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Record W2810556165 · doi:10.1515/crpm-2018-0003

Severe congenital autoimmune neutropenia in preterm monozygotic twins: case series and literature review

2018· article· en· W2810556165 on OpenAlexaff
Rehab Abdelhamid, Kamran Yusuf, Abhay Lodha, Essa Hamadan Al Awad

Bibliographic record

VenueCase Reports in Perinatal Medicine · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBlood disorders and treatments
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineNeutropeniaImmunologyAntibodyPediatricsInternal medicineChemotherapy

Abstract

fetched live from OpenAlex

Abstract The presence of high levels of neutrophil associated immunoglobulins (NAIG) in the serum of newborns with neutropenia and their mothers is usually associated with the diagnosis of allo-immune neonatal neutropenia (AINN). We describe a set of otherwise healthy late preterm monozygotic twins who presented with an isolated severe neonatal neutropenia on the first day of life. Flow cytometry for neutrophil antibody screen for both twins detected elevated levels of NAIG with normal serum levels of allo anti-neutrophil antibody (allo-NAB). Maternal serum did not contain either NAIG or allo-NAB. Also, the NAIG immunoglobulin M (IgM) levels were markedly increased in both twins if compared to the increase in the NAIG immunoglobulin G (IgG). Both twins showed very good response to a short course treatment with granulocyte colony stimulating factor (G-CSF), they remained clinically well until 12 months of age. We suggest that this case may be an early presentation of autoimmune neutropenia of infancy. This case study is the earliest report of autoimmune neutropenia of infancy in preterm monozygotic twins.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.151
Threshold uncertainty score0.680

Codex and Gemma teacher scores by category

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

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 head0.007
GPT teacher head0.262
Teacher spread0.255 · 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 teacher head, 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
Published2018
Admission routes1
Has abstractyes

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