Approximately 2.3 million people in the United States and 4.5 million people in Europe have atrial fibrillation (AF), with an increase in prevalence with age to 8% among patients aged 80 years and older.[1] The most feared and potentially preventable complications of AF are stroke or systemic thromboembolism, and stroke in particular is increased approximately 5‐fold in patients with nonvalvular atrial fibrillation (NVAF).[2] For over 50 years, warfarin and similar vitamin K antagonists have been the principal anticoagulants used for preventing stroke in NVAF, with consistent reductions in systemic thromboembolic events when compared with placebo or aspirin.[2, 3] However, because of its narrow therapeutic window and related management difficulties (ie, frequent monitoring of international normalized ratio [INR] levels, dietary and medication restrictions, interindividual variability in dosing), many patients with NVAF do not receive warfarin or are inadequately treated.[4]

In response to the need for antithrombotic agents with better efficacy, patient tolerance, and convenience, the US Food and Drug Administration (FDA) recently approved 3 novel oral anticoagulants (NOACs) as alternatives to warfarin for NVAF: dabigatran, rivaroxaban, and apixaban. In this review, we evaluated the pharmacologic properties and clinical studies of these NOACs, including the continued role of warfarin in many patients requiring systemic anticoagulation, to guide practicing clinicians in providing individualized, patient‐centered care to each of their patients with NVAF.

PHARMACOLOGY

CLINICAL STUDIES

Randomized trials evaluating warfarin against placebo or aspirin for NVAF have spanned more than 3 decades, encompassing a variety of study designs, patient populations, and analytic techniques.[2, 3] Despite differences between trials, these studies have provided the framework for contemporary AF management, with consistent reductions in thromboembolic events with systemic anticoagulation, most notably among patients with multiple risk factors for stroke. Current professional guidelines recommend risk assessment of patients with NVAF, using the CHADS₂ (1 point each for Congestive heart failure, Hypertension, Age 75 years, Diabetes, and 2 points for prior Stroke) or similar risk scores, to identify patients most likely to benefit from systemic anticoagulation.[1, 13] As a result of this extensive background literature, the 3 NOACs have primarily been evaluated against warfarin (instead of aspirin or placebo) as potential alternatives for reducing thromboembolic events in patients with NVAF. The 1 exception is a prematurely terminated trial of apixaban in warfarin‐ineligible patients with NVAF, in which apixaban reduced stroke or systemic embolism by 55% compared with aspirin after only 1.1 years of follow‐up, with no significant difference in major bleeding.[14]

Pivotal Clinical Trials

The 3 principal trials evaluating the NOACs against warfarin for NVAF are summarized in Table 2. In the Randomized Evaluation of Long‐term anticoagulation Therapy (RE‐LY) trial, dabigatran was compared with warfarin in 18,113 patients recruited from 951 clinical centers in 44 countries using a noninferiority study design.[15] Two different doses of dabigatran were studied, but only the 150‐mg BID dose was approved by the FDA. As a result, only the findings from the clinically approved 150‐mg dose are summarized in this review. Although RE‐LY was considered a semiblinded randomized trial, patients enrolled in the warfarin control arm underwent regular INR surveillance by their treating physicians, leaving the trial open to potential reporting biases. The authors tried to minimize bias by providing a standardized protocol for INR management, and by assigning 2 independent investigators blinded to the treatment assignments to adjudicate each event.

The Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET‐AF) study involved 14,264 patients from 1178 participating sites in 45 countries.[16] Again, a noninferiority design was used to evaluate 20‐mg daily rivaroxaban against warfarin, but the 2 arms were compared in double‐blinded, double‐dummy fashion (thus eliminating the reporting bias related to the warfarin control arm in RE‐LY). In addition, whereas RE‐LY randomized patients to fixed doses of dabigatran within their respective treatment arms, ROCKET‐AF required a lower dose of rivaroxaban (15 mg daily) for patients with moderately reduced creatinine clearance (3049 mL/min). Also of note, ROCKET‐AF reported both intention‐to‐treat and on‐treatment analyses, with outcomes listed as number of events per 100 patient‐years (instead of percent per year). To facilitate comparisons between trials, only the intention‐to‐treat data are reported in this review.

Like ROCKET‐AF, the Apixaban for Reduction in Stroke and Other Thromboembolic Events in Atrial Fibrillation (ARISTOTLE) study randomized patients using a double‐blind, double‐dummy, noninferiority design to therapy with apixaban 5 mg BID versus warfarin, ultimately enrolling 18,201 patients at 1034 clinical sites in 39 countries.[17] ARISTOTLE also provided a lower dose of apixaban (2.5 mg BID) for patients at higher risk of bleeding, defined by the authors as patients with 2 of the following characteristics: age 80 years and older, weight 60 kg, or serum creatinine 1.5 mg/dL. However, <5% of all patients in ARISTOTLE met these criteria and received the lower dose of apixaban.

Patient Populations and Study End Points

All 3 trials used relatively similar criteria for enrolling and following patients, with individual thromboembolic risk calculated using the CHADS₂ definition, where higher scores are associated with incrementally higher risk of stroke.[18] However, ROCKET‐AF required a minimum CHADS₂ score of 2 and permitted patients with lower left ventricular ejection fractions (35%), thus enrolling a higher‐risk patient population than RE‐LY and ARISTOTLE (where ejection fraction 40% was considered a risk factor for thromboembolism). As a result, more patients in ROCKET‐AF had prior stroke or systemic embolism than the other 2 trials (55% vs 20% in RE‐LY and 19% in ARISTOTLE) and more patients had significant heart failure (63%,vs 32% in RE‐LY and 36% in ARISTOTLE). These differences in enrollment ultimately translated into a higher overall risk profile in ROCKET‐AF (Table 3), which may have impacted some of the study results. In addition, patients requiring dual antiplatelet therapy (ie, clopidogrel and aspirin) were permitted in RE‐LY (5% of the final randomized population) but were excluded from the other 2 trials. The primary outcome for all 3 trials was the composite of stroke or systemic embolism, and the primary safety end point was major bleeding (RE‐LY and ARISTOTLE), or combined major and clinically relevant nonmajor bleeding events (ROCKET‐AF).

INR Control

In prior randomized trials and observational registries of patients with AF, INR control has been highly variable, and better clinical outcomes were observed among patients consistently achieving INR levels between 2 and 3.[3, 19] For all 3 randomized trials of the NOACs summarized in this review, the warfarin control arms were analyzed using the Rosendaal method of evaluating total time in therapeutic range (TTR), reflecting the percent of time the patient had an INR between 2 and 3.[20] Overall, the mean TTR was 64% to 66% in the RE‐LY and ARISTOTLE trials, but only 55% in ROCKET‐AF. This has led to considerable criticism of the ROCKET‐AF trial, given concerns for a less robust comparator arm for rivaroxaban (and thus the potential for inflated efficacy of rivaroxaban over warfarin).[21, 22] However, these TTR levels are similar to those reported in prior studies of warfarin and may better represent real‐world INR management across multiple countries.[23]

Of note, the heterogeneity of INR management also appeared to impact clinical outcomes. For example, in RE‐LY, the INR control for warfarin was particularly poor in countries from east and southeast Asia, which may explain the more robust performance of dabigatran in these regions (vs Western and Central Europe, where TTR was >64%).[24] In the same analysis of variability within the RE‐LY trial, center‐specific TTRs demonstrated higher rates of cardiovascular events and major bleeds in centers with TTR <57%.[24] A different issue was noted in ROCKET‐AF, where TTR was relatively low in the overall trial and clinical outcomes were more equivalent between rivaroxaban and warfarin, when compared with the superiority of the new drugs in RE‐LY and ARISTOTLE. However, in ROCKET‐AF centers with mean TTR >68%, rivaroxaban was associated with higher rates of stroke and systemic embolism, and in the US subgroup (where TTR was 64%), rivaroxaban had a higher bleeding rate than warfarin.[9] Taken together, these findings highlight the potential for net clinical benefit among patients and populations with poor INR control during warfarin therapy, and conversely, the loss of benefit (and even potential harm) if replacing good INR management with the newer antithrombotic drugs.

To further explore these questions regarding NOAC efficacy and safety, the FDA review of rivaroxaban included a calculation of the major bleeds incurred per embolic event prevented.[9] Using this risk‐benefit ratio, the FDA confirmed that the advantage of using rivaroxaban over warfarin in ROCKET‐AF occurred among patients with difficult INR control, whereas patients with better INR management did not experience this net clinical benefit. As a result, in the absence of carefully managed INR levels in randomized trials (where INRs are managed through an intensive protocol), careful selection of patients with poor INR control may be prudent when considering rivaroxaban or other NOACs over warfarin.

Patient‐Centered Selection of Therapy

Although none of the NOACs have been compared with each other, several important drug and trial characteristics may help identify patients most likely to benefit from a specific drug choice for preventing thromboembolism in NVAF (Figure 1). For example, the modest increase in myocardial infarction noted among patients randomized to dabigatran in RE‐LY remains inadequately understood, and may lead some practitioners to favor using rivaroxaban or apixaban for NVAF patients at risk for coronary events. Others may point to the mortality reduction and lower rates of bleeding, including no increase in gastrointestinal hemorrhage, among patients receiving apixaban in ARISTOTLE. Concerns about reversibility also may impact drug selection, as none of the NOACs can be easily reversed for major life‐threatening bleeding, although potential antidotes are in development and may hopefully address this concern in the near future.[25] Other considerations include patient adherence to the twice‐daily dosing regimen of dabigatran or apixaban, comorbid conditions such as bleeding risk, drug‐drug interactions, outcomes reported during postmarketing surveillance, and cost. Overall, the noninferiority of these new agents compared with warfarin, plus their superiority in reducing the risk of important clinical events like intracranial hemorrhage, has led some professional societies to recommend the NOACs over warfarin in patients with NVAF whose CHADS₂ scores are 1 or greater.[26]

Figure 1

Limitations

Several important limitations to these agents and their principal clinical trials should be noted. First, all 3 NOACs were compared with warfarin (or aspirin in the 1 prematurely halted apixaban trial), so comparisons between each drug and comparisons with placebo cannot be extrapolated from the data available. Second, the importance of remaining on label and using the NOACs appropriately for NVAF cannot be overemphasized, as recent experience with the NOACs among patients with mechanical heart valves or other clinical scenarios outside of the patient populations from the pivotal clinical trials (eg, severe renal dysfunction) will likely result in adverse patient outcomes.[27] Third, despite greater reliability in drug effects between patients and lack of need for intensive INR monitoring, more than 1 in 5 patients treated with the NOACs in these trials prematurely stopped therapy before reaching a study end point. Some of this premature discontinuation may be related to the more consistent degree of systemic anticoagulation with NOACs when compared with warfarin, thus resulting in higher bleeding rates (major, minor, or nuisance) than those reported in older trials using aspirin or placebo as the comparator. For each new antithrombotic medication, annual rates of major bleeding were higher than annual thromboembolic event rates (3.1% vs 1.1% in RE‐LY, 3.6% vs 2.1% in ROCKET‐AF, and 2.1% vs 1.3% in ARISTOTLE, respectively), although similar trends were noted for patients treated with warfarin. Nonetheless, because the average thromboembolic event may have more devastating consequences than the average bleeding event,[28] these clinical considerations must be carefully weighed for each patient when expanding the use of all 3 new drugs to the general population with NVAF. Further evaluation of the NOACs in real‐world populations, including an assessment of these drugs among patients taking dual antiplatelet therapy, is clearly warranted.

CONCLUSIONS

The recent development of alternative anticoagulation strategies to warfarin represents an exciting new opportunity for preventing the devastating consequences of stroke or systemic thromboembolism in patients with NVAF. However, despite the limitations of chronic warfarin therapy, it remains highly effective for a large proportion of patients with good INR control. Future studies will allow clinicians to better understand the advantages and disadvantages of each NOAC, so that ultimately an individualized, patient‐centered plan of care may be developed for each patient with NVAF.

Approximately 2.3 million people in the United States and 4.5 million people in Europe have atrial fibrillation (AF), with an increase in prevalence with age to 8% among patients aged 80 years and older.[1] The most feared and potentially preventable complications of AF are stroke or systemic thromboembolism, and stroke in particular is increased approximately 5‐fold in patients with nonvalvular atrial fibrillation (NVAF).[2] For over 50 years, warfarin and similar vitamin K antagonists have been the principal anticoagulants used for preventing stroke in NVAF, with consistent reductions in systemic thromboembolic events when compared with placebo or aspirin.[2, 3] However, because of its narrow therapeutic window and related management difficulties (ie, frequent monitoring of international normalized ratio [INR] levels, dietary and medication restrictions, interindividual variability in dosing), many patients with NVAF do not receive warfarin or are inadequately treated.[4]

In response to the need for antithrombotic agents with better efficacy, patient tolerance, and convenience, the US Food and Drug Administration (FDA) recently approved 3 novel oral anticoagulants (NOACs) as alternatives to warfarin for NVAF: dabigatran, rivaroxaban, and apixaban. In this review, we evaluated the pharmacologic properties and clinical studies of these NOACs, including the continued role of warfarin in many patients requiring systemic anticoagulation, to guide practicing clinicians in providing individualized, patient‐centered care to each of their patients with NVAF.

PHARMACOLOGY

CLINICAL STUDIES

Randomized trials evaluating warfarin against placebo or aspirin for NVAF have spanned more than 3 decades, encompassing a variety of study designs, patient populations, and analytic techniques.[2, 3] Despite differences between trials, these studies have provided the framework for contemporary AF management, with consistent reductions in thromboembolic events with systemic anticoagulation, most notably among patients with multiple risk factors for stroke. Current professional guidelines recommend risk assessment of patients with NVAF, using the CHADS₂ (1 point each for Congestive heart failure, Hypertension, Age 75 years, Diabetes, and 2 points for prior Stroke) or similar risk scores, to identify patients most likely to benefit from systemic anticoagulation.[1, 13] As a result of this extensive background literature, the 3 NOACs have primarily been evaluated against warfarin (instead of aspirin or placebo) as potential alternatives for reducing thromboembolic events in patients with NVAF. The 1 exception is a prematurely terminated trial of apixaban in warfarin‐ineligible patients with NVAF, in which apixaban reduced stroke or systemic embolism by 55% compared with aspirin after only 1.1 years of follow‐up, with no significant difference in major bleeding.[14]

Pivotal Clinical Trials

The 3 principal trials evaluating the NOACs against warfarin for NVAF are summarized in Table 2. In the Randomized Evaluation of Long‐term anticoagulation Therapy (RE‐LY) trial, dabigatran was compared with warfarin in 18,113 patients recruited from 951 clinical centers in 44 countries using a noninferiority study design.[15] Two different doses of dabigatran were studied, but only the 150‐mg BID dose was approved by the FDA. As a result, only the findings from the clinically approved 150‐mg dose are summarized in this review. Although RE‐LY was considered a semiblinded randomized trial, patients enrolled in the warfarin control arm underwent regular INR surveillance by their treating physicians, leaving the trial open to potential reporting biases. The authors tried to minimize bias by providing a standardized protocol for INR management, and by assigning 2 independent investigators blinded to the treatment assignments to adjudicate each event.

The Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET‐AF) study involved 14,264 patients from 1178 participating sites in 45 countries.[16] Again, a noninferiority design was used to evaluate 20‐mg daily rivaroxaban against warfarin, but the 2 arms were compared in double‐blinded, double‐dummy fashion (thus eliminating the reporting bias related to the warfarin control arm in RE‐LY). In addition, whereas RE‐LY randomized patients to fixed doses of dabigatran within their respective treatment arms, ROCKET‐AF required a lower dose of rivaroxaban (15 mg daily) for patients with moderately reduced creatinine clearance (3049 mL/min). Also of note, ROCKET‐AF reported both intention‐to‐treat and on‐treatment analyses, with outcomes listed as number of events per 100 patient‐years (instead of percent per year). To facilitate comparisons between trials, only the intention‐to‐treat data are reported in this review.

Like ROCKET‐AF, the Apixaban for Reduction in Stroke and Other Thromboembolic Events in Atrial Fibrillation (ARISTOTLE) study randomized patients using a double‐blind, double‐dummy, noninferiority design to therapy with apixaban 5 mg BID versus warfarin, ultimately enrolling 18,201 patients at 1034 clinical sites in 39 countries.[17] ARISTOTLE also provided a lower dose of apixaban (2.5 mg BID) for patients at higher risk of bleeding, defined by the authors as patients with 2 of the following characteristics: age 80 years and older, weight 60 kg, or serum creatinine 1.5 mg/dL. However, <5% of all patients in ARISTOTLE met these criteria and received the lower dose of apixaban.

Patient Populations and Study End Points

All 3 trials used relatively similar criteria for enrolling and following patients, with individual thromboembolic risk calculated using the CHADS₂ definition, where higher scores are associated with incrementally higher risk of stroke.[18] However, ROCKET‐AF required a minimum CHADS₂ score of 2 and permitted patients with lower left ventricular ejection fractions (35%), thus enrolling a higher‐risk patient population than RE‐LY and ARISTOTLE (where ejection fraction 40% was considered a risk factor for thromboembolism). As a result, more patients in ROCKET‐AF had prior stroke or systemic embolism than the other 2 trials (55% vs 20% in RE‐LY and 19% in ARISTOTLE) and more patients had significant heart failure (63%,vs 32% in RE‐LY and 36% in ARISTOTLE). These differences in enrollment ultimately translated into a higher overall risk profile in ROCKET‐AF (Table 3), which may have impacted some of the study results. In addition, patients requiring dual antiplatelet therapy (ie, clopidogrel and aspirin) were permitted in RE‐LY (5% of the final randomized population) but were excluded from the other 2 trials. The primary outcome for all 3 trials was the composite of stroke or systemic embolism, and the primary safety end point was major bleeding (RE‐LY and ARISTOTLE), or combined major and clinically relevant nonmajor bleeding events (ROCKET‐AF).

INR Control

In prior randomized trials and observational registries of patients with AF, INR control has been highly variable, and better clinical outcomes were observed among patients consistently achieving INR levels between 2 and 3.[3, 19] For all 3 randomized trials of the NOACs summarized in this review, the warfarin control arms were analyzed using the Rosendaal method of evaluating total time in therapeutic range (TTR), reflecting the percent of time the patient had an INR between 2 and 3.[20] Overall, the mean TTR was 64% to 66% in the RE‐LY and ARISTOTLE trials, but only 55% in ROCKET‐AF. This has led to considerable criticism of the ROCKET‐AF trial, given concerns for a less robust comparator arm for rivaroxaban (and thus the potential for inflated efficacy of rivaroxaban over warfarin).[21, 22] However, these TTR levels are similar to those reported in prior studies of warfarin and may better represent real‐world INR management across multiple countries.[23]

Of note, the heterogeneity of INR management also appeared to impact clinical outcomes. For example, in RE‐LY, the INR control for warfarin was particularly poor in countries from east and southeast Asia, which may explain the more robust performance of dabigatran in these regions (vs Western and Central Europe, where TTR was >64%).[24] In the same analysis of variability within the RE‐LY trial, center‐specific TTRs demonstrated higher rates of cardiovascular events and major bleeds in centers with TTR <57%.[24] A different issue was noted in ROCKET‐AF, where TTR was relatively low in the overall trial and clinical outcomes were more equivalent between rivaroxaban and warfarin, when compared with the superiority of the new drugs in RE‐LY and ARISTOTLE. However, in ROCKET‐AF centers with mean TTR >68%, rivaroxaban was associated with higher rates of stroke and systemic embolism, and in the US subgroup (where TTR was 64%), rivaroxaban had a higher bleeding rate than warfarin.[9] Taken together, these findings highlight the potential for net clinical benefit among patients and populations with poor INR control during warfarin therapy, and conversely, the loss of benefit (and even potential harm) if replacing good INR management with the newer antithrombotic drugs.

To further explore these questions regarding NOAC efficacy and safety, the FDA review of rivaroxaban included a calculation of the major bleeds incurred per embolic event prevented.[9] Using this risk‐benefit ratio, the FDA confirmed that the advantage of using rivaroxaban over warfarin in ROCKET‐AF occurred among patients with difficult INR control, whereas patients with better INR management did not experience this net clinical benefit. As a result, in the absence of carefully managed INR levels in randomized trials (where INRs are managed through an intensive protocol), careful selection of patients with poor INR control may be prudent when considering rivaroxaban or other NOACs over warfarin.

Patient‐Centered Selection of Therapy

Although none of the NOACs have been compared with each other, several important drug and trial characteristics may help identify patients most likely to benefit from a specific drug choice for preventing thromboembolism in NVAF (Figure 1). For example, the modest increase in myocardial infarction noted among patients randomized to dabigatran in RE‐LY remains inadequately understood, and may lead some practitioners to favor using rivaroxaban or apixaban for NVAF patients at risk for coronary events. Others may point to the mortality reduction and lower rates of bleeding, including no increase in gastrointestinal hemorrhage, among patients receiving apixaban in ARISTOTLE. Concerns about reversibility also may impact drug selection, as none of the NOACs can be easily reversed for major life‐threatening bleeding, although potential antidotes are in development and may hopefully address this concern in the near future.[25] Other considerations include patient adherence to the twice‐daily dosing regimen of dabigatran or apixaban, comorbid conditions such as bleeding risk, drug‐drug interactions, outcomes reported during postmarketing surveillance, and cost. Overall, the noninferiority of these new agents compared with warfarin, plus their superiority in reducing the risk of important clinical events like intracranial hemorrhage, has led some professional societies to recommend the NOACs over warfarin in patients with NVAF whose CHADS₂ scores are 1 or greater.[26]

Figure 1

Limitations

Several important limitations to these agents and their principal clinical trials should be noted. First, all 3 NOACs were compared with warfarin (or aspirin in the 1 prematurely halted apixaban trial), so comparisons between each drug and comparisons with placebo cannot be extrapolated from the data available. Second, the importance of remaining on label and using the NOACs appropriately for NVAF cannot be overemphasized, as recent experience with the NOACs among patients with mechanical heart valves or other clinical scenarios outside of the patient populations from the pivotal clinical trials (eg, severe renal dysfunction) will likely result in adverse patient outcomes.[27] Third, despite greater reliability in drug effects between patients and lack of need for intensive INR monitoring, more than 1 in 5 patients treated with the NOACs in these trials prematurely stopped therapy before reaching a study end point. Some of this premature discontinuation may be related to the more consistent degree of systemic anticoagulation with NOACs when compared with warfarin, thus resulting in higher bleeding rates (major, minor, or nuisance) than those reported in older trials using aspirin or placebo as the comparator. For each new antithrombotic medication, annual rates of major bleeding were higher than annual thromboembolic event rates (3.1% vs 1.1% in RE‐LY, 3.6% vs 2.1% in ROCKET‐AF, and 2.1% vs 1.3% in ARISTOTLE, respectively), although similar trends were noted for patients treated with warfarin. Nonetheless, because the average thromboembolic event may have more devastating consequences than the average bleeding event,[28] these clinical considerations must be carefully weighed for each patient when expanding the use of all 3 new drugs to the general population with NVAF. Further evaluation of the NOACs in real‐world populations, including an assessment of these drugs among patients taking dual antiplatelet therapy, is clearly warranted.

CONCLUSIONS

The recent development of alternative anticoagulation strategies to warfarin represents an exciting new opportunity for preventing the devastating consequences of stroke or systemic thromboembolism in patients with NVAF. However, despite the limitations of chronic warfarin therapy, it remains highly effective for a large proportion of patients with good INR control. Future studies will allow clinicians to better understand the advantages and disadvantages of each NOAC, so that ultimately an individualized, patient‐centered plan of care may be developed for each patient with NVAF.

Approximately 2.3 million people in the United States and 4.5 million people in Europe have atrial fibrillation (AF), with an increase in prevalence with age to 8% among patients aged 80 years and older.[1] The most feared and potentially preventable complications of AF are stroke or systemic thromboembolism, and stroke in particular is increased approximately 5‐fold in patients with nonvalvular atrial fibrillation (NVAF).[2] For over 50 years, warfarin and similar vitamin K antagonists have been the principal anticoagulants used for preventing stroke in NVAF, with consistent reductions in systemic thromboembolic events when compared with placebo or aspirin.[2, 3] However, because of its narrow therapeutic window and related management difficulties (ie, frequent monitoring of international normalized ratio [INR] levels, dietary and medication restrictions, interindividual variability in dosing), many patients with NVAF do not receive warfarin or are inadequately treated.[4]

In response to the need for antithrombotic agents with better efficacy, patient tolerance, and convenience, the US Food and Drug Administration (FDA) recently approved 3 novel oral anticoagulants (NOACs) as alternatives to warfarin for NVAF: dabigatran, rivaroxaban, and apixaban. In this review, we evaluated the pharmacologic properties and clinical studies of these NOACs, including the continued role of warfarin in many patients requiring systemic anticoagulation, to guide practicing clinicians in providing individualized, patient‐centered care to each of their patients with NVAF.

PHARMACOLOGY

CLINICAL STUDIES

Randomized trials evaluating warfarin against placebo or aspirin for NVAF have spanned more than 3 decades, encompassing a variety of study designs, patient populations, and analytic techniques.[2, 3] Despite differences between trials, these studies have provided the framework for contemporary AF management, with consistent reductions in thromboembolic events with systemic anticoagulation, most notably among patients with multiple risk factors for stroke. Current professional guidelines recommend risk assessment of patients with NVAF, using the CHADS₂ (1 point each for Congestive heart failure, Hypertension, Age 75 years, Diabetes, and 2 points for prior Stroke) or similar risk scores, to identify patients most likely to benefit from systemic anticoagulation.[1, 13] As a result of this extensive background literature, the 3 NOACs have primarily been evaluated against warfarin (instead of aspirin or placebo) as potential alternatives for reducing thromboembolic events in patients with NVAF. The 1 exception is a prematurely terminated trial of apixaban in warfarin‐ineligible patients with NVAF, in which apixaban reduced stroke or systemic embolism by 55% compared with aspirin after only 1.1 years of follow‐up, with no significant difference in major bleeding.[14]

Pivotal Clinical Trials

The 3 principal trials evaluating the NOACs against warfarin for NVAF are summarized in Table 2. In the Randomized Evaluation of Long‐term anticoagulation Therapy (RE‐LY) trial, dabigatran was compared with warfarin in 18,113 patients recruited from 951 clinical centers in 44 countries using a noninferiority study design.[15] Two different doses of dabigatran were studied, but only the 150‐mg BID dose was approved by the FDA. As a result, only the findings from the clinically approved 150‐mg dose are summarized in this review. Although RE‐LY was considered a semiblinded randomized trial, patients enrolled in the warfarin control arm underwent regular INR surveillance by their treating physicians, leaving the trial open to potential reporting biases. The authors tried to minimize bias by providing a standardized protocol for INR management, and by assigning 2 independent investigators blinded to the treatment assignments to adjudicate each event.

The Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET‐AF) study involved 14,264 patients from 1178 participating sites in 45 countries.[16] Again, a noninferiority design was used to evaluate 20‐mg daily rivaroxaban against warfarin, but the 2 arms were compared in double‐blinded, double‐dummy fashion (thus eliminating the reporting bias related to the warfarin control arm in RE‐LY). In addition, whereas RE‐LY randomized patients to fixed doses of dabigatran within their respective treatment arms, ROCKET‐AF required a lower dose of rivaroxaban (15 mg daily) for patients with moderately reduced creatinine clearance (3049 mL/min). Also of note, ROCKET‐AF reported both intention‐to‐treat and on‐treatment analyses, with outcomes listed as number of events per 100 patient‐years (instead of percent per year). To facilitate comparisons between trials, only the intention‐to‐treat data are reported in this review.

Like ROCKET‐AF, the Apixaban for Reduction in Stroke and Other Thromboembolic Events in Atrial Fibrillation (ARISTOTLE) study randomized patients using a double‐blind, double‐dummy, noninferiority design to therapy with apixaban 5 mg BID versus warfarin, ultimately enrolling 18,201 patients at 1034 clinical sites in 39 countries.[17] ARISTOTLE also provided a lower dose of apixaban (2.5 mg BID) for patients at higher risk of bleeding, defined by the authors as patients with 2 of the following characteristics: age 80 years and older, weight 60 kg, or serum creatinine 1.5 mg/dL. However, <5% of all patients in ARISTOTLE met these criteria and received the lower dose of apixaban.

Patient Populations and Study End Points

All 3 trials used relatively similar criteria for enrolling and following patients, with individual thromboembolic risk calculated using the CHADS₂ definition, where higher scores are associated with incrementally higher risk of stroke.[18] However, ROCKET‐AF required a minimum CHADS₂ score of 2 and permitted patients with lower left ventricular ejection fractions (35%), thus enrolling a higher‐risk patient population than RE‐LY and ARISTOTLE (where ejection fraction 40% was considered a risk factor for thromboembolism). As a result, more patients in ROCKET‐AF had prior stroke or systemic embolism than the other 2 trials (55% vs 20% in RE‐LY and 19% in ARISTOTLE) and more patients had significant heart failure (63%,vs 32% in RE‐LY and 36% in ARISTOTLE). These differences in enrollment ultimately translated into a higher overall risk profile in ROCKET‐AF (Table 3), which may have impacted some of the study results. In addition, patients requiring dual antiplatelet therapy (ie, clopidogrel and aspirin) were permitted in RE‐LY (5% of the final randomized population) but were excluded from the other 2 trials. The primary outcome for all 3 trials was the composite of stroke or systemic embolism, and the primary safety end point was major bleeding (RE‐LY and ARISTOTLE), or combined major and clinically relevant nonmajor bleeding events (ROCKET‐AF).

INR Control

In prior randomized trials and observational registries of patients with AF, INR control has been highly variable, and better clinical outcomes were observed among patients consistently achieving INR levels between 2 and 3.[3, 19] For all 3 randomized trials of the NOACs summarized in this review, the warfarin control arms were analyzed using the Rosendaal method of evaluating total time in therapeutic range (TTR), reflecting the percent of time the patient had an INR between 2 and 3.[20] Overall, the mean TTR was 64% to 66% in the RE‐LY and ARISTOTLE trials, but only 55% in ROCKET‐AF. This has led to considerable criticism of the ROCKET‐AF trial, given concerns for a less robust comparator arm for rivaroxaban (and thus the potential for inflated efficacy of rivaroxaban over warfarin).[21, 22] However, these TTR levels are similar to those reported in prior studies of warfarin and may better represent real‐world INR management across multiple countries.[23]

Of note, the heterogeneity of INR management also appeared to impact clinical outcomes. For example, in RE‐LY, the INR control for warfarin was particularly poor in countries from east and southeast Asia, which may explain the more robust performance of dabigatran in these regions (vs Western and Central Europe, where TTR was >64%).[24] In the same analysis of variability within the RE‐LY trial, center‐specific TTRs demonstrated higher rates of cardiovascular events and major bleeds in centers with TTR <57%.[24] A different issue was noted in ROCKET‐AF, where TTR was relatively low in the overall trial and clinical outcomes were more equivalent between rivaroxaban and warfarin, when compared with the superiority of the new drugs in RE‐LY and ARISTOTLE. However, in ROCKET‐AF centers with mean TTR >68%, rivaroxaban was associated with higher rates of stroke and systemic embolism, and in the US subgroup (where TTR was 64%), rivaroxaban had a higher bleeding rate than warfarin.[9] Taken together, these findings highlight the potential for net clinical benefit among patients and populations with poor INR control during warfarin therapy, and conversely, the loss of benefit (and even potential harm) if replacing good INR management with the newer antithrombotic drugs.

To further explore these questions regarding NOAC efficacy and safety, the FDA review of rivaroxaban included a calculation of the major bleeds incurred per embolic event prevented.[9] Using this risk‐benefit ratio, the FDA confirmed that the advantage of using rivaroxaban over warfarin in ROCKET‐AF occurred among patients with difficult INR control, whereas patients with better INR management did not experience this net clinical benefit. As a result, in the absence of carefully managed INR levels in randomized trials (where INRs are managed through an intensive protocol), careful selection of patients with poor INR control may be prudent when considering rivaroxaban or other NOACs over warfarin.

Patient‐Centered Selection of Therapy

Although none of the NOACs have been compared with each other, several important drug and trial characteristics may help identify patients most likely to benefit from a specific drug choice for preventing thromboembolism in NVAF (Figure 1). For example, the modest increase in myocardial infarction noted among patients randomized to dabigatran in RE‐LY remains inadequately understood, and may lead some practitioners to favor using rivaroxaban or apixaban for NVAF patients at risk for coronary events. Others may point to the mortality reduction and lower rates of bleeding, including no increase in gastrointestinal hemorrhage, among patients receiving apixaban in ARISTOTLE. Concerns about reversibility also may impact drug selection, as none of the NOACs can be easily reversed for major life‐threatening bleeding, although potential antidotes are in development and may hopefully address this concern in the near future.[25] Other considerations include patient adherence to the twice‐daily dosing regimen of dabigatran or apixaban, comorbid conditions such as bleeding risk, drug‐drug interactions, outcomes reported during postmarketing surveillance, and cost. Overall, the noninferiority of these new agents compared with warfarin, plus their superiority in reducing the risk of important clinical events like intracranial hemorrhage, has led some professional societies to recommend the NOACs over warfarin in patients with NVAF whose CHADS₂ scores are 1 or greater.[26]

Figure 1

Limitations

Several important limitations to these agents and their principal clinical trials should be noted. First, all 3 NOACs were compared with warfarin (or aspirin in the 1 prematurely halted apixaban trial), so comparisons between each drug and comparisons with placebo cannot be extrapolated from the data available. Second, the importance of remaining on label and using the NOACs appropriately for NVAF cannot be overemphasized, as recent experience with the NOACs among patients with mechanical heart valves or other clinical scenarios outside of the patient populations from the pivotal clinical trials (eg, severe renal dysfunction) will likely result in adverse patient outcomes.[27] Third, despite greater reliability in drug effects between patients and lack of need for intensive INR monitoring, more than 1 in 5 patients treated with the NOACs in these trials prematurely stopped therapy before reaching a study end point. Some of this premature discontinuation may be related to the more consistent degree of systemic anticoagulation with NOACs when compared with warfarin, thus resulting in higher bleeding rates (major, minor, or nuisance) than those reported in older trials using aspirin or placebo as the comparator. For each new antithrombotic medication, annual rates of major bleeding were higher than annual thromboembolic event rates (3.1% vs 1.1% in RE‐LY, 3.6% vs 2.1% in ROCKET‐AF, and 2.1% vs 1.3% in ARISTOTLE, respectively), although similar trends were noted for patients treated with warfarin. Nonetheless, because the average thromboembolic event may have more devastating consequences than the average bleeding event,[28] these clinical considerations must be carefully weighed for each patient when expanding the use of all 3 new drugs to the general population with NVAF. Further evaluation of the NOACs in real‐world populations, including an assessment of these drugs among patients taking dual antiplatelet therapy, is clearly warranted.

CONCLUSIONS

The recent development of alternative anticoagulation strategies to warfarin represents an exciting new opportunity for preventing the devastating consequences of stroke or systemic thromboembolism in patients with NVAF. However, despite the limitations of chronic warfarin therapy, it remains highly effective for a large proportion of patients with good INR control. Future studies will allow clinicians to better understand the advantages and disadvantages of each NOAC, so that ultimately an individualized, patient‐centered plan of care may be developed for each patient with NVAF.

Fanucchi et al. provide compelling evidence that geographic localization decreases pager frequency in a dose‐dependent fashion.[1] However, the study's inability to capture the burden of face‐to‐face interruptions for localized teams undermines their conclusion that reduced paging will decrease resident workload and increase physician efficiency.

Although in‐person communications are less prone to error, psychological research suggests it is the actual interruption (and not just the modality) that disrupts cognitive processes and thus impedes problem solving, decision making, patient care efficiency, and safety.[2]

One study based in a teaching hospital emergency room (an effectively completely geographically localized care setting) found that attending physicians were interrupted once every 13.8 minutes on average. Only 1.86% of intrusions were from pages; 85.7% were face‐to‐face interruptions by nurses or medical staff.[3] Anecdotal evidence after restructuring our hospital's housestaff medicine teams to a geographic model was analogous. Such frequent disruptions would contradict Fanucchi et al.'s claim that direct communication[s]lead to fewer overall interruptions,[1] and would nullify the benefit of decreased paging.

Geographic localization offers potential advantages. However, rigorous scrutiny measuring amalgamate pager and in‐person interruptions is needed to know whether these translate into tangible workflow benefits.

Fanucchi et al. provide compelling evidence that geographic localization decreases pager frequency in a dose‐dependent fashion.[1] However, the study's inability to capture the burden of face‐to‐face interruptions for localized teams undermines their conclusion that reduced paging will decrease resident workload and increase physician efficiency.

Although in‐person communications are less prone to error, psychological research suggests it is the actual interruption (and not just the modality) that disrupts cognitive processes and thus impedes problem solving, decision making, patient care efficiency, and safety.[2]

One study based in a teaching hospital emergency room (an effectively completely geographically localized care setting) found that attending physicians were interrupted once every 13.8 minutes on average. Only 1.86% of intrusions were from pages; 85.7% were face‐to‐face interruptions by nurses or medical staff.[3] Anecdotal evidence after restructuring our hospital's housestaff medicine teams to a geographic model was analogous. Such frequent disruptions would contradict Fanucchi et al.'s claim that direct communication[s]lead to fewer overall interruptions,[1] and would nullify the benefit of decreased paging.

Geographic localization offers potential advantages. However, rigorous scrutiny measuring amalgamate pager and in‐person interruptions is needed to know whether these translate into tangible workflow benefits.

Fanucchi et al. provide compelling evidence that geographic localization decreases pager frequency in a dose‐dependent fashion.[1] However, the study's inability to capture the burden of face‐to‐face interruptions for localized teams undermines their conclusion that reduced paging will decrease resident workload and increase physician efficiency.

Although in‐person communications are less prone to error, psychological research suggests it is the actual interruption (and not just the modality) that disrupts cognitive processes and thus impedes problem solving, decision making, patient care efficiency, and safety.[2]

One study based in a teaching hospital emergency room (an effectively completely geographically localized care setting) found that attending physicians were interrupted once every 13.8 minutes on average. Only 1.86% of intrusions were from pages; 85.7% were face‐to‐face interruptions by nurses or medical staff.[3] Anecdotal evidence after restructuring our hospital's housestaff medicine teams to a geographic model was analogous. Such frequent disruptions would contradict Fanucchi et al.'s claim that direct communication[s]lead to fewer overall interruptions,[1] and would nullify the benefit of decreased paging.

Geographic localization offers potential advantages. However, rigorous scrutiny measuring amalgamate pager and in‐person interruptions is needed to know whether these translate into tangible workflow benefits.

There are approximately 3 million cases of Clostridium difficile infection (CDI) per year in the United States.[1, 2, 3, 4] Of these, 10% result in a hospitalization or occur as a consequence of the exposures and treatments associated with hospitalization.[1, 2, 3, 4] Some patients with CDI experience mild diarrhea that is responsive to therapy, but other patients experience severe, life‐threatening disease that is refractory to treatment, leading to pseudomembranous colitis, toxic megacolon, and sepsis with a 60‐day mortality rate that exceeds 12%.[5, 6, 7, 8, 9, 10, 11, 12, 13, 14]

Hospital‐onset CDI (HOCDI), defined as C difficile‐associated diarrhea and related symptoms with onset more than 48 hours after admission to a healthcare facility,[15] represents a unique marriage of CDI risk factors.[5] A vulnerable patient is introduced into an environment that contains both exposure to C difficile (through other patients or healthcare workers) and treatment with antibacterial agents that may diminish normal flora. Consequently, CDI is common among hospitalized patients.[16, 17, 18] A particularly important group for understanding the burden of disease is patients who initially present to the hospital with sepsis and subsequently develop HOCDI. Sepsis patients are often critically ill and are universally treated with antibiotics.

Determining the incremental cost and mortality risk attributable to HOCDI is methodologically challenging. Because HOCDI is associated with presenting severity, the sickest patients are also the most likely to contract the disease. HOCDI is also associated with time of exposure or length of stay (LOS). Because LOS is a risk factor, comparing LOS between those with and without HOCDI will overestimate the impact if the time to diagnosis is not taken into account.[16, 17, 19, 20] We aimed to examine the impact of HOCDI in hospitalized patients with sepsis using a large, multihospital database with statistical methods that took presenting severity and time to diagnosis into account.

METHODS

RESULTS

We identified 486,943 adult sepsis admissions to a Premier hospital between July 1, 2004 and December 31, 2010. After applying all exclusion criteria, we had a final sample of 218,915 admissions with sepsis (from 400 hospitals) at risk for HOCDI (Figure 1). Of these, 2368 (1.08%) met criteria for diagnosis of CDI after hospital day 2 and were matched to controls using index date and propensity score.

Figure 1

Distribution by LOS, Index Day, and Risk for Mortality

The unadjusted and unmatched LOS was longer for cases than controls (19 days vs 8 days, Table 2) (see Supporting Figure 1 in the online version of this article). Approximately 90% of the patients had an index day of 14 or less (Figure 2). Among patients both with and without CDI, the unadjusted mortality risk increased as the index day (and thus the total LOS) increased.

Table 2.Comparison of Length of Stay, Mortality, and Costs for Propensity‐Matched Patients With and Without HOCDI

Outcome	HOCDI	No HOCDI	Difference (95% CI)	P
NOTE: Abbreviations: CI, confidence interval; HOCDI, hospital‐onset Clostridium difficile infection; RR, relative risk.
Length of stay, d
Raw results	19.2	8.3	8.4 (8.48.5)	<0.01
Raw results for survivors only	18.6	8.0	10.6 (10.311.0)	<0.01
Matched results	19.2	14.2	5.1(4.45.7)	<0.01
Matched results for survivors only	18.6	13.6	5.1 (4.45.8)	<0.01
Mortality, %
Raw results	24.0	10.1	13.9 (12.615.1), RR=2.4 (2.22.5)	<0.01
Matched results	24.0	15.4	8.6 (6.410.9), RR=1.6 (1.41.8)	<0.01
Costs, US$
Raw results median costs [interquartile range]	$26,187 [$15,117$46,273]	$9,988 [$6,296$17,351]	$16,190 ($15,826$16,555)	<0.01
Raw results for survivors only [interquartile range]	$24,038 [$14,169$41,654]	$9,429 [$6,070$15,875]	$14,620 ($14,246$14,996)	<0.01
Matched results [interquartile range]	$26,187 [$15,117$46,273]	$19,160 [$12,392$33,777]	$5,308 ($4,521$6,108)
Matched results for survivors only [interquartile range]	$24,038 [$14,169$41,654]	$17,811 [$11,614$29,298]	$4,916 ($4,088$5,768)	<0.01

Figure 2

Adjusted Results

Compared to patients without disease, HOCDI patients had an increased unadjusted mortality (24% vs 10%, P<0.001). This translates into a relative risk of 2.4 (95% confidence interval [CI]: 2.2, 2.5). In the matched cohort, the difference in the mortality rates was attenuated, but still significantly higher in the HOCDI patients (24% versus 15%, P<0.001, an absolute difference of 9%; 95% CI: 6.410.8). The adjusted relative risk of mortality for HOCDI was 1.6 (95% CI: 1.41.8; Table 2). After matching, patients with CDI had a LOS of 19.2 days versus 14.2 days in matched controls (difference of 5.1 days; 95% CI: 4.45.7; P<0.001). When the LOS analysis was limited to survivors only, this difference of 5 days remained (P<0.001). In an analysis limited to survivors only, the difference in median costs between cases and controls was $4916 (95% CI: $4088$5768; P<0.001). In a secondary analysis examining heterogeneity between HOCDI and outcomes across clinical subgroups, the absolute difference in mortality and costs between cases and controls varied across demographics, comorbidity, and ICU admission, but the relative risks were similar (Figure 3) (see Supporting Figure 3 in the online version of this article).

Figure 3

DISCUSSION

In this large cohort of patients with sepsis, we found that approximately 1 in 100 patients with sepsis developed HOCDI. Even after matching with controls based on the date of symptom onset and propensity score, patients who developed HOCDI were more than 1.6 times more likely to die in the hospital. HOCDI also added 5 days to the average hospitalization for patients with sepsis and increased median costs by approximately $5000. These findings suggest that a hospital that prevents 1 case of HOCDI per month in sepsis patients could avoid 1 death and 60 inpatient days annually, achieving an approximate yearly savings of $60,000.

Until now, the incremental cost and mortality attributable to HOCDI in sepsis patients have been poorly understood. Attributing outcomes can be methodologically challenging because patients who are at greatest risk for poor outcomes are the most likely to contract the disease and are at risk for longer periods of time. Therefore, it is necessary to take into account differences in severity of illness and time at risk between diseased and nondiseased populations and to ensure that outcomes attributed to the disease occur after disease onset.[28, 32] The majority of prior studies examining the impact of CDI on hospitalized patients have been limited by a lack of adequate matching to controls, small sample size, or failure to take into account time to infection.[16, 17, 19, 20]

A few studies have taken into account severity, time to infection, or both in estimating the impact of HOCDI. Using a time‐dependent Cox model that accounted for time to infection, Micek et al. found no difference in mortality but a longer LOS in mechanically ventilated patients (not limited to sepsis) with CDI.[33] However, their study was conducted at only 3 centers, did not take into account severity at the time of diagnosis, and did not clearly distinguish between community‐onset CDI and HOCDI. Oake et al. and Forster et al. examined the impact of CDI on patients hospitalized in a 2‐hospital health system in Canada.[12, 13] Using the baseline mortality estimate in a Cox multivariate proportional hazards regression model that accounted for the time‐varying nature of CDI, they found that HOCDI increased absolute risk of death by approximately 10%. Also, notably similar to our study were their findings that HOCDI occurred in approximately 1 in 100 patients and that the attributable median increase in LOS due to hospital‐onset CDI was 6 days. Although methodologically rigorous, these 2 small studies did not assess the impact of CDI on costs of care, were not focused on sepsis patients or even patients who received antibiotics, and also did not clearly distinguish between community‐onset CDI and HOCDI.

Our study therefore has important strengths. It is the first to examine the impact of HOCDI, including costs, on the outcomes of patients hospitalized with sepsis. The fact that we took into account both time to diagnosis and severity at the time of diagnosis (by using an index date for both cases and controls and determining severity on that date) prevented us from overestimating the impact of HOCDI on outcomes. The large differences in outcomes we observed in unadjusted and unmatched data were tempered after multivariate adjustment (eg, difference in LOS from 10.6 days to 5.1 additional days, costs from $14,620 to $4916 additional costs after adjustment). Our patient sample was derived from a large, multihospital database that contains actual hospital costs as derived from internal accounting systems. The fact that our study used data from hundreds of hospitals means that our estimates of cost, LOS, and mortality may be more generalizable than the work of Micek et al., Oake et al., and Forster et al.

This work also has important implications. First, hospital administrators, clinicians, and researchers can use our results to evaluate the cost‐effectiveness of HOCDI prevention measures (eg, hand hygiene programs, antibiotic stewardship). By quantifying the cost per case in sepsis patients, we allow administrators and researchers to compare the incremental costs of HOCDI prevention programs to the dollars and lives saved due to prevention efforts. Second, we found that our propensity model identified patients whose risk varied greatly. This suggests that an opportunity exists to identify subgroups of patients that are at highest risk. Identifying high‐risk subgroups will allow for targeted risk reduction interventions and the opportunity to reduce transmission (eg, by placing high‐risk patients in a private room). Finally, we have reaffirmed that time to diagnosis and presenting severity need to be rigorously addressed prior to making estimates of the impact of CDI burden and other hospital‐acquired conditions and injuries.

There are limitations to this study as well. We did not have access to microbiological data. However, we required a diagnosis code of CDI, evidence of testing, and treatment after the date of testing to confirm a diagnosis. We also adopted detailed exclusion criteria to ensure that CDI that was not present on admission and that controls did not have CDI. These stringent inclusion and exclusion criteria strengthened the internal validity of our estimates of disease impact. We used administrative claims data, which limited our ability to adjust for severity. However, the detailed nature of the database allowed us to use treatments, such as vasopressors and antibiotics, to identify cases; treatments were also used as a validated indicator of severity,[26] which may have helped to reduce some of this potential bias. Although our propensity model included many predictors of CDI, such as use of proton pump inhibitors and factors associated with mortality, not every confounder was completely balanced after propensity matching, although the statistical differences may have been related to our large sample size and therefore might not be clinically significant. We also may have failed to include all possible predictors of CDI in the propensity model.

In a large, diverse cohort of hospitalized patients with sepsis, we found that HOCDI lengthened hospital stay by approximately 5 days, increased risk of in‐hospital mortality by 9%, and increased hospital cost by approximately $5000 per patient. These findings highlight the importance of identifying effective prevention measures and of determining the patient populations at greatest risk for HOCDI.

Disclosures: The study was conducted with funding from the Division of Critical Care and the Center for Quality of Care Research at Baystate Medical Center. Dr. Lagu is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114745. Dr. Stefan is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114631. Drs. Lagu and Lindenauer had full access to all of the data in the study; they take responsibility for the integrity of the data and the accuracy of the data analysis. Drs. Lagu, Lindenauer, Steingrub, Higgins, Stefan, Haessler, and Rothberg conceived of the study. Dr. Lindenauer acquired the data. Drs. Lagu, Lindenauer, Rothberg, Steingrub, Nathanson, Stefan, Haessler, Higgins, and Mr. Hannon analyzed and interpreted the data. Dr. Lagu drafted the manuscript. Drs. Lagu, Lindenauer, Rothberg, Steingrub, Nathanson, Stefan, Haessler, Higgins, and Mr. Hannon critically reviewed the manuscript for important intellectual content. Dr. Nathanson carried out the statistical analyses. Dr. Nathanson, through his company OptiStatim LLC, was paid by the investigators with funding from the Department of Medicine at Baystate Medical Center to assist in conducting the statistical analyses in this study. The authors report no further conflicts of interest.

There are approximately 3 million cases of Clostridium difficile infection (CDI) per year in the United States.[1, 2, 3, 4] Of these, 10% result in a hospitalization or occur as a consequence of the exposures and treatments associated with hospitalization.[1, 2, 3, 4] Some patients with CDI experience mild diarrhea that is responsive to therapy, but other patients experience severe, life‐threatening disease that is refractory to treatment, leading to pseudomembranous colitis, toxic megacolon, and sepsis with a 60‐day mortality rate that exceeds 12%.[5, 6, 7, 8, 9, 10, 11, 12, 13, 14]

Hospital‐onset CDI (HOCDI), defined as C difficile‐associated diarrhea and related symptoms with onset more than 48 hours after admission to a healthcare facility,[15] represents a unique marriage of CDI risk factors.[5] A vulnerable patient is introduced into an environment that contains both exposure to C difficile (through other patients or healthcare workers) and treatment with antibacterial agents that may diminish normal flora. Consequently, CDI is common among hospitalized patients.[16, 17, 18] A particularly important group for understanding the burden of disease is patients who initially present to the hospital with sepsis and subsequently develop HOCDI. Sepsis patients are often critically ill and are universally treated with antibiotics.

Determining the incremental cost and mortality risk attributable to HOCDI is methodologically challenging. Because HOCDI is associated with presenting severity, the sickest patients are also the most likely to contract the disease. HOCDI is also associated with time of exposure or length of stay (LOS). Because LOS is a risk factor, comparing LOS between those with and without HOCDI will overestimate the impact if the time to diagnosis is not taken into account.[16, 17, 19, 20] We aimed to examine the impact of HOCDI in hospitalized patients with sepsis using a large, multihospital database with statistical methods that took presenting severity and time to diagnosis into account.

METHODS

RESULTS

We identified 486,943 adult sepsis admissions to a Premier hospital between July 1, 2004 and December 31, 2010. After applying all exclusion criteria, we had a final sample of 218,915 admissions with sepsis (from 400 hospitals) at risk for HOCDI (Figure 1). Of these, 2368 (1.08%) met criteria for diagnosis of CDI after hospital day 2 and were matched to controls using index date and propensity score.

Figure 1

Distribution by LOS, Index Day, and Risk for Mortality

The unadjusted and unmatched LOS was longer for cases than controls (19 days vs 8 days, Table 2) (see Supporting Figure 1 in the online version of this article). Approximately 90% of the patients had an index day of 14 or less (Figure 2). Among patients both with and without CDI, the unadjusted mortality risk increased as the index day (and thus the total LOS) increased.

Table 2.Comparison of Length of Stay, Mortality, and Costs for Propensity‐Matched Patients With and Without HOCDI

Outcome	HOCDI	No HOCDI	Difference (95% CI)	P
NOTE: Abbreviations: CI, confidence interval; HOCDI, hospital‐onset Clostridium difficile infection; RR, relative risk.
Length of stay, d
Raw results	19.2	8.3	8.4 (8.48.5)	<0.01
Raw results for survivors only	18.6	8.0	10.6 (10.311.0)	<0.01
Matched results	19.2	14.2	5.1(4.45.7)	<0.01
Matched results for survivors only	18.6	13.6	5.1 (4.45.8)	<0.01
Mortality, %
Raw results	24.0	10.1	13.9 (12.615.1), RR=2.4 (2.22.5)	<0.01
Matched results	24.0	15.4	8.6 (6.410.9), RR=1.6 (1.41.8)	<0.01
Costs, US$
Raw results median costs [interquartile range]	$26,187 [$15,117$46,273]	$9,988 [$6,296$17,351]	$16,190 ($15,826$16,555)	<0.01
Raw results for survivors only [interquartile range]	$24,038 [$14,169$41,654]	$9,429 [$6,070$15,875]	$14,620 ($14,246$14,996)	<0.01
Matched results [interquartile range]	$26,187 [$15,117$46,273]	$19,160 [$12,392$33,777]	$5,308 ($4,521$6,108)
Matched results for survivors only [interquartile range]	$24,038 [$14,169$41,654]	$17,811 [$11,614$29,298]	$4,916 ($4,088$5,768)	<0.01

Figure 2

Adjusted Results

Compared to patients without disease, HOCDI patients had an increased unadjusted mortality (24% vs 10%, P<0.001). This translates into a relative risk of 2.4 (95% confidence interval [CI]: 2.2, 2.5). In the matched cohort, the difference in the mortality rates was attenuated, but still significantly higher in the HOCDI patients (24% versus 15%, P<0.001, an absolute difference of 9%; 95% CI: 6.410.8). The adjusted relative risk of mortality for HOCDI was 1.6 (95% CI: 1.41.8; Table 2). After matching, patients with CDI had a LOS of 19.2 days versus 14.2 days in matched controls (difference of 5.1 days; 95% CI: 4.45.7; P<0.001). When the LOS analysis was limited to survivors only, this difference of 5 days remained (P<0.001). In an analysis limited to survivors only, the difference in median costs between cases and controls was $4916 (95% CI: $4088$5768; P<0.001). In a secondary analysis examining heterogeneity between HOCDI and outcomes across clinical subgroups, the absolute difference in mortality and costs between cases and controls varied across demographics, comorbidity, and ICU admission, but the relative risks were similar (Figure 3) (see Supporting Figure 3 in the online version of this article).

Figure 3

DISCUSSION

In this large cohort of patients with sepsis, we found that approximately 1 in 100 patients with sepsis developed HOCDI. Even after matching with controls based on the date of symptom onset and propensity score, patients who developed HOCDI were more than 1.6 times more likely to die in the hospital. HOCDI also added 5 days to the average hospitalization for patients with sepsis and increased median costs by approximately $5000. These findings suggest that a hospital that prevents 1 case of HOCDI per month in sepsis patients could avoid 1 death and 60 inpatient days annually, achieving an approximate yearly savings of $60,000.

Until now, the incremental cost and mortality attributable to HOCDI in sepsis patients have been poorly understood. Attributing outcomes can be methodologically challenging because patients who are at greatest risk for poor outcomes are the most likely to contract the disease and are at risk for longer periods of time. Therefore, it is necessary to take into account differences in severity of illness and time at risk between diseased and nondiseased populations and to ensure that outcomes attributed to the disease occur after disease onset.[28, 32] The majority of prior studies examining the impact of CDI on hospitalized patients have been limited by a lack of adequate matching to controls, small sample size, or failure to take into account time to infection.[16, 17, 19, 20]

A few studies have taken into account severity, time to infection, or both in estimating the impact of HOCDI. Using a time‐dependent Cox model that accounted for time to infection, Micek et al. found no difference in mortality but a longer LOS in mechanically ventilated patients (not limited to sepsis) with CDI.[33] However, their study was conducted at only 3 centers, did not take into account severity at the time of diagnosis, and did not clearly distinguish between community‐onset CDI and HOCDI. Oake et al. and Forster et al. examined the impact of CDI on patients hospitalized in a 2‐hospital health system in Canada.[12, 13] Using the baseline mortality estimate in a Cox multivariate proportional hazards regression model that accounted for the time‐varying nature of CDI, they found that HOCDI increased absolute risk of death by approximately 10%. Also, notably similar to our study were their findings that HOCDI occurred in approximately 1 in 100 patients and that the attributable median increase in LOS due to hospital‐onset CDI was 6 days. Although methodologically rigorous, these 2 small studies did not assess the impact of CDI on costs of care, were not focused on sepsis patients or even patients who received antibiotics, and also did not clearly distinguish between community‐onset CDI and HOCDI.

Our study therefore has important strengths. It is the first to examine the impact of HOCDI, including costs, on the outcomes of patients hospitalized with sepsis. The fact that we took into account both time to diagnosis and severity at the time of diagnosis (by using an index date for both cases and controls and determining severity on that date) prevented us from overestimating the impact of HOCDI on outcomes. The large differences in outcomes we observed in unadjusted and unmatched data were tempered after multivariate adjustment (eg, difference in LOS from 10.6 days to 5.1 additional days, costs from $14,620 to $4916 additional costs after adjustment). Our patient sample was derived from a large, multihospital database that contains actual hospital costs as derived from internal accounting systems. The fact that our study used data from hundreds of hospitals means that our estimates of cost, LOS, and mortality may be more generalizable than the work of Micek et al., Oake et al., and Forster et al.

This work also has important implications. First, hospital administrators, clinicians, and researchers can use our results to evaluate the cost‐effectiveness of HOCDI prevention measures (eg, hand hygiene programs, antibiotic stewardship). By quantifying the cost per case in sepsis patients, we allow administrators and researchers to compare the incremental costs of HOCDI prevention programs to the dollars and lives saved due to prevention efforts. Second, we found that our propensity model identified patients whose risk varied greatly. This suggests that an opportunity exists to identify subgroups of patients that are at highest risk. Identifying high‐risk subgroups will allow for targeted risk reduction interventions and the opportunity to reduce transmission (eg, by placing high‐risk patients in a private room). Finally, we have reaffirmed that time to diagnosis and presenting severity need to be rigorously addressed prior to making estimates of the impact of CDI burden and other hospital‐acquired conditions and injuries.

There are limitations to this study as well. We did not have access to microbiological data. However, we required a diagnosis code of CDI, evidence of testing, and treatment after the date of testing to confirm a diagnosis. We also adopted detailed exclusion criteria to ensure that CDI that was not present on admission and that controls did not have CDI. These stringent inclusion and exclusion criteria strengthened the internal validity of our estimates of disease impact. We used administrative claims data, which limited our ability to adjust for severity. However, the detailed nature of the database allowed us to use treatments, such as vasopressors and antibiotics, to identify cases; treatments were also used as a validated indicator of severity,[26] which may have helped to reduce some of this potential bias. Although our propensity model included many predictors of CDI, such as use of proton pump inhibitors and factors associated with mortality, not every confounder was completely balanced after propensity matching, although the statistical differences may have been related to our large sample size and therefore might not be clinically significant. We also may have failed to include all possible predictors of CDI in the propensity model.

In a large, diverse cohort of hospitalized patients with sepsis, we found that HOCDI lengthened hospital stay by approximately 5 days, increased risk of in‐hospital mortality by 9%, and increased hospital cost by approximately $5000 per patient. These findings highlight the importance of identifying effective prevention measures and of determining the patient populations at greatest risk for HOCDI.

Disclosures: The study was conducted with funding from the Division of Critical Care and the Center for Quality of Care Research at Baystate Medical Center. Dr. Lagu is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114745. Dr. Stefan is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114631. Drs. Lagu and Lindenauer had full access to all of the data in the study; they take responsibility for the integrity of the data and the accuracy of the data analysis. Drs. Lagu, Lindenauer, Steingrub, Higgins, Stefan, Haessler, and Rothberg conceived of the study. Dr. Lindenauer acquired the data. Drs. Lagu, Lindenauer, Rothberg, Steingrub, Nathanson, Stefan, Haessler, Higgins, and Mr. Hannon analyzed and interpreted the data. Dr. Lagu drafted the manuscript. Drs. Lagu, Lindenauer, Rothberg, Steingrub, Nathanson, Stefan, Haessler, Higgins, and Mr. Hannon critically reviewed the manuscript for important intellectual content. Dr. Nathanson carried out the statistical analyses. Dr. Nathanson, through his company OptiStatim LLC, was paid by the investigators with funding from the Department of Medicine at Baystate Medical Center to assist in conducting the statistical analyses in this study. The authors report no further conflicts of interest.

There are approximately 3 million cases of Clostridium difficile infection (CDI) per year in the United States.[1, 2, 3, 4] Of these, 10% result in a hospitalization or occur as a consequence of the exposures and treatments associated with hospitalization.[1, 2, 3, 4] Some patients with CDI experience mild diarrhea that is responsive to therapy, but other patients experience severe, life‐threatening disease that is refractory to treatment, leading to pseudomembranous colitis, toxic megacolon, and sepsis with a 60‐day mortality rate that exceeds 12%.[5, 6, 7, 8, 9, 10, 11, 12, 13, 14]

Hospital‐onset CDI (HOCDI), defined as C difficile‐associated diarrhea and related symptoms with onset more than 48 hours after admission to a healthcare facility,[15] represents a unique marriage of CDI risk factors.[5] A vulnerable patient is introduced into an environment that contains both exposure to C difficile (through other patients or healthcare workers) and treatment with antibacterial agents that may diminish normal flora. Consequently, CDI is common among hospitalized patients.[16, 17, 18] A particularly important group for understanding the burden of disease is patients who initially present to the hospital with sepsis and subsequently develop HOCDI. Sepsis patients are often critically ill and are universally treated with antibiotics.

Determining the incremental cost and mortality risk attributable to HOCDI is methodologically challenging. Because HOCDI is associated with presenting severity, the sickest patients are also the most likely to contract the disease. HOCDI is also associated with time of exposure or length of stay (LOS). Because LOS is a risk factor, comparing LOS between those with and without HOCDI will overestimate the impact if the time to diagnosis is not taken into account.[16, 17, 19, 20] We aimed to examine the impact of HOCDI in hospitalized patients with sepsis using a large, multihospital database with statistical methods that took presenting severity and time to diagnosis into account.

METHODS

RESULTS

We identified 486,943 adult sepsis admissions to a Premier hospital between July 1, 2004 and December 31, 2010. After applying all exclusion criteria, we had a final sample of 218,915 admissions with sepsis (from 400 hospitals) at risk for HOCDI (Figure 1). Of these, 2368 (1.08%) met criteria for diagnosis of CDI after hospital day 2 and were matched to controls using index date and propensity score.

Figure 1

Distribution by LOS, Index Day, and Risk for Mortality

The unadjusted and unmatched LOS was longer for cases than controls (19 days vs 8 days, Table 2) (see Supporting Figure 1 in the online version of this article). Approximately 90% of the patients had an index day of 14 or less (Figure 2). Among patients both with and without CDI, the unadjusted mortality risk increased as the index day (and thus the total LOS) increased.

Table 2.Comparison of Length of Stay, Mortality, and Costs for Propensity‐Matched Patients With and Without HOCDI

Outcome	HOCDI	No HOCDI	Difference (95% CI)	P
NOTE: Abbreviations: CI, confidence interval; HOCDI, hospital‐onset Clostridium difficile infection; RR, relative risk.
Length of stay, d
Raw results	19.2	8.3	8.4 (8.48.5)	<0.01
Raw results for survivors only	18.6	8.0	10.6 (10.311.0)	<0.01
Matched results	19.2	14.2	5.1(4.45.7)	<0.01
Matched results for survivors only	18.6	13.6	5.1 (4.45.8)	<0.01
Mortality, %
Raw results	24.0	10.1	13.9 (12.615.1), RR=2.4 (2.22.5)	<0.01
Matched results	24.0	15.4	8.6 (6.410.9), RR=1.6 (1.41.8)	<0.01
Costs, US$
Raw results median costs [interquartile range]	$26,187 [$15,117$46,273]	$9,988 [$6,296$17,351]	$16,190 ($15,826$16,555)	<0.01
Raw results for survivors only [interquartile range]	$24,038 [$14,169$41,654]	$9,429 [$6,070$15,875]	$14,620 ($14,246$14,996)	<0.01
Matched results [interquartile range]	$26,187 [$15,117$46,273]	$19,160 [$12,392$33,777]	$5,308 ($4,521$6,108)
Matched results for survivors only [interquartile range]	$24,038 [$14,169$41,654]	$17,811 [$11,614$29,298]	$4,916 ($4,088$5,768)	<0.01

Figure 2

Adjusted Results

Compared to patients without disease, HOCDI patients had an increased unadjusted mortality (24% vs 10%, P<0.001). This translates into a relative risk of 2.4 (95% confidence interval [CI]: 2.2, 2.5). In the matched cohort, the difference in the mortality rates was attenuated, but still significantly higher in the HOCDI patients (24% versus 15%, P<0.001, an absolute difference of 9%; 95% CI: 6.410.8). The adjusted relative risk of mortality for HOCDI was 1.6 (95% CI: 1.41.8; Table 2). After matching, patients with CDI had a LOS of 19.2 days versus 14.2 days in matched controls (difference of 5.1 days; 95% CI: 4.45.7; P<0.001). When the LOS analysis was limited to survivors only, this difference of 5 days remained (P<0.001). In an analysis limited to survivors only, the difference in median costs between cases and controls was $4916 (95% CI: $4088$5768; P<0.001). In a secondary analysis examining heterogeneity between HOCDI and outcomes across clinical subgroups, the absolute difference in mortality and costs between cases and controls varied across demographics, comorbidity, and ICU admission, but the relative risks were similar (Figure 3) (see Supporting Figure 3 in the online version of this article).

Figure 3

DISCUSSION

In this large cohort of patients with sepsis, we found that approximately 1 in 100 patients with sepsis developed HOCDI. Even after matching with controls based on the date of symptom onset and propensity score, patients who developed HOCDI were more than 1.6 times more likely to die in the hospital. HOCDI also added 5 days to the average hospitalization for patients with sepsis and increased median costs by approximately $5000. These findings suggest that a hospital that prevents 1 case of HOCDI per month in sepsis patients could avoid 1 death and 60 inpatient days annually, achieving an approximate yearly savings of $60,000.

Until now, the incremental cost and mortality attributable to HOCDI in sepsis patients have been poorly understood. Attributing outcomes can be methodologically challenging because patients who are at greatest risk for poor outcomes are the most likely to contract the disease and are at risk for longer periods of time. Therefore, it is necessary to take into account differences in severity of illness and time at risk between diseased and nondiseased populations and to ensure that outcomes attributed to the disease occur after disease onset.[28, 32] The majority of prior studies examining the impact of CDI on hospitalized patients have been limited by a lack of adequate matching to controls, small sample size, or failure to take into account time to infection.[16, 17, 19, 20]

A few studies have taken into account severity, time to infection, or both in estimating the impact of HOCDI. Using a time‐dependent Cox model that accounted for time to infection, Micek et al. found no difference in mortality but a longer LOS in mechanically ventilated patients (not limited to sepsis) with CDI.[33] However, their study was conducted at only 3 centers, did not take into account severity at the time of diagnosis, and did not clearly distinguish between community‐onset CDI and HOCDI. Oake et al. and Forster et al. examined the impact of CDI on patients hospitalized in a 2‐hospital health system in Canada.[12, 13] Using the baseline mortality estimate in a Cox multivariate proportional hazards regression model that accounted for the time‐varying nature of CDI, they found that HOCDI increased absolute risk of death by approximately 10%. Also, notably similar to our study were their findings that HOCDI occurred in approximately 1 in 100 patients and that the attributable median increase in LOS due to hospital‐onset CDI was 6 days. Although methodologically rigorous, these 2 small studies did not assess the impact of CDI on costs of care, were not focused on sepsis patients or even patients who received antibiotics, and also did not clearly distinguish between community‐onset CDI and HOCDI.

Our study therefore has important strengths. It is the first to examine the impact of HOCDI, including costs, on the outcomes of patients hospitalized with sepsis. The fact that we took into account both time to diagnosis and severity at the time of diagnosis (by using an index date for both cases and controls and determining severity on that date) prevented us from overestimating the impact of HOCDI on outcomes. The large differences in outcomes we observed in unadjusted and unmatched data were tempered after multivariate adjustment (eg, difference in LOS from 10.6 days to 5.1 additional days, costs from $14,620 to $4916 additional costs after adjustment). Our patient sample was derived from a large, multihospital database that contains actual hospital costs as derived from internal accounting systems. The fact that our study used data from hundreds of hospitals means that our estimates of cost, LOS, and mortality may be more generalizable than the work of Micek et al., Oake et al., and Forster et al.

This work also has important implications. First, hospital administrators, clinicians, and researchers can use our results to evaluate the cost‐effectiveness of HOCDI prevention measures (eg, hand hygiene programs, antibiotic stewardship). By quantifying the cost per case in sepsis patients, we allow administrators and researchers to compare the incremental costs of HOCDI prevention programs to the dollars and lives saved due to prevention efforts. Second, we found that our propensity model identified patients whose risk varied greatly. This suggests that an opportunity exists to identify subgroups of patients that are at highest risk. Identifying high‐risk subgroups will allow for targeted risk reduction interventions and the opportunity to reduce transmission (eg, by placing high‐risk patients in a private room). Finally, we have reaffirmed that time to diagnosis and presenting severity need to be rigorously addressed prior to making estimates of the impact of CDI burden and other hospital‐acquired conditions and injuries.

There are limitations to this study as well. We did not have access to microbiological data. However, we required a diagnosis code of CDI, evidence of testing, and treatment after the date of testing to confirm a diagnosis. We also adopted detailed exclusion criteria to ensure that CDI that was not present on admission and that controls did not have CDI. These stringent inclusion and exclusion criteria strengthened the internal validity of our estimates of disease impact. We used administrative claims data, which limited our ability to adjust for severity. However, the detailed nature of the database allowed us to use treatments, such as vasopressors and antibiotics, to identify cases; treatments were also used as a validated indicator of severity,[26] which may have helped to reduce some of this potential bias. Although our propensity model included many predictors of CDI, such as use of proton pump inhibitors and factors associated with mortality, not every confounder was completely balanced after propensity matching, although the statistical differences may have been related to our large sample size and therefore might not be clinically significant. We also may have failed to include all possible predictors of CDI in the propensity model.

In a large, diverse cohort of hospitalized patients with sepsis, we found that HOCDI lengthened hospital stay by approximately 5 days, increased risk of in‐hospital mortality by 9%, and increased hospital cost by approximately $5000 per patient. These findings highlight the importance of identifying effective prevention measures and of determining the patient populations at greatest risk for HOCDI.

Disclosures: The study was conducted with funding from the Division of Critical Care and the Center for Quality of Care Research at Baystate Medical Center. Dr. Lagu is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114745. Dr. Stefan is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114631. Drs. Lagu and Lindenauer had full access to all of the data in the study; they take responsibility for the integrity of the data and the accuracy of the data analysis. Drs. Lagu, Lindenauer, Steingrub, Higgins, Stefan, Haessler, and Rothberg conceived of the study. Dr. Lindenauer acquired the data. Drs. Lagu, Lindenauer, Rothberg, Steingrub, Nathanson, Stefan, Haessler, Higgins, and Mr. Hannon analyzed and interpreted the data. Dr. Lagu drafted the manuscript. Drs. Lagu, Lindenauer, Rothberg, Steingrub, Nathanson, Stefan, Haessler, Higgins, and Mr. Hannon critically reviewed the manuscript for important intellectual content. Dr. Nathanson carried out the statistical analyses. Dr. Nathanson, through his company OptiStatim LLC, was paid by the investigators with funding from the Department of Medicine at Baystate Medical Center to assist in conducting the statistical analyses in this study. The authors report no further conflicts of interest.