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Web-based tool for dynamic functional outcome after acute ischemic stroke and comparison with existing models
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 Func...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4255632/ https://www.ncbi.nlm.nih.gov/pubmed/25927216 http://dx.doi.org/10.1186/s12883-014-0214-z |
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author | Ji, Ruijun Du, Wanliang Shen, Haipeng Pan, Yuesong Wang, Penglian Liu, Gaifen Wang, Yilong Li, Hao Zhao, Xingquan Wang, Yongjun |
author_facet | Ji, Ruijun Du, Wanliang Shen, Haipeng Pan, Yuesong Wang, Penglian Liu, Gaifen Wang, Yilong Li, Hao Zhao, Xingquan Wang, Yongjun |
author_sort | Ji, Ruijun |
collection | PubMed |
description | 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12883-014-0214-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4255632 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-42556322014-12-05 Web-based tool for dynamic functional outcome after acute ischemic stroke and comparison with existing models Ji, Ruijun Du, Wanliang Shen, Haipeng Pan, Yuesong Wang, Penglian Liu, Gaifen Wang, Yilong Li, Hao Zhao, Xingquan Wang, Yongjun BMC Neurol Research Article 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12883-014-0214-z) contains supplementary material, which is available to authorized users. BioMed Central 2014-11-25 /pmc/articles/PMC4255632/ /pubmed/25927216 http://dx.doi.org/10.1186/s12883-014-0214-z Text en © Ji et al.; licensee BioMed Central Ltd. 2014 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Ji, Ruijun Du, Wanliang Shen, Haipeng Pan, Yuesong Wang, Penglian Liu, Gaifen Wang, Yilong Li, Hao Zhao, Xingquan Wang, Yongjun Web-based tool for dynamic functional outcome after acute ischemic stroke and comparison with existing models |
title | Web-based tool for dynamic functional outcome after acute ischemic stroke and comparison with existing models |
title_full | Web-based tool for dynamic functional outcome after acute ischemic stroke and comparison with existing models |
title_fullStr | Web-based tool for dynamic functional outcome after acute ischemic stroke and comparison with existing models |
title_full_unstemmed | Web-based tool for dynamic functional outcome after acute ischemic stroke and comparison with existing models |
title_short | Web-based tool for dynamic functional outcome after acute ischemic stroke and comparison with existing models |
title_sort | web-based tool for dynamic functional outcome after acute ischemic stroke and comparison with existing models |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4255632/ https://www.ncbi.nlm.nih.gov/pubmed/25927216 http://dx.doi.org/10.1186/s12883-014-0214-z |
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