Assessment of Cardiovascular Risk for Prevention and Control of Cardiovascular Disease in Ghana’s Northern Region A Cross-sectional Study of 4 Rural Districts using World Health Organization / International Society of Hypertension (WHO/ISH) Risk Prediction Charts
Bibliographic record
Abstract
Ghana is experiencing an increase in cardiovascular (CVD) -related mortality with poor rural communities suffering greater complications and premature deaths. The point of this exploratory research is to evaluate the prevalence of CVD risk factors and to calculate the cardiovascular risk among adults aged > 40 years in Ghana’s Northern Region. A cross-sectional study was performed with 536 subjects. A pre-tested questionnaire, anthropometric measurements, and standardized WHO/ISH risk prediction charts assessed for 10-year risk of a fatal or non-fatal major cardiovascular event according to age, sex, blood pressure, smoking status, and diabetes mellitus status. Low, moderate and high CVD prevalence risk in females was 88.4%, 7.1%, and 4.5% while in males the prevalence was 91.3%, 5.8%, and 2.9%, respectively. Hypertension was noted as a clinically significant risk factor with females at 37.3% versus males at 32%. The 10-year risk of a fatal or non-fatal cardiovascular event was statistically significant for females according to age group. A moderate to high CVD risk of a fatal or non-fatal cardiovascular event was found in 10.4% of subjects. Notable CVD risk factors included a high prevalence of hypertension. Decentralizing care to local village healthcare facilities is one way to tackle cardiovascular risk reduction. Task shifting of primary care duties from physicians to nurses in terms of cardiovascular (CV) risk assessment and management of uncomplicated CV risk factors is a potential solution to the acute shortage of trained health staffs for the control and prevention of CVD in Northern Ghana.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".