期刊
EBIOMEDICINE
卷 47, 期 -, 页码 309-318出版社
ELSEVIER
DOI: 10.1016/j.ebiom.2019.08.028
关键词
Advanced Schistosomiasis; Mortality risk; Prediction model; Integrated discrimination improvement; Net reclassification improvement
资金
- National Key R&D Program of China [2017YFC1310000]
To date, no risk prediction tools have been developed to identify high mortality risk of patients with advanced schistosomiasis within 2 years after discharge. We aim to derive and validate a risk prediction model to be applied in clinical practice. The risk prediction model was derived from 1487 patients from Jingzhou and externally validated by 723 patients of Huangshi, two prefecture-level cities in Hubei province, China (from September 2014 to January 2015. with follow-up to January 2017). The baseline variables were collected. The mean age [SDI was 62.89[10.38] years for the derivation cohort and 62.95 [12.22] years for the external validation cohort. The females accounted for 363% and 43.7% of the derivation and validation cohorts, respectively. 827% patients (123/1487) in the derivation cohort and 7.75% patients (56/723) in the external validation cohort died within 2 years after discharge. We constructed 4 models based on the 7 selected variables: age, clinical classification, serum direct bilirubin (DBil), aspartate aminotransferase (AST), alkaline phosphatase (ALP), hepatitis B surface antigen (HBsAg), alpha fetoprotein (AR) at admission. In the external validation cohort, the multivariate model including 7 variables had a C statistic of 0.717 (95% CI, 0.646-0.788) and improved integrated disciimination improvement (IDI) value and net reclassification improvement (NRI) value compared to the other reduced models. Therefore, a multivariate model was developed to predict the 2-year mortality risk for patients with advanced schistosomiasis after discharge. It could also help guide follow-up, aid prognostic assessment and inform resource allocation. (C) 2019 Published by Elsevier B.V.
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