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The Long-Term Impact of Early Cardiovascular Therapy Intensification for Postoperative Troponin Elevation After Major Vascular Surgery

Foucrier, Arnaud MD*†; Rodseth, Reitze MD‡§; Aissaoui, Mohamed MD*†; Ibanes, Cristina MD*†; Goarin, Jean-Pierre MD*†; Landais, Paul MD, PhD; Coriat, Pierre MD*†; Le Manach, Yannick MD, PhD

doi: 10.1213/ANE.0000000000000302
Cardiovascular Anesthesiology: Research Report

BACKGROUND: Acute cardiac events are a frequent cause of morbidity after vascular surgery. The impact of early evidence-based treatment for patients with an acute cardiac event after vascular surgery on long-term postoperative outcomes has not been extensively studied. We hypothesized that providing appropriate evidence-based treatment to patients with elevated postoperative cardiac troponin levels may limit long-term mortality.

METHODS: We conducted a study of 667 consecutive major vascular surgery patients with an elevated postoperative troponin I level. We then determined which of these patients received medical therapy as per the 2007 American College of Cardiology/American Heart Association recommendations for the medical management of patients with chronic stable angina. All patients with troponin elevation were then matched with 2 control patients without postoperative troponin elevation. Matching was done using logistic regression and nearest-neighbor matching methods. The primary study end point was 12 months survival without a major cardiac event (i.e., death, myocardial infarction, coronary revascularization, or pulmonary edema requiring hospitalization).

RESULTS: Therapy was intensified in 43 of 66 patients (65%) who suffered a troponin I elevation after surgery. Patients with a troponin I elevation not receiving intensified cardiovascular treatment had a hazard ratio (HR) of 1.77 (95% confidence interval (CI), 1.13–2.42; P = 0.004) for the primary study outcome as compared with the control group. In contrast, patients with a troponin I elevation who received intensified cardiovascular treatment had an HR of 0.63 (95% CI, 0.10–1.19; P = 0.45) for the primary outcome as compared with the control group. Patients with a troponin I elevation not receiving treatment intensification likely were at higher risk for a major cardiac event (HR, 2.80; 95% CI, 1.05–24.2; P = 0.04) compared with patients who did receive treatment intensification.

CONCLUSIONS: The main finding of this study was that in patients with elevated troponin I levels after noncardiac surgery, long-term adverse cardiac outcomes may likely be improved by following evidence-based recommendations for the medical management of acute coronary syndromes.

Published ahead of print June 17, 2014.

From the *Department of Anesthesiology and Critical Care, University Pierre et Marie-Curie-Paris 6, Assistance Publique-Hôpitaux de Paris, Paris, France; Hospital Pitié-Salpétrière, Paris, France; Department of Anaesthesia, Perioperative Research Group, University of KwaZulu-Natal, Pietermarizburg, South Africa; §The Perioperative Research Group, Population Health Research Institute, Hamilton, Ontario, Canada; Biostatistical and Clinical Epidemiology Department, Faculty of Medicine, Nimes University Hospital, Montpellier 1 University, Montpellier, France; and Departments of Anesthesia & Clinical Epidemiology and Biostatistics, Michael DeGroote School of Medicine, Faculty of Health Sciences, McMaster University and Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Perioperative Medicine and Surgical Research Unit, Hamilton, Ontario, Canada.

Published ahead of print June 17, 2014.

Arnaud Foucrier, MD, is currently affiliated with Department of Anesthesiology and Critical Care, AP-HP Beaujon Hospital, Clichy, France.

Accepted for publication April 11, 2014.

Funding: Not funded.

The authors declare no conflicts of interest.

Reprints will not be available from the authors.

Address correspondence to Arnaud Foucrier, MD, Department of Anesthesiology and Critical Care, AP-HP Beaujon Hospital, Clichy, France. Address e-mail to arnaud.foucrier@bjn.aphp.fr.

Perioperative myocardial infarction (MI) after noncardiac surgery occurs commonly and as many as 1 in 10 of those who suffer a perioperative MI die within 30 days after surgery.1 This increased mortality risk is also evident in patients with isolated postoperative troponin elevations (i.e., a postoperative troponin elevation without electrocardiogram (ECG) changes suggesting MI)2–4 and is associated with a frequent incidence of short- and long-term adverse events, and prolonged hospitalization and increased costs.5,6 The role of secondary prevention in patients suffering nonoperative MI has been well established, with guidelines advocating the aggressive use of medical therapy such as HMG-CoA reductase inhibitors (i.e., “statins”), antiplatelet drugs, β-adrenergic receptor blockers, and angiotensin-converting enzyme (ACE) inhibitors.7,8 However, perioperative patient management has largely focused on MI prevention,9–11 and few studies have attempted to determine the impact on patient outcome of using these secondary preventative therapies in patients with perioperative MI or isolated troponin elevation. A single retrospective study demonstrated that patients receiving combination therapy (i.e., ACE inhibitors, aspirin, β-blockers, statins) after vascular surgery had a lower 6-month mortality risk.12 However, that study did not evaluate the impact on patients who suffered perioperative MI or isolated troponin elevation.

In this study of vascular surgery patients who suffered perioperative MI or isolated troponin elevation, we sought to determine the effect of early treatment with evidence-based medical therapy on short- and long-term major cardiac events. We hypothesized that providing appropriate secondary preventative treatment to patients with elevated postoperative cardiac troponin levels may limit long-term mortality.

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METHODS

This observational study was performed in accordance with published guidelines for observational studies (Strengthening the Reporting of Observational Studies in Epidemiology [STROBE]),13 with adaptations described below.

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Study Design

We performed a retrospective, case-controlled study among all patients aged >18 years who underwent major vascular surgery between January 1, 2005, and July 15, 2008, in the Pitié-Salpêtrière Hospital, Paris, France, using the computerized Vascular Surgery Register. This system contains demographic and perioperative data for all patients admitted for vascular surgery since 1984.5,14,15 The registry was established in 1984, and routine postoperative troponin surveillance was instituted in 1995. Our hospital switched from troponin I to high sensitivity troponin I in August 2008. As a result, we chose to conduct the current study by including patients undergoing surgery from January 1, 2005, to July 15, 2008.

Patients were considered eligible if they underwent elective infrarenal aortic reconstructive surgery (i.e., for aneurysm or occlusive disease of the aorta) during the study period. Patients undergoing emergency surgery or endoprosthetic procedures were not included. The study was approved by our institutional ethics committee (Comité de Protection des Personnes d’Ile-de-France VI, Groupe Hospitalier Pitié-Salpêtrière, Paris, France), and the requirement for written consent for this analysis was waived. To ensure full disclosure to our patients, we informed them that their data would be used for the purpose of this specific study and obtained their verbal consent before including them in the study.

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Perioperative Management

All patients in this study underwent elective surgery and so were all investigated and managed according to standardized hospital protocols based on the recommendations of the American College of Cardiology/American Heart Association Task Force.16,17 Surgery was performed under general anesthesia, with IV propofol, sufentanil, and atracurium. As previously described, patients presenting with postoperative hypertension >30% of baseline received nicardipine or clonidine, and those with tachycardia >80 bpm received an IV β blocker.15 All patients received subcutaneous low molecular weight heparin until postoperative day 30. No uniform postoperative regimen for the treatment of perioperative MI or an isolated troponin elevation was prescribed, and the provision of all medications, including medical therapy of the treatment of coronary artery disease, was at the discretion of the attending physician.

Blood was obtained for measurement of cardiac troponin I (cTnI) in all patients on arrival at the postanesthetic care unit, on the first, second, and third postoperative days. This measurement was performed using an immunoenzymofluorometric assay on a Stratus autoanalyzer (Dade-Behring, Paris La Défense, France). An ECG was performed on arrival at the postanesthetic care unit, and on the first, second, and third postoperative days, and after the third day in the presence of clinical abnormalities and/or if the cTnI concentration was increased.

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Definition of Variables and End Points

We defined an elevated troponin as an abnormal cTnI concentration at any time during the postoperative period.18 The cutoff used defined normality was 0.15 ng/mL. This value corresponds to the 99th percentile for our laboratory during each study period.19 The lower detection limit for cTnI assay was 0.03 ng/mL, and the interassay coefficient of variation was 8% at 1.5 ng/mL and 15% at 0.6 ng/mL.

Postoperative MI was defined as an elevated cTnI concentration associated with one of the following: symptoms of ischemia and/or ECG changes indicative of new ischemia (new ST–T changes or new left bundle branch block), development of pathological Q waves on the ECG, and/or imaging evidence of new loss of viable myocardium or new regional wall motion abnormality.20

The primary end point of the study was survival to 1 year after surgery, without experiencing a major cardiac event (i.e., MI, myocardial revascularization, or pulmonary edema requiring hospitalization).

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Selection of Cases and Controls

Case subjects were patients with perioperative MI or an isolated troponin I elevation (hereafter referred to as a perioperative MI). From the remaining patients without perioperative MI, we selected 2 controls for each case. We used the following variables to match patients: the Revised Cardiac Risk Index,21 age, sex, date, type of surgery (aneurysm or occlusive disease of the aorta), and presence of intraoperative complications. These variables were identified as independent predictors of adverse cardiac outcomes in a previous analysis of vascular patients from our hospital.15

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Outcome and Postoperative Cardiovascular Treatment Analyses

Preoperative cardiovascular treatments and treatments at the time of hospital discharge were noted. Drug classes studied were antiplatelet drugs, statins, β-blockers, and ACE inhibitors. Each patient was subsequently interviewed by telephone at least 12 months after surgery to obtain information about the primary end point. The need for hospitalization for cardiac reasons after surgery was also determined. When patients indicated that an event had occurred, we contacted the patient’s primary physician and obtained patient records to verify the diagnosis. When patients were hospitalized, medical records were checked to determine whether hospitalization was as a result of a cardiac complication.

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Secondary Preventative Therapy Adjudication

Three cardiologists, each with a minimum of 10 years experience independently reviewed each patient’s history to determine: (1) whether additional postoperative therapy had been instituted as compared with the preoperative period; and (2) whether therapy at the end of the 1-year follow-up period was different from therapy at the time of hospital discharge.

Predefined rules were used to make this assessment. Additional cardiovascular therapy was defined as the new introduction of one of the 4 main cardiovascular drugs (antiplatelet, β-blockers, statins, or ACE inhibitors) during the postoperative period or a dose increase in those patients already taking such medication. Optimal cardiovascular treatment was defined as a patient receiving a drug from all 4 classes (i.e., antiplatelet, β-blocker, ACE inhibitor, and a statin) in compliance with the 2007 American College of Cardiology/American Heart Association recommendations for the medical management of patients with chronic stable angina.22 The committee members reviewed the cases independently, were blinded for the outcome of the evaluated patients, and were not directly involved in any aspect of patient care.

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Statistical Analysis

Summary statistics were constructed using frequencies and proportions for categorical data and means, medians, and interquartile ranges for continuous variables. We compared the baseline characteristics of patients with perioperative MI with those patients who did not suffer a perioperative MI. χ2 and z tests were used to assess the relationship between a perioperative MI and any potential confounders.

The reliability of agreement among the 3 blinded experts was assessed using Fleiss κ test. The bootstrapped 95% confidence interval (CI) of the Fleiss κ was calculated, and the lower limit of the 95% CI is reported. It is assumed that a κ value between 0.61 and 0.80 denotes agreement, whereas a value higher than 0.81 relates to near substantial agreement. To evaluate the potential impact of allocation errors in this study, we reported any incomplete agreement among experts as allocation error, and we conducted simulations (Appendix) to evaluate their impact on the estimation of the treatment effect.

To select controls for patients with a perioperative MI, we first developed a propensity score to determine the estimated probability of suffering a perioperative MI based on preoperative and intraoperative predictors. We did this by creating a semiparsimonious logistic regression model to derive the probability of presenting with a perioperative MI. This model included 2 classes of predictors.23 The first class of predictors reflects the preoperative state of each patient (history of coronary artery disease, preoperative renal failure, diabetes, etc.) and can be summarized by the Revised Cardiac Risk Index. For the second set of predictors, we used intraoperative variables that have been demonstrated to predict a perioperative MI, that is, the number of packed red blood cells transfused and the need for surgical reintervention, of any type, in the first 3 postoperative hours.5,15 Model discrimination was assessed by calculating the area under the receiver operating characteristic curve (c-index), and its calibration was assessed using the Hosmer-Lemeshow statistic (P > 0.05 for no significant difference between the predictive model and the observed data). We performed cross validation, using a leave-one-out cross-validation method, to test the internal validity of the model and determined the prediction error of the model.

We then used a nearest neighbor matching technique to create case-control pairs. Nearest neighbor matching selects a patient with a perioperative MI (case) and then finds a patient among those without a perioperative MI (control) who has the closest propensity score to that of the case. For each case, we identified 2 controls. The goal of matching is to ensure that case and control groups resemble each other in everything but the presence of a perioperative MI. In well-matched groups, the distribution of the covariates of all variables will be similar, and such groups are referred to as “balanced.” We evaluated the success of matching by comparing the standardized differences of all variables, including those not included in the matching procedure. The standardized difference is a percentage that is calculated by dividing the difference in the mean of a variable between the groups by the standard deviation (SD) of the variable. An absolute standardized difference above 10% to 15% is considered a meaningful imbalance.

The final step of the analysis was to estimate the effect additional cardiovascular treatment had on the study outcome. We created a survival curve (survivors without major cardiac events) for the 3 groups of patients (perioperative MI, perioperative MI with intensification, and control). To consider the matched nature of the population, we used a Cox proportional hazard model stratified on the matched pairs. Hazard ratios (HRs) were presented after bootstrap estimates. We have evaluated the robustness of our results with specific additional statistical analyses (Appendix). R 2.14 software (R Foundation for Statistical Computing, Vienna, Austria) was used for statistical analyses.24

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RESULTS

Of the 667 patients screened, 20 (3%) were excluded due to missing data. Sixty-six (10%) of the 647 remaining patients suffered a perioperative MI. The study flowchart is shown in Figure 1, and the main clinical characteristics of the perioperative MI group are compared with the other patients in the study population in Table 1. Patients were followed for a mean of 14 months (range, 6–31 months). In the 66 patients who suffered a perioperative MI, 39 (59%) patients survived to follow-up without suffering a major adverse cardiac event.

Table 1

Table 1

Figure 1

Figure 1

The expert committee determined that 43 (65%) of the patients with a perioperative MI received additional cardiovascular medication during their hospitalization (κ = 0.90, lower 95% CI limit 0.79, incomplete agreement observed in 4 patients) and that of these 43 patients, 38 (88%) patients had received optimal cardiovascular treatment (i.e., a drug from all 4 classes) (κ = 0.81, lower 95% CI limit 0.46, incomplete agreement observed in 3 patients). Fifty-one (77%) patients with a perioperative MI had no modification to their cardiovascular treatment at the end of the follow-up (Fleiss κ = 0.90, lower 95% CI limit 0.74, incomplete agreement observed in 4 patients).

The logistic model used for matching cases with controls included age, sex, Revised Cardiac Risk Index, coronary artery disease, history of MI and/or heart failure, the type of aortic disease (aneurysm or occlusive disease of the aorta), the need for surgical reintervention, of any type, in the first 3 postoperative hours, and transfusion of >3 units of packed red blood cells. The c-index associated with this model was 0.73, and the Hosmer-Lemeshow test was P = 0.80 (4.62, degrees of freedom = 8). Furthermore, a cross-validation estimate of prediction error of 12.2% was retrieved after 10-fold cross validation (12.3% with the leave-one-out cross-validation method). This suggests that the model used to match the patients was robust, well-calibrated, and had a relatively good discriminative ability to predict a perioperative MI. After matching, the absolute standardized differences showed no severe imbalance between the characteristics of patients with a perioperative MI and those of the control group (Table 2).

Table 2

Table 2

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Comparison Between Postoperative and Preoperative Periods

Figure 2 shows the type of medication that patients in the therapy intensification group were taking preoperatively and then at the time of hospital discharge. Statins, β-blockers, and antiplatelet drugs were prescribed significantly more frequently in the postoperative period than in the preoperative period (93% vs 51%; 77 vs 33%; and 93 vs 21%; P < 0.001, P < 0.001 and P = 0.05, respectively). Figure 3 shows the use of the 4 drug classes before surgery and after intensification of therapy. At least 77% of patients were treated with at least 3 drug groups vs 35% during the preoperative period. Seventy percent of patients were treated by a combination of antiplatelets, β-blockers, ACE inhibitors, and statins.

Figure 2

Figure 2

Figure 3

Figure 3

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Survival Analysis

The first analysis evaluated the survival difference among 3 groups: (1) patients without perioperative MI, (2) patients with perioperative MI without treatment intensification, and (3) patients with perioperative MI with treatment intensification. Patients with a perioperative MI and no modification of their cardiovascular treatment had a HR of 1.77 (95% CI, 1.13–2.42; P = 0.004) for the primary study outcome as compared with the control group. In contrast, patients with a perioperative MI who received intensified postoperative cardiovascular treatment had a HR of 0.63 (95% CI, 0.10–1.19; P = 0.45) for the primary outcome as compared with the control group (Fig. 4); When conducting the simulation analysis for this first survival analysis, we found that even when introducing 4 allocation errors, 95% of the simulated results still remained statistically significant (i.e., P ≤ 0.05) (Appendix).

Figure 4

Figure 4

The second survival analysis compared 2 groups: (1) patients with perioperative MI receiving postoperative treatment intensification, and (2) patients with perioperative MI not receiving treatment intensification. Patients with a perioperative MI who did not receive treatment intensification had a HR of 2.80 (95% CI, 1.05–24.2; P = 0.04) compared with patients with a perioperative MI who did receive treatment intensification. The simulation analysis conducted in this smaller population found that the introduction of allocation errors had a greater impact on the robustness of our results (Appendix). The introduction of 3 allocation errors resulted in nonsignificant (i.e., P > 0.05) results in >35% of the cases.

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DISCUSSION

The main finding of this study was that a long-term increase in adverse cardiovascular events (HR: 2.80; 95% CI, 1.05–24.2; P = 0.04) was observed in patients with perioperative cTnI elevation when they did not receive evidence-based medical therapy for the treatment of coronary artery disease. Furthermore, using Monte Carlo simulations, we demonstrated that this result was not dramatically affected by potential allocation errors related to the expert committee’s disagreements (i.e., even when introducing 4 allocation errors, 54% of the simulated results still remained statistically significant). Our results further provide a rationale for a postoperative strategy of screening patients undergoing vascular surgery for elevations in cTnI after surgery and intensifying therapy using evidence-based medical treatments for coronary artery disease in patients demonstrating myocardial injury as a means for improving patient survival.

With the introduction of sensitive, cardiac-specific biomarkers such as cTnI, the ability to identify patients with perioperative MIs even in the absence of ECG changes or symptoms of myocardial ischemia has been greatly enhanced. Indeed, even small increases in perioperative cTnI concentrations have been found to be associated with poorer short-term25 and long-term outcomes.6 This correlation between perioperative cTnI concentration and the incidence of cardiac complications in the months after noncardiac surgery confirms the specificity of this biological marker as an indicator of myocardial injury. It is important to note that as was the case in this study, troponin elevations occur in most patients in the absence of anginal symptoms or ECG changes and, therefore, often go undetected by caregivers. Perioperative cTnI surveillance, thus, may not only enable early detection of patients at risk for short- and long-term morbidity and mortality, but they may also allow for the early initiation of appropriate therapeutic interventions.

Patients who suffer an acute coronary event are at very high risk of further coronary events. Although improvements in medical therapy over the past 2 decades have reduced this risk significantly, it still remains high. In the medical setting, recent developments in secondary prevention have been suggested,26 based on the findings of large, randomized trials. The routine use of 4 main prophylactic drug groups (antiplatelet drugs, β-blockers, ACE inhibitors, and statins) is now recommended by international guidelines for the secondary prevention of coronary artery disease.27,28 Most postoperative patients suffer non-ST segment elevation MI29, and it is likely that the use of these therapies in patients with isolated cTnI elevation30 may improve patient outcomes.31 It must, however, be appreciated that guidelines developed in nonoperative populations cannot necessarily be extrapolated to operative populations. The hemodynamic impact of instituting aggressive ACE or β-blocker therapy is unclear, and the bleeding risk associated with aggressive antiplatelet therapy remains to be investigated.

Our study has several limitations. First, this was a single-center, retrospective study, involving only 1 type of surgery (major vascular surgery), and therefore, we cannot generalize our results to all noncardiac surgeries. Second, elevation of cTnI plasma concentration was the single criterion for patient selection, and although troponin I offers high tissue specificity, it does not indicate the mechanism of myocardial injury.32–34 We did not discern the etiology of the elevation of cTnI (coronary or otherwise) but treated it as a coronary injury using cardioprotective drugs. Third, there was a limited number of patients in this study that may further confound its interpretation for other groups of patients. As is the case in all survival analyses using a primary end point other than mortality, the possibility of competing risks cannot be excluded. Fourth, it is possible that, due to the small number of patients in the study, variation in how patients were allocated to treatment groups by the expert committee may impact the validity of the study finding. However, for both κ estimates, the lower bound of the 95% CI was well above 0.61, the threshold denoting substantial agreement. Finally, due to the small sample size, we were unable to obtain complete balance of the preoperative risk factors among the groups despite propensity matching.

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CONCLUSIONS

The main finding of this study was that in patients with a perioperative MI, long-term outcomes may likely be improved by following evidence-based recommendations for the medical management of acute coronary syndromes.

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APPENDIX

In our methodology, an expert committee evaluated whether, in their opinion, patients received postoperative intensification of cardiovascular treatment. Errors in the accuracy of this evaluation process would impact on the estimation of our treatment effect. We therefore conducted a simulation analysis to explore the impact of such errors on our results.

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SIMULATION METHODS

We generated simulated populations using the original study population. Patients from the original population and their treatment allocations were changed to simulate allocation errors. When a randomly selected patient was “treated” in the original population, we considered him as “not treated” for the simulation. Conversely, when he was “not treated,” we changed his allocation to “treated.” We allowed the number of allocation errors (i.e., the number of patients who had their allocation changed) to vary from 1 to 4, and we conducted 10,000 replications for each scenario (i.e., 1 to 4 allocation changes). This procedure therefore generated 40,000 simulation populations.

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Impact of Allocation Errors on the Survival Analyses

The first survival analysis included 198 patients and compared 3 groups: (1) patients without postoperative myocardial necrosis, (2) patients with postoperative myocardial necrosis without treatment intensification, and (3) patients with postoperative myocardial necrosis with treatment intensification. The results observed in the original population showed a HR of 1.77 (95% CI, 1.13–2.42; P = 0.004). When conducting the simulation analysis for this outcome (Appendix Figure 1), we found that even when introducing 4 allocation errors, 95% of the simulated results still remained statistically significant (i.e., P ≤ 0.05). We therefore concluded that this analysis was unlikely to have been impacted by allocation errors made by the expert committee.

Appendix Fi

Appendix Fi

Although expert disagreements and allocation errors are not interchangeable, we considered that allocation errors are more likely to happen when incomplete agreement occurred. Pushing this argument to the extreme, we considered that any incomplete agreement (i.e., 1 expert disagreed with the 2 others regarding 1 patient's treatment) was an allocation error. As such, incomplete agreement was observed in 4 cases for this analysis; we concluded that these potential allocation errors had a limited impact on the estimation of the treatment effect in this analysis.

In a second simulation, we evaluate the survival analysis comparing patients with postoperative myocardial necrosis, with or without postoperative cardiovascular treatment intensification (2 groups, 66 patients). In the original population we found that long-term adverse cardiovascular events were more frequent (HR: 2.80; 95% CI, 1.05–24.2; P = 0.04) in patients without postoperative cardiovascular treatment intensification.

In this smaller population, the introduction of allocation errors had a greater impact on the robustness of our results (Appendix Figure 2). The introduction of 1 allocation error resulted in nonsignificant study results (i.e., P > 0.05) in 11.23% of cases, 3 allocation errors resulted in nonsignificant study results in 35% of cases, and 4 allocation errors resulted in nonsignificant study results in 45.41% of cases.

Appendix Fi

Appendix Fi

In this analysis, incomplete agreement was observed in 3 patients. Assuming that they all correspond to allocation errors, the observed treatment effect would remain significant in >65% of the cases (Appendix Figure 2). We therefore concluded that, while the results of this analysis were more sensitive to allocation errors, the robustness of the results warrant serious consideration.

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DISCLOSURES

Name: Arnaud Foucrier, MD.

Contribution: This author helped design and conduct the study, analyze the data, and write the manuscript.

Attestation: Arnaud Foucrier has seen the original study data, reviewed the analysis of the data, approved the final manuscript, and is the author responsible for archiving the study files.

Name: Reitze Rodseth, MD.

Contribution: This author helped design the study, analyze the data, and write the manuscript.

Attestation: Reitze Rodesth has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.

Name: Mohamed Aissaoui, MD.

Contribution: This author helped designand conduct the study and analyze the data.

Attestation: Mohamed Aissaoui has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.

Name: Cristina Ibanes, MD.

Contribution: This author helped design and conduct the study and analyze the data.

Attestation: Cristina Ibanes has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.

Name: Jean-Pierre Goarin, MD.

Contribution: This author helped write the manuscript.

Attestation: Jean-Pierre Goarin has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.

Name: Paul Landais, MD, PhD.

Contribution: This author helped design the study and analyze the data.

Attestation: Paul Landais has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.

Name: Pierre Coriat, MD.

Contribution: This author helped design the study and write the manuscript.

Attestation: Pierre Coriat has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.

Name: Yannick Le Manach, MD, PhD.

Contribution: This author helped design and conduct the study, analyze the data, and write the manuscript.

Attestation: Yannick Le Manach has seen the original study data, reviewed the analysis of the data, approved the final manuscript, and is the author responsible for archiving the study files.

This manuscript was handled by: Charles W. Hogue, Jr, MD.

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