Weak and fragmented regulatory frameworks on the accuracy of blood pressure‐measuring devices pose a major impediment for the implementation of HEARTS in the Americas
Bibliographic record
Abstract
Global HEARTS is a WHO initiative for cardiovascular disease prevention and control. Accurate blood pressure (BP) measurement is an essential component of the initiative. This study aimed to determine the regulatory frameworks governing the accuracy of BPMDs in countries of the Americas participating in the HEARTS initiative. Quantitative and qualitative analysis of the laws and regulations relevant to ensuring the accuracy of BPMDs were determined from the Ministries of Health/Regulatory Agencies among 13 countries in Latin America and the Caribbean. Analysis included characterizing the scope of regulations (ie, pre-market approval, sales and promotion, labeling, cuff sizes, and procurement), information systems for monitoring the models of BPMDs used in primary health care (PHC), and systems to enforce compliance with regulations. Ten of the 13 countries had medical device laws, but regulations that specifically address BPMDs only existed in three countries. Only one country (Brazil) had regulations for mandatory accuracy validation testing and only two countries regulated internet sales of BPMDs. Labeling and cuff size regulations existed in four and two countries, respectively. Less than half the countries reported having a data repository on the BPMD models being used in PHC facilities (four countries) or sold (five countries). Weak and fragmented regulatory frameworks on the accuracy of BPMDs exist among countries of the Americas. This will adversely affect the accuracy of blood pressure assessment and hence poses a major impediment for successful implementation of HEARTS initiative.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".