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Record W2909534334 · doi:10.1177/1753495x18819338

Out-of-office blood pressure measurement for the diagnosis of hypertension in pregnancy: Survey of Canadian Obstetric Medicine and Maternal Fetal Medicine specialists

2019· article· en· W2909534334 on OpenAlexafffundabout
KC Tran, Jayson Potts, Julie Robertson, Kathleen N. Ly, Natalie Dayan, NA Khan, Wee‐Shian Chan

Bibliographic record

VenueObstetric Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsCentre for Advancing Health OutcomesMcGill University Health CentreUniversity of British Columbia
FundersHypertension Canada
KeywordsMedicineBlood pressurePregnancyAmbulatory blood pressureObstetricsMaternal-fetal medicineAmbulatoryHypertension in PregnancyEmergency medicinePreeclampsiaObstetrics and gynaecologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Multiple hypertension guidelines recommend out-of-office measurements for the diagnosis of hypertension in non-pregnant adults, whereas pregnancy guidelines recommend in-office blood pressure measurements. The objective of our study was to determine how Canadian Obstetric Medicine and Maternal Fetal Medicine specialists measure blood pressure in pregnancy. METHODS: An email survey was sent to 69 Canadian Obstetric Medicine and Maternal Fetal Medicine specialists in academic centers across Canada to explore the practice patterns of blood pressure measurement in pregnant women. RESULTS: The response rate was 48%. The majority of respondents (63.6%) preferred office blood pressure measurement for diagnosing hypertension, but relied on home blood pressure readings for ongoing monitoring and management of hypertension during pregnancy (59.4%). The preferred method of out-of-office blood pressure measurement was home monitoring; 24-hour ambulatory blood pressure monitoring was not used due to limited availability and cost. CONCLUSIONS: There is wide practice variation in methods of measuring blood pressure among Canadian specialists managing hypertension in pregnancy.

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)0.002
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.670
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.003
Science and technology studies0.0000.001
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 head0.121
GPT teacher head0.282
Teacher spread0.160 · 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.

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

Citations4
Published2019
Admission routes3
Has abstractyes

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