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Published on: February 10, 2022
Clinical predictions and decisions to perform cardiac surgery on high-risk patients
1Cardiac Division of Anesthesiology, University of Ottawa Heart Institute, Ontario, Canada. jydupuis@ottawaheart.ca
Insights
High-risk cardiac surgery patients often survive and have good quality of life, despite predictions. Clinical judgment should minimally impact decisions to operate, as risk models are unreliable.
Area of Science:
- Cardiology
- Thoracic Surgery
- Critical Care Medicine
Background:
- The proportion of high-risk patients undergoing cardiac surgery has risen.
- Concerns exist regarding the appropriateness of intensive interventions for these patients.
- Predictive models for surgical outcomes have limitations.
Purpose of the Study:
- To evaluate the role of predictive risk models in high-risk cardiac surgery.
- To assess the outcomes and quality of life for high-risk patients after prolonged intensive care unit (ICU) stays.
- To inform decisions about denying surgery to high-risk patients.
Main Methods:
- Review of existing literature on risk prediction models in cardiac surgery.
- Analysis of outcomes for patients with prolonged ICU stays post-cardiac surgery.
- Comparison of predictive model accuracy with actual patient outcomes.
Main Results:
- Predictive models often lack superior discrimination compared to clinical judgment alone.
- Risk models lose calibration over time and tend to overestimate adverse outcomes.
- A significant proportion of high-risk patients survive prolonged ICU stays with good quality of life (50% at 1 year, 40% at 2 years).
Conclusions:
- Cardiac surgery should rarely be denied to high-risk patients based solely on predictive models.
- Clinical predictions should play a marginal role in surgical decisions for high-risk individuals.
- Focus should be on patient selection for complex cardiac procedures, considering survival and quality of life.
Abstract:
The proportion of high-risk patients undergoing cardiac surgery has increased steadily over the last two decades. Many of those patients have a catastrophic postoperative course and use hospital resources in a proportion that largely outweighs their number. Consequently, the appropriateness of invasive and intensive interventions in those patients has been questioned. If futility of care were predictable preoperatively, cardiac surgery would probably be denied to many high-risk patients. Logistic regression has been used to develop many complex predictive models to identify high-risk patients and predict their outcome; however, those models do not provide much more discrimination than clinical judgment alone. Moreover, with continuous improvement in medical care all risk models lose their calibration over time. As a result, they often overestimate the probabilities of poor outcome in the individual patients. Many high-risk cardiac surgical patients require a prolonged stay in the intensive care unit (ICU). The analysis of small cohorts of patients who had a prolonged postoperative stay in the ICU shows that 50% and 40% of them are still alive at 1- and 2-year follow-up, respectively; and most survivors report a good quality of life. Considering the limitations of predictive risk models and the satisfaction of cardiac surgical patients who survive after a prolonged ICU stay, it is reasonable to recognize that cardiac surgery should rarely be denied to high-risk patients unless technically unfeasible, and clinical predictions should have only a marginal role in the decision to operate on those patients.
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