Predicting the risk of death following coronary artery bypass graft made simple: a retrospective study using the American College of Surgeons National Surgical Quality Improvement Program database.

Paul J Chung,Gainosuke Sugiyama,Joshua H Burack,Sophia Tam,Timothy I Carter,Antonio Alfonso

doi:10.1186/s13019-015-0269-y

Abstract

IntroductionRisk models to predict 30-day mortality following isolated coronary artery bypass graft is an active area of research. Simple risk predictors are particularly important for cardiothoracic surgeons who are coming under increased scrutiny since these physicians typically care for higher risk patients and thus expect worse outcomes. The objective of this study was to develop a 30-day postoperative mortality risk model for patients undergoing CABG using the American College of Surgeons National Surgical Quality Improvement Program database.Material and methodsData was extracted and analyzed from the American College of Surgeons National Surgical Quality Improvement Program Participant Use Files (2005–2010). Patients that had ischemic heart disease (ICD9 410–414) undergoing one to four vessel CABG (CPT 33533–33536) were selected. To select for acquired heart disease, only patients age 40 and older were included. Multivariate logistic regression analysis was used to create a risk model. The C-statistic and the Hosmer-Lemeshow goodness-of-fit test were used to evaluate the model. Bootstrap-validated C-statistic was calculated.ResultsA total of 2254 cases met selection criteria. Forty-nine patients (2.2%) died within 30 days. Six independent risk factors predictive of short-term mortality were identified including age, preoperative sodium, preoperative blood urea nitrogen, previous percutaneous coronary intervention, dyspnea at rest, and history of prior myocardial infarction. The C-statistic for this model was 0.773 while the bootstrap-validated C-statistic was 0.750. The Hosmer-Lemeshow test had a p-value of 0.675, suggesting the model does not overfit the data.ConclusionsThe American College of Surgeons National Surgical Quality Improvement Program risk model has good discrimination for 30-day mortality following coronary artery bypass graft surgery. The model employs six independent variables, making it easy to use in the clinical setting.

Highlights

Risk models to predict 30-day mortality following isolated coronary artery bypass graft is an active area of research
From 2005–2010, a total of 2254 cases fitting the inclusion criteria were found from a total of 4317 coronary artery bypass graft (CABG) recorded during that time period
Previous percutaneous coronary intervention (PCI) was found to be marginally significant with p = 0.0648, it was kept because the C-statistic of the final model decreased from 0.773 to 0.762, suggesting its importance

Summary

Introduction

Risk models to predict 30-day mortality following isolated coronary artery bypass graft is an active area of research. The objective of this study was to develop a 30-day postoperative mortality risk model for patients undergoing CABG using the American College of Surgeons National Surgical Quality Improvement Program database. Developing risk models to predict 30-day postoperative mortality following isolated coronary artery bypass graft (CABG) has been an active area of research [1,2,3]. No such risk model has been developed using the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) database. Male Female Height, m, mean (SD) Weight, kg, mean (SD) BMI, mean (SD) Emergency ASA Classification Class I Class II Class III Class IV Class V Dyspnea None With exertion At rest History of MI History of CHF History of PCI Previous Cardiac Surgery Hypertension Requiring Medication History of Revascularization/Amputation for PVD Rest Pain/Gangrene Acute Renal Failure Functional Status Independent Partially Dependent Totally Dependent Do Not Resuscitate Coma >24 Hours Chemotherapy Within 30 Days of Surgery Transfusion >4 Units pRBCs Within 72 Hours of Surgery Systemic Sepsis None SIRS Sepsis Septic Shock Preoperative Sodium, mean (SD) Preoperative BUN, mean (SD) Preoperative Creatinine, mean (SD) Preoperative Hematocrit, mean (SD)

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