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Journal of Cardiothoracic Surgery

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Open Access 01-12-2015 | Research article

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

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

Published in: Journal of Cardiothoracic Surgery | Issue 1/2015

Abstract

Introduction

Risk 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 methods

Data 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.

Results

A 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.

Conclusions

The 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.

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Title: 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
Authors: Paul J Chung
Timothy I Carter
Joshua H Burack
Sophia Tam
Antonio Alfonso
Gainosuke Sugiyama
Publication date: 01-12-2015
Publisher: BioMed Central
Published in: Journal of Cardiothoracic Surgery / Issue 1/2015
Electronic ISSN: 1749-8090
DOI: https://doi.org/10.1186/s13019-015-0269-y

At a glance: The STEP trials

Springer Medicine

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

Abstract

Introduction

Material and methods

Results

Conclusions

At a glance: The STEP trials

Springer Medicine

Abstract

Introduction

Material and methods

Results

Conclusions

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