Dynamic Modified Early Warning Score for predicting postoperative mortality in acute type A aortic dissection: a...

Area of Science:

• Cardiology
• Thoracic Surgery
• Critical Care Medicine

Background:

• The Modified Early Warning Score (MEWS) is underutilized in predicting outcomes for acute type A aortic dissection (AAAD).
• Early identification of mortality risk in AAAD patients is crucial for timely intervention.
• Understanding MEWS dynamics post-surgery can improve patient stratification.

Purpose of the Study:

• To assess the predictive accuracy of MEWS at various postoperative time points in AAAD patients.
• To explore the relationship between MEWS trajectories and in-hospital mortality.
• To validate MEWS as a tool for risk stratification in AAAD surgery.

Main Methods:

• Retrospective analysis of 279 AAAD patients undergoing surgery (January 2020 - December 2022).
• MEWS calculated hourly for the first 24 hours post-surgery.
• Receiver operating characteristic (ROC) curves and latent class growth modeling (LCGM) used for analysis.

Main Results:

• In-hospital mortality rate was 13.3% among the 279 patients.
• Higher MEWS scores consistently correlated with increased mortality (P<0.05).
• MEWS at 12 hours post-surgery showed the highest predictive accuracy (AUC=0.758, cutoff=4); high-risk MEWS trajectories predicted 45.9% mortality.

Conclusions:

• MEWS serves as a dependable early predictor of postoperative mortality in AAAD.
• Sustained elevated MEWS trajectories are strongly linked to higher mortality risks.
• MEWS facilitates early risk stratification and enhances postoperative management strategies for AAAD patients.