Abstract WP242: Modeling Prevention, Prediction or Explanation of Stroke Risk: Insights From Meta-Analysis of Studies With Models Predicting Stroke or Composite Outcomes

Anshul Saxena; Peter McGranaghan; Sankalp Das; Muni Rubens; Joseph A Salami; Emir Veledar

doi:10.1161/str.50.suppl_1.wp242

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Abstract WP242: Modeling Prevention, Prediction or Explanation of Stroke Risk: Insights From Meta-Analysis of Studies With Models Predicting Stroke or Composite Outcomes

Journal article

Peer reviewed

Abstract WP242: Modeling Prevention, Prediction or Explanation of Stroke Risk: Insights From Meta-Analysis of Studies With Models Predicting Stroke or Composite Outcomes

Anshul Saxena, Peter McGranaghan, Sankalp Das, Muni Rubens, Joseph A Salami and Emir Veledar

Stroke, Vol.50

2019

DOI: https://doi.org/10.1161/str.50.suppl_1.wp242

Abstract

Objective: Models predicting stroke suffer from several problems: they are not accurate, contain mostly non-modifiable factors, and they explain more than they predict. We performed a meta-analysis...

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https://www.ahajournals.org/doi/abs/10.1161/str.50.suppl_1.WP242View

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https://works.bepress.com/sankalp-das/39/View

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https://scholarlycommons.baptisthealth.net/se-all-publications/3054/View

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Title: Abstract WP242: Modeling Prevention, Prediction or Explanation of Stroke Risk: Insights From Meta-Analysis of Studies With Models Predicting Stroke or Composite Outcomes
Creators: Anshul Saxena - Baptist Health South Florida
Peter McGranaghan - Baptist Health South Florida
Sankalp Das - Baptist Health South Florida
Muni Rubens
Joseph A Salami - Baptist Health South Florida
Emir Veledar - Baptist Health South Florida
Publication Details: Stroke, Vol.50
Publisher: Ovid Technologies (Wolters Kluwer Health); United States
Academic Unit: Miller School of Medicine; UMMG Department of Neurology
Resource Type: Journal article
Record Identifier: 991031996606502976