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Record W1952447368 · doi:10.14740/jocmr2158w

Neonatal Hyperbilirubinemia in a Turkish Cohort: Association of Vitamin B<sub>12</sub>

2015· article· en· W1952447368 on OpenAlexvenueno aff
Nilgün Eroğlu, Yaşar Kandur, Salih Kalay, Zuhal Kalay, Özgür Güney

Bibliographic record

VenueJournal of Clinical Medicine Research · 2015
Typearticle
Languageen
FieldMedicine
TopicNeonatal Health and Biochemistry
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineVitamin B12JaundiceGastroenterologyInternal medicineBilirubinPediatrics

Abstract

fetched live from OpenAlex

BACKGROUND: Deficiency of vitamin B12 (VitB12) causes failure of erytrocyte maturation leading to cell lysis. Red blood cell lysis causes excess heme production that ends with hyperbilirubinemia. In this study, we aimed to evaluate the role of VitB12 in neonatal hyperbilirubinemia (NNH) with prolonged jaundice and to compare patients with control group who did not develop hyperbilirubinemia. METHODS: A total of 20 patients (M/F = 13/7) with jaundice and 20 healthy controls (M/F = 11/9) were included in the study. RESULTS: The mean indirect bilirubin level of patient group was 9.91 ± 1.90 mg/dL (6.71 - 15.2 mg/dL) and control group was 3.18 ± 1.24 mg/dL (1.16 - 4.96 mg/dL). The mean VitB12 level of patient group was 119.9 ± 43.9 ng/L (42.35 - 178 ng/L) and the control group was 286.17 ± 97.43 ng/L (207.90 - 624.10 ng/L). There was a statistically significant difference in terms of VitB12 level (< 0.001) between the study groups. CONCLUSION: To our knowledge, this study is the first study showing that low VitB12 level has been observed as a risk factor in NNH for the first time in the literature. We suggest that prophylactic use of VitB12 by pregnant women so will greatly benefit to prevent VitB12 deficiency and its complications in the first years of life such as NNH.

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)0.001
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: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.174
GPT teacher head0.516
Teacher spread0.342 · 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

Citations9
Published2015
Admission routes1
Has abstractyes

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