Hypertension prevalence and knowledge assessment in rural Haiti.
Bibliographic record
Abstract
OBJECTIVE: Hypertension is an important risk factor for cardiovascular disease throughout the world. Little is known about the prevalence of hypertension in rural Haiti. Our study aims to estimate prevalence and knowledge of hypertension in Northern Haiti. DESIGN: Cross-sectional. SETTING: Four rural communities surrounding Milot, Haiti. PARTICIPANTS: Participants (69 males, 106 females, 175 total) were eligible to take part if they were aged > 18 years and not pregnant. Enrollment was voluntary. METHODS: Two initial blood pressure measurements were taken for each participant. Participants who had an average systolic blood pressure > or = 140 mm Hg or diastolic blood pressure > or = 90 mm Hg were instructed to return in 1 week for two additional confirmatory measurements. Based on these measures, participants were classified as either hypertensive or not. All participants were surveyed to assess their knowledge of hypertension. RESULTS: The prevalence of hypertension among the study sample was 36.6%. Overall, 47% of women and 21% of men were hypertensive. Approximately 30% of women of reproductive age (18-39 years) were hypertensive. Participants showed little knowledge of the asymptomatic nature of hypertension and the need for lifelong treatment. CONCLUSIONS: Hypertension is prevalent in Haiti. The high prevalence of hypertension among women of reproductive age is a concern since it is a risk factor for cardiovascular disease. Lack of knowledge surrounding hypertension indicates low awareness of the condition and is a possible target for future educational interventions.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 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".