Literature DB >> 30553646

GWTG Risk Model for All Stroke Types Predicts In-Hospital and 3-Month Mortality in Chinese Patients with Acute Stroke.

Shichao Sun1, Yuesong Pan2, Lei Bai3, Xingquan Zhao2, Liping Liu2, Hao Li2, Yilong Wang2, Li Guo4, Yongjun Wang5.   

Abstract

BACKGROUND: We aimed to externally validate the Get With the Guidelines (GWTG) risk model for all stroke types to predict in-hospital stroke mortality in Chinese patients and moreover to explore its prognostic value in predicting 3-month mortality after stroke.
METHODS: The prognostic model was applied to patients with acute stroke from China National Stroke Registry II (CNSR II) to predict in-hospital and 3-month mortality. Model discrimination was estimated by calculating c-statistic and 95% confidence intervals (CIs). Calibration was assessed by Pearson correlation coefficient and Hosmer-Lemeshow test.
RESULTS: Date from 21,684 stroke patients with complete data for in-hospital mortality prediction and 20,348 stroke patients with complete data for 3-month mortality prediction in the CNSR II were abstracted. The in-hospital and 3-month mortality were 1.4% and 5.6%, respectively. The c-statistics in the CNSR II were .86 (95% CI, .84-.88) and .83 (95% CI, .81-.84) for in-hospital and 3-month mortality, respectively. Calibration plot presented high correlation between the observed and predicted mortality rates (Pearson correlation coefficient, .996 for in-hospital and .998 for 3-month mortality; both P < .001). The Hosmer-Lemeshow statistics for the prediction of in-hospital and 3-month mortality were 0.21 and less than .001, respectively. The model performed nearly as well in each stroke type as in the overall model including all types.
CONCLUSIONS: The GWTG risk model for all stroke types is a valid clinical tool to predict in-hospital and 3-month mortality in Chinese patients with acute stroke of any type.
Copyright © 2018 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Stroke; mortality; outcomes; prognosis; risk factors

Mesh:

Year:  2018        PMID: 30553646     DOI: 10.1016/j.jstrokecerebrovasdis.2018.11.024

Source DB:  PubMed          Journal:  J Stroke Cerebrovasc Dis        ISSN: 1052-3057            Impact factor:   2.136


  2 in total

1.  Integrative Multi-omics Analysis to Characterize Human Brain Ischemia.

Authors:  Laura Ramiro; Teresa García-Berrocoso; Ferran Briansó; Leire Goicoechea; Alba Simats; Víctor Llombart; Ricardo Gonzalo; Alexandre Hainard; Elena Martínez-Saez; Francesc Canals; Jean-Charles Sanchez; Alex Sánchez-Pla; Joan Montaner
Journal:  Mol Neurobiol       Date:  2021-05-03       Impact factor: 5.590

Review 2.  The Association of Autonomic Nervous System Function With Ischemic Stroke, and Treatment Strategies.

Authors:  Mengxi Zhao; Ling Guan; Yilong Wang
Journal:  Front Neurol       Date:  2020-01-22       Impact factor: 4.003

  2 in total

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