Cardiac surgery risk models: a position article.

David M Shahian; Eugene H Blackstone; Fred H Edwards; Frederick L Grover; Gary L Grunkemeier; David C Naftel; Samer A M Nashef; William C Nugent; Eric D Peterson; STS workforce on evidence-based surgery

doi:10.1016/j.athoracsur.2004.05.054

PubMed · 15511504

Cardiac surgery risk models: a position article.

David M Shahian·Eugene H Blackstone·Fred H Edwards·Frederick L Grover·Gary L Grunkemeier·David C Naftel·Samer A M Nashef·William C Nugent·Eric D Peterson·STS workforce on evidence-based surgery

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Abstract

Differences in medical outcomes may result from disease severity, treatment effectiveness, or chance. Because most outcome studies are observational rather than randomized, risk adjustment is necessary to account for case mix. This has usually been accomplished through the use of standard logistic regression models, although Bayesian models, hierarchical linear models, and machine-learning techniques such as neural networks have also been used. Many factors are essential to insuring the accuracy and usefulness of such models, including selection of an appropriate clinical database, inclusion of critical core variables, precise definitions for predictor variables and endpoints, proper model development, validation, and audit. Risk models may be used to assess the impact of specific predictors on outcome, to aid in patient counseling and treatment selection, to profile provider quality, and to serve as the basis of continuous quality improvement activities.

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Bayes Theorem Cardiac Surgical Procedures Coronary Artery Bypass Databases, Factual Diagnosis-Related Groups Forecasting Humans Logistic Models Models, Cardiovascular Odds Ratio Probability ROC Curve Reproducibility of Results Risk Assessment Risk Factors Stroke Volume Treatment Outcome Journal Article Review

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David M Shahian, Eugene H Blackstone, Fred H Edwards, Frederick L Grover, Gary L Grunkemeier, David C Naftel, Samer A M Nashef, William C Nugent, Eric D Peterson, STS workforce on evidence-based surgery. 2004. Cardiac surgery risk models: a position article.. https://doi.org/10.1016/j.athoracsur.2004.05.054

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