Supported by two or more “moderate-quality” studies or one “high-quality” study.

• Limited: Supported by two or more “low-quality” studies or one “moderate-quality” study, or the evidence is considered insufficient or conflicting.

• Consensus: No supporting evidence but the guidelines development group made a recommendation based on clinical opinion.

Diagnosis and risk evidence

For diagnosis of CTS, the guidelines rate the evidence for the value of both observation and physical signs as strong, but assign ratings of moderate to MRI and limited to ultrasound. Evidence is strong for thenar atrophy, or diminished thumb muscle mass, being associated with CTS, but a lack of thenar atrophy is not enough to rule out a diagnosis. Common evaluation tools such the Phalen test, Tinel sign, Flick sign, or Upper-Limb Neurodynamic/Nerve Tension test (ULNT) are weakly supported as independent physical examination maneuvers to rule in or rule out carpal tunnel and the guidelines suggest that they not be used as sole diagnostic tools.

Moderate evidence supports exercise and physical activity to reduce the risk of developing CTS. The guidelines consider obesity a strong risk factor for CTS, but assign moderate ratings to evidence for a host of other factors, perimenopausal status, wrist ratio/index, rheumatoid arthritis, psychosocial factors, and activities such as gardening and computer use among them.  

Treatment evidence

For treatment, the guidelines evaluate evidence for both surgical and nonsurgical strategies. In general, evidence for the efficacy of splinting, steroids (oral or injection), the use of ketoprofen phonophoresis gel, and magnetic therapy is strong. But therapeutic ultrasound and laser therapy are backed up with only limited evidence from the literature.

As might be expected, the evidence is strong for the efficacy of surgery to release the transverse carpal ligament. “Strong evidence supports that surgical treatment of carpal tunnel syndrome should have a greater treatment benefit at 6 and 12 months as compared to splinting, NSAIDs/therapy, and a single steroid injection.” But the value of adjunctive techniques such as epineurotomy, neurolysis, flexor tenosynovectomy, and lengthening/reconstruction of the flexor retinaculum (transverse carpal ligament) is not supported with strong evidence at this point. And the superiority of the endoscopic surgical approach is supported with only limited evidence.

“The impetus for this came from trying to help physicians cull through literally thousands and thousands of published research papers concerning various diagnoses,” said Dr. Allan E. Peljovich, vice-chair of the Guideline Work Group and AAOS representative to the group. It’s a tool to help orthopedic surgeons and other practitioners “understand what our best evidence tells us about diagnosing and treating a variety of conditions,” he said.

The effort to develop the CTS guidelines started February 2013 and involved the Guideline Work Group formulating a set of questions that, as Dr. Peljovich explained, were “the most pertinent questions that anybody interested in a particular diagnosis would want to have answered.” Then a team of statisticians and epidemiologists culled through the “incredible expanse of English language literature” to correlate data to answer those questions.

In May 2015 the work group then met to review the evidence and draft final recommendations. After a period of editing, the draft was submitted for peer review in September. The AAOS board of directors adopted the guidelines in February.

“The guidelines are not intended to be a cookbook on how to treat a condition,” Dr. Peljovich said. “They are really designed to tell you what the best evidence says about a particular set of questions. It helps you to be as updated as you want to be; it’s not designed to tell you this is the only way to do anything. ... It’s an educational tool.”

Members of the Guideline Work Group, AAOS staff, and contributing members submitted their disclosures to the AAOS.

The American Academy of Orthopaedic Surgeons has adopted clinical practice guidelines that assign evidence-based ratings for common strategies used to diagnose and treat carpal tunnel syndrome (CTS).

The 982-page comprehensive guidelines have been endorsed by the American Society for the Surgery of the Hand and the American College of Radiology. The guidelines address the burden of CTS, the second most common cause of sick days from work, according to AAOS, and its etiology, risk factors, emotional and physical impact, potential benefits, harms, contraindications, and future research. The document is available on the OrthoGuidelines Web-based app at orthoguidelines.org.

©nebari/Thinkstock.com

The assessments of evidence are based upon a systematic review of the current scientific and clinical information and accepted approaches to treatment and/or diagnosis of carpal tunnel syndrome. In addition to a concise summary, the report includes an exhaustive list of studies used to establish levels of evidence and a summary of the evidence in each. Also included is a list of studies not included, many because of poor study design or very small samples.

The guidelines make recommendations on practices to diagnose and manage CTS based on four levels of evidence:

• Strong: Supported by two or more “high-quality” studies with consistent findings.

• Moderate: Supported by two or more “moderate-quality” studies or one “high-quality” study.

• Limited: Supported by two or more “low-quality” studies or one “moderate-quality” study, or the evidence is considered insufficient or conflicting.

• Consensus: No supporting evidence but the guidelines development group made a recommendation based on clinical opinion.

Diagnosis and risk evidence

For diagnosis of CTS, the guidelines rate the evidence for the value of both observation and physical signs as strong, but assign ratings of moderate to MRI and limited to ultrasound. Evidence is strong for thenar atrophy, or diminished thumb muscle mass, being associated with CTS, but a lack of thenar atrophy is not enough to rule out a diagnosis. Common evaluation tools such the Phalen test, Tinel sign, Flick sign, or Upper-Limb Neurodynamic/Nerve Tension test (ULNT) are weakly supported as independent physical examination maneuvers to rule in or rule out carpal tunnel and the guidelines suggest that they not be used as sole diagnostic tools.

Moderate evidence supports exercise and physical activity to reduce the risk of developing CTS. The guidelines consider obesity a strong risk factor for CTS, but assign moderate ratings to evidence for a host of other factors, perimenopausal status, wrist ratio/index, rheumatoid arthritis, psychosocial factors, and activities such as gardening and computer use among them.  

Treatment evidence

For treatment, the guidelines evaluate evidence for both surgical and nonsurgical strategies. In general, evidence for the efficacy of splinting, steroids (oral or injection), the use of ketoprofen phonophoresis gel, and magnetic therapy is strong. But therapeutic ultrasound and laser therapy are backed up with only limited evidence from the literature.

As might be expected, the evidence is strong for the efficacy of surgery to release the transverse carpal ligament. “Strong evidence supports that surgical treatment of carpal tunnel syndrome should have a greater treatment benefit at 6 and 12 months as compared to splinting, NSAIDs/therapy, and a single steroid injection.” But the value of adjunctive techniques such as epineurotomy, neurolysis, flexor tenosynovectomy, and lengthening/reconstruction of the flexor retinaculum (transverse carpal ligament) is not supported with strong evidence at this point. And the superiority of the endoscopic surgical approach is supported with only limited evidence.

“The impetus for this came from trying to help physicians cull through literally thousands and thousands of published research papers concerning various diagnoses,” said Dr. Allan E. Peljovich, vice-chair of the Guideline Work Group and AAOS representative to the group. It’s a tool to help orthopedic surgeons and other practitioners “understand what our best evidence tells us about diagnosing and treating a variety of conditions,” he said.

The effort to develop the CTS guidelines started February 2013 and involved the Guideline Work Group formulating a set of questions that, as Dr. Peljovich explained, were “the most pertinent questions that anybody interested in a particular diagnosis would want to have answered.” Then a team of statisticians and epidemiologists culled through the “incredible expanse of English language literature” to correlate data to answer those questions.

In May 2015 the work group then met to review the evidence and draft final recommendations. After a period of editing, the draft was submitted for peer review in September. The AAOS board of directors adopted the guidelines in February.

“The guidelines are not intended to be a cookbook on how to treat a condition,” Dr. Peljovich said. “They are really designed to tell you what the best evidence says about a particular set of questions. It helps you to be as updated as you want to be; it’s not designed to tell you this is the only way to do anything. ... It’s an educational tool.”

Members of the Guideline Work Group, AAOS staff, and contributing members submitted their disclosures to the AAOS.