USING THE WOLF MOTOR TEST TO QUANTIFY STROKE UPPER EXTREMITY FUNCTION ON AN INPATIENT STROKE UNIT CAN BE PROBLEMATIC - A RANDOMIZED CONTROLLED TRIAL
Bibliographic record
Abstract
Title: Using the Wolf Motor Test to Quantify Stroke Upper Extremity Function on an Inpatient Stroke Unit can be Problematic - A Randomized Controlled Trial.Authors: Lisa Sheehy PT, PhD 1,3; Christine Yang1,2 MD; Martin Bilodeau PhD1,3; Heidi Sveistrup PhD1,3; Anne Taillon-Hobson PT, MSc 1; Hillel Finestone2,3 MDCM FRCPCInstitution Affiliation: 1. Bruyu00e8re Continuing Care2. University of Ottawa, Division of Physical Medicine and Rehabilitation, Department of Medicine - Bruyu00e8re Continuing Care.3. University of Ottawa, School of Rehabilitation SciencesContext/Objective: Sitting ability and function are commonly impaired after stroke. Balance training has been shown to be helpful, but abundant repetitions are required for optimal recovery and patients must be motivated to perform rehabilitation exercises repeatedly to maximize treatment intensity. Virtual reality training (VRT), which allows patients to interact with a virtual environment using computer software and hardware, is enjoyable and may encourage greater repetition of therapeutic exercises. However, the potential for VRT to promote sitting balance has not yet been explored. The objectives of this randomized controlled trial was to determine if supplemental sitting balance exercises, administered via VRT, improve sitting balance and upper extremity function. The objective of this poster was to determine if the Wolf Motor Function Test (WMFT) is suitable to assess upper extremity function before and after isolated upper extremity virtual reality exercises in patients undergoing inpatient rehabilitation.Design: Secondary analysis of assessor-blinded randomized controlled trial.Setting: Inpatient stroke rehabilitation unit.Participants: Patients with stroke who could sit independently for at least 1 minute but could not stand for more than one minute.Interventions: Group 1: isolated upper extremity VR games. The participantu2019s trunk was restrained with straps. Group 2: VR games that challenged sitting balance. Both groups received 10-12 sessions of 30-45 minutes over 2u00bd weeks. Outcome Measures: Outcome measures were assessed pre, post and 1 month post-intervention. The outcome measure relevant to this poster is the Wolf Motor Function Test (Wolf 1989). The Functional Ability Score (FAS) and the Performance Time Score (PTS) components of the WMFT as well as the number of items completed were assessed.Results: 25/76 participants (33%) completed u22643 of the 15 items on the WMFT. 51/76 completed u226512 items. Therefore two categories of participants on the inpatient stroke unit met the inclusion criteria for the study; those with minimal upper extremity recovery and those with good upper extremity recovery. The resulting non-normal data distribution suggested that the WMFT was not an ideal outcome measure for this sample.Conclusions: The WMFT was not useful to measure change over time in a stroke rehabilitation inpatient sample. The WMFT was designed to monitor progression of individuals with moderate to mild impairment. Patients with stroke who are in inpatient rehabilitation may have a wide range of upper extremity impairment, and on average are more impaired than participants in studies for which the WMFT was designed. Caution must be used when choosing outcome measures of upper extremity function for stroke rehabilitation in-patient population in the future. Ones with greater ability to quantify stroke related weakness, sensory loss and function should be sought.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.179 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".