A description of functional needs of community-dwelling stroke survivors in Rwanda: a prospective observational cohort study
Bibliographic record
Abstract
PURPOSE: Stroke survivors in low- and middle-income countries have different needs compared to those in high-income countries. Our aim was to describe the unmet functional needs of Rwandan stroke survivors at discharge and three months after stroke. METHODS: A study using an adapted modified Needs Assessment Questionnaire (mNAQ) was conducted at six hospitals in Rwanda. Moderate or severe needs are described using descriptive statistics and logistic regression models. RESULTS: A total of 337 participants, with a mean age of 61 years, were recruited. Most were female (59%), and 70% had an ischemic stroke, while 71% had hypertension. At discharge, 97% of participants had moderate to severe needs. Follow-up at three months was available for 78% of participants and 22% died. At three months, over 70% of participants continued to have moderate to severe needs. CONCLUSIONS: Almost all Rwandan stroke survivors have moderate to severe needs and disability at the time of discharge, and for those that survive, over 70% continue to have moderate to severe needs at 3 months. This estimate is much higher than previously reported. Improving functioning in the community is essential for Rwandan stroke survivors.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".