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Record W4389958777 · doi:10.2196/49592

Home Blood Pressure Telemonitoring Technology for Patients With Asymptomatic Elevated Blood Pressure Discharged From the Emergency Department: Pilot Study

2023· article· en· W4389958777 on OpenAlexafffundvenueabout
Karen C. Tran, Meagan Mak, Laura M. Kuyper, Jesse Bittman, Birinder Mangat, Heather Lindsay, Chad Kim Sing, Liang Xu, Hubert Wong, Martin Dawes, Nadia Khan, Kendall Ho

Bibliographic record

VenueJMIR Formative Research · 2023
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsCentre for Advancing Health OutcomesUniversity of British Columbia
FundersVancouver Coastal Health Research Institute
KeywordsMedicineAsymptomaticBlood pressureEmergency departmentTelehealthEmergency medicineTelemedicineInternal medicineHealth careNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Hypertension affects 1 in 5 Canadians and is the leading cause of morbidity and mortality globally. Hypertension control is declining due to multiple factors including lack of access to primary care. Consequently, patients with hypertension frequently visit the emergency department (ED) due to high blood pressure (BP). Telehealth for Emergency-Community Continuity of Care Connectivity via Home-Telemonitoring Blood Pressure is a pilot project that implements and evaluates a comprehensive home blood pressure telemonitoring (HBPT) and physician case management protocol designed as a postdischarge management strategy to support patients with asymptomatic elevated BP as they transition from the ED to home. OBJECTIVE: Our objective was to conduct a feasibility study of an HBPT program for patients with asymptomatic elevated BP discharged from the ED. METHODS: Patients discharged from an urban, tertiary care hospital ED with asymptomatic elevated BP were recruited in Vancouver, British Columbia, Canada, and provided with HBPT technology for 3 months of monitoring post discharge and referred to specialist hypertension clinics. Participants monitored their BP twice in the morning and evenings and tele-transmitted readings via Bluetooth Sensor each day using an app. A monitoring clinician received these data and monitored the patient's condition daily and adjusted antihypertensive medications. Feasibility outcomes included eligibility, recruitment, adherence to monitoring, and retention rates. Secondary outcomes included proportion of those who were defined as having hypertension post-ED visits, changes in mean BP, overall BP control, medication adherence, changes to antihypertensive medications, quality of life, and end user experience at 3 months. RESULTS: A total of 46 multiethnic patients (mean age 63, SD 17 years, 69%, n=32 women) found to have severe hypertension (mean 191, SD 23/mean 100, SD 14 mm Hg) in the ED were recruited, initiated on HBPT with hypertension specialist physician referral and followed up for 3 months. Eligibility and recruitment rates were 40% (56/139) and 88% (49/56), respectively. The proportion of participants that completed ≥80% of home BP measurements at 1 and 3 months were 67% (31/46) and 41% (19/46), respectively. The proportion of individuals who achieved home systolic BP and diastolic BP control at 3 months was 71.4% (30/42) and 85.7% (36/42) respectively. Mean home systolic and diastolic BP improved by -13/-5 mm Hg after initiation of HBPT to the end of the study. Patients were prescribed 1 additional antihypertensive medication. No differences in medication adherence from enrollment to 3 months were noted. Most patients (76%, 25/33) were highly satisfied with the HBPT program and 76% (25/33) found digital health tools easy to use. CONCLUSIONS: HBPT intervention is a feasible postdischarge management strategy and can be beneficial in supporting patients with asymptomatic elevated BP from the ED. A randomized trial is underway to evaluate the efficacy of this intervention on BP control.

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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.049
GPT teacher head0.354
Teacher spread0.305 · 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 designNon-randomized trial
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

Citations3
Published2023
Admission routes4
Has abstractyes

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