A decision making algorithm for rehabilitation after stroke: A guide to choose an appropriate and safe treadmill training.
BACKGROUND: Walking independently after a stroke can be difficult or impossible, and walking reeducation is vital. But the approach used is often arbitrary, relying on the devices available and subjective evaluations by the doctor/physiotherapist. Objective decision making tools could be useful. OBJ...
| Published in: | NeuroRehabilitation Vol. 49; no. 1; pp. 75 - 86 |
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| Main Authors: | , , , , , , |
| Format: | algorithm research tables/charts Journal Article |
| Published: |
Sage Publications Inc.
2021
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=151973961&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 151973961 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10538135 3RE jtl: NeuroRehabilitation issn: 10538135 maglogo: N pubinfo: dt: 2021 vid: 49 iid: 1 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 151973961 150510327 151973961 151973961 10.3233/NRE-210065 151973961 ppf: 75 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: A decision making algorithm for rehabilitation after stroke: A guide to choose an appropriate and safe treadmill training. aug: au: Vanoglio, Fabio Olivares, Adriana Bonometti, Gian Pietro Damiani, Silvia Gaiani, Marta Comini, Laura Luisa, Alberto affil: Istituti Clinici Scientifici Maugeri IRCCS, Neurological Rehabilitation Unit of the Institute of Lumezzane, Brescia, Italy sug: subj: Stroke Patients Stroke Rehabilitation Physical Therapists Patient Safety Gait Training Methods Decision Support Techniques Motor Skills Human Scales Retrospective Design Chi Square Test Pearson's Correlation Coefficient Body-Weight-Supported Treadmill Training Morse Fall Scale ab: BACKGROUND: Walking independently after a stroke can be difficult or impossible, and walking reeducation is vital. But the approach used is often arbitrary, relying on the devices available and subjective evaluations by the doctor/physiotherapist. Objective decision making tools could be useful. OBJECTIVES: To develop a decision making algorithm able to select for post-stroke patients, based on their motor skills, an appropriate mode of treadmill training (TT), including type of physiotherapist support/supervision required and safety conditions necessary. METHODS: We retrospectively analyzed data from 97 post-stroke inpatients admitted to a NeuroRehabilitation unit. Patients attended TT with body weight support (BWSTT group) or without support (FreeTT group), depending on clinical judgment. Patients' sociodemographic and clinical characteristics, including the Cumulative Illness Rating Scale (CIRS) plus measures of walking ability (Functional Ambulation Classification [FAC], total Functional Independence Measure [FIM] and Tinetti Performance-Oriented Mobility Assessment [Tinetti]) and fall risk profile (Morse and Stratify) were retrieved from institutional database. RESULTS: No significant differences emerged between the two groups regarding sociodemographic and clinical characteristics. Regarding walking ability, FAC, total FIM and its Motor component and the Tinetti scale differed significantly between groups (for all, p < 0.001). FAC and Tinetti scores were used to elaborate a decision making algorithm classifying patients into 4 risk/safety (RS) classes. As expected, a strong association (Pearson chi-squared, p < 0.0001) was found between RS classes and the initial BWSTT/FreeTT classification. CONCLUSION: This decision making algorithm provides an objective tool to direct post-stroke patients, on admission to the rehabilitation facility, to the most appropriate form of TT. pubtype: Academic Journal doctype: algorithm research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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