Abstract
BackgroundIn clinical practice, therapists often rely on clinical outcome measures to quantify a patient’s impairment and function. Predicting a patient’s discharge outcome using baseline clinical information may help clinicians design more targeted treatment strategies and better anticipate the patient’s assistive needs and discharge care plan. The objective of this study was to develop predictive models for four standardized clinical outcome measures (Functional Independence Measure, Ten-Meter Walk Test, Six-Minute Walk Test, Berg Balance Scale) during inpatient rehabilitation.MethodsFifty stroke survivors admitted to a United States inpatient rehabilitation hospital participated in this study. Predictors chosen for the clinical discharge scores included demographics, stroke characteristics, and scores of clinical tests at admission. We used the Pearson product-moment and Spearman’s rank correlation coefficients to calculate correlations among clinical outcome measures and predictors, a cross-validated Lasso regression to develop predictive equations for discharge scores of each clinical outcome measure, and a Random Forest based permutation analysis to compare the relative importance of the predictors.ResultsThe predictive equations explained 70–77% of the variance in discharge scores and resulted in a normalized error of 13–15% for predicting the outcomes of new patients. The most important predictors were clinical test scores at admission. Additional variables that affected the discharge score of at least one clinical outcome were time from stroke onset to rehabilitation admission, age, sex, body mass index, race, and diagnosis of dysphasia or speech impairment.ConclusionsThe models presented in this study could help clinicians and researchers to predict the discharge scores of clinical outcomes for individuals enrolled in an inpatient stroke rehabilitation program that adheres to U.S. Medicare standards.
Highlights
In clinical practice, therapists often rely on clinical outcome measures to quantify a patient’s impairment and function
From admission to discharge, Functional Independence Measure [4] (FIM) scores increased by 47.5% (26.6 points), walking speed from TMWT increased by 61.7% (0.29 m/s), walking endurance from Six-Minute Walk Test [18] (SMWT) increased by 82% (185 m), and Berg Balance Scale [17] (BBS) scores increased by 43% (9 points)
The strongest correlation was found between the TMWT and SMWT at admission
Summary
Therapists often rely on clinical outcome measures to quantify a patient’s impairment and function. Predicting a patient’s discharge outcome using baseline clinical information may help clinicians design more targeted treatment strategies and better anticipate the patient’s assistive needs and discharge care plan. The objective of this study was to develop predictive models for four standardized clinical outcome measures (Functional Independence Measure, Ten-Meter Walk Test, Six-Minute Walk Test, Berg Balance Scale) during inpatient rehabilitation. Clinicians use standardized assessment tools or clinical outcome measures such as the Functional Independence Measure [4] (FIM) for level of disability or the Ten-Meter Walk Test [5] (TMWT) for walking ability. Clinicians assess a patient’s functional abilities based on performance in these standardized tests, such as classifying patients as household ambulators or limited community ambulators based on walking speed score from the TMWT [8, 9]. Estimating a patient’s future discharge scores early in a rehabilitation program would help clinicians set realistic rehabilitation goals and anticipate needs for additional care or medical equipment at discharge
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