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Record W4375864071 · doi:10.1177/1753495x231172050

Implementation of a home blood pressure monitoring program for the management of hypertensive disorders of pregnancy, an observational study in British Columbia, Canada

2023· article· en· W4375864071 on OpenAlexaffabout
Karen C. Tran, Sabina Freiman, Tessa Chaworth-Musters, Susan Purkiss, Colleen Foster, Nadia Khan, Wee‐Shian Chan

Bibliographic record

VenueObstetric Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Impact on Reproduction
Canadian institutionsCentre for Advancing Health OutcomesUniversity of British Columbia
Fundersnot available
KeywordsMedicineObservational studyPregnancyBlood pressureGeneralizability theoryEmergency medicineGestational hypertensionObstetricsPandemicPediatricsIntensive care medicineCoronavirus disease 2019 (COVID-19)PreeclampsiaDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Background: COVID-19 pandemic has influenced health care delivery. We conducted an observational study to understand how obstetric medicine (ObM) physicians utilized home blood pressure monitoring (HBPM) to manage hypertension in pregnancy. Methods: Pregnant participants with risk factors or diagnosis of hypertensive disorders of pregnancy (HDP) were enrolled, May 2020-December 2021, and provided with validated home blood pressure (BP) monitor. ObM physicians completed questionnaires to elicit how home BP readings were interpreted to manage HDP. Results: We enrolled 103 people: 44 antepartum patients (33.5 ± 5 years, gestational age of 24 ± 5 weeks); 59 postpartum patients (35 ± 6 years, enrolled 6 ± 4 days post-partum). ObM physicians used range of home BP readings (70%) for management of HDP. Conclusions: HBPM to manage HDP is acceptable and can be used to manage hypertension during pregnancy. Further studies are needed to assess the generalizability of our findings and the safety of HBPM reliance alone in management of HDP.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.147
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.080
GPT teacher head0.367
Teacher spread0.287 · 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 teacher head, 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

Citations5
Published2023
Admission routes2
Has abstractyes

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