A mentor told me during my pediatrics residency that going to school is “the main job of a teenager.” This is because at school, teenagers will be spending the majority of their time and energy learning and growing to become a thriving adult. However, the school environment matters. We are familiar with how excellent teachers, the availability of tutoring, and an administration dedicated to academic achievement play a big role. We also should be aware that if teenagers feel unsafe going to school – especially if they are victims of bullying – they are unable to take advantage of these resources.

Bullying is a repetitive, unwanted, and aggressive behavior among children and adolescents that involves a real or perceived power imbalance.¹ Despite the increasing visibility of lesbian, gay, bisexual, and transgender (LGBT) individuals, bullying remains a serious problem for this population. Although between one in four and one in three of all youth experience bullying,² according to the Youth Risk Behavior Survey, LGBT students are two to four times as likely to be threatened or injured with a weapon on school property, two to three times as likely not to go to school because they feel unsafe, and about two times as likely to be bullied at school, compared with their heterosexual peers.³ Alarmingly, more than half of transgender students experience bullying and harassment at school.⁴

A key component of bullying is the power imbalance. Bullying perpetrators feel that they have more power physically (e.g., in size) or socially (e.g., in social status).⁵ LGBT youth are often the victims of bullying because of the societal stigma against same-sex attraction or gender nonconformity. As a result, they tend to have a lower social status, putting them at risk for bullying. Remember, however, that this power imbalance is perceived. Even straight teenagers can be victims of antigay and antitrans bullying because they don’t conform to gender norms (e.g., a straight boy interested in theater instead of sports).⁶ Therefore, any teenager can be a victim of antigay and antitrans bullying.

Although many believe that experiencing bullying is a “rite of passage,” a look at the research on bullying contradicts this. Youth who experience bullying have higher rates of depression, loneliness, and, most worrisome of all, suicide.^7,8 One study showed that LGBT youth who experience bullying are almost six times as likely to consider suicide.⁹ Such sobering statistics prove that bullying is harmful. Furthermore, the effects of bullying can last into adulthood. One study showed that LGBT youth who experienced bullying during high school are more likely to have depressive symptoms and to be dissatisfied with life as a young adult.¹⁰ If rites of passage are designed to make a teenager into a well-adjusted young adult, then bullying does a poor job.

Although antigay bullying and harassment occur outside the clinic, providers can encounter both the perpetrator and the victim as patients and not realize it. Providers who have patients at risk for bullying – such as LGBT or gender-nonconforming youth – should routinely ask them about bullying through such questions as:

• “How many good friends do you have in school?”

• “Do you ever feel afraid to go to school? Why?”

• “Do other kids ever bully you at school, in your neighborhood, or online? Who bullies you?

• When and where does it happen? What do they say or do?”¹¹

Asking these questions is especially important if you or your patient’s caregivers notice school phobia, attention problems, or psychosomatic complaints.11 Once you identify a victim, refer the patient to a mental health provider to develop skills to cope with the stress of bullying. Such skills include how to make friends. Emphasize that it is not the victim’s fault that they are experiencing bullying. Avoid telling victims to fight back or “suck it up.” In addition, work with parents and school authorities to intervene on behalf of the child to stop the bullying behavior.

Lisa Quarfoth/Thinkstock

At the same time, it is especially important to identify perpetrators. Perpetrators tend to have conduct problems, increased depressive symptoms, and poor school adjustment.¹² They may have been bullied themselves. Also refer perpetrators to a mental health provider and other resources to address these problems.

However, with your limited time to screen for bullying or to create an individualized plan to protect bullying victims, approaches to reducing bullying and their adverse effects require a community effort. Use your expertise and access to the latest scientific research to advocate and help create policies schools can use to address antigay bullying. Clark and Tilly recommend a three-tier approach in addressing antigay bullying. In the first tier, schools should create a safe and affirmative environment for all students. An example of such an approach is to have a speaker – such as a physician from the community – talking to students about bullying and encouraging bystanders to speak up (i.e., be an ally) for bullying victims. Although some schools may be hesitant to implement a schoolwide intervention, they may implement a second-tier approach, such as classroom curricula on how to be an ally or incentive programs for helping vulnerable students (e.g., tutoring). Finally, the third tier requires intensive individualized interventions for bullying victims. Schools should have a step-by-step plan involving school authorities that students and their parents can use if students are experiencing bullying.¹³ Implementation of this plan requires timely follow-up from school officials to ensure cessation of the bullying behavior.10

Another way you can advocate for your LGBT patients is to be knowledgeable about the laws surrounding bullying. Bullying laws vary according to state. This is especially true if such laws specifically prohibit bullying based on sexual orientation or gender identity. This is known as “enumeration.” Enumerated laws grant school authorities the power to prevent and to correct any bullying based on sexual orientation and gender identity. Currently, 18 states and the District of Columbia have enumerated antibullying laws.¹⁴ If you live in a state that does not have an enumerated antibullying law, you can contact your state government officials to urge them to pass such a law.

Bullying has a powerful impact on the health and well-being of LGBT youth. Screen for bullying in your LGBT patients and work with schools and parents to protect them from such behaviors. Most importantly, advocate for creating a safe school environment for LGBT youth so that they can focus on their main job of learning and becoming a thriving adult.

Resources

• The website www.stopbullying.gov is a comprehensive resource for bullying and how to address it.

• Society of Adolescent Health & Medicine (SAHM) position statement on bullying (J Adolesc Health. 2005 Jan;36[1]:88-91).

• American Academy of Pediatrics (AAP) position statement on bullying (Pediatrics. 2009 July. doi: 10.1542/peds.2009-0943).

• Gay, Lesbian & Straight Education Network (GLSEN) information on enumerated antibullying laws by state (www.glsen.org/article/state-maps).

References

1. Bullying definition at www.stopbullying.gov.

2. Student Reports of Bullying and Cyber-Bullying: Results From the 2011 School Crime Supplement to the National Crime Victimization Survey.

3. J Adolesc Health. 2014 Sep;55(3):432-8.

4. Injustice at Every Turn: A Report of the National Transgender Discrimination Survey. Washington: National Center for Transgender Equality and National Gay and Lesbian Task Force, 2011.

5. Can Fam Physician. 2009 Apr;55(4):356-60.

6. J Adolesc Health. 2016 Feb;58(2):S1-S2.

7. Pediatrics. 2003;111(6 Pt 1):1312-7.

8. Journal of Educational Psychology. 2000 Jun;92(2):349-59.

9. Prev Sci. 2015 Apr;16(3):451-62.

10. Dev Psychol. 2010 Nov;46(6):1580-9.

11. Roles for pediatricians in bullying prevention and intervention (www.stopbullying.gov/resources-files/roles-for-pediatricians-tipsheet.pdf).

12. J Adolesc Health. 2005 Jan;36(1):88-91.

13. Clark JP, Tilly, WD. The evolution of response to intervention. In: Clark JP, Alvarez, Michelle, ed. Response to intervention: A guide for school social worker. (New York: Oxford University Press; 2010:3-18).

14. Enumerated antibullying laws by state(www.glsen.org/article/state-maps).

Dr. Montano is an adolescent medicine fellow at Children’s Hospital of Pittsburgh of UPMC and a postdoctoral fellow in the department of pediatrics at the University of Pittsburgh.

A mentor told me during my pediatrics residency that going to school is “the main job of a teenager.” This is because at school, teenagers will be spending the majority of their time and energy learning and growing to become a thriving adult. However, the school environment matters. We are familiar with how excellent teachers, the availability of tutoring, and an administration dedicated to academic achievement play a big role. We also should be aware that if teenagers feel unsafe going to school – especially if they are victims of bullying – they are unable to take advantage of these resources.

Bullying is a repetitive, unwanted, and aggressive behavior among children and adolescents that involves a real or perceived power imbalance.¹ Despite the increasing visibility of lesbian, gay, bisexual, and transgender (LGBT) individuals, bullying remains a serious problem for this population. Although between one in four and one in three of all youth experience bullying,² according to the Youth Risk Behavior Survey, LGBT students are two to four times as likely to be threatened or injured with a weapon on school property, two to three times as likely not to go to school because they feel unsafe, and about two times as likely to be bullied at school, compared with their heterosexual peers.³ Alarmingly, more than half of transgender students experience bullying and harassment at school.⁴

A key component of bullying is the power imbalance. Bullying perpetrators feel that they have more power physically (e.g., in size) or socially (e.g., in social status).⁵ LGBT youth are often the victims of bullying because of the societal stigma against same-sex attraction or gender nonconformity. As a result, they tend to have a lower social status, putting them at risk for bullying. Remember, however, that this power imbalance is perceived. Even straight teenagers can be victims of antigay and antitrans bullying because they don’t conform to gender norms (e.g., a straight boy interested in theater instead of sports).⁶ Therefore, any teenager can be a victim of antigay and antitrans bullying.

Although many believe that experiencing bullying is a “rite of passage,” a look at the research on bullying contradicts this. Youth who experience bullying have higher rates of depression, loneliness, and, most worrisome of all, suicide.^7,8 One study showed that LGBT youth who experience bullying are almost six times as likely to consider suicide.⁹ Such sobering statistics prove that bullying is harmful. Furthermore, the effects of bullying can last into adulthood. One study showed that LGBT youth who experienced bullying during high school are more likely to have depressive symptoms and to be dissatisfied with life as a young adult.¹⁰ If rites of passage are designed to make a teenager into a well-adjusted young adult, then bullying does a poor job.

Although antigay bullying and harassment occur outside the clinic, providers can encounter both the perpetrator and the victim as patients and not realize it. Providers who have patients at risk for bullying – such as LGBT or gender-nonconforming youth – should routinely ask them about bullying through such questions as:

• “How many good friends do you have in school?”

• “Do you ever feel afraid to go to school? Why?”

• “Do other kids ever bully you at school, in your neighborhood, or online? Who bullies you?

• When and where does it happen? What do they say or do?”¹¹

Asking these questions is especially important if you or your patient’s caregivers notice school phobia, attention problems, or psychosomatic complaints.11 Once you identify a victim, refer the patient to a mental health provider to develop skills to cope with the stress of bullying. Such skills include how to make friends. Emphasize that it is not the victim’s fault that they are experiencing bullying. Avoid telling victims to fight back or “suck it up.” In addition, work with parents and school authorities to intervene on behalf of the child to stop the bullying behavior.

Lisa Quarfoth/Thinkstock

At the same time, it is especially important to identify perpetrators. Perpetrators tend to have conduct problems, increased depressive symptoms, and poor school adjustment.¹² They may have been bullied themselves. Also refer perpetrators to a mental health provider and other resources to address these problems.

However, with your limited time to screen for bullying or to create an individualized plan to protect bullying victims, approaches to reducing bullying and their adverse effects require a community effort. Use your expertise and access to the latest scientific research to advocate and help create policies schools can use to address antigay bullying. Clark and Tilly recommend a three-tier approach in addressing antigay bullying. In the first tier, schools should create a safe and affirmative environment for all students. An example of such an approach is to have a speaker – such as a physician from the community – talking to students about bullying and encouraging bystanders to speak up (i.e., be an ally) for bullying victims. Although some schools may be hesitant to implement a schoolwide intervention, they may implement a second-tier approach, such as classroom curricula on how to be an ally or incentive programs for helping vulnerable students (e.g., tutoring). Finally, the third tier requires intensive individualized interventions for bullying victims. Schools should have a step-by-step plan involving school authorities that students and their parents can use if students are experiencing bullying.¹³ Implementation of this plan requires timely follow-up from school officials to ensure cessation of the bullying behavior.10

Another way you can advocate for your LGBT patients is to be knowledgeable about the laws surrounding bullying. Bullying laws vary according to state. This is especially true if such laws specifically prohibit bullying based on sexual orientation or gender identity. This is known as “enumeration.” Enumerated laws grant school authorities the power to prevent and to correct any bullying based on sexual orientation and gender identity. Currently, 18 states and the District of Columbia have enumerated antibullying laws.¹⁴ If you live in a state that does not have an enumerated antibullying law, you can contact your state government officials to urge them to pass such a law.

Bullying has a powerful impact on the health and well-being of LGBT youth. Screen for bullying in your LGBT patients and work with schools and parents to protect them from such behaviors. Most importantly, advocate for creating a safe school environment for LGBT youth so that they can focus on their main job of learning and becoming a thriving adult.

Resources

• The website www.stopbullying.gov is a comprehensive resource for bullying and how to address it.

• Society of Adolescent Health & Medicine (SAHM) position statement on bullying (J Adolesc Health. 2005 Jan;36[1]:88-91).

• American Academy of Pediatrics (AAP) position statement on bullying (Pediatrics. 2009 July. doi: 10.1542/peds.2009-0943).

• Gay, Lesbian & Straight Education Network (GLSEN) information on enumerated antibullying laws by state (www.glsen.org/article/state-maps).

References

1. Bullying definition at www.stopbullying.gov.

2. Student Reports of Bullying and Cyber-Bullying: Results From the 2011 School Crime Supplement to the National Crime Victimization Survey.

3. J Adolesc Health. 2014 Sep;55(3):432-8.

4. Injustice at Every Turn: A Report of the National Transgender Discrimination Survey. Washington: National Center for Transgender Equality and National Gay and Lesbian Task Force, 2011.

5. Can Fam Physician. 2009 Apr;55(4):356-60.

6. J Adolesc Health. 2016 Feb;58(2):S1-S2.

7. Pediatrics. 2003;111(6 Pt 1):1312-7.

8. Journal of Educational Psychology. 2000 Jun;92(2):349-59.

9. Prev Sci. 2015 Apr;16(3):451-62.

10. Dev Psychol. 2010 Nov;46(6):1580-9.

11. Roles for pediatricians in bullying prevention and intervention (www.stopbullying.gov/resources-files/roles-for-pediatricians-tipsheet.pdf).

12. J Adolesc Health. 2005 Jan;36(1):88-91.

13. Clark JP, Tilly, WD. The evolution of response to intervention. In: Clark JP, Alvarez, Michelle, ed. Response to intervention: A guide for school social worker. (New York: Oxford University Press; 2010:3-18).

14. Enumerated antibullying laws by state(www.glsen.org/article/state-maps).

Dr. Montano is an adolescent medicine fellow at Children’s Hospital of Pittsburgh of UPMC and a postdoctoral fellow in the department of pediatrics at the University of Pittsburgh.

A mentor told me during my pediatrics residency that going to school is “the main job of a teenager.” This is because at school, teenagers will be spending the majority of their time and energy learning and growing to become a thriving adult. However, the school environment matters. We are familiar with how excellent teachers, the availability of tutoring, and an administration dedicated to academic achievement play a big role. We also should be aware that if teenagers feel unsafe going to school – especially if they are victims of bullying – they are unable to take advantage of these resources.

Bullying is a repetitive, unwanted, and aggressive behavior among children and adolescents that involves a real or perceived power imbalance.¹ Despite the increasing visibility of lesbian, gay, bisexual, and transgender (LGBT) individuals, bullying remains a serious problem for this population. Although between one in four and one in three of all youth experience bullying,² according to the Youth Risk Behavior Survey, LGBT students are two to four times as likely to be threatened or injured with a weapon on school property, two to three times as likely not to go to school because they feel unsafe, and about two times as likely to be bullied at school, compared with their heterosexual peers.³ Alarmingly, more than half of transgender students experience bullying and harassment at school.⁴

A key component of bullying is the power imbalance. Bullying perpetrators feel that they have more power physically (e.g., in size) or socially (e.g., in social status).⁵ LGBT youth are often the victims of bullying because of the societal stigma against same-sex attraction or gender nonconformity. As a result, they tend to have a lower social status, putting them at risk for bullying. Remember, however, that this power imbalance is perceived. Even straight teenagers can be victims of antigay and antitrans bullying because they don’t conform to gender norms (e.g., a straight boy interested in theater instead of sports).⁶ Therefore, any teenager can be a victim of antigay and antitrans bullying.

Although many believe that experiencing bullying is a “rite of passage,” a look at the research on bullying contradicts this. Youth who experience bullying have higher rates of depression, loneliness, and, most worrisome of all, suicide.^7,8 One study showed that LGBT youth who experience bullying are almost six times as likely to consider suicide.⁹ Such sobering statistics prove that bullying is harmful. Furthermore, the effects of bullying can last into adulthood. One study showed that LGBT youth who experienced bullying during high school are more likely to have depressive symptoms and to be dissatisfied with life as a young adult.¹⁰ If rites of passage are designed to make a teenager into a well-adjusted young adult, then bullying does a poor job.

Although antigay bullying and harassment occur outside the clinic, providers can encounter both the perpetrator and the victim as patients and not realize it. Providers who have patients at risk for bullying – such as LGBT or gender-nonconforming youth – should routinely ask them about bullying through such questions as:

• “How many good friends do you have in school?”

• “Do you ever feel afraid to go to school? Why?”

• “Do other kids ever bully you at school, in your neighborhood, or online? Who bullies you?

• When and where does it happen? What do they say or do?”¹¹

Asking these questions is especially important if you or your patient’s caregivers notice school phobia, attention problems, or psychosomatic complaints.11 Once you identify a victim, refer the patient to a mental health provider to develop skills to cope with the stress of bullying. Such skills include how to make friends. Emphasize that it is not the victim’s fault that they are experiencing bullying. Avoid telling victims to fight back or “suck it up.” In addition, work with parents and school authorities to intervene on behalf of the child to stop the bullying behavior.

Lisa Quarfoth/Thinkstock

At the same time, it is especially important to identify perpetrators. Perpetrators tend to have conduct problems, increased depressive symptoms, and poor school adjustment.¹² They may have been bullied themselves. Also refer perpetrators to a mental health provider and other resources to address these problems.

However, with your limited time to screen for bullying or to create an individualized plan to protect bullying victims, approaches to reducing bullying and their adverse effects require a community effort. Use your expertise and access to the latest scientific research to advocate and help create policies schools can use to address antigay bullying. Clark and Tilly recommend a three-tier approach in addressing antigay bullying. In the first tier, schools should create a safe and affirmative environment for all students. An example of such an approach is to have a speaker – such as a physician from the community – talking to students about bullying and encouraging bystanders to speak up (i.e., be an ally) for bullying victims. Although some schools may be hesitant to implement a schoolwide intervention, they may implement a second-tier approach, such as classroom curricula on how to be an ally or incentive programs for helping vulnerable students (e.g., tutoring). Finally, the third tier requires intensive individualized interventions for bullying victims. Schools should have a step-by-step plan involving school authorities that students and their parents can use if students are experiencing bullying.¹³ Implementation of this plan requires timely follow-up from school officials to ensure cessation of the bullying behavior.10

Another way you can advocate for your LGBT patients is to be knowledgeable about the laws surrounding bullying. Bullying laws vary according to state. This is especially true if such laws specifically prohibit bullying based on sexual orientation or gender identity. This is known as “enumeration.” Enumerated laws grant school authorities the power to prevent and to correct any bullying based on sexual orientation and gender identity. Currently, 18 states and the District of Columbia have enumerated antibullying laws.¹⁴ If you live in a state that does not have an enumerated antibullying law, you can contact your state government officials to urge them to pass such a law.

Bullying has a powerful impact on the health and well-being of LGBT youth. Screen for bullying in your LGBT patients and work with schools and parents to protect them from such behaviors. Most importantly, advocate for creating a safe school environment for LGBT youth so that they can focus on their main job of learning and becoming a thriving adult.

Resources

• The website www.stopbullying.gov is a comprehensive resource for bullying and how to address it.

• Society of Adolescent Health & Medicine (SAHM) position statement on bullying (J Adolesc Health. 2005 Jan;36[1]:88-91).

• American Academy of Pediatrics (AAP) position statement on bullying (Pediatrics. 2009 July. doi: 10.1542/peds.2009-0943).

• Gay, Lesbian & Straight Education Network (GLSEN) information on enumerated antibullying laws by state (www.glsen.org/article/state-maps).

References

1. Bullying definition at www.stopbullying.gov.

2. Student Reports of Bullying and Cyber-Bullying: Results From the 2011 School Crime Supplement to the National Crime Victimization Survey.

3. J Adolesc Health. 2014 Sep;55(3):432-8.

4. Injustice at Every Turn: A Report of the National Transgender Discrimination Survey. Washington: National Center for Transgender Equality and National Gay and Lesbian Task Force, 2011.

5. Can Fam Physician. 2009 Apr;55(4):356-60.

6. J Adolesc Health. 2016 Feb;58(2):S1-S2.

7. Pediatrics. 2003;111(6 Pt 1):1312-7.

8. Journal of Educational Psychology. 2000 Jun;92(2):349-59.

9. Prev Sci. 2015 Apr;16(3):451-62.

10. Dev Psychol. 2010 Nov;46(6):1580-9.

11. Roles for pediatricians in bullying prevention and intervention (www.stopbullying.gov/resources-files/roles-for-pediatricians-tipsheet.pdf).

12. J Adolesc Health. 2005 Jan;36(1):88-91.

13. Clark JP, Tilly, WD. The evolution of response to intervention. In: Clark JP, Alvarez, Michelle, ed. Response to intervention: A guide for school social worker. (New York: Oxford University Press; 2010:3-18).

14. Enumerated antibullying laws by state(www.glsen.org/article/state-maps).

Dr. Montano is an adolescent medicine fellow at Children’s Hospital of Pittsburgh of UPMC and a postdoctoral fellow in the department of pediatrics at the University of Pittsburgh.

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.

INDIAN WELLS, CALIF. – Using chlorhexidine-alcohol preoperative skin antisepsis at the time of abdominal hysterectomy is associated with a lower incidence of surgical site infections (SSIs), compared with using povidone-iodine antiseptic solution, a large retrospective study showed.

“Surgical site infections have been linked to longer hospital stays, higher readmission rates, and overall increased healthcare costs,” Ali Bazzi, the lead study author, said at the annual scientific meeting of the Society of Gynecologic Surgeons. “Preoperative topical skin antiseptics have decreased the rate of SSIs over the years and have led to improved patient outcomes. Current published guidelines for skin preparations, specifically abdominal hysterectomies, do not routinely specify a choice of antiseptic. With greater than 500,000 hysterectomies performed each year in the United States, and about half done via laparotomy, this can have significant clinical implications.”

In an effort to determine whether the choice of preoperative topical antisepsis independently affects SSIs, Mr. Bazzi, a fourth-year medical student at the University of Michigan, Ann Arbor, and his associates in the university’s department of gynecologic oncology evaluated chlorhexidine-gluconate in alcohol versus povidone-iodine in aqueous solution. The second objective focused on determining certain patient factors and operative predictors of SSIs.

The researchers used the Michigan Surgical Quality Collaborative database to perform a retrospective cohort analysis of patients who underwent abdominal hysterectomy from July 2012 to February 2015. The primary outcome was diagnosis of a superficial, deep, or organ space SSI within 30 days of surgery, while the primary predictor was whether the individual cases received either the chlorhexidine-alcohol or the povidone-iodine antiseptic solution.

The researchers excluded cases with missing data, preoperative sepsis or emergent operative cases, and patients on chronic steroids due to immunosuppression, since these cases were associated with a higher than baseline risk of developing SSIs. Other types of skin preparation agents did not meet a large enough sample size and thus were underpowered. These cases were not included in the final analysis. Multivariate logistic regression models estimated the independent effect of skin antiseptic choice on the rate of SSI.

Mr. Bazzi reported results from 5,074 abdominal hysterectomies. Compared with patients in the povidone-iodine group, those in the chlorhexidine-alcohol group had several medical comorbidities, demographic and perioperative factors associated with the development of SSIs, including being more likely to have a BMI of 30 kg/m² or greater; American Society of Anesthesiology Class of 3 or greater; dependent functional status; malignancy as a preoperative indication for surgery; estimated blood loss of greater than 250 cc; and surgery lasting longer than 3 hours.

The overall rate of any SSI was 3.6%. The unadjusted SSI rates based on antiseptic choice were 3.5% in the chlorhexidine-alcohol group and 3.8% in the povidone-iodine group. After using multivariate logistic regression adjusted for population differences, the researchers determined that chlorhexidine-alcohol was associated with a 30% lower odds of developing SSIs, compared with those in the povidone-iodine group (odds ratio, 0.71; 95% confidence interval, 0.51-0.98; P = .037).

Mr. Bazzi, who begins an ob.gyn. residency at St. John Hospital and Medical Center in Detroit in July 2016, acknowledged that other qualitative factors not included in the analysis could affect the incidence of SSIs, such as operative experience, surgical technique, resident exposure, type of ligature used, and excessive use of electrosurgical devices.

He noted that future randomized, controlled trials of skin antiseptic preparations given prior to abdominal hysterectomy would be helpful. For now, “we believe that future guidelines should specify the choice of antisepsis prior to abdominal hysterectomy,” he said at the meeting, which is jointly sponsored by the American College of Surgeons.

Mr. Bazzi reported having no financial disclosures.

[email protected]

INDIAN WELLS, CALIF. – Using chlorhexidine-alcohol preoperative skin antisepsis at the time of abdominal hysterectomy is associated with a lower incidence of surgical site infections (SSIs), compared with using povidone-iodine antiseptic solution, a large retrospective study showed.

“Surgical site infections have been linked to longer hospital stays, higher readmission rates, and overall increased healthcare costs,” Ali Bazzi, the lead study author, said at the annual scientific meeting of the Society of Gynecologic Surgeons. “Preoperative topical skin antiseptics have decreased the rate of SSIs over the years and have led to improved patient outcomes. Current published guidelines for skin preparations, specifically abdominal hysterectomies, do not routinely specify a choice of antiseptic. With greater than 500,000 hysterectomies performed each year in the United States, and about half done via laparotomy, this can have significant clinical implications.”

In an effort to determine whether the choice of preoperative topical antisepsis independently affects SSIs, Mr. Bazzi, a fourth-year medical student at the University of Michigan, Ann Arbor, and his associates in the university’s department of gynecologic oncology evaluated chlorhexidine-gluconate in alcohol versus povidone-iodine in aqueous solution. The second objective focused on determining certain patient factors and operative predictors of SSIs.

The researchers used the Michigan Surgical Quality Collaborative database to perform a retrospective cohort analysis of patients who underwent abdominal hysterectomy from July 2012 to February 2015. The primary outcome was diagnosis of a superficial, deep, or organ space SSI within 30 days of surgery, while the primary predictor was whether the individual cases received either the chlorhexidine-alcohol or the povidone-iodine antiseptic solution.

The researchers excluded cases with missing data, preoperative sepsis or emergent operative cases, and patients on chronic steroids due to immunosuppression, since these cases were associated with a higher than baseline risk of developing SSIs. Other types of skin preparation agents did not meet a large enough sample size and thus were underpowered. These cases were not included in the final analysis. Multivariate logistic regression models estimated the independent effect of skin antiseptic choice on the rate of SSI.

Mr. Bazzi reported results from 5,074 abdominal hysterectomies. Compared with patients in the povidone-iodine group, those in the chlorhexidine-alcohol group had several medical comorbidities, demographic and perioperative factors associated with the development of SSIs, including being more likely to have a BMI of 30 kg/m² or greater; American Society of Anesthesiology Class of 3 or greater; dependent functional status; malignancy as a preoperative indication for surgery; estimated blood loss of greater than 250 cc; and surgery lasting longer than 3 hours.

The overall rate of any SSI was 3.6%. The unadjusted SSI rates based on antiseptic choice were 3.5% in the chlorhexidine-alcohol group and 3.8% in the povidone-iodine group. After using multivariate logistic regression adjusted for population differences, the researchers determined that chlorhexidine-alcohol was associated with a 30% lower odds of developing SSIs, compared with those in the povidone-iodine group (odds ratio, 0.71; 95% confidence interval, 0.51-0.98; P = .037).

Mr. Bazzi, who begins an ob.gyn. residency at St. John Hospital and Medical Center in Detroit in July 2016, acknowledged that other qualitative factors not included in the analysis could affect the incidence of SSIs, such as operative experience, surgical technique, resident exposure, type of ligature used, and excessive use of electrosurgical devices.

He noted that future randomized, controlled trials of skin antiseptic preparations given prior to abdominal hysterectomy would be helpful. For now, “we believe that future guidelines should specify the choice of antisepsis prior to abdominal hysterectomy,” he said at the meeting, which is jointly sponsored by the American College of Surgeons.

Mr. Bazzi reported having no financial disclosures.

[email protected]

INDIAN WELLS, CALIF. – Using chlorhexidine-alcohol preoperative skin antisepsis at the time of abdominal hysterectomy is associated with a lower incidence of surgical site infections (SSIs), compared with using povidone-iodine antiseptic solution, a large retrospective study showed.

“Surgical site infections have been linked to longer hospital stays, higher readmission rates, and overall increased healthcare costs,” Ali Bazzi, the lead study author, said at the annual scientific meeting of the Society of Gynecologic Surgeons. “Preoperative topical skin antiseptics have decreased the rate of SSIs over the years and have led to improved patient outcomes. Current published guidelines for skin preparations, specifically abdominal hysterectomies, do not routinely specify a choice of antiseptic. With greater than 500,000 hysterectomies performed each year in the United States, and about half done via laparotomy, this can have significant clinical implications.”

In an effort to determine whether the choice of preoperative topical antisepsis independently affects SSIs, Mr. Bazzi, a fourth-year medical student at the University of Michigan, Ann Arbor, and his associates in the university’s department of gynecologic oncology evaluated chlorhexidine-gluconate in alcohol versus povidone-iodine in aqueous solution. The second objective focused on determining certain patient factors and operative predictors of SSIs.

The researchers used the Michigan Surgical Quality Collaborative database to perform a retrospective cohort analysis of patients who underwent abdominal hysterectomy from July 2012 to February 2015. The primary outcome was diagnosis of a superficial, deep, or organ space SSI within 30 days of surgery, while the primary predictor was whether the individual cases received either the chlorhexidine-alcohol or the povidone-iodine antiseptic solution.

The researchers excluded cases with missing data, preoperative sepsis or emergent operative cases, and patients on chronic steroids due to immunosuppression, since these cases were associated with a higher than baseline risk of developing SSIs. Other types of skin preparation agents did not meet a large enough sample size and thus were underpowered. These cases were not included in the final analysis. Multivariate logistic regression models estimated the independent effect of skin antiseptic choice on the rate of SSI.

Mr. Bazzi reported results from 5,074 abdominal hysterectomies. Compared with patients in the povidone-iodine group, those in the chlorhexidine-alcohol group had several medical comorbidities, demographic and perioperative factors associated with the development of SSIs, including being more likely to have a BMI of 30 kg/m² or greater; American Society of Anesthesiology Class of 3 or greater; dependent functional status; malignancy as a preoperative indication for surgery; estimated blood loss of greater than 250 cc; and surgery lasting longer than 3 hours.

The overall rate of any SSI was 3.6%. The unadjusted SSI rates based on antiseptic choice were 3.5% in the chlorhexidine-alcohol group and 3.8% in the povidone-iodine group. After using multivariate logistic regression adjusted for population differences, the researchers determined that chlorhexidine-alcohol was associated with a 30% lower odds of developing SSIs, compared with those in the povidone-iodine group (odds ratio, 0.71; 95% confidence interval, 0.51-0.98; P = .037).

Mr. Bazzi, who begins an ob.gyn. residency at St. John Hospital and Medical Center in Detroit in July 2016, acknowledged that other qualitative factors not included in the analysis could affect the incidence of SSIs, such as operative experience, surgical technique, resident exposure, type of ligature used, and excessive use of electrosurgical devices.

He noted that future randomized, controlled trials of skin antiseptic preparations given prior to abdominal hysterectomy would be helpful. For now, “we believe that future guidelines should specify the choice of antisepsis prior to abdominal hysterectomy,” he said at the meeting, which is jointly sponsored by the American College of Surgeons.

Mr. Bazzi reported having no financial disclosures.

[email protected]

INDIAN WELLS, CALIF. – A rapid screening tool found that about 5% of urogynecologic patients aged 65-74 years showed signs of cognitive impairment, with that figure rising to more than 30% for patients age 85 and older, according to the results of a single-center study.

“As our gynecologic patients continue to age, it’s increasingly important that we continue to identify and manage the risk factors for cognitive decline that occur in the ambulatory and the perioperative care settings,” Dr. Elisa R. Trowbridge, lead study author, said at the annual scientific meeting of the Society of Gynecologic Surgeons. “However, data are lacking to describe the prevalence of cognitive impairment in this very specific population.”

In 2013, the Centers for Disease Control and Prevention estimated that one in eight patients older than 60 years of age deal with memory loss and confusion. However, fewer than 20% of these patients report this to their health care providers, said Dr. Trowbridge, division director of the University of Virginia Women’s Center for Continence and Pelvic Surgery in Charlottesville.

“For this reason the aim of our study was to evaluate the prevalence of cognitive impairment in a urogynecologic ambulatory population, and to evaluate the feasibility of using a standardized, validated screening questionnaire in the tertiary care setting,” she said.

The researchers invited 371 English-speaking patients aged 65 and older to participate and used two cognitive screening tools: the Mini-Cog and the AD8 (8-item Interview to Differentiate Aging and Dementia). They also used the Geriatric Depression Scale, as there is an association between depression and cognition in the elderly.

“Advantages of the Mini-Cog are that it’s administered in less than 3 minutes, it requires no special equipment, and it is not influenced by level of education, or any language variations,” Dr. Trowbridge said.

Of the 371 patients, 39 were excluded due to pre-existing cognitive impairment/dementia, active psychotic disorders, acute/unstable medical conditions, neurologic injury/disorders, alcohol/drug abuse, severe visual/hearing impairment, and illiteracy. An additional 37 patients declined to participate because they “were frustrated that we had asked to evaluate their memory,” she said. This left a total of 295 patients with a mean age of 75 years. Most (97%) were Caucasian, 62% were married, and each had an average of four major medical conditions, including hypertension, hyperlipidemia, and depression. The researchers stratified patients into three age groups: 65-74, 75-84, and 85 and older.

Cognitive impairment as measured by the Mini-Cog was identified in 5.3% of patients aged 65-74 years, 13.7% of those aged 75-84 years, and 31% of those aged 85 and older. The difference in impairment between those aged 65-74 years and those aged 75 years and older reached significance, with a P value of less than .001.

Cognitive impairment as measured by the AD8 found that all three age groups perceived themselves to have early cognitive changes: 25.9% of patients aged 65-74 years, 31.9% of those aged 75-84 years, and 40% of those aged 85 and older. There were no significant between-group differences in these results (P = .4). The most commonly identified areas of impairment were problems with thinking and memory (62%), judgment (52%), and trouble learning new tools or gadgets (44%).

Dr. Trowbridge also reported that 6.4% of the study population screened positive for depression on the Geriatric Depression Scale, with no significant differences between the age groups.

“In our study population, cognitive impairment as measured by a validated questionnaire is prevalent among women greater than 75 years of age,” she said at the meeting, which was jointly sponsored by the American College of Surgeons. “The Mini-Cog is a feasible screening tool for routine use in clinical practice that can be integrated easily into the urogynecologic evaluation. However, remember these are screening tools that effectively screen for previously unrecognized impairment, but a definitive diagnosis requires additional evaluation.”

Dr. Trowbridge reported having no financial disclosures.

[email protected]

INDIAN WELLS, CALIF. – A rapid screening tool found that about 5% of urogynecologic patients aged 65-74 years showed signs of cognitive impairment, with that figure rising to more than 30% for patients age 85 and older, according to the results of a single-center study.

“As our gynecologic patients continue to age, it’s increasingly important that we continue to identify and manage the risk factors for cognitive decline that occur in the ambulatory and the perioperative care settings,” Dr. Elisa R. Trowbridge, lead study author, said at the annual scientific meeting of the Society of Gynecologic Surgeons. “However, data are lacking to describe the prevalence of cognitive impairment in this very specific population.”

In 2013, the Centers for Disease Control and Prevention estimated that one in eight patients older than 60 years of age deal with memory loss and confusion. However, fewer than 20% of these patients report this to their health care providers, said Dr. Trowbridge, division director of the University of Virginia Women’s Center for Continence and Pelvic Surgery in Charlottesville.

“For this reason the aim of our study was to evaluate the prevalence of cognitive impairment in a urogynecologic ambulatory population, and to evaluate the feasibility of using a standardized, validated screening questionnaire in the tertiary care setting,” she said.

The researchers invited 371 English-speaking patients aged 65 and older to participate and used two cognitive screening tools: the Mini-Cog and the AD8 (8-item Interview to Differentiate Aging and Dementia). They also used the Geriatric Depression Scale, as there is an association between depression and cognition in the elderly.

“Advantages of the Mini-Cog are that it’s administered in less than 3 minutes, it requires no special equipment, and it is not influenced by level of education, or any language variations,” Dr. Trowbridge said.

Of the 371 patients, 39 were excluded due to pre-existing cognitive impairment/dementia, active psychotic disorders, acute/unstable medical conditions, neurologic injury/disorders, alcohol/drug abuse, severe visual/hearing impairment, and illiteracy. An additional 37 patients declined to participate because they “were frustrated that we had asked to evaluate their memory,” she said. This left a total of 295 patients with a mean age of 75 years. Most (97%) were Caucasian, 62% were married, and each had an average of four major medical conditions, including hypertension, hyperlipidemia, and depression. The researchers stratified patients into three age groups: 65-74, 75-84, and 85 and older.

Cognitive impairment as measured by the Mini-Cog was identified in 5.3% of patients aged 65-74 years, 13.7% of those aged 75-84 years, and 31% of those aged 85 and older. The difference in impairment between those aged 65-74 years and those aged 75 years and older reached significance, with a P value of less than .001.

Cognitive impairment as measured by the AD8 found that all three age groups perceived themselves to have early cognitive changes: 25.9% of patients aged 65-74 years, 31.9% of those aged 75-84 years, and 40% of those aged 85 and older. There were no significant between-group differences in these results (P = .4). The most commonly identified areas of impairment were problems with thinking and memory (62%), judgment (52%), and trouble learning new tools or gadgets (44%).

Dr. Trowbridge also reported that 6.4% of the study population screened positive for depression on the Geriatric Depression Scale, with no significant differences between the age groups.

“In our study population, cognitive impairment as measured by a validated questionnaire is prevalent among women greater than 75 years of age,” she said at the meeting, which was jointly sponsored by the American College of Surgeons. “The Mini-Cog is a feasible screening tool for routine use in clinical practice that can be integrated easily into the urogynecologic evaluation. However, remember these are screening tools that effectively screen for previously unrecognized impairment, but a definitive diagnosis requires additional evaluation.”

Dr. Trowbridge reported having no financial disclosures.

[email protected]

INDIAN WELLS, CALIF. – A rapid screening tool found that about 5% of urogynecologic patients aged 65-74 years showed signs of cognitive impairment, with that figure rising to more than 30% for patients age 85 and older, according to the results of a single-center study.

“As our gynecologic patients continue to age, it’s increasingly important that we continue to identify and manage the risk factors for cognitive decline that occur in the ambulatory and the perioperative care settings,” Dr. Elisa R. Trowbridge, lead study author, said at the annual scientific meeting of the Society of Gynecologic Surgeons. “However, data are lacking to describe the prevalence of cognitive impairment in this very specific population.”

In 2013, the Centers for Disease Control and Prevention estimated that one in eight patients older than 60 years of age deal with memory loss and confusion. However, fewer than 20% of these patients report this to their health care providers, said Dr. Trowbridge, division director of the University of Virginia Women’s Center for Continence and Pelvic Surgery in Charlottesville.

“For this reason the aim of our study was to evaluate the prevalence of cognitive impairment in a urogynecologic ambulatory population, and to evaluate the feasibility of using a standardized, validated screening questionnaire in the tertiary care setting,” she said.

The researchers invited 371 English-speaking patients aged 65 and older to participate and used two cognitive screening tools: the Mini-Cog and the AD8 (8-item Interview to Differentiate Aging and Dementia). They also used the Geriatric Depression Scale, as there is an association between depression and cognition in the elderly.

“Advantages of the Mini-Cog are that it’s administered in less than 3 minutes, it requires no special equipment, and it is not influenced by level of education, or any language variations,” Dr. Trowbridge said.

Of the 371 patients, 39 were excluded due to pre-existing cognitive impairment/dementia, active psychotic disorders, acute/unstable medical conditions, neurologic injury/disorders, alcohol/drug abuse, severe visual/hearing impairment, and illiteracy. An additional 37 patients declined to participate because they “were frustrated that we had asked to evaluate their memory,” she said. This left a total of 295 patients with a mean age of 75 years. Most (97%) were Caucasian, 62% were married, and each had an average of four major medical conditions, including hypertension, hyperlipidemia, and depression. The researchers stratified patients into three age groups: 65-74, 75-84, and 85 and older.

Cognitive impairment as measured by the Mini-Cog was identified in 5.3% of patients aged 65-74 years, 13.7% of those aged 75-84 years, and 31% of those aged 85 and older. The difference in impairment between those aged 65-74 years and those aged 75 years and older reached significance, with a P value of less than .001.

Cognitive impairment as measured by the AD8 found that all three age groups perceived themselves to have early cognitive changes: 25.9% of patients aged 65-74 years, 31.9% of those aged 75-84 years, and 40% of those aged 85 and older. There were no significant between-group differences in these results (P = .4). The most commonly identified areas of impairment were problems with thinking and memory (62%), judgment (52%), and trouble learning new tools or gadgets (44%).

Dr. Trowbridge also reported that 6.4% of the study population screened positive for depression on the Geriatric Depression Scale, with no significant differences between the age groups.

“In our study population, cognitive impairment as measured by a validated questionnaire is prevalent among women greater than 75 years of age,” she said at the meeting, which was jointly sponsored by the American College of Surgeons. “The Mini-Cog is a feasible screening tool for routine use in clinical practice that can be integrated easily into the urogynecologic evaluation. However, remember these are screening tools that effectively screen for previously unrecognized impairment, but a definitive diagnosis requires additional evaluation.”

Dr. Trowbridge reported having no financial disclosures.

[email protected]

In a prospective study of 40 patients with primary plasma cell leukemia, upfront autotransplantation followed by allotransplant for younger patients and by consolidation/maintenance for older patients was associated with a median overall survival of 36.3 months and a median progression-free survival of 15.1 months.

Patients with this aggressive form of multiple myeloma received a regimen that combined standard chemotherapy, a proteasome inhibitor, high-dose melphalan followed by autologous stem cell transplantation, and allogeneic transplantation or immunomodulatory drugs, reported Dr. Bruno Royer of University Hospital in Amiens, France, and his associates.

Induction therapy consisted of four 21-day cycles: Cycles 1 and 3 included subcutaneous bortezomib, intravenous pegylated doxorubicin, and oral dexamethasone; cycles 2 and 4 included subcutaneous bortezomib, oral cyclophosphamide, and oral dexamethasone. Of 39 patients – one patient died 24 hours after study inclusion – 35 completed the four cycles. The overall response rate to induction was 69%: 10% of patients had a complete response and 26% had a very good partial response. Of 27 responding patients, 25 underwent high-dose melphalan followed by autologous stem cell transplantation.

The high response rates allowed 16 patients who were younger than 66 years and had an HLA-matched donor to then receive high-dose melphalan followed by autologous stem cell transplantation followed by consolidation with either an reduced-intensity conditioning allograft or a second high-dose melphalan followed by autologous stem cell transplantation and subsequent maintenance with lenalidomide, bortezomib, and dexamethasone for 1 year, the researchers said (J Clin Oncol. 2016 Apr 25. doi: 10.1200/JCO.2015.63.1929).

A total of 20% of patients had a complete response to the entire treatment protocol, 13% had a stringent complete response, 26% had a very good partial response, 5% had stable disease, and 5% had progressive disease. Thirteen patients died of progressive disease and four died of infections, including three that occurred during induction or after allograft.

This is only the second prospective trial in patients with primary plasma cell leukemia, an aggressive form of multiple myeloma that accounts for 2%-4% of cases, the researchers said. Future prospective trials should seek to optimize induction with newer combinations, such as carfilzomib, lenalidomide, dexamethasone, or monoclonal anti-CD38 antibodies. Also, optimizing the stem cell conditioning procedure and the postallograft immunomodulation may further benefit younger patients.

Dr. Royer reported receiving honoraria from Amgen and having served as a consultant or advisor for Octapharma Plasma. Fifteen coinvestigators also reported financial relationships with a number of pharmaceutical companies.

In a prospective study of 40 patients with primary plasma cell leukemia, upfront autotransplantation followed by allotransplant for younger patients and by consolidation/maintenance for older patients was associated with a median overall survival of 36.3 months and a median progression-free survival of 15.1 months.

Patients with this aggressive form of multiple myeloma received a regimen that combined standard chemotherapy, a proteasome inhibitor, high-dose melphalan followed by autologous stem cell transplantation, and allogeneic transplantation or immunomodulatory drugs, reported Dr. Bruno Royer of University Hospital in Amiens, France, and his associates.

Induction therapy consisted of four 21-day cycles: Cycles 1 and 3 included subcutaneous bortezomib, intravenous pegylated doxorubicin, and oral dexamethasone; cycles 2 and 4 included subcutaneous bortezomib, oral cyclophosphamide, and oral dexamethasone. Of 39 patients – one patient died 24 hours after study inclusion – 35 completed the four cycles. The overall response rate to induction was 69%: 10% of patients had a complete response and 26% had a very good partial response. Of 27 responding patients, 25 underwent high-dose melphalan followed by autologous stem cell transplantation.

The high response rates allowed 16 patients who were younger than 66 years and had an HLA-matched donor to then receive high-dose melphalan followed by autologous stem cell transplantation followed by consolidation with either an reduced-intensity conditioning allograft or a second high-dose melphalan followed by autologous stem cell transplantation and subsequent maintenance with lenalidomide, bortezomib, and dexamethasone for 1 year, the researchers said (J Clin Oncol. 2016 Apr 25. doi: 10.1200/JCO.2015.63.1929).

A total of 20% of patients had a complete response to the entire treatment protocol, 13% had a stringent complete response, 26% had a very good partial response, 5% had stable disease, and 5% had progressive disease. Thirteen patients died of progressive disease and four died of infections, including three that occurred during induction or after allograft.

This is only the second prospective trial in patients with primary plasma cell leukemia, an aggressive form of multiple myeloma that accounts for 2%-4% of cases, the researchers said. Future prospective trials should seek to optimize induction with newer combinations, such as carfilzomib, lenalidomide, dexamethasone, or monoclonal anti-CD38 antibodies. Also, optimizing the stem cell conditioning procedure and the postallograft immunomodulation may further benefit younger patients.

Dr. Royer reported receiving honoraria from Amgen and having served as a consultant or advisor for Octapharma Plasma. Fifteen coinvestigators also reported financial relationships with a number of pharmaceutical companies.

In a prospective study of 40 patients with primary plasma cell leukemia, upfront autotransplantation followed by allotransplant for younger patients and by consolidation/maintenance for older patients was associated with a median overall survival of 36.3 months and a median progression-free survival of 15.1 months.

Patients with this aggressive form of multiple myeloma received a regimen that combined standard chemotherapy, a proteasome inhibitor, high-dose melphalan followed by autologous stem cell transplantation, and allogeneic transplantation or immunomodulatory drugs, reported Dr. Bruno Royer of University Hospital in Amiens, France, and his associates.

Induction therapy consisted of four 21-day cycles: Cycles 1 and 3 included subcutaneous bortezomib, intravenous pegylated doxorubicin, and oral dexamethasone; cycles 2 and 4 included subcutaneous bortezomib, oral cyclophosphamide, and oral dexamethasone. Of 39 patients – one patient died 24 hours after study inclusion – 35 completed the four cycles. The overall response rate to induction was 69%: 10% of patients had a complete response and 26% had a very good partial response. Of 27 responding patients, 25 underwent high-dose melphalan followed by autologous stem cell transplantation.

The high response rates allowed 16 patients who were younger than 66 years and had an HLA-matched donor to then receive high-dose melphalan followed by autologous stem cell transplantation followed by consolidation with either an reduced-intensity conditioning allograft or a second high-dose melphalan followed by autologous stem cell transplantation and subsequent maintenance with lenalidomide, bortezomib, and dexamethasone for 1 year, the researchers said (J Clin Oncol. 2016 Apr 25. doi: 10.1200/JCO.2015.63.1929).

A total of 20% of patients had a complete response to the entire treatment protocol, 13% had a stringent complete response, 26% had a very good partial response, 5% had stable disease, and 5% had progressive disease. Thirteen patients died of progressive disease and four died of infections, including three that occurred during induction or after allograft.

This is only the second prospective trial in patients with primary plasma cell leukemia, an aggressive form of multiple myeloma that accounts for 2%-4% of cases, the researchers said. Future prospective trials should seek to optimize induction with newer combinations, such as carfilzomib, lenalidomide, dexamethasone, or monoclonal anti-CD38 antibodies. Also, optimizing the stem cell conditioning procedure and the postallograft immunomodulation may further benefit younger patients.

Dr. Royer reported receiving honoraria from Amgen and having served as a consultant or advisor for Octapharma Plasma. Fifteen coinvestigators also reported financial relationships with a number of pharmaceutical companies.

Editor’s note: “Everything We Say and Do” is an informational series developed by SHM’s Patient Experience Committee to provide readers with thoughtful and actionable communication tactics that have great potential to positively impact patients’ experience of care. Each column will focus on how the contributor applies one of the “Key Communication” areas in practice.

View a chart outlining key communication tactics

What I Say and Do

I counsel and deliver the diagnosis or give recommendations through a dialogue, instead of a monologue, using active listening.

Why I Do It

The monologue, or lecture, is among the least effective ways to instill behavior change. Research studies have demonstrated that, after a monologue, only around 20% to 60% of medical information is remembered by the end of a visit. Out of what is remembered, less than 50% is accurate. Furthermore, 47% of Americans have health literacy levels below the intermediate range, defined as the ability to determine when to take a medication with food from reading the label.

Lecturing the patient without first understanding what the patient knows and finds important, and understanding the barriers to plan implementation, runs the risk of decreased comprehension, a lack of understanding, or a lack of personal relevance—all leading to decreased adherence. Doing the opposite, by involving the patient in decision making, inspires change that comes from within in the context of the patient’s own needs. This approach is more enduring, emphasizes self-accountability, and ultimately leads to better outcomes.

How I Do It

I open up a dialogue using the Cleveland Clinic’s ARIA approach as adapted from the REDE model of healthcare communication.1

• First, assess: What does the patient know about diagnosis and treatment? How much and what type of education does the patient desire/need? What are the patient’s treatment preferences and health literacy?
• Second, reflect on what the patient just said. Validate meaning and emotion.
• Third, inform the patient within the context of the patient’s perspectives and preferences. Speak slowly and provide small chunks of information at a time. Use understandable language and visual aids. (This will increase recall by 60%.)
• Finally, assess the patient’s understanding and emotional reaction to information provided.
• Repeat the cycle to introduce other chunks of information.

Dr. Velez is director of faculty development in the Center for Excellence in Healthcare Communication at the Cleveland Clinic.

Reference

1. Windover A, Boissy A, Rice T, Gilligan T, Velez V, Merlino J. The REDE model of healthcare communication: optimizing relationship as a therapeutic agent. J Patient Exp. 2014;1(1):8-13.

Editor’s note: “Everything We Say and Do” is an informational series developed by SHM’s Patient Experience Committee to provide readers with thoughtful and actionable communication tactics that have great potential to positively impact patients’ experience of care. Each column will focus on how the contributor applies one of the “Key Communication” areas in practice.

View a chart outlining key communication tactics

What I Say and Do

I counsel and deliver the diagnosis or give recommendations through a dialogue, instead of a monologue, using active listening.

Why I Do It

The monologue, or lecture, is among the least effective ways to instill behavior change. Research studies have demonstrated that, after a monologue, only around 20% to 60% of medical information is remembered by the end of a visit. Out of what is remembered, less than 50% is accurate. Furthermore, 47% of Americans have health literacy levels below the intermediate range, defined as the ability to determine when to take a medication with food from reading the label.

Lecturing the patient without first understanding what the patient knows and finds important, and understanding the barriers to plan implementation, runs the risk of decreased comprehension, a lack of understanding, or a lack of personal relevance—all leading to decreased adherence. Doing the opposite, by involving the patient in decision making, inspires change that comes from within in the context of the patient’s own needs. This approach is more enduring, emphasizes self-accountability, and ultimately leads to better outcomes.

How I Do It

I open up a dialogue using the Cleveland Clinic’s ARIA approach as adapted from the REDE model of healthcare communication.1

• First, assess: What does the patient know about diagnosis and treatment? How much and what type of education does the patient desire/need? What are the patient’s treatment preferences and health literacy?
• Second, reflect on what the patient just said. Validate meaning and emotion.
• Third, inform the patient within the context of the patient’s perspectives and preferences. Speak slowly and provide small chunks of information at a time. Use understandable language and visual aids. (This will increase recall by 60%.)
• Finally, assess the patient’s understanding and emotional reaction to information provided.
• Repeat the cycle to introduce other chunks of information.

Dr. Velez is director of faculty development in the Center for Excellence in Healthcare Communication at the Cleveland Clinic.

Reference

1. Windover A, Boissy A, Rice T, Gilligan T, Velez V, Merlino J. The REDE model of healthcare communication: optimizing relationship as a therapeutic agent. J Patient Exp. 2014;1(1):8-13.

Editor’s note: “Everything We Say and Do” is an informational series developed by SHM’s Patient Experience Committee to provide readers with thoughtful and actionable communication tactics that have great potential to positively impact patients’ experience of care. Each column will focus on how the contributor applies one of the “Key Communication” areas in practice.

View a chart outlining key communication tactics

What I Say and Do

I counsel and deliver the diagnosis or give recommendations through a dialogue, instead of a monologue, using active listening.

Why I Do It

The monologue, or lecture, is among the least effective ways to instill behavior change. Research studies have demonstrated that, after a monologue, only around 20% to 60% of medical information is remembered by the end of a visit. Out of what is remembered, less than 50% is accurate. Furthermore, 47% of Americans have health literacy levels below the intermediate range, defined as the ability to determine when to take a medication with food from reading the label.

Lecturing the patient without first understanding what the patient knows and finds important, and understanding the barriers to plan implementation, runs the risk of decreased comprehension, a lack of understanding, or a lack of personal relevance—all leading to decreased adherence. Doing the opposite, by involving the patient in decision making, inspires change that comes from within in the context of the patient’s own needs. This approach is more enduring, emphasizes self-accountability, and ultimately leads to better outcomes.

How I Do It

I open up a dialogue using the Cleveland Clinic’s ARIA approach as adapted from the REDE model of healthcare communication.1

• First, assess: What does the patient know about diagnosis and treatment? How much and what type of education does the patient desire/need? What are the patient’s treatment preferences and health literacy?
• Second, reflect on what the patient just said. Validate meaning and emotion.
• Third, inform the patient within the context of the patient’s perspectives and preferences. Speak slowly and provide small chunks of information at a time. Use understandable language and visual aids. (This will increase recall by 60%.)
• Finally, assess the patient’s understanding and emotional reaction to information provided.
• Repeat the cycle to introduce other chunks of information.

Dr. Velez is director of faculty development in the Center for Excellence in Healthcare Communication at the Cleveland Clinic.

Reference

1. Windover A, Boissy A, Rice T, Gilligan T, Velez V, Merlino J. The REDE model of healthcare communication: optimizing relationship as a therapeutic agent. J Patient Exp. 2014;1(1):8-13.

Hematopoietic stem cells

in the bone marrow

Preclinical research suggests chronic inflammation leads to an imbalanced blood system, which may have an impact on hematopoietic stem cell (HSC) transplant.

The study showed that chronic exposure to an inflammatory “emergency” signal, interleukin-1 (IL-1), has a negative effect on HSCs—restricting differentiation, impairing self-renewal capacity, and priming HSCs to fail massive replicative challenges such as transplantation.

However, these effects proved to be fully reversible.

Eric M. Pietras, PhD, of the University of Colorado Anschutz Medical Campus in Aurora, and his colleagues recounted these findings in Nature Cell Biology.

While HSCs are usually dormant in the bone marrow, Dr Pietras said he and his colleagues showed that, “these cells are also exquisitely sensitive to changes in their environment and react accordingly.”

The team showed that HSCs are sensitive to the amount of IL-1 they encounter. Chronic IL-1 exposure prompts accelerated cell division and pushes HSCs toward myeloid differentiation through activation of the NF-κB pathway and engagement of a PU.1-dependent myeloid gene program.

So HSCs that are overexposed to IL-1 lose their ability to differentiate into lymphoid and erythroid cells.

“[The HSCs are] receiving a signal telling them they need to keep building myeloid cells, and, as a result, they don’t make the other blood cells you need,” Dr Pietras explained.

“You can end up with too few red blood cells, reducing the body’s ability to deliver oxygen to cells. Or we see decreased production of new lymphoid cells, leaving the system potentially immunodeficient. These are all common features of chronically inflamed, and even aged, blood systems.”

Chronic IL-1 exposure also led to decreased self-renewal activity and regenerative potential in HSCs in response to transplantation in mice. Dr Pietras and his colleagues believe these findings may translate to HSC transplant in humans.

“Our results show that not only should we be looking for markers of blood system compatibility [in HSC donors], but we may also want to explore whether a potential donor’s [HSCs] have been exposed to inflammation and may not be as effective at rebuilding the patient’s blood system,” Dr Pietras said.

“Likewise, the presence of inflammation in the individual receiving the [HSC transplant] could also be an important factor in how well the stem cells regenerate a new blood system once they are transplanted.”

Fortunately, Dr Pietras and his colleagues found the damaging effects of chronic IL-1 exposure could be reversed upon IL-1 withdrawal.

To test the durability of IL-1’s effects, the researchers treated mice with IL-1 for 20 days and then stopped for several weeks to see if the HSCs recovered.

“Our data suggest that it is possible to turn back the clock and reverse the effects of chronic inflammation on [HSCs], perhaps using therapies already available in the clinic to block inflammatory signals such as IL-1,” Dr Pietras said.

“Of course, we don’t yet know, on a human scale, how long it takes a stem cell to ‘remember’ these insults. It may be that, after a longer period of exposure to IL-1, these changes become more fixed.”

Hematopoietic stem cells

in the bone marrow

Preclinical research suggests chronic inflammation leads to an imbalanced blood system, which may have an impact on hematopoietic stem cell (HSC) transplant.

The study showed that chronic exposure to an inflammatory “emergency” signal, interleukin-1 (IL-1), has a negative effect on HSCs—restricting differentiation, impairing self-renewal capacity, and priming HSCs to fail massive replicative challenges such as transplantation.

However, these effects proved to be fully reversible.

Eric M. Pietras, PhD, of the University of Colorado Anschutz Medical Campus in Aurora, and his colleagues recounted these findings in Nature Cell Biology.

While HSCs are usually dormant in the bone marrow, Dr Pietras said he and his colleagues showed that, “these cells are also exquisitely sensitive to changes in their environment and react accordingly.”

The team showed that HSCs are sensitive to the amount of IL-1 they encounter. Chronic IL-1 exposure prompts accelerated cell division and pushes HSCs toward myeloid differentiation through activation of the NF-κB pathway and engagement of a PU.1-dependent myeloid gene program.

So HSCs that are overexposed to IL-1 lose their ability to differentiate into lymphoid and erythroid cells.

“[The HSCs are] receiving a signal telling them they need to keep building myeloid cells, and, as a result, they don’t make the other blood cells you need,” Dr Pietras explained.

“You can end up with too few red blood cells, reducing the body’s ability to deliver oxygen to cells. Or we see decreased production of new lymphoid cells, leaving the system potentially immunodeficient. These are all common features of chronically inflamed, and even aged, blood systems.”

Chronic IL-1 exposure also led to decreased self-renewal activity and regenerative potential in HSCs in response to transplantation in mice. Dr Pietras and his colleagues believe these findings may translate to HSC transplant in humans.

“Our results show that not only should we be looking for markers of blood system compatibility [in HSC donors], but we may also want to explore whether a potential donor’s [HSCs] have been exposed to inflammation and may not be as effective at rebuilding the patient’s blood system,” Dr Pietras said.

“Likewise, the presence of inflammation in the individual receiving the [HSC transplant] could also be an important factor in how well the stem cells regenerate a new blood system once they are transplanted.”

Fortunately, Dr Pietras and his colleagues found the damaging effects of chronic IL-1 exposure could be reversed upon IL-1 withdrawal.

To test the durability of IL-1’s effects, the researchers treated mice with IL-1 for 20 days and then stopped for several weeks to see if the HSCs recovered.

“Our data suggest that it is possible to turn back the clock and reverse the effects of chronic inflammation on [HSCs], perhaps using therapies already available in the clinic to block inflammatory signals such as IL-1,” Dr Pietras said.

“Of course, we don’t yet know, on a human scale, how long it takes a stem cell to ‘remember’ these insults. It may be that, after a longer period of exposure to IL-1, these changes become more fixed.”

Hematopoietic stem cells

in the bone marrow

Preclinical research suggests chronic inflammation leads to an imbalanced blood system, which may have an impact on hematopoietic stem cell (HSC) transplant.

The study showed that chronic exposure to an inflammatory “emergency” signal, interleukin-1 (IL-1), has a negative effect on HSCs—restricting differentiation, impairing self-renewal capacity, and priming HSCs to fail massive replicative challenges such as transplantation.

However, these effects proved to be fully reversible.

Eric M. Pietras, PhD, of the University of Colorado Anschutz Medical Campus in Aurora, and his colleagues recounted these findings in Nature Cell Biology.

While HSCs are usually dormant in the bone marrow, Dr Pietras said he and his colleagues showed that, “these cells are also exquisitely sensitive to changes in their environment and react accordingly.”

The team showed that HSCs are sensitive to the amount of IL-1 they encounter. Chronic IL-1 exposure prompts accelerated cell division and pushes HSCs toward myeloid differentiation through activation of the NF-κB pathway and engagement of a PU.1-dependent myeloid gene program.

So HSCs that are overexposed to IL-1 lose their ability to differentiate into lymphoid and erythroid cells.

“[The HSCs are] receiving a signal telling them they need to keep building myeloid cells, and, as a result, they don’t make the other blood cells you need,” Dr Pietras explained.

“You can end up with too few red blood cells, reducing the body’s ability to deliver oxygen to cells. Or we see decreased production of new lymphoid cells, leaving the system potentially immunodeficient. These are all common features of chronically inflamed, and even aged, blood systems.”

Chronic IL-1 exposure also led to decreased self-renewal activity and regenerative potential in HSCs in response to transplantation in mice. Dr Pietras and his colleagues believe these findings may translate to HSC transplant in humans.

“Our results show that not only should we be looking for markers of blood system compatibility [in HSC donors], but we may also want to explore whether a potential donor’s [HSCs] have been exposed to inflammation and may not be as effective at rebuilding the patient’s blood system,” Dr Pietras said.

“Likewise, the presence of inflammation in the individual receiving the [HSC transplant] could also be an important factor in how well the stem cells regenerate a new blood system once they are transplanted.”

Fortunately, Dr Pietras and his colleagues found the damaging effects of chronic IL-1 exposure could be reversed upon IL-1 withdrawal.

To test the durability of IL-1’s effects, the researchers treated mice with IL-1 for 20 days and then stopped for several weeks to see if the HSCs recovered.

“Our data suggest that it is possible to turn back the clock and reverse the effects of chronic inflammation on [HSCs], perhaps using therapies already available in the clinic to block inflammatory signals such as IL-1,” Dr Pietras said.

“Of course, we don’t yet know, on a human scale, how long it takes a stem cell to ‘remember’ these insults. It may be that, after a longer period of exposure to IL-1, these changes become more fixed.”

Blood samples

Photo by William Weinert

The US Centers for Disease Control and Prevention (CDC) and the Occupational Safety and Health Administration (OSHA) have issued an interim guidance for protecting workers from occupational exposure to the Zika virus.

The guidance is for healthcare and laboratory workers, outdoor workers, mosquito control workers, and business travelers.

It includes recommendations to help protect these workers from mosquito bites and exposure to an infected person’s blood or other body fluids.

The CDC noted that, although Zika virus is primarily spread by infected mosquitoes, exposure to an infected person’s blood or other body fluids may also result in transmission.

So healthcare workers who may be exposed to contaminated blood or other potentially infectious materials from people infected with Zika virus may require additional protection.

Recommendations for healthcare and laboratory workers

Employers and workers in healthcare settings and laboratories should follow standard infection control and biosafety practices (including universal precautions) as appropriate to prevent or minimize the risk of Zika virus transmission.

Standard precautions include, but are not limited to, hand hygiene and the use of personal protective equipment (PPE) to avoid direct contact with blood and other potentially infectious materials, including laboratory specimens/samples. PPE may include gloves, gowns, masks, and eye protection.

Hand hygiene consists of washing with soap and water or using alcohol-based hand rubs containing at least 60% alcohol. Soap and water are best for hands that are visibly soiled. Perform hand hygiene before and after any contact with a patient, after any contact with potentially infectious material, and before putting on and upon removing PPE, including gloves.

Laboratories should ensure that their facilities and practices meet the appropriate Biosafety Level for the type of work being conducted (including the specific biologic agents—in this case, Zika virus) in the laboratory.

Employers should ensure that workers follow workplace standard operating procedures (eg, workplace exposure control plans) and use the engineering controls and work practices available in the workplace to prevent exposure to blood or other potentially infectious materials.

Employers should ensure workers do not bend, recap, or remove contaminated needles or other contaminated sharps. Properly dispose of these items in closable, puncture-resistant, leak-proof, and labeled or color-coded containers. Workers should use sharps with engineered sharps injury protection to avoid sharps-related injuries.

Additional details and recommendations for business travelers, outdoor workers, and mosquito control workers are available in the full guidance document.

The CDC said it will continue to update this guidance based on accumulating evidence. For updates, visit www.cdc.gov/zika.

Blood samples

Photo by William Weinert

The US Centers for Disease Control and Prevention (CDC) and the Occupational Safety and Health Administration (OSHA) have issued an interim guidance for protecting workers from occupational exposure to the Zika virus.

The guidance is for healthcare and laboratory workers, outdoor workers, mosquito control workers, and business travelers.

It includes recommendations to help protect these workers from mosquito bites and exposure to an infected person’s blood or other body fluids.

The CDC noted that, although Zika virus is primarily spread by infected mosquitoes, exposure to an infected person’s blood or other body fluids may also result in transmission.

So healthcare workers who may be exposed to contaminated blood or other potentially infectious materials from people infected with Zika virus may require additional protection.

Recommendations for healthcare and laboratory workers

Employers and workers in healthcare settings and laboratories should follow standard infection control and biosafety practices (including universal precautions) as appropriate to prevent or minimize the risk of Zika virus transmission.

Standard precautions include, but are not limited to, hand hygiene and the use of personal protective equipment (PPE) to avoid direct contact with blood and other potentially infectious materials, including laboratory specimens/samples. PPE may include gloves, gowns, masks, and eye protection.

Hand hygiene consists of washing with soap and water or using alcohol-based hand rubs containing at least 60% alcohol. Soap and water are best for hands that are visibly soiled. Perform hand hygiene before and after any contact with a patient, after any contact with potentially infectious material, and before putting on and upon removing PPE, including gloves.

Laboratories should ensure that their facilities and practices meet the appropriate Biosafety Level for the type of work being conducted (including the specific biologic agents—in this case, Zika virus) in the laboratory.

Employers should ensure that workers follow workplace standard operating procedures (eg, workplace exposure control plans) and use the engineering controls and work practices available in the workplace to prevent exposure to blood or other potentially infectious materials.

Employers should ensure workers do not bend, recap, or remove contaminated needles or other contaminated sharps. Properly dispose of these items in closable, puncture-resistant, leak-proof, and labeled or color-coded containers. Workers should use sharps with engineered sharps injury protection to avoid sharps-related injuries.

Additional details and recommendations for business travelers, outdoor workers, and mosquito control workers are available in the full guidance document.

The CDC said it will continue to update this guidance based on accumulating evidence. For updates, visit www.cdc.gov/zika.

Blood samples

Photo by William Weinert

The US Centers for Disease Control and Prevention (CDC) and the Occupational Safety and Health Administration (OSHA) have issued an interim guidance for protecting workers from occupational exposure to the Zika virus.

The guidance is for healthcare and laboratory workers, outdoor workers, mosquito control workers, and business travelers.

It includes recommendations to help protect these workers from mosquito bites and exposure to an infected person’s blood or other body fluids.

The CDC noted that, although Zika virus is primarily spread by infected mosquitoes, exposure to an infected person’s blood or other body fluids may also result in transmission.

So healthcare workers who may be exposed to contaminated blood or other potentially infectious materials from people infected with Zika virus may require additional protection.

Recommendations for healthcare and laboratory workers

Employers and workers in healthcare settings and laboratories should follow standard infection control and biosafety practices (including universal precautions) as appropriate to prevent or minimize the risk of Zika virus transmission.

Standard precautions include, but are not limited to, hand hygiene and the use of personal protective equipment (PPE) to avoid direct contact with blood and other potentially infectious materials, including laboratory specimens/samples. PPE may include gloves, gowns, masks, and eye protection.

Hand hygiene consists of washing with soap and water or using alcohol-based hand rubs containing at least 60% alcohol. Soap and water are best for hands that are visibly soiled. Perform hand hygiene before and after any contact with a patient, after any contact with potentially infectious material, and before putting on and upon removing PPE, including gloves.

Laboratories should ensure that their facilities and practices meet the appropriate Biosafety Level for the type of work being conducted (including the specific biologic agents—in this case, Zika virus) in the laboratory.

Employers should ensure that workers follow workplace standard operating procedures (eg, workplace exposure control plans) and use the engineering controls and work practices available in the workplace to prevent exposure to blood or other potentially infectious materials.

Employers should ensure workers do not bend, recap, or remove contaminated needles or other contaminated sharps. Properly dispose of these items in closable, puncture-resistant, leak-proof, and labeled or color-coded containers. Workers should use sharps with engineered sharps injury protection to avoid sharps-related injuries.

Additional details and recommendations for business travelers, outdoor workers, and mosquito control workers are available in the full guidance document.

The CDC said it will continue to update this guidance based on accumulating evidence. For updates, visit www.cdc.gov/zika.

Prescription medications

Photo courtesy of the CDC

The combination of vorinostat and bortezomib, with or without dexamethasone, can be active in patients with multiple myeloma (MM) that is refractory to novel treatments, according to researchers.

In a phase 2 trial, the combination produced an overall response rate of 11% among MM patients who were refractory to bortezomib and were either refractory to or could not receive treatment with an immunomodulatory agent (IMiD).

About 92% of patients had drug-related adverse events (AEs), and 20% had serious drug-related AEs.

These results were published in Clinical Lymphoma, Myeloma & Leukemia. The study was funded by Merck & Co., Inc., which markets vorinostat as Zolinza.

This trial (VANTAGE 095) enrolled 143 MM patients from 41 centers in 12 countries. The patients had a median age of 63 (range, 37-81) and had received a median of 4 prior lines of therapy (range, 2-17).

All 143 patients were considered refractory to previous bortezomib, which was defined as less than 25% response on therapy or progression during/less than 60 days after the completion of bortezomib therapy.

All but 1 patient had been exposed to 1 or more IMiDs (99.3%). Roughly 87% of patients exposed to IMiDs were considered to have disease refractory to at least 1 IMiD and 40% to at least 2 different IMiDs. Three percent of patients were considered ineligible for further IMiD-based therapy because of previous toxicities.

For this study, patients received 21-day cycles of bortezomib (1.3 mg/m² intravenously; days 1, 4, 8, and 11) plus oral vorinostat at 400 mg/d on days 1 to 14.

If a patient had no change as the best response after 4 cycles of treatment or progressive disease after 2 cycles of treatment, oral dexamethasone at 20 mg on the day of and day after each dose of bortezomib could be added to the treatment regimen.

Patients were treated until disease progression, unacceptable toxicities, or withdrawal from the study.

One hundred and forty-two patients were evaluable for safety and efficacy. Fifty-seven of these patients received dexamethasone per protocol.

The overall response rate (partial response or better), as assessed by an independent adjudication committee, was 11.3%.

All 16 responses were partial responses. The median time to response was 44 days (range, 22-71), and the median duration of response was 211 days (range, 64-550 days).

Eleven patients (7.7%) had a minimal response, and 87 (61.3%) had stable disease.

The median progression-free survival was 3.13 months, and the median time to progression was 3.47 months. The median overall survival was 11.2 months, with a 2-year survival rate of 32%.

All 142 patients had at least 1 AE, and 131 (92.3%) had drug-related AEs. Most AEs were grade 3 (28.9%) or 4 (50.7%). Serious AEs occurred in 64.8% of patients, and serious drug-related AEs occurred in 20.4%.

Twenty-seven patients (19%) discontinued treatment due to an AE. And 24 patients (16.9%) died from an AE, although 18 of these deaths were attributable to progression of underlying MM.

The most common AEs were thrombocytopenia (69.7%), nausea (57.0%), diarrhea (53.5%), anemia (52.1%), and fatigue (48.6%).

Prescription medications

Photo courtesy of the CDC

The combination of vorinostat and bortezomib, with or without dexamethasone, can be active in patients with multiple myeloma (MM) that is refractory to novel treatments, according to researchers.

In a phase 2 trial, the combination produced an overall response rate of 11% among MM patients who were refractory to bortezomib and were either refractory to or could not receive treatment with an immunomodulatory agent (IMiD).

About 92% of patients had drug-related adverse events (AEs), and 20% had serious drug-related AEs.

These results were published in Clinical Lymphoma, Myeloma & Leukemia. The study was funded by Merck & Co., Inc., which markets vorinostat as Zolinza.

This trial (VANTAGE 095) enrolled 143 MM patients from 41 centers in 12 countries. The patients had a median age of 63 (range, 37-81) and had received a median of 4 prior lines of therapy (range, 2-17).

All 143 patients were considered refractory to previous bortezomib, which was defined as less than 25% response on therapy or progression during/less than 60 days after the completion of bortezomib therapy.

All but 1 patient had been exposed to 1 or more IMiDs (99.3%). Roughly 87% of patients exposed to IMiDs were considered to have disease refractory to at least 1 IMiD and 40% to at least 2 different IMiDs. Three percent of patients were considered ineligible for further IMiD-based therapy because of previous toxicities.

For this study, patients received 21-day cycles of bortezomib (1.3 mg/m² intravenously; days 1, 4, 8, and 11) plus oral vorinostat at 400 mg/d on days 1 to 14.

If a patient had no change as the best response after 4 cycles of treatment or progressive disease after 2 cycles of treatment, oral dexamethasone at 20 mg on the day of and day after each dose of bortezomib could be added to the treatment regimen.

Patients were treated until disease progression, unacceptable toxicities, or withdrawal from the study.

One hundred and forty-two patients were evaluable for safety and efficacy. Fifty-seven of these patients received dexamethasone per protocol.

The overall response rate (partial response or better), as assessed by an independent adjudication committee, was 11.3%.

All 16 responses were partial responses. The median time to response was 44 days (range, 22-71), and the median duration of response was 211 days (range, 64-550 days).

Eleven patients (7.7%) had a minimal response, and 87 (61.3%) had stable disease.

The median progression-free survival was 3.13 months, and the median time to progression was 3.47 months. The median overall survival was 11.2 months, with a 2-year survival rate of 32%.

All 142 patients had at least 1 AE, and 131 (92.3%) had drug-related AEs. Most AEs were grade 3 (28.9%) or 4 (50.7%). Serious AEs occurred in 64.8% of patients, and serious drug-related AEs occurred in 20.4%.

Twenty-seven patients (19%) discontinued treatment due to an AE. And 24 patients (16.9%) died from an AE, although 18 of these deaths were attributable to progression of underlying MM.

The most common AEs were thrombocytopenia (69.7%), nausea (57.0%), diarrhea (53.5%), anemia (52.1%), and fatigue (48.6%).

Prescription medications

Photo courtesy of the CDC

The combination of vorinostat and bortezomib, with or without dexamethasone, can be active in patients with multiple myeloma (MM) that is refractory to novel treatments, according to researchers.

In a phase 2 trial, the combination produced an overall response rate of 11% among MM patients who were refractory to bortezomib and were either refractory to or could not receive treatment with an immunomodulatory agent (IMiD).

About 92% of patients had drug-related adverse events (AEs), and 20% had serious drug-related AEs.

These results were published in Clinical Lymphoma, Myeloma & Leukemia. The study was funded by Merck & Co., Inc., which markets vorinostat as Zolinza.

This trial (VANTAGE 095) enrolled 143 MM patients from 41 centers in 12 countries. The patients had a median age of 63 (range, 37-81) and had received a median of 4 prior lines of therapy (range, 2-17).

All 143 patients were considered refractory to previous bortezomib, which was defined as less than 25% response on therapy or progression during/less than 60 days after the completion of bortezomib therapy.

All but 1 patient had been exposed to 1 or more IMiDs (99.3%). Roughly 87% of patients exposed to IMiDs were considered to have disease refractory to at least 1 IMiD and 40% to at least 2 different IMiDs. Three percent of patients were considered ineligible for further IMiD-based therapy because of previous toxicities.

For this study, patients received 21-day cycles of bortezomib (1.3 mg/m² intravenously; days 1, 4, 8, and 11) plus oral vorinostat at 400 mg/d on days 1 to 14.

If a patient had no change as the best response after 4 cycles of treatment or progressive disease after 2 cycles of treatment, oral dexamethasone at 20 mg on the day of and day after each dose of bortezomib could be added to the treatment regimen.

Patients were treated until disease progression, unacceptable toxicities, or withdrawal from the study.

One hundred and forty-two patients were evaluable for safety and efficacy. Fifty-seven of these patients received dexamethasone per protocol.

The overall response rate (partial response or better), as assessed by an independent adjudication committee, was 11.3%.

All 16 responses were partial responses. The median time to response was 44 days (range, 22-71), and the median duration of response was 211 days (range, 64-550 days).

Eleven patients (7.7%) had a minimal response, and 87 (61.3%) had stable disease.

The median progression-free survival was 3.13 months, and the median time to progression was 3.47 months. The median overall survival was 11.2 months, with a 2-year survival rate of 32%.

All 142 patients had at least 1 AE, and 131 (92.3%) had drug-related AEs. Most AEs were grade 3 (28.9%) or 4 (50.7%). Serious AEs occurred in 64.8% of patients, and serious drug-related AEs occurred in 20.4%.

Twenty-seven patients (19%) discontinued treatment due to an AE. And 24 patients (16.9%) died from an AE, although 18 of these deaths were attributable to progression of underlying MM.

The most common AEs were thrombocytopenia (69.7%), nausea (57.0%), diarrhea (53.5%), anemia (52.1%), and fatigue (48.6%).