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Record W2766357401 · doi:10.14740/jnr.v7i4-5.458

DiGeorge Syndrome Presenting With Seizures: A Case Report

2017· article· en· W2766357401 on OpenAlexvenueno aff
Samaneh Noroozi Asl, Hoda Khatib Masjedi, Ali Rajabpour Sanati

Bibliographic record

VenueJournal of Neurology Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCongenital heart defects research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDiGeorge syndromePediatricsDuctus arteriosusTetralogy of FallotGirlAuscultationAortic archCardiologyInternal medicineHeart diseaseAortaPsychiatry

Abstract

fetched live from OpenAlex

DiGeorge syndrome was described for the first time in 1968 as a defect affecting structures derived from the third and fourth embryonic pharyngeal arches along with absent parathyroid glands. According to the low incidence of this disease as well as a wide spectrum of symptoms, it is essential to report cases with less prevalent features. In this case report, a child was introduced with a diagnosis of DiGeorge syndrome presenting with seizures. The patient was a 27-day-old baby girl due to seizures admitted to Hospital Imam Reza (AS), Mashhad, Iran. Hypocalcemia was observed in early clinical trials requested. The patient underwent echocardiography according to holosystolic murmur grade 3/6 auscultation, which showed a patent ductus arteriosus (PDA), tetralogy of Fallot (TOF), ventricular septal defect (VSD), atrial septal defect (ASD), and pulmonary atresia (PA). No thymus was found on chest X-ray, and evidence of previous conflicts was observed in the heart. Finally, fluorescent in situ hybridization (FISH) was performed to check out Tuple gene deletion on chromosome 22q11.2, and the diagnosis was confirmed for DiGeorge syndrome. Although the incidences of neurological symptoms associated with hypocalcemia suggest a wide range of diseases as a differential diagnosis, pediatrics should consider the heart disorders for DiGeorge syndrome through clinical examinations and imaging, if necessary. J Neurol Res. 2017;7(4-5):94-96 doi: https://doi.org/10.14740/jnr410e

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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0030.002
Scholarly communication0.0020.003
Open science0.0020.003
Research integrity0.0060.004
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 head0.061
GPT teacher head0.404
Teacher spread0.343 · 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
Published2017
Admission routes1
Has abstractyes

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