Cuffless Blood Pressure Devices
Bibliographic record
Abstract
Hypertension is associated with more end-organ damage, cardiovascular events, and disability-adjusted life years lost in the United States compared with all other modifiable risk factors. Several guidelines and scientific statements now endorse the use of out-of-office blood pressure (BP) monitoring with ambulatory BP monitoring or home BP monitoring to confirm or exclude hypertension status based on office BP measurement. Current ambulatory or home BP monitoring devices have been reliant on the placement of a BP cuff, typically on the upper arm, to measure BP. There are numerous limitations to this approach. Cuff-based BP may not be well-tolerated for repeated measurements as is utilized with ambulatory BP monitoring. Furthermore, improper technique, including incorrect cuff placement or use of the wrong cuff size, may lead to erroneous readings, affecting diagnosis and management of hypertension. Compared with devices that utilize a cuff, cuffless BP devices may overcome challenges related to technique, tolerability, and overall utility in the outpatient setting. However, cuffless devices have several potential limitations that limit its routine use for the diagnosis and management of hypertension. The review discusses the different approaches for determining BP using various cuffless devices including engineering aspects of cuffless device technologies, validation protocols to test accuracy of cuffless devices, potential barriers to widespread implementation, and future areas of research. This review is intended for the clinicians who utilize out-of-office BP monitoring for the diagnosis and management of hypertension.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".