Very Early Rehabilitation or Intensive Telemetry after Stroke: A Pilot Randomised Trial
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Stroke patients are more likely to make a good recovery if they receive care in a well-organised stroke unit. However, there are uncertainties about how best to provide such care. We studied 2 key aspects of early stroke unit care: early active mobilisation (EM) and automated monitoring (AM) for physiological complications such as hypoxia. METHODS: This was an observer-blinded, factorial (2 x 2) pilot randomised controlled trial recruiting stroke patients within 36 h of symptom onset. The patients were randomised to 1 of 4 nurse-led treatment protocols: (a) standard stroke unit care, (b) EM, (c) AM or (d) combined EM and AM. The primary outcome was the Rankin score at 3 months. We also report the data on feasibility and safety. RESULTS: We randomised 32 patients (mean age = 65 years; mean baseline modified NIH score = 6). On unadjusted comparisons, the EM patients were significantly (p < 0.05) more likely to mobilise very early (within 1 h of randomisation) and to achieve walking by day 5 and were less likely to develop complications of immobility. The AM group was significantly (p < 0.05) more likely to have pre-defined physiological complication events detected. All these associations remained, but were less statistically significant, after correcting for age, baseline NIH score and co-interventions. There were no significant safety concerns. DISCUSSION: We have demonstrated the feasibility of implementing EM and AM for physiological complications in a randomised controlled trial. Larger trials are warranted to determine whether these interventions have clinical benefits.
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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 | 0.000 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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 it