Clinical radiology · 2025
Integrated clinical and imaging predictors of 60-day mortality in acute aortic dissection: emphasizing innominate and carotid artery involvement.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Zhou L, Chen C, Gong W, Shang L, Liu L, Duan W, Zheng M
Аннотация
OBJECTIVES: To develop and validate a risk stratification model for 60-day mortality in acute aortic dissection by integrating computed tomography angiography and echocardiographic findings, with particular emphasis on aortic branch vessel involvement and surgical timing outcomes.
METHODS: This retrospective cohort study analyzed 1,464 acute aortic dissection patients (development cohort) and two validation cohorts (temporal: n=340; geographical: n=421) between 2007-2019. Risk factors were assessed through CT angiography and echocardiography. Multivariable logistic regression and LASSO analyses identified independent predictors of 60-day mortality. Model performance was evaluated using AUC-ROC analysis and calibration plots.
RESULTS: The 60-day mortality rate was 14.3% (210/1,464 patients). Independent predictors included age (adjusted OR 1.28, 95% CI 1.06-1.54), Stanford Type A (adjusted OR 1.85, 95% CI 1.42-2.41), innominate artery involvement (adjusted OR 1.45, 95% CI 1.15-1.83), left atrial enlargement (adjusted OR 1.32, 95% CI 1.04-1.67), and elevated FDP (adjusted OR 1.35, 95% CI 1.01-1.80). Combined risk factors showed the highest mortality, particularly pericardial effusion plus aortic regurgitation (42.3% in Type A). Mortality increased with delayed intervention from 15.2% (≤6 hours) to 35.8% (>24 hours) in Type A dissections. The model demonstrated robust performance in the temporal (AUC 0.77) and geographical (AUC 0.78) validation cohorts.
CONCLUSIONS: Integration of imaging parameters with clinical factors provides reliable mortality prediction in acute aortic dissection. Upper aortic branch involvement and cardiac imaging markers are significant predictors of mortality. Early intervention, particularly within 6 hours, is associated with improved survival. This risk stratification model may guide clinical decision-making regarding intervention timing and treatment strategy selection.
METHODS: This retrospective cohort study analyzed 1,464 acute aortic dissection patients (development cohort) and two validation cohorts (temporal: n=340; geographical: n=421) between 2007-2019. Risk factors were assessed through CT angiography and echocardiography. Multivariable logistic regression and LASSO analyses identified independent predictors of 60-day mortality. Model performance was evaluated using AUC-ROC analysis and calibration plots.
RESULTS: The 60-day mortality rate was 14.3% (210/1,464 patients). Independent predictors included age (adjusted OR 1.28, 95% CI 1.06-1.54), Stanford Type A (adjusted OR 1.85, 95% CI 1.42-2.41), innominate artery involvement (adjusted OR 1.45, 95% CI 1.15-1.83), left atrial enlargement (adjusted OR 1.32, 95% CI 1.04-1.67), and elevated FDP (adjusted OR 1.35, 95% CI 1.01-1.80). Combined risk factors showed the highest mortality, particularly pericardial effusion plus aortic regurgitation (42.3% in Type A). Mortality increased with delayed intervention from 15.2% (≤6 hours) to 35.8% (>24 hours) in Type A dissections. The model demonstrated robust performance in the temporal (AUC 0.77) and geographical (AUC 0.78) validation cohorts.
CONCLUSIONS: Integration of imaging parameters with clinical factors provides reliable mortality prediction in acute aortic dissection. Upper aortic branch involvement and cardiac imaging markers are significant predictors of mortality. Early intervention, particularly within 6 hours, is associated with improved survival. This risk stratification model may guide clinical decision-making regarding intervention timing and treatment strategy selection.