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Aortic regurgitation (AR) is when the aortic valve does not close or seal properly, leading to backward blood circulation from the aorta into the left ventricle during diastole. Common causes of AR include rheumatic heart disease, congenital valve defects, and aortic root dilation. Managing AR requires a multifaceted approach to alleviate symptoms, preserve left ventricular function, and address the underlying cause of the regurgitation. Patients with symptomatic AR or significant left...
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MET Level Score Outperforms Comorbidities in Predicting Perioperative Open Aortic Surgery Morbidity.

L Ciofani1, P Acciarri1, R Ricci1

  • 1Department of Surgery, Unit of Vascular Surgery, S. Anna University Hospital of Ferrara, and University of Ferrara, Ferrara, Italy.

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Summary

The Metabolic Equivalent of Tasks (METs) score is a more accurate predictor of major complications and hospital stay after open aortic repair (OAR) than the Society for Vascular Surgery (SVS) score. Combining METs with the SVS score further improves prediction of OAR outcomes.

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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.