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Record W2801032799 · doi:10.2196/jmir.8009

A Comparison and Calibration of a Wrist-Worn Blood Pressure Monitor for Patient Management: Assessing the Reliability of Innovative Blood Pressure Devices

2018· article· en· W2801032799 on OpenAlexafffundabout
Sarah Melville, Robert J. Teskey, Shona Philip, Jeremy A. Simpson, Sohrab Lutchmedial, Keith R. Brunt

Bibliographic record

VenueJournal of Medical Internet Research · 2018
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsUniversity of GuelphHorizon Health NetworkSaint John Regional Hospital
FundersFondation de la recherche en santé du Nouveau-BrunswickNatural Sciences and Engineering Research Council of CanadaHeart and Stroke Foundation of Canada
KeywordsBlood pressureMedicineWristCuffDiastoleReliability (semiconductor)SphygmomanometerPressure measurementPhysical therapyCardiologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Clinical guidelines recommend monitoring of blood pressure at home using an automatic blood pressure device for the management of hypertension. Devices are not often calibrated against direct blood pressure measures, leaving health care providers and patients with less reliable information than is possible with current technology. Rigorous assessments of medical devices are necessary for establishing clinical utility. OBJECTIVE: The purpose of our study was 2-fold: (1) to assess the validity and perform iterative calibration of indirect blood pressure measurements by a noninvasive wrist cuff blood pressure device in direct comparison with simultaneously recorded peripheral and central intra-arterial blood pressure measurements and (2) to assess the validity of the measurements thereafter of the noninvasive wrist cuff blood pressure device in comparison with measurements by a noninvasive upper arm blood pressure device to the Canadian hypertension guidelines. METHODS: The cloud-based blood pressure algorithms for an oscillometric wrist cuff device were iteratively calibrated to direct pressure measures in 20 consented patient participants. We then assessed measurement validity of the device, using Bland-Altman analysis during routine cardiovascular catheterization. RESULTS: The precalibrated absolute mean difference between direct intra-arterial to wrist cuff pressure measurements were 10.8 (SD 9.7) for systolic and 16.1 (SD 6.3) for diastolic. The postcalibrated absolute mean difference was 7.2 (SD 5.1) for systolic and 4.3 (SD 3.3) for diastolic pressures. This is an improvement in accuracy of 33% systolic and 73% diastolic with a 48% reduction in the variability for both measures. Furthermore, the wrist cuff device demonstrated similar sensitivity in measuring high blood pressure compared with the direct intra-arterial method. The device, when calibrated to direct aortic pressures, demonstrated the potential to reduce a treatment gap in high blood pressure measurements. CONCLUSIONS: The systolic pressure measurements of the wrist cuff have been iteratively calibrated using gold standard central (ascending aortic) pressure. This improves the accuracy of the indirect measures and potentially reduces the treatment gap. Devices that undergo auscultatory (indirect) calibration for licensing can be greatly improved by additional iterative calibration via intra-arterial (direct) measures of blood pressure. Further clinical trials with repeated use of the device over time are needed to assess the reliability of the device in accordance with current and evolving guidelines for informed decision making in the management of hypertension. TRIAL REGISTRATION: ClinicalTrials.gov NCT03015363; https://clinicaltrials.gov/ct2/show/NCT03015363 (Archived by WebCite at http://www.webcitation.org/6xPZgseYS).

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 imitation

Not 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.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.061
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.085
GPT teacher head0.438
Teacher spread0.352 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2018
Admission routes3
Has abstractyes

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