医学
心脏病学
狭窄
危险分层
内科学
分级(工程)
钙化
主动脉瓣
主动脉瓣狭窄
放射科
土木工程
工程类
作者
Lionel Tastet,Mulham Ali,Philippe Pîbarot,Romain Capoulade,Kristian Altern Øvrehus,Marie Arsenault,Amal Haujir,Élisabeth Bédard,Axel Cosmus Pyndt Diederichsen,Jordi S. Dahl,Marie‐Annick Clavel
标识
DOI:10.1161/jaha.123.035605
摘要
Background Thresholds of aortic valve calcification (AVC) to define hemodynamically moderate aortic stenosis (AS) from mild are lacking. We aimed to establish a novel grading classification of AVC as quantified by computed tomography and determine its prognostic value. Methods and Results This study included 915 patients with at least mild AS (mean age 70±12 years, 30% women) from a multicenter prospective registry. All patients underwent Doppler‐echocardiography and noncontrast computed tomography within 3 months. Primary end point was the occurrence of all‐cause death. Receiver operating characteristic curves analyses were used to determine the sensitivity and specificity of sex‐specific thresholds of AVC to identify hemodynamically moderate AS. Optimal thresholds (ie, with best sensitivity/specificity) of AVC to distinguish moderate (aortic valve area 1.0–1.5 cm 2 and mean gradient 20–39 mm Hg) from mild AS (aortic valve area >1.5 cm 2 and mean gradient <20 mm Hg) were AVC ≥360 arbitrary units in women and ≥1037 arbitrary units in men. Based on the guidelines' thresholds for severe AS and the new thresholds in our study for moderate AS, 312 (34%) patients had mild, 253 (28%) moderate, and 350 (38%) severe AVC. During a mean follow‐up of 5.6±3.9 years, 183 (27%) deaths occurred. In Cox multivariable models, AVC remained associated with an increased risk of death (adjusted hazard ratio per grade increase, 1.94 [95% CI, 1.53–2.56]; P <0.001). Conclusions A novel grading classification of anatomic AS severity based on sex‐specific thresholds of AVC provides significant prognostic value for predicting mortality. These findings support the complementarity of computed tomography‐calcium scoring to Doppler‐echocardiography to corroborate AS severity and enhance risk stratification in patients with AS.
科研通智能强力驱动
Strongly Powered by AbleSci AI