Bridging the gap: the effectiveness of teaming a stroke coordinator with patient's personal physician on the outcome of stroke
Bibliographic record
Abstract
OBJECTIVES: to test the hypothesis as to whether persons newly discharged into the community following an acute stroke and assigned a stroke case manager would experience, compared to usual post-hospital care, better health-related quality of life (HRQL), fewer emergency room visits and less non-elective hospitalisations. DESIGN: a stratified, balanced, evaluator-blinded, randomised clinical trial. SETTING: five university-affiliated acute-care hospitals in Montreal, Quebec, Canada. PARTICIPANTS: persons (n = 190) returning home directly from the acute-care hospital following a first or recurrent stroke with a need for health care supervision post-discharge because of low function, co-morbidity, or isolation. INTERVENTION: for 6 weeks following hospital discharge a nurse stroke care manager maintained contact with patients through home visits and telephone calls designed to coordinate care with the person's personal physician and link the stroke survivor into community-based stroke services. MEASUREMENTS: the primary outcome was the Physical Component Summary (PCS) of the Short-Form (SF)-36 survey. A secondary outcome was utilisation of health services. Also measured was the impact of stroke on functioning. Measurements were made at hospital discharge (baseline), following the 6-week intervention and at 6-months post-stroke. RESULTS: the average age of the participants was 70 years. Discharge was achieved on average 12 days post-stroke and most participants had had a stroke of moderate severity. There were no differences between groups on the primary outcome measure, health services utilisation, or any of the secondary outcome measures. CONCLUSION: for this population, there was no evidence that this type of passive case management inferred any added benefit in terms of improvement in health-related quality of life or reduction in health services utilisation and stroke impact, than usual post-discharge management.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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".