P27 Non-validated Blood Pressure Devices Dominate the Online Marketplace: An Initiative of the Lancet Commission on Hypertension Group
Bibliographic record
Abstract
Abstract Introduction Home BP monitoring is recommended to guide clinical decisions on hypertension and is used worldwide. People make their own decisions when purchasing BP measurement devices, which are often made online. One potential barrier to accurate home BP monitoring is that patients may purchase an unvalidated device (one that has not been proven accurate according to an internationally sanctioned protocol). This study aimed to evaluate the number, type, percentage validated and cost of home BP devices available online. Methods A systematic search of online businesses selling BP devices that may be used for home BP monitoring was conducted. Multinational companies make international deliveries, so searches were restricted to BP devices available for one nation (Australia) as an example of device availability through the globally connected online marketplace. Validation status of BP devices was determined according to established protocols. Results 59 online businesses, selling 972 unique BP devices were identified. These included 278 upper-arm cuff devices (18.3% validated), 162 wrist-cuff devices (8.0% validated) and 532 wrist-band wearables (0% validated). Most BP devices (92.4%) were stocked by international ‘e-commerce’ businesses (e.g. eBay, Amazon), but only 5.5% of these were validated. Validated cuff BP devices were more expensive than non-validated devices: median (interquartile range) of 101.14 (75.00 to 151.50; versus 67.37 (30.40 to 112.83) AUD, p < 0.0001. Conclusion Non-validated BP devices dominate the online marketplace and are sold at lower cost than validated devices. The widespread use of non-validated BP devices is a barrier to accurate home BP monitoring and must be urgently addressed.
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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 | 0.020 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".