Risk Score to Predict Hospital-Acquired Pneumonia After Spontaneous Intracerebral Hemorrhage

作者：Ruijun Ji, Haipeng Shen, Yuesong Pan, Wanliang Du, Penglian Wang, Gaifen Liu, Yilong Wang, Hao Li, Xingquan Zhao, Yongjun Wang, Qi Bi, Weiwei Zhang, Liying Cui, Yu-heng Sun, Maolin He, Dongsheng Fan, Xunming Ji, Jimei Li, Fang Zhang, Kai Feng, Xiaojun Zhang, Yansheng Li, Shaoshi Wang, Wei Fan, Zhenguo Liu, Xiaojiang Sun, Wěi Li, Jianrong Liu, Xu Chen, Qingke Bai, Gu Dexiang, Xin Li, Qiang Dong, Yan Cheng, Yu Lan, Bin Li, Tongyu Wang, Kun Zhao, Chaodong Zhang, Dingbo Tao, Lin Yin, Fang Qu, Jingbo Zhang, Jianfeng Wang, Ying Lian, Fang Qu, Jun Fan, Ying Gao, Mingdong Cheng, Jiang Wu, Huashan Sun, Jinying Li, Guozhong Li, Yulan Zhu, Zichao Yang, Fengmin Yang, Jun Zhou, Minxia Guo, Zhengyi Li, Qilin Ma, Renbin Huang, Bo Xiao, Kangning Chen, Xinyue Qin, Changlin Hu, Li Gao, Jinsheng Zeng, Anding Xu, Xiong Zhang, Ming Shao, Qi Feng, Weimin Xiao, Suping Zhang, Xiaoping Pan, Suyue Pan, Yefeng Cai, Qi Wan, Yun Xu, Kaifu Ke, Yuenan Kong, Qing Di, Fengyang Shao, Yajun Jiang, Daming Wang, Li Guo, Wencui Xue · 发表于：Stroke · 年份：2014 · DOI：10.1161/strokeaha.114.005023 · 被引用次数：69 · 研究领域：Intracerebral and Subarachnoid Hemorrhage Research、Nosocomial Infections in ICU、Acute Ischemic Stroke Management

BACKGROUND AND PURPOSE: We aimed to develop a risk score (intracerebral hemorrhage-associated pneumonia score, ICH-APS) for predicting hospital-acquired stroke-associated pneumonia (SAP) after ICH. METHODS: The ICH-APS was developed based on the China National Stroke Registry (CNSR), in which eligible patients were randomly divided into derivation (60%) and validation (40%) cohorts. Variables routinely collected at presentation were used for predicting SAP after ICH. For testing the added value of hematoma volume measure, we separately developed 2 models with (ICH-APS-B) and without (ICH-APS-A) hematoma volume included. Multivariable logistic regression was performed to identify independent predictors. The area under the receiver operating characteristic curve (AUROC), Hosmer-Lemeshow goodness-of-fit test, and integrated discrimination index were used to assess model discrimination, calibration, and reclassification, respectively. RESULTS: The SAP was 16.4% and 17.7% in the overall derivation (n=2998) and validation (n=2000) cohorts, respectively. A 23-point ICH-APS-A was developed based on a set of predictors and showed good discrimination in the overall derivation (AUROC, 0.75; 95% confidence interval, 0.72-0.77) and validation (AUROC, 0.76; 95% confidence interval, 0.71-0.79) cohorts. The ICH-APS-A was more sensitive for patients with length of stay >48 hours (AUROC, 0.78; 95% confidence interval, 0.75-0.81) than those with length of stay <48 hours (AUROC, 0.64; 95% confid...