A global perspective on the costs of hypertension: a systematic review
Bibliographic record
Abstract
INTRODUCTION: Hypertension, particularly untreated, leads to serious complications and contributes to high costs incurred by the whole society. The aim of the review was to carry out a social and economic comparison of various categories of hypertension costs from different countries. MATERIAL AND METHODS: The study was a systematic review. PubMed, Cochrane Library and Google Scholar databases were searched. Hypertension costs were analyzed in 8 cost categories. An attempt was made to determine whether selected economic and social factors (such as HDI or GDP) influenced hypertension costs. RESULTS: The review included data from 15 countries: Brazil, Cambodia, Canada, China, Greece, Indonesia, Italy, Jamaica, Kyrgyzstan, Mexico, Poland, Spain, USA, Vietnam and Zimbabwe. The papers included in the review were heterogeneous with respect to cost categories, which made comparisons difficult. The average total costs of hypertension for all the studied countries, calculated per person, amounted to 630.14 Int$, direct costs - 1,497.36 Int$, and indirect costs - 282.34 Int$. The ranking of countries by costs and by selected economic and social indices points at the possible relationship between these indices and hypertension costs. CONCLUSIONS: The costs of hypertension calculated per country reached the region of several dozen billion Int$. Other sources usually showed lower costs than those presented in this review. This indicates a growth in costs from year to year and the future increasing burden on society. Globally uniform cost terminology and cost calculation standards need to be developed. That would facilitate making more informed decisions regarding fund allocation in hypertension management schemes.
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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 | 0.008 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".