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Utility of clinical risk predictors for preoperative cardiovascular risk prediction
1Perioperative Research Unit, Department of Anaesthetics, Inkosi Albert Luthuli Central Hospital, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Private Bag 7, Congella 4013, South Africa. biccardb@ukzn.ac.za
Insights
Improving cardiovascular risk prediction for non-cardiac surgery requires uniform definitions and continuous variables. Risk factors should reflect organ dysfunction and be assessed throughout the perioperative period for better stratification.
Area of Science:
- Cardiology
- Anesthesiology
- Medical Informatics
Background:
- Cardiovascular risk prediction is crucial for non-cardiac surgery.
- European and American algorithms rely on clinical risk factors for preoperative assessment and perioperative management.
Purpose of the Study:
- To review existing clinical risk factors for cardiovascular risk prediction in non-cardiac surgery.
- To identify limitations and propose improvements for clinical decision-making and risk stratification.
Main Methods:
- Review of current clinical risk factors and their application in risk assessment algorithms.
- Analysis of limitations in current risk stratification models.
- Identification of factors to enhance predictive performance.
Main Results:
- Current risk factors require uniform definitions for cardiovascular outcomes and risk factors.
- Risk factors should indicate organ dysfunction, not just historical diagnoses.
- Parsimonious models with continuous variables and age inclusion are recommended.
- Risk assessment should span the entire perioperative period, with varying factors based on timing.
Conclusions:
- Enhancing cardiovascular risk prediction necessitates standardized definitions and a focus on organ dysfunction.
- Parsimonious, continuous variable models incorporating age improve stratification.
- Dynamic, perioperative risk assessment is essential for optimal patient management.
Abstract:
Cardiovascular risk prediction using clinical risk factors is integral to both the European and the American algorithms for preoperative cardiac risk assessment and perioperative management for non-cardiac surgery. We have reviewed these risk factors and their ability to guide clinical decision making. We examine their limitations and attempt to identify factors which may improve their performance when used for clinical risk stratification. To improve the performance of the clinical risk factors, it is necessary to create uniformity in the definitions of both cardiovascular outcomes and the clinical risk factors. The risk factors selected should reflect the degree of organ dysfunction rather than a historical diagnosis. Parsimonious model design should be applied, making use of a minimal number of continuous variables rather than creating overfitted models. The inclusion of age in the model may assist partly in controlling for the duration of risk factor exposure. Risk assignment should occur throughout the perioperative period and the risk factors chosen for model inclusion should vary depending on when the assignment occurs (before operation, intraoperatively, or after operation).
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