Monitoring changes in locomotion-related daily life activities in post-stroke patients: the responsiveness of ABILOCO-Benin questionnaire
Bibliographic record
Abstract
Purpose To investigate the responsiveness of ABILOCO-Benin questionnaire, a West-African adapted questionnaire of performance in locomotion-related daily-life activities in adults with stroke.Materials and methods We conducted a longitudinal study involving 81 stroke patients (mean (SD) age: 54.6 (10.8) years; 58% male, mean (SD) time after stroke onset: 4.3 (2.5) weeks). Participants were assessed at baseline (T1), two-month later (T2), and on average of 1.5 (0.5) years after stroke (T3), with the ABILOCO-Benin questionnaire, functional ambulation classification (FAC), six-minute walking test, ACTIVLIM-Stroke questionnaire, modified Rankin Scale, and Stroke Impairment Assessment Scale. Global-, sub-group- (stable and improved based on FAC scores), and individual-based analysis of changes were performed.Results Participants showed significantly larger improvement for all outcomes during the acute phase (T1–T2). Changes in the ABILOCO-Benin measures were significantly correlated with changes in other outcome measures. ABILOCO-Benin questionnaire detected a significant improvement in both the stable and improved groups at both T2 and T3 in the sub-group approach. Individual-based analysis with ABILOCO-Benin measures showed a significantly higher proportion of stable patients (n = 55) and lower proportion of improved ones (n = 23) between T2 and T3 (LR(df) = 15.52(4), p = 0.004).Conclusions ABILOCO-Benin is responsive to changes in adult stroke patients within both acute and chronic phases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".