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

动态改良早期预警评分预测急性A型主动脉夹层术后死亡率:一项回顾性研究

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Abstract

BACKGROUND: The Modified Early Warning Score (MEWS) is a valuable tool for predicting in-hospital mortality, yet it is seldom applied to acute type A aortic dissection (AAAD). This study aimed to evaluate the predictive accuracy of MEWS at different times within the first 24 hours after AAAD surgery, and to investigate the association between MEWS trajectories and postoperative mortality. METHODS: This retrospective study included 279 patients who underwent AAAD surgery from January 2020 to December 2022. MEWS was calculated at 0, 4, 8, 12, 16, 20, and 24 hours postoperatively. Predictive value for mortality was assessed using receiver operating characteristic (ROC) curves. Latent class growth modeling (LCGM) was applied to classify MEWS trajectories and analyze their association with postoperative mortality. RESULTS: Among 279 AAAD patients, the in-hospital mortality rate was 13.3%. MEWS was higher in the death group at all postoperative time points (P<0.05). The highest predictive accuracy occurred at 12 hours postoperatively [area under the curve (AUC) =0.758, cutoff =4]. LCGM identified three MEWS trajectories, with the highest-risk trajectory associated with a 45.9% incidence of mortality. CONCLUSIONS: MEWS is a reliable early indicator of postoperative mortality in AAAD patients. Persistently high MEWS trajectories is strongly associated with increased mortality risk, supporting its use in early risk stratification and postoperative management.

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