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Systematic review of risk prediction models for falls after stroke

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dc.contributor.author Walsh, Mary E.
dc.contributor.author Horgan, Frances N.
dc.contributor.author Walsh, Cathal Dominic
dc.contributor.author Galvin, Rose
dc.date.accessioned 2017-12-07T14:19:35Z
dc.date.available 2017-12-07T14:19:35Z
dc.date.issued 2016
dc.identifier.uri http://hdl.handle.net/10344/6325
dc.description peer-reviewed en_US
dc.description.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.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. en_US
dc.language.iso eng en_US
dc.publisher BMJ Publishing Group en_US
dc.relation.ispartofseries Journal of Epidemiology and Community Health;70, pp. 513-519
dc.relation.uri http://dx.doi.org/10.1136/jech-2015-206475
dc.subject decision making en_US
dc.subject falls en_US
dc.subject stroke en_US
dc.subject systematic reviews en_US
dc.title Systematic review of risk prediction models for falls after stroke en_US
dc.type info:eu-repo/semantics/article en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.date.updated 2017-12-07T14:13:55Z
dc.description.version ACCEPTED
dc.identifier.doi 10.1136/jech-2015-206475
dc.contributor.sponsor IRC en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US
dc.internal.rssid 1631989
dc.internal.copyrightchecked Yes
dc.identifier.journaltitle Journal Of Epidemiology And Community Health
dc.description.status peer-reviewed


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