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Record W4250208719 · doi:10.21203/rs.2.21146/v1

The effect of prenatal and postnatal treatment with intravenous immunoglobulin on severity of neonatal hemochromatosis: the tale of two brothers (case report)

2020· preprint· en· W4250208719 on OpenAlexaff
Veronica Samedi, Michelle Ryan, Essa Al Awad, Adel Elsharkawy

Bibliographic record

VenueResearch Square (Research Square) · 2020
Typepreprint
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsUniversity of SaskatchewanUniversity of Calgary
Fundersnot available
KeywordsHemochromatosisMedicineAntibodyPediatricsIntravenous ironImmunologyInternal medicineAnemiaIron deficiency

Abstract

fetched live from OpenAlex

Abstract Background: Neonatal hemochromatosis (NH) is a rare condition that was the main reason for liver transplantation in infants. With the realization that NH results from the fetal complement-mediated liver injury, intravenous immunoglobulins (IVIG) were successfully introduced for the treatment. Case Presentation: We present two cases of NH from the same family to illustrate the role of antenatal treatment with IVIG in alleviation and possible prevention of this serious morbidity. Conclusion: A prenatal treatment and early postnatal administration of IVIG are effective ways to manage NH that help to reduce the severity of the symptoms, prevent liver failure and avoid the need for liver transplantation Keywords: Neonatal hemochromatosis, Intravenous immunoglobulin, prenatal treatment

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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
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 head0.030
GPT teacher head0.376
Teacher spread0.346 · 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
Published2020
Admission routes1
Has abstractyes

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