Optimizing falls risk prediction for inpatient stroke rehabilitation: A secondary data analysis.
Identifying individuals at risk for falls during inpatient stroke rehabilitation can ensure timely implementation of falls prevention strategies to minimize the negative personal and health system consequences of falls. To compare sociodemographic and clinical characteristics of fallers and non-fall...
| Publicado en: | Physiotherapy Theory & Practice Vol. 39; no. 8; pp. 1704 - 1716 |
|---|---|
| Autores principales: | , , , , , , , , |
| Formato: | questionnaire/scale research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Aug2023
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=164705145&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 164705145 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09593985 BCJ jtl: Physiotherapy Theory & Practice issn: 09593985 maglogo: Y pubinfo: dt: Aug2023 vid: 39 iid: 8 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 164705145 155635309 164705145 164705145 10.1080/09593985.2022.2043498 164705145 ppf: 1704 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Optimizing falls risk prediction for inpatient stroke rehabilitation: A secondary data analysis. aug: au: Gangar, Surekha Sivakumaran, Shajicaa Anderson, Ashley N. Shaw, Kelsey R. Estrela, Luke A. Kwok, Heather Davies, Robyn C. Tong, Agnes Salbach, Nancy M. affil: Department of Physical Therapy, University of Toronto, Toronto, ON, Canada sug: subj: Stroke Rehabilitation Accidental Falls Risk Factors Risk Assessment Methods Hospitalization Scales Instrument Validation Sociodemographic Factors Evaluation Disease Attributes Sensitivity and Specificity Predictive Value of Tests Human Inpatients Rehabilitation Patients Secondary Analysis Male Female Middle Age Aged Aged, 80 and Over Morse Fall Scale Comparative Studies Prospective Studies Record Review Hospitals, Urban Descriptive Statistics Validation Studies Funding Source Middle Aged: 45-64 years Aged: 65+ years Aged, 80 & over Male Female ab: Identifying individuals at risk for falls during inpatient stroke rehabilitation can ensure timely implementation of falls prevention strategies to minimize the negative personal and health system consequences of falls. To compare sociodemographic and clinical characteristics of fallers and non-fallers; and evaluate the ability of the Berg Balance Scale (BBS) and Morse Falls Scale (MFS) to predict falls in an inpatient stroke rehabilitation setting. A longitudinal study involving a secondary analysis of health record data from 818 patients with stroke admitted to an urban, rehabilitation hospital was conducted. A fall was defined as having ≥1 fall during the hospital stay. Cut-points on the BBS and MFS, alone and in combination, that optimized sensitivity and specificity for predicting falls, were identified. Low admission BBS score and admission to a low-intensity rehabilitation program were associated with falling (p <.05). Optimal cut-points were 29 for the BBS (sensitivity: 82.4%; specificity: 57.4%) and 30 for the MFS (sensitivity: 73.2%; specificity: 31.4%) when used alone. Cut-points of 45 (BBS) and 30 (MFS) in combination optimized sensitivity (74.1%) and specificity (42.7%). A BBS cut-point of 29 alone appears superior to using the MFS alone or combined with the BBS to predict falls. pubtype: Academic Journal doctype: questionnaire/scale research tables/charts Journal Article ougenre: Unknown language: English refInfo: holdings: @attributes: islocal: N |
|---|