Addressing global disparities in blood pressure control: perspectives of the International Society of Hypertension
Bibliographic record
Abstract
ABSTRACT: Raised blood pressure (BP) is the leading cause of preventable death in the world. Yet, its global prevalence is increasing, and it remains poorly detected, treated, and controlled in both high- and low-resource settings. From the perspective of members of the International Society of Hypertension based in all regions, we reflect on the past, present, and future of hypertension care, highlighting key challenges and opportunities, which are often region-specific. We report that most countries failed to show sufficient improvements in BP control rates over the past three decades, with greater improvements mainly seen in some high-income countries, also reflected in substantial reductions in the burden of cardiovascular disease and deaths. Globally, there are significant inequities and disparities based on resources, sociodemographic environment, and race with subsequent disproportionate hypertension-related outcomes. Additional unique challenges in specific regions include conflict, wars, migration, unemployment, rapid urbanization, extremely limited funding, pollution, COVID-19-related restrictions and inequalities, obesity, and excessive salt and alcohol intake. Immediate action is needed to address suboptimal hypertension care and related disparities on a global scale. We propose a Global Hypertension Care Taskforce including multiple stakeholders and societies to identify and implement actions in reducing inequities, addressing social, commercial, and environmental determinants, and strengthening health systems implement a well-designed customized quality-of-care improvement framework.
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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 | 0.015 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".