Leveraging American Society of Anesthesiologists Physical Status Classification and Surgeon Risk Estimates to...

Area of Science:

• Anesthesiology and Perioperative Medicine
• Surgical Risk Assessment
• Health Services Research

Background:

• The American Society of Anesthesiologists Physical Status Classification (ASA PS class) is a standard pre-surgical risk assessment tool.
• However, the ASA PS class does not incorporate surgery-specific factors or intraoperative events, limiting its predictive accuracy for postoperative complications.
• There is a need for enhanced postsurgical risk stratification tools that integrate multiple predictive elements.

Purpose of the Study:

• To develop and validate a postsurgical risk stratification tool by combining the ASA PS class with surgeon-generated risk estimates.
• To assess the accuracy of this combined tool in predicting 30-day postoperative morbidity.
• To compare the performance of the combined tool against traditional clinical data-based models.

Main Methods:

• Surgeons at an academic center provided pre-operative risk estimates for their patients.
• Data on ASA PS class, pre-surgical clinical features, and post-surgical outcomes were collected from institutional databases and electronic health records.
• Binomial regression models were used to predict 30-day morbidity, comparing models using clinical features, ASA PS class, surgeon risk estimates, and combinations thereof.

Main Results:

• The study included 286 patients across 68 procedure types, with 61.89% having ASA PS class 3 or higher.
• The overall complication rate was 27.27%.
• Combining ASA PS class and surgeon risk estimates achieved a model discrimination (AUC 0.84) comparable to a clinical data-based model (AUC 0.84) and superior to either assessment alone (ASA PS AUC 0.79; surgeon estimate AUC 0.71).

Conclusions:

• Both ASA PS class and surgeon risk estimates are independently predictive of 30-day morbidity.
• The combination of ASA PS class and surgeon risk estimates significantly improves the prediction of postsurgical complications.
• Judgment-derived assessments, when combined with standardized tools like ASA PS class, offer a powerful and accurate method for postsurgical risk stratification.