Clinical and Kinematic Data of the ENHANCE trial in patients with stroke
Bibliographic record
Abstract
Clinical and kinematic data from a clinical trial involving a novel training approach motivated by motor control theory where reaching training was done within a spasticity-free elbow extension ranges determined individually or in a non-specific range. Patients with subacute stroke (≤6mo; n=46) and elbow flexor spasticity were randomly allocated to a 10-day upper limb training protocol, either personalized by restricting reaching to the spasticity-free range defined by the tonic stretch reflex threshold (TSRT) of elbow flexors or non-personalized (non-restricted). Outcomes assessed before, after, and one-month post-intervention were elbow flexor TSRT angle and reach-to-grasp arm kinematics (primary), and stretch reflex velocity sensitivity, clinical measures of impairment, and activity levels (secondary). Ethical approval was obtained from the appropriate ethics committees before the beginning of the study. The Centre de Recherche Interdisciplinaire en Réadaptation du Montréal Métropolitain (Montréal, Canada) approved the study for the Jewish Rehabilitation Hospital and the Institut de Réadaptation Gingras-Lindsay de Montréal (CRIR1112-1115). The Institutional Ethics Review Board of Loewenstein Rehabilitation Hospital (Ra’anana, Israel) approved the study for the Loewenstein Rehabilitation Hospital (000-11-15-LOE) and the Institutional Ethics Committee of Tel Aviv University (Tel Aviv, Israel). The Institutional Ethics Committee of Kasturba Hospital (Manipal, India) approved the study for the Kasturba Medical Hospital (IEC-32/2016). The database includes 2 files: ENHANCE_RawData.xlsx - data file ENHANCE-Clinical and Kinematic Raw Data Definitions.doc - data definitions file
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".