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Published in: BMC Neurology 1/2014

Open Access 01-12-2014 | Research article

Web-based tool for dynamic functional outcome after acute ischemic stroke and comparison with existing models

Authors: Ruijun Ji, Wanliang Du, Haipeng Shen, Yuesong Pan, Penglian Wang, Gaifen Liu, Yilong Wang, Hao Li, Xingquan Zhao, Yongjun Wang

Published in: BMC Neurology | Issue 1/2014

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Abstract

Background

Acute ischemic stroke (AIS) is one of the leading causes of death and adult disability worldwide. In the present study, we aimed to develop a web-based risk model for predicting dynamic functional status at discharge, 3-month, 6-month, and 1-year after acute ischemic stroke (Dynamic Functional Status after Acute Ischemic Stroke, DFS-AIS).

Methods

The DFS-AIS was developed based on the China National Stroke Registry (CNSR), in which eligible patients were randomly divided into derivation (60%) and validation (40%) cohorts. Good functional outcome was defined as modified Rankin Scale (mRS) score ≤ 2 at discharge, 3-month, 6-month, and 1-year after AIS, respectively. Independent predictors of each outcome measure were obtained using multivariable logistic regression. The area under the receiver operating characteristic curve (AUROC) and plot of observed and predicted risk were used to assess model discrimination and calibration.

Results

A total of 12,026 patients were included and the median age was 67 (interquartile range: 57–75). The proportion of patients with good functional outcome at discharge, 3-month, 6-month, and 1-year after AIS was 67.9%, 66.5%, 66.9% and 66.9%, respectively. Age, gender, medical history of diabetes mellitus, stroke or transient ischemic attack, current smoking and atrial fibrillation, pre-stroke dependence, pre-stroke statins using, admission National Institutes of Health Stroke Scale score, admission blood glucose were identified as independent predictors of functional outcome at different time points after AIS. The DFS-AIS was developed from sets of predictors of mRS ≤ 2 at different time points following AIS. The DFS-AIS demonstrated good discrimination in the derivation and validation cohorts (AUROC range: 0.837-0.845). Plots of observed versus predicted likelihood showed excellent calibration in the derivation and validation cohorts (all r = 0.99, P < 0.001). When compared to 8 existing models, the DFS-AIS showed significantly better discrimination for good functional outcome and mortality at discharge, 3-month, 6-month, and 1-year after AIS (all P < 0.0001).

Conclusion

The DFS-AIS is a valid risk model to predict functional outcome at discharge, 3-month, 6-month, and 1-year after AIS.
Appendix
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Metadata
Title
Web-based tool for dynamic functional outcome after acute ischemic stroke and comparison with existing models
Authors
Ruijun Ji
Wanliang Du
Haipeng Shen
Yuesong Pan
Penglian Wang
Gaifen Liu
Yilong Wang
Hao Li
Xingquan Zhao
Yongjun Wang
Publication date
01-12-2014
Publisher
BioMed Central
Published in
BMC Neurology / Issue 1/2014
Electronic ISSN: 1471-2377
DOI
https://doi.org/10.1186/s12883-014-0214-z

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