Effectiveness of a Health Education Program to Reduce Recurrence of Stroke by Controlling Modifiable Risk Factors in a Specialized Hospital in Bangladesh: Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Health education could be an effective way to increase knowledge regarding behavioral changes to prevent the recurrence of stroke; however, the evidence is ambiguous. A lack of both knowledge and compliance with treatment to control modifiable risk factors and unhealthy lifestyles increases the risk of stroke recurrence. OBJECTIVE: This study aimed to evaluate the effectiveness of a health education program among patients with stroke postdischarge and their family caregivers in a tertiary specialized hospital in Bangladesh to reduce stroke recurrence by controlling modifiable risk factors. METHODS: A parallel (1:1), open-label, prospective randomized controlled trial was conducted in Bangladesh. A total of 432 patients with first-time stroke, aged ≥18 years and a modified Rankin Scale (mRS) score of 0-4, were randomly enrolled at the National Institute of Neuroscience & Hospital. We stratified the patients by age and type of stroke and randomly allocated to an intervention group (IG) and a control group (CG). We collected sociodemographic and clinical data by using a structured questionnaire. The IG received (self) management education, including monitoring blood pressure (BP), medication, diet, and exercise for 12 months, and the CG received usual care. The outcomes were (1) recurrence after 28 days of stroke and (2) all adverse events related to stroke after 12-month follow-up. RESULTS: Of 432 patients (n=216, 50%, in each group), stroke recurrence was observed 14 (6.5%) patients in the IG and 8 (3.7%) patients in the CG, and the difference was not significant (P=.19). Death was lower in the IG (n=39, 18.1%, vs n=56, 25.9%) compared to the CG. In Cox regression analysis, the unadjusted model showed death was significant (hazard ratio [HR] 1.531, 95% CI 1.017-2.304; P=.04); however, the difference was not significant after adjusting the mRS score at baseline (HR 0.818, 95% CI 0.540-1.238; P=.34). Patients' medication adherence significantly improved at 6-month (P<.001) and 12-month (P=.002) follow-up after the intervention. CONCLUSIONS: This study failed to demonstrate the effectiveness of health education in reducing recurrence, death, and stroke-related adverse events. However, health education enhanced medication adherence. Some causes of death could not be diagnosed due to inadequate health care systems. Further research with diagnostic facilities and a long observation period is necessary to explore the underlying cause of recurrence. The results suggest the importance of structuring acute care management for patients with stroke into the health care system of Bangladesh. TRIAL REGISTRATION: ClinicalTrials.gov NCT05520034; https://clinicaltrials.gov/ct2/show/NCT05520034.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".