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Record W4415622362 · doi:10.1177/1753495x251386568

The impact of COVID-19 on the management of hypertensive disorders of pregnancy: An assessment of quality of care and outcomes

2025· article· en· W4415622362 on OpenAlexaffabout
Celya Tidafi, Annabelle Cumyn, Mandy Malick, Abla Alj, Leena Toban, Élisabeth Gagnon, Samuel Lemaire‐Paquette, Marie‐Ève Roy‐Lacroix, Anne‐Marie Côté

Bibliographic record

VenueObstetric Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Impact on Reproduction
Canadian institutionsCentre Hospitalier Universitaire de Sherbrooke
Fundersnot available
KeywordsTelehealthTelemedicineContinuity of careFlexibility (engineering)Quality (philosophy)Quality managementPrenatal careMEDLINE

Abstract

fetched live from OpenAlex

Background: Hypertensive disorders of pregnancy (HDP) affect up to 10% of women and require close monitoring to prevent adverse outcomes. The COVID-19 pandemic disrupted in-person care, prompting adaptations in follow-up strategies. This study assesses the pandemic's impact on HDP management at a Quebec tertiary-level health center. Methods: A retrospective cohort study compared a pandemic group to a prepandemic matched control group of pregnant women with HDP (2015-2020). The primary outcome was the difference in the total number of antenatal follow ups. Results: Although nonsignificant, total follow ups increased by 11% during the pandemic (RR = 1.11; p = 0.122), driven by a fivefold rise in telephone visits (RR = 5.05; p < 0.001), while in-person visits remained stable. Adverse outcomes rates showed no significant changes. Conclusion: Increased telehealth use complemented stable in-person care, supporting continuity and flexibility in HDP management. Telehealth holds promise as a supportive tool in prenatal care delivery.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.105
Threshold uncertainty score0.648

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.054
GPT teacher head0.443
Teacher spread0.388 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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