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Record W4385464295 · doi:10.14740/jmc4128

There’s More Than Meets the Eye: Wolfram Syndrome in a Type I Diabetic Patient

2023· article· en· W4385464295 on OpenAlexvenueno aff
Jasvindar Kumar, Atif Ahmed, Mashal Khan, Yasir Ahmed

Bibliographic record

VenueJournal of Medical Cases · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEndoplasmic Reticulum Stress and Disease
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePolyuriaPolydipsiaWolfram syndromeDiabetes insipidusDesmopressinPediatricsAtrophyDiabetes mellitusMagnetic resonance imagingSurgeryInternal medicineEndocrinologyRadiology

Abstract

fetched live from OpenAlex

Wolfram syndrome (WS) is a rare neurodegenerative and genetic disorder, also known by the synonym DIDMOAD, which stands for diabetes insipidus (DI), childhood-onset diabetes mellitus (DM), optic atrophy (OA), and deafness (D). We present a case of a 25-year-old diabetic patient, using insulin for 15 years, who had increasing polyuria and polydipsia, along with progressive hearing and vision loss. Laboratory tests revealed elevated hemoglobin A1c (HbA1c) and blood sugar levels. Optic nerve, optic chiasm, pons, and brain stem atrophy was seen on magnetic resonance imaging (MRI) of brain. After workup, a diagnosis of DI was made. Once the diagnosis was reached, treatment with subcutaneous insulin and nasal desmopressin improved patient's symptoms. In juvenile diabetic patients presenting with new onset or worsening polyuria and polydipsia, the possibility of WS should be considered. Early diagnosis and initiation of appropriate management leads to improved outcomes and the quality of life.

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: 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
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0020.002
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 head0.012
GPT teacher head0.287
Teacher spread0.275 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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