MET Level Score Outperforms Comorbidities in Predicting Perioperative Open Aortic Surgery Morbidity

Area of Science:

• Cardiovascular Surgery
• Surgical Outcomes Research
• Predictive Analytics in Medicine

Background:

• Assessing patient risk is crucial for optimizing surgical outcomes.
• Current risk stratification tools for open aortic repair (OAR) include the Society for Vascular Surgery (SVS) comorbidity score.
• The predictive value of the Metabolic Equivalent of Tasks (METs) score for OAR outcomes requires further investigation.

Purpose of the Study:

• To compare the predictive performance of the METs score and the SVS comorbidity score for perioperative outcomes in patients undergoing OAR.
• To evaluate the combined predictive accuracy of METs and SVS scores for OAR.
• To identify the most effective tool for risk stratification in OAR patients.

Main Methods:

• Retrospective analysis of 169 patients undergoing elective OAR (2018-2023).
• Primary outcomes: major adverse events (MAEs), intensive care unit (ICU) admission, and length of hospital stay.
• Predictive performance assessed using receiver operating characteristic (ROC) curves and area under the curve (AUC) analysis.

Main Results:

• METs score demonstrated superior discrimination for MAEs (AUC 0.89) compared to SVS score (AUC 0.71).
• The combined METs+SVS model achieved the highest AUC for MAEs (0.91) and ICU admission (0.75).
• METs-based models showed a clinically relevant advantage in predicting adverse outcomes.

Conclusions:

• The METs score is a more effective predictor of major complications, ICU admission, and prolonged hospitalization after OAR than the SVS score.
• Integrating METs with the SVS score significantly enhances the accuracy of predicting perioperative outcomes in OAR.
• METs-based risk stratification offers a valuable tool for improving patient management in OAR.