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Record W3145986338 · doi:10.2196/27496

Wireless Home Blood Pressure Monitoring System With Automatic Outcome-Based Feedback and Financial Incentives to Improve Blood Pressure in People With Hypertension: Protocol for a Randomized Controlled Trial

2021· article· en· W3145986338 on OpenAlexvenueno aff
Marcel Bilger, Agnes Koong, Ian Kwong Yun Phoon, Ngiap Chuan Tan, Juliana Bahadin, Joann Bairavi, Ada Portia M Batcagan-Abueg, Eric Finkelstein

Bibliographic record

VenueJMIR Research Protocols · 2021
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsnot available
FundersNational Medical Research CouncilMedical Research Council
KeywordsBlood pressureMedicineRandomized controlled trialIncentivePrehypertensionEmergency medicineInternal medicineCardiologyIntensive care medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Hypertension is prevalent in Singapore and is a major risk factor for cardiovascular morbidity and mortality and increased health care costs. Strategies to lower blood pressure include lifestyle modifications and home blood pressure monitoring. Nonetheless, adherence to home blood pressure monitoring remains low. This protocol details an algorithm for remote management of primary care patients with hypertension. OBJECTIVE: The objective of this study was to determine whether wireless home blood pressure monitoring with or without financial incentives is more effective at reducing systolic blood pressure than nonwireless home blood pressure monitoring (usual care). METHODS: This study was designed as a randomized controlled open-label superiority study. A sample size of 224 was required to detect differences of 10 mmHg in average systolic blood pressure. Participants were to be randomized, in the ratio of 2:3:3, into 1 of 3 parallel study arms :(1) usual care, (2) wireless home blood pressure monitoring, and (3) wireless home blood pressure monitoring with financial incentives. The primary outcome was the mean change in systolic blood pressure at month 6. The secondary outcomes were the mean reduction in diastolic blood pressure, cost of financial incentives, time taken for the intervention, adherence to home blood pressure monitoring, effectiveness of the framing of financial incentives in decreasing nonadherence to blood pressure self-monitoring and the adherence to antihypertensive medication at month 6. RESULTS: This study was approved by SingHealth Centralised Institutional Review Board and registered. Between January 24, 2018 and July 10, 2018, 42 participants (18.75% of the required sample size) were enrolled, and 33 participants completed the month 6 assessment by January 31, 2019. CONCLUSIONS: Due to unforeseen events, the study was stopped prematurely; therefore, no results are available. Depending on the blood pressure information received from the patients, the algorithm can trigger immediate blood pressure advice (eg, Accident and Emergency department visit advice for extremely high blood pressure), weekly feedback on blood pressure monitoring, medication titration, or skipping of routine follow-ups. The inclusion of financial incentives framed as health capital provides a novel idea on how to promote adherence to remote monitoring, and ultimately, improve chronic disease management. TRIAL REGISTRATION: ClinicalTrials.gov NCT03368417; https://clinicaltrials.gov/ct2/show/NCT03368417. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/27496.

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)0.030
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.073
Threshold uncertainty score0.245

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.027
Meta-epidemiology (narrow)0.0060.003
Meta-epidemiology (broad)0.0130.007
Bibliometrics0.0030.004
Science and technology studies0.0030.004
Scholarly communication0.0050.003
Open science0.0040.002
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0730.012

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 head0.071
GPT teacher head0.410
Teacher spread0.339 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations1
Published2021
Admission routes1
Has abstractyes

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