Undiagnosed Isolated Systolic and Diastolic Hypertension Subtypes and Their Correlates in Bangladesh: A Nationwide Survey
Bibliographic record
Abstract
OBJECTIVES: This study was performed to identify the distribution of undiagnosed isolated hypertension subtypes and their correlates amongst adults aged 35 years and older in Bangladesh using data from the Bangladesh Demography and Health Survey 2011. METHODS: Out of a total of 17,964 selected households, 7,880 were included in the final analysis for this study. Systolic and diastolic blood pressure (BP) were measured 3× at 10-minute intervals. Hypertension subtypes were defined for individuals not under antihypertensive treatment as systolic-diastolic hypertension (SDH): systolic BP (SBP) ≥ 140 mm Hg and diastolic BP (DBP) ≥ 90 mm Hg; isolated diastolic hypertension (IDH): SBP < 140 mm Hg and DBP ≥ 90 mm Hg, and isolated systolic hypertension (ISH): SBP ≥140 mm Hg and DBP < 90 mm Hg. RESULTS: The predominant hypertension subtypes were SDH and IDH [5.2%; 95% confidence interval (CI): 4.7-5.1] followed by ISH (3.8%; 95% CI: 3.4-4.2). Multiple logistic regression showed that age and gender were significant predictors of ISH. SDH was associated with females [odds ratio (OR): 1.8; 95% CI: 1.3-2.6], the older age group (OR-7.4; 95% CI: 4.3-12.7), and overweight or obese individuals (OR: 1.6; 95% CI: 1.1-2.4). Non-manual work (OR: 1.5; 95% CI: 1.0-2.0]) and being overweight or obese (OR: 1.9; 95% CI: 1.4-2.8) were factors associated with IDH. CONCLUSION: ISH, IDH and SDH represent salient subtypes of hypertension in Bangladesh. To identify preventive intervention for averting adverse cardiovascular events, further research is needed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".