Peer Reviewed

1

Document Type

Article

Publication Date

14-1-2016

Keywords

Systematic reviews, Falls, Stroke, Decision Making PR

Funder/Sponsor

Funding was received from the Irish Research Council (Government of Ireland Postgraduate Scholarship Scheme 2013).

Comments

This article has been accepted for publication in Journal of Epidemiology and Community Health following peer review. The definitive copyedited, typeset version Walsh ME, Horgan NF, Walsh CD, Galvin R. Systematic review of risk prediction models for falls after stroke. Journal of Epidemiology and Community Health. 2016;70(5):513-9. [Epub 2016 Jan 14.] is available online at: http://jech.bmj.com/content/70/5/513.long

Abstract

BACKGROUND: Falls are a significant cause of morbidity after stroke. The aim of this review was to identify, critically appraise and summarise risk prediction models for the occurrence of falling after stroke.

METHODS: A systematic literature search was conducted in December 2014 and repeated in June 2015. Studies that used multivariable analysis to build risk prediction models for falls early after stroke were included. 2 reviewers independently assessed methodological quality. Data relating to model calibration, discrimination (C-statistic) and clinical utility (sensitivity and specificity) were extracted. A narrative review of models was conducted. PROSPERO reference: CRD42014015612.

RESULTS: The 12 included articles presented 18 risk prediction models. 7 studies predicted falls among inpatients only and 5 recorded falls in the community. Methodological quality was variable. A C-statistic was reported for 7 models and values ranged from 0.62 to 0.87. Models for use in the inpatient setting most frequently included measures of hemi-inattention, while those predicting community events included falls (or near-falls) history and balance measures most commonly. Only 2 studies reported any form of validation, and none presented a validated model with acceptable performance.

CONCLUSIONS: A number of falls-risk prediction models have been developed for use in the acute and subacute stages of stroke. Future research should focus on validating and improving existing models, with reference to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines to ensure quality reporting and expedite clinical implementation.

Disciplines

Medicine and Health Sciences | Rehabilitation and Therapy

Citation

Walsh ME, Horgan NF, Walsh CD, Galvin R. Systematic review of risk prediction models for falls after stroke. Journal of Epidemiology and Community Health. 2016;70(5):513-9. [Epub 2016 Jan 14.]

PubMed ID

26767405

DOI Link

10.1136/jech-2015-206475

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.

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