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Record W3183324835 · doi:10.7759/cureus.16691

Equitable Timing of HIV Diagnosis Prior to Pregnancy: A Canadian Perspective

2021· article· en· W3183324835 on OpenAlexaffabout
Esther S. Shoemaker, Kate Volpini, Stephanie Smith, Mona Loutfy, Claire Kendall

Bibliographic record

VenueCureus · 2021
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsWomen's College HospitalUniversity of TorontoInstitute for Clinical Evaluative SciencesUniversity of OttawaBruyèreOttawa Hospital
Fundersnot available
KeywordsMedicinePregnancyHuman immunodeficiency virus (HIV)ObstetricsCohortPopulationPrenatal careRetrospective cohort studyCohort studyHIV diagnosisPediatricsFamily medicineViral loadAntiretroviral therapyEnvironmental healthSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Initiating antiretrovirals prior to conception leads to a negligible risk of perinatal transmission. This study aimed to determine the timing of HIV diagnosis among pregnant women with HIV in Ontario. A retrospective population-level cohort study using linked health administrative databases was conducted to establish maternal HIV status and timing of HIV diagnosis of all women living with HIV who gave birth in 2006-2018. The majority of the 1012 women living with HIV who gave birth in Ontario were diagnosed prior to pregnancy (87.9%); however, many were not (12.1%). Among those diagnosed during pregnancy, only 23% were diagnosed in the first trimester. While HIV screening tests are being well directed towards young women, several women still enter pregnancy undiagnosed and are not diagnosed early. This calls for a continuous effort to promote universal pre-conception screening and to use HIV point-of-care testing for at-risk pregnant women and those presenting late to prenatal care.

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)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.069
Threshold uncertainty score0.500

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0050.002
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.049
GPT teacher head0.363
Teacher spread0.314 · 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 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

Citations1
Published2021
Admission routes2
Has abstractyes

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