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Record W2804752358 · doi:10.14341/probl8616

Problems of the differential diagnosis of MODY3 in obesity

2018· article· en· W2804752358 on OpenAlexaff
E. A. Sechko, Екатерина Андреевна Андрианова, О.Н. Иванова, Тамара Леонидовна Кураева

Bibliographic record

VenueProblems of Endocrinology · 2018
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsMcGill-Queen's University Press
Fundersnot available
KeywordsObesityDifferential diagnosisDifferential (mechanical device)MedicinePsychologyInternal medicineEngineeringPathology

Abstract

fetched live from OpenAlex

MODY3 is one of the most common subtypes of MODY. Obesity in MODY3 patients modifies the disease course and complicates diagnostics at the clinical stage. A proband was diagnosed with type 2 diabetes mellitus (T2DM) at the age of 12 years; metformin therapy was used. A family history of DM involves three generations: the mother, aunt, and maternal grandfather have suffered from insulin-dependent DM since the age of 23, 22, and 40 years, respectively. The patient was examined at the age of 14 years. Obesity was present (SDS BMI 2.3). The insulin and C-peptide levels were 4.4 μU/mL and 1.5 ng/mL, respectively. The HbA1c level was 7.3%. Under glucose load, glycemia reached diabetic values; hyperinsulinemia and insulin resistance were not detected. Specific pancreatic antibodies were absent. Metformin was discontinued, and a sulfonylurea (SU) drug was prescribed, which had a positive effect. The heterozygous mutation p.P291fs was identified in the HNF1A gene. Therefore, MODY3 was verified. The presence of concomitant obesity in the patient significantly complicates the differential diagnosis, and only a careful comprehensive analysis of clinical and laboratory parameters and a family history makes it possible to suspect the diagnosis of MODY3 (requiring subsequent molecular genetic verification) and prescribe pathogenetic therapy.

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)0.002
metaresearch head score (Gemma)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.024
GPT teacher head0.259
Teacher spread0.236 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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