Open AccessFactors predicting clinically significant functional gain and discharge to home in stroke in-patients after rehabilitation – A retrospective cohort study
Author(s) -
Tony Kwun-Tak Li,
Bobby Hin-Po Ng,
Dora Y L Chan,
Ruthy Suet-Fan Chung,
Kim-Kam Teresa Yu
Publication year - 2020
Publication title -
hong kong journal of occupational therapy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.301
H-Index - 13
eISSN - 1876-4398
pISSN - 1569-1861
DOI - 10.1177/1569186120979428
Subject(s) - logistic regression , rehabilitation , functional independence measure , medicine , physical therapy , stroke (engine) , minimal clinically important difference , multivariate statistics , glasgow coma scale , multivariate analysis , bayesian multivariate linear regression , cohort , activities of daily living , regression analysis , physical medicine and rehabilitation , surgery , randomized controlled trial , mechanical engineering , statistics , mathematics , machine learning , computer science , engineering
Objective This study explored factors which predict stroke survivors who could achieve “clinically significant functional gain” and return home when being discharged from a local hospital after in-patient stroke rehabilitation programme.Methods This study included 562 inpatients with stroke who were residing at community dwellings before onset of stroke, and transferred to a convalescent hospital for rehabilitation from four acute hospitals over one year. The main outcome variables of prediction were (a) achieving “clinically significant functional gain” as measured by (a1) achievement of “minimal clinically important difference” (MCID) of improvement in Functional Independence Measure Motor Measure (FIM-MM)”, (a2) one or more level(s) of improvement in function group according to the patients’ FIM-MM, and (b) discharge to home. Sixteen predictor variables were identified and studied firstly with univariate binary logistic regression and those significant variables were then put into multivariate binary logistic regression.Results Based on multivariate regression, the significant predictors for “clinically significant functional gain” were: younger age <75 years old, higher Glasgow Coma Scale score at admission, with haemorrhagic stroke, intermediate FIM-MM function group. Those significant predictors for “discharge to home” were: living with family/caregivers before stroke, higher FIM score at admission, and one or more level(s) of improvement in FIM-MM function group.Conclusions This study identified findings consistent with overseas studies in additional to some new interesting findings. Early prediction of stroke discharge outcomes helps rehabilitation professionals and occupational therapists to focus on the use of appropriate intervention strategies and pre-discharge preparation.