ENHANCE proof-of-concept three-arm randomized trial: effects of reaching training of the hemiparetic upper limb restricted to the spasticity-free elbow range
Bibliographic record
Abstract
Post-stroke motor recovery processes remain unknown. Timescales and patterns of upper-limb (UL) recovery suggest a major impact of biological factors, with modest contributions from rehabilitation. We assessed a novel impairment-based training motivated by motor control theory where reaching occurs within the spasticity-free elbow range. Patients with subacute stroke (≤ 6 month; n = 46) and elbow flexor spasticity were randomly allocated to a 10-day UL training protocol, either personalized by restricting reaching to the spasticity-free elbow range defined by the tonic stretch reflex threshold (TSRT) or non-personalized (non-restricted) and with/without anodal transcranial direct current stimulation. Outcomes assessed before, after, and 1 month post-intervention were elbow flexor TSRT angle and reach-to-grasp arm kinematics (primary) and stretch reflex velocity sensitivity, clinical impairment, and activity (secondary). Results were analyzed for 3 groups as well as those of the effects of impairment-based training. Clinical measures improved in both groups. Spasticity-free range training resulted in faster and smoother reaches, smaller (i.e., better) arm-plane path length, and closer-to-normal shoulder/elbow movement patterns. Non-personalized training improved clinical scores without improving arm kinematics, suggesting that clinical measures do not account for movement quality. Impairment-based training within a spasticity-free elbow range is promising since it may improve clinical scores together with arm movement quality.Clinical Trial Registration: URL: http://www.clinicaltrials.gov . Unique Identifier: NCT02725853; Initial registration date: 01/04/2016.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".