Preoperative risk assessment is evolving to incorporate complex prediction models, frailty assessments, and novel biomarkers to better individualize patient care.
Complex models may refine preoperative risk prediction; leaves open prospective validation and clinical integration.
PURPOSE OF REVIEW: The central question of preoperative assessment is not "What can be done?" but "What should be done and how?" Predicting a patient's risk of unwanted outcomes is vital to answering this question. This review discusses risk prediction tools currently available and anticipates future developments. RECENT FINDINGS: Simple, parsimonious risk scales and scores are being replaced by complex risk prediction models as high-capacity information systems become ubiquitous. The accuracy of risk estimation will be further increased by improved assessment of physical fitness, frailty, and incorporation of existing and novel biomarkers. However, the limitations of risk prediction for individual patient care must be recognized. SUMMARY: Risk prediction is transforming from clinical estimation to statistical science. Predictions should be used within the context of a patient's baseline risk (life expectancy independent of surgery), personal circumstances, quality of life, their expectations and values, and consideration of outcomes that are meaningful for the patient.
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Ajitsaria et al. (2018) studied this question.
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