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Record W4410793559 · doi:10.1136/bcr-2023-257172

Antenatal presentations of congenital sideroblastic anaemia as severe fetal anaemia

2025· article· en· W4410793559 on OpenAlexaff
Kwan Hoong Ng, Michelle Rougerie, Daniel L. Rolnik

Bibliographic record

VenueBMJ Case Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsB.C. Women's Hospital & Health Centre
Fundersnot available
KeywordsMedicinePregnancyEtiologyFetusPediatricsObstetricsTwin PregnancyAnemiaInternal medicine

Abstract

fetched live from OpenAlex

Severe fetal anaemia of unknown aetiology can present a diagnostic challenge. Rare causes of fetal anaemia include congenital sideroblastic anaemia (CSA), a rare group of disorders that typically manifest during infancy and early childhood. This case report describes three pregnancies complicated by CSA presenting antenatally in the same woman. The index case was a twin pregnancy in which both neonates were born severely anaemic with one surviving twin. The subsequent cases of severe fetal anaemia were detected during pregnancy and successfully managed with intrauterine blood transfusions (IUTs). The three surviving children required several neonatal transfusions and were later diagnosed with CSA. To our knowledge, this is the first case report describing CSA presenting in the antenatal period with surviving patients and thereby highlights the importance of considering fetal anaemia early in pregnancy and the potential for early intervention with IUTs to improve survival outcomes in this group of patients.

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)0.005
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.011
GPT teacher head0.303
Teacher spread0.292 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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