Comparison of Three Instruments for Activity Disability in Acute Ischemic Stroke Survivors
Bibliographic record
Abstract
BACKGROUND: Disabilities in physical activity and functional independence affect the early rehabilitation of stroke survivors. Moreover, a good instrument for assessing activity disability allows accurate assessment of physical disability and assists in prognosis determination. OBJECTIVE: To compare three assessment tools for physical activity in acute-phase stroke survivors. METHODS: We conducted this prospective observational study at an affiliated hospital of a Medical University in Shanghai, China, from June 2018 to November 2019. We administered three instruments to all patients during post-stroke days 5-7, including the Modified Barthel Index (MBI), Instrumental Activities of Daily Living (IADL), and modified Rankin scale (mRs). We analyzed correlations among the aforementioned scales and the National Institutes of Health Stroke Scale (NIHSS) using Spearman's rank-order correlations test. Univariate analyses were performed using the Mann-Whitney U test. We used a binary logistic regression model to assess the association between the NIHSS (30 days) and patient-related variables. Finally, we used receiver operating characteristic (ROC) curves to assess the predictive value of the multivariate regression models. RESULTS: There was a high correlation among the three instruments; furthermore, the MBI had a higher correlation with the NIHSS (days 5-7). The NIHSS (day 30) was correlated with thrombolysis. ROC analysis revealed that the mRs-measured disability level had the highest predictive value of short-term stroke severity (30 days). CONCLUSION: The MBI was the best scale for measuring disability in physical activity, whereas the mRs showed better accuracy in short-term prediction of stroke severity.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".