Development and validation of a clinical prediction rule for major adverse outcomes in coronary bypass grafting

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Abstract

In this study, we develop and internally validate a clinical prediction rule for in-hospital major adverse outcomes, defined as death, renal failure, reinfarction, cardiac arrest, cerebrovascular accident, or coma, in patients who underwent coronary artery bypass grafting (CABG). All adult patients (n = 9,498) who underwent a CABG and no other concomitant surgery at 12 academic medical centers from August 1993 to October 1995 were included in the study. We assessed in-hospital major adverse outcomes and their predictors using information on admission, coronary angiography, and postoperative hospital course. Predictor variables were limited to information available before the procedure, and outcome variables were represented only by events that occurred postoperatively. We developed and internally validated a clinical prediction rule for any major adverse outcome after CABG. The rule’s ability to discriminate outcomes and its calibration were assessed using receiver-operating characteristic analysis and the Hosmer-Lemeshow goodness-of-fit statistic, respectively. A major adverse outcome occurred in 6.5% of patients in the derivation set and 7.2% in the validation set. Death occurred in 2.5% of patients in the derivation set and 2.2% in the validation set. Sixteen variables were independently correlated with major adverse outcomes, with the risk score value attributed to each risk factor ranging from 2 to 12 points. The rule stratified patients into 6 levels of risk based on the total risk score. The spread in probability between the lowest and highest risk groups of having a major adverse outcome was 1.7% to 32.3% in the derivation set and 2.2% to 22.3% in the validation set. The prediction model performed well in both outcome discrimination and calibration. Thus, this clinical prediction rule allows accurate stratification of potential CABG candidates before surgery according to the risk of experiencing a major adverse outcome postoperatively.

Section snippets

Patient population:

Data collection took place at 12 medical centers. All 12 were large tertiary care centers and were members of the Academic Medical Center Consortium, which sponsored the study called the Quality Measurement and Management Initiative (QMMI) Coronary Revascularization Project. Patient enrollment took place from August 1993 to October 1995. Patients enrolled in the study included all patients who underwent a CABG procedure not involving valvular or other surgeries at any of the 12 participating

Results

The QMMI dataset included 9,498 patients who underwent CABG not involving valvular or other concomitant procedures, with 6,237 patients allocated at random to the derivation set and the remaining 3,261 to the validation set (Table 1). Differences in preoperative patient characteristics were not significant across groups. One or more major adverse outcomes were found to occur in 6.5% of patients in the derivation subset. A total of 408 patients had a major adverse event. Of these, there were 157

Discussion

In this study, we developed and internally validated a clinical prediction rule that estimated the risk of major adverse outcomes after CABG surgery in a large cohort of patients from 12 large, geographically dispersed academic medical centers. Given the increasing availability of information on patient outcomes from different clinical settings, a severity model such as this has the potential to fill certain important roles, such as facilitating more accurate comparisons of outcomes across

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    A list of the members of the Academic Medical Center Consortium Quality Measurement and Management Initiative Working Group appears in the Appendix.

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