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Record W3102634053 · doi:10.1097/fm9.0000000000000081

Intrauterine Blood Transfusion in an HCV and HIV Co-Infected Woman

2020· article· en· W3102634053 on OpenAlexaff
Jodie Charison, Carol Ellison Schneider, Vanessa Poliquin

Bibliographic record

VenueMaternal-Fetal Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsUniversity of ManitobaResearch Manitoba
Fundersnot available
KeywordsMedicineTransmission (telecommunications)FetusBlood transfusionPregnancyObstetricsHuman immunodeficiency virus (HIV)Hepatitis CImmunologyVirologyBiology

Abstract

fetched live from OpenAlex

Abstract Hepatitis C infection is not uncommon in pregnant women. Vertical transmission of the virus from mother to fetus is estimated at 4%-8%, however this transmission rate is significantly higher when the mother is co-infected with HIV. Intrauterine blood transfusions can be a necessary part of management for certain perinatal conditions like hemolytic disease of the fetus. Currently there is no published material available on the vertical transmission risk of HCV infection to the fetus as a result of this procedure, irrespective of HIV co-infection. We present a case of a pregnant woman co-infected with HCV and HIV that required an intrauterine blood transfusion during pregnancy. Vertical transmission of either infection to the child did not occur. This provides important evidence that vertical transmission of HCV and/or HIV does not necessarily occur with intrauterine blood transfusions.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.031
GPT teacher head0.325
Teacher spread0.293 · 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 designCase report
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
Published2020
Admission routes1
Has abstractyes

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