Nonvalidated Home Blood Pressure Devices Dominate the Online Marketplace in Australia
Bibliographic record
Abstract
Self-home blood pressure (BP) monitoring is recommended to guide clinical decisions on hypertension and is used worldwide for cardiovascular risk management. People usually make their own decisions when purchasing BP devices, which can be made online. If patients purchase nonvalidated devices (those not proven accurate according to internationally accepted standards), hypertension management may be based on inaccurate readings resulting in under- or over-diagnosis or treatment. This study aimed to evaluate the number, type, percentage validated, and cost of home BP devices available online. A search of online businesses selling devices for home BP monitoring was conducted. Multinational companies make worldwide deliveries, so searches were restricted to BP devices available for one nation (Australia) as an example of device availability through the global online marketplace. Validation status of BP devices was determined according to established protocols. Fifty nine 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 (eg, eBay, Amazon), but only 5.5% were validated. Validated cuff BP devices were more expensive than nonvalidated devices: median (interquartile range) of 101.1 (75.0-151.5) versus 67.4 (30.4-112.8) Australian Dollars. Nonvalidated BP devices dominate the online marketplace and are sold at lower cost than validated ones, which is a major barrier to accurate home BP monitoring and cardiovascular risk management. Before purchasing a BP device, people should check it has been validated at https://www.stridebp.org.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".