医学
布里氏评分
接收机工作特性
回顾性队列研究
队列
急诊医学
人口
外科
内科学
统计
数学
环境卫生
作者
Chaoyang Tong,Qihang Li,Xinwei Du,Mengqin Shan,Yuxin Zhang,WU Hai-xi,Ziyun Shen,Zhuoming Xu,Xiaodong Ge,Shuang Cai,X Fu,Kan Zhang,Haibo Zhang,Shoujun Li,Changhong Miao,Jijian Zheng
标识
DOI:10.1097/aln.0000000000005514
摘要
Background: The applicability of four major traditional in-hospital mortality models in the Chinese setting is unclear due to disease spectrum and population heterogeneity. This study aimed to test the performance of these models in the Chinese setting and to construct and externally validate a novel model. Methods: 21,855 consecutive pediatric patients who underwent congenital heart surgery from January 2015 to December 2021 in Shanghai Children’s Medical Center were enrolled. For external validation, we additionally pooled 5,221 consecutive pediatric patients who underwent this surgical treatment from January 2020 to December 2021 in Beijing Fuwai Hospital. The performance of Aristotle Basis Complexity (ABC) score, Risk Adjustment for Congenital Heart Surgery (RACHS)-1 categories, Society of Thoracic Surgeons (STS)-European Association for Cardiothoracic Surgery (STAT) score, and STAT categories was tested. Independent predictors were used to develop a model. The area under the receiver operating characteristic curves (AUROCs) and Brier score were used to examine the model performance. Results: The AUROCs were 0.778 for ABC score, 0.685 for RACHS-1 categories, 0.808 for STAT score, and 0.784 for STAT categories. When preoperative covariates were added to four models, the AUROCs improved: ABC score (AUROC=0.860), RACHS-1 categories (AUROC=0.844), STAT score (AUROC= 0.856), and STAT categories (AUROC=0.864). The best-performing model incorporated 6 variables, including age, height, oxygen support, previous cardiac operation, emergency surgery, and STAT categories. The AUROCs and Brier score were 0.864 and 0.00977 in the development cohort, and 0.860 and 0.00654 in the external validation cohort. Conclusions: Four major traditional models were only moderately effective in predicting in-hospital mortality after congenital heart surgery in the Chinese setting. The novel model founded on the STAT categories in combination with preoperative covariates can serve as a useful and effective tool for predicting the risk of in-hospital mortality after congenital heart surgery in the Chinese setting.
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