医学
接收机工作特性
内科学
队列
临床终点
判别式
弗雷明翰风险评分
心力衰竭
临床试验
疾病
人工智能
计算机科学
作者
Consuelo Fernández‐Avilés,Martín Ruiz Ortiz,A Trujillano Ruíz,Gloria Heredia Campos,Adriana Resúa Collazo,Rafael González‐Manzanares,Mónica Delgado Ortega,Ana Almodóvar,Fátima Esteban Martínez,Luis Carlos Maestre Luque,A Moran Salinas,Alberto Torres Zamudio,Javier Herrera Flores,Manuel Díaz Andrade,José López‐Aguilera,Manuel Anguita Sánchez,Manuel Pan Álvarez‐Osorio,Dolores Mesa Rubio
摘要
Abstract Background Four scores have been published in 2022 for assessing mortality risk of patients with tricuspid regurgitation (TR): the TRI‐SCORE, those reported by Hochstadt and Wang and the TRIO score. Our objective was to perform an external validation of available scores for predicting mortality and the combined endpoint of mortality and heart failure (HF) admission, in an independent cohort of patients with severe TR and to compare their discriminative ability. Methods Discriminative ability of the scores for predicting events was assessed by means of receiver operating characteristics (ROC) curves. Results The validation cohort retrospectively included 614 consecutive patients (69 ± 13 years, 72% women) with severe TR studied with echocardiography in a tertiary care hospital and followed for up to 14 years (median 5 years, p25‐75 2–7 years), with 358 deaths and 620 HF admissions on follow‐up. Discriminative abilities for predicting death (C‐statistic .72 [95% CI .68–.76] for the TRI‐SCORE; .75 [.71–.78] for the Hochstadt score; .72 [.68–.76] for the Wang score; and .74 [.70–.78] for the TRIO score, p < .0005 for all) or the combined endpoint (C‐statistic .74 [.70–.78]; .74 [.70–.78], .73 [.69–.77] and .76 [.72–.80], respectively, p < .0005 for all) on follow‐up were statistically significant for all of them. Paired comparisons among them for predicting both endpoints were all non‐significant. Conclusions All tested scores showed significant and similar discriminative ability for predicting the combined endpoint of mortality or HF admission in this independent validation study of patients with severe TR.
科研通智能强力驱动
Strongly Powered by AbleSci AI