国家神经系统疾病临床医学研究中心数据管理与共享系统

发表杂志：Stroke

发表类型: Original Contributions

影响因子(IF): 7.914

PMID: 25028448 Pubmed原文链接 全文下载

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% confidence interval, 0.55-0.73). The ICH-APS-A was well calibrated (Hosmer-Lemeshow test) in the derivation (P=0.20) and validation (P=0.66) cohorts. Similarly, a 26-point ICH-APS-B was established. The ICH-APS-A and ICH-APS-B were not significantly different in discrimination and reclassification for SAP after ICH. CONCLUSION: The ICH-APSs are valid risk scores for predicting SAP after ICH, especially for patients with length of stay >48 hours.

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.