The beneficial effects of transitional care for patients with stroke: A meta‐analysis
Bibliographic record
Abstract
INTRODUCTION: Transitional care interventions have emerged as a promising method of ensuring treatment continuity and health care coordination when patients are discharged from hospital to home. However, few studies have investigated the frequency and duration of interventions and the effects of interventions on physical function. Therefore, this study aimed to determine the efficacy of transitional care for patients with stroke. METHODS: Six databases and the grey literature were searched to obtain relevant articles from October 1, 2022 to March 10, 2023. The primary outcomes studied were motor performance, walking speed, activities of daily living (ADLs) and caregiver burden following hospital-to-home transitional care. The quality of the studies was assessed with Cochrane risk of bias version 2. The quality and sensitivity of the evidence were assessed to ensure rigour of the findings. Meta-analyses were performed using stata 17.0. RESULTS: A total of 2966 patients were identified from 23 studies. Transitional care improved post-stroke motor performance, walking speed and ADLs, and reduced caregiver burden. CONCLUSION: The findings suggest that provision of transitional care model implementation in patients with stroke is important because it reduces disability in stroke patients and helps to decrease caregivers' burden. IMPACT: The findings of the study emphasize the importance of transitional care programmes for stroke patients after they are discharged from the hospital and returned to their homes. To meet the needs of patients, all levels of health professionals including nurses should be aware of the discharge process and care plan.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| 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".