Prevalence and Factors Associated with Hypertension Among HIV Positive Patients on Antiretroviral Therapy: A Hospital-Based Cross-Sectional Study in Rwanda
Bibliographic record
Abstract
Introduction: The human immunodeficiency virus (HIV) and the use of antiretroviral therapy (ART) are influential elements contributing to hypertension, which is a public health concern particularly in sub-Saharan Africa where its underdiagnosis and limited investigation persist. Moreover, hypertension prevails at higher rates among individuals living with HIV (PLWH) in comparison to the general population. Therefore, our study determined the prevalence of hypertension and its associated factors among PLWH who are undergoing ART treatment at Byumba District Hospital. Methods: A cross-sectional study design was conducted among 406 PLWH over the age of 14 years who were undergoing ART within the HIV department. We performed statistical analyses using STATA version 13. Significant independent variables identified in the bivariate analysis were further exported in a multivariable logistic regression model to ascertain their association with hypertension. This model elucidated factors associated with hypertension, presenting outcomes through odds ratios and their respective 95% confidence intervals, with statistical significance set at p < 0.05. Results: The prevalence of hypertension was 24.7%, which means that roughly 1 in 4 PLWH were hypertensive. Notably, individuals aged 41 years and above demonstrated a significant association with heightened hypertension [AOR = 4.49; 95% CI = 2.45-8.21, p < 0.001] in contrast to those aged between 14 and 40 years. Additionally, smokers [AOR = 12.12; 95% CI = 4.48-32.74, p < 0.001] and individuals with a family history of hypertension [AOR = 4.28; 95% CI = 1.01-18.13, p = 0.049] demonstrated a higher likelihood of hypertension than their counterparts. Moreover, alcohol consumers [AOR = 5.5; 95% CI = 2.75-10.9, p < 0.001] had an increased likelihoods of hypertension compared to non-drinkers. Lastly, diabetics were almost 6 times more likely to be hypotensive [AOR = 4.50; 95% CI = 2.55-7.95, p = 0.018] when compared to those without diabetes. Conclusion: Our findings strongly underscore the urgency for the implementation of targeted programs aimed at enhancing awareness and comprehension of the factors and potential complications tied to hypertension among PLWH. Such programs could be integrated into routine HIV care services to provide patients with the information and skills required to manage their hypertension effectively.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".