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Record W2948945163 · doi:10.2337/db19-1681-p

1681-P: Polyendocrinopathy in Type 1 Diabetes: A Transatlantic Comparison

2019· article· en· W2948945163 on OpenAlexaboutno aff
Julia M. Hermann, Kellee M. Miller, Gabor Szinnai, Nicole C. Foster, Thomas Kapellen, Linda A. DiMeglio, Elke Fröhlich‐Reiterer, Janet B. McGill, Reinhard W. Holl, David M. Maahs

Bibliographic record

VenueDiabetes · 2019
Typearticle
Languageen
FieldMedicine
TopicAdrenal Hormones and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInternal medicineDiabetes mellitusThyroid diseaseAtrophic gastritisLogistic regressionDiseasePediatricsGastroenterologyThyroidGastritisEndocrinology

Abstract

fetched live from OpenAlex

Type 1 diabetes (T1D) is associated with additional autoimmune and endocrine disorders; however, their prevalences internationally are poorly understood. We analyzed 22,632 patients from the U.S. T1D Exchange (T1DX) registry (median age 18 years) and 38,470 patients from the German/Austrian DPV registry (median age 16 years) with T1D duration ≥1 year (median duration 10 and 6 years, respectively) with data between 01/2016 and 03/2018. Reported prevalences of thyroid disease, arthritis, Addison’s disease, and atrophic gastritis were compared using logistic regression models with registry, age group, and sex as covariates. Thyroid disease was more frequent in the T1DX, whereas arthritis was more frequent in the DPV. Prevalence increased with age in both registries. We found no significant differences between T1DX and DPV for Addison’s disease (Figure). Atrophic gastritis was rare in both registries (T1DX: n=3, DPV: n=21). After adjustment for age, thyroid disease was about twice as frequent in females compared with males (T1DX: 25 vs. 13%, DPV: 15 vs. 7%, both p<0.001). Likewise, arthritis was more frequent in females (T1DX: 0.23 vs. 0.16%, p=0.034; DPV: 1.45 vs. 0.88%, p<0.001), whereas Addison’s disease did not differ significantly by sex. Despite different prevalences, patterns of disease frequencies by age and sex were comparable in both registries. However, standardized clinical diagnoses are needed for valid comparisons between countries. Disclosure J. Hermann: None. K. Miller: None. G. Szinnai: None. N.C. Foster: None. T.M. Kapellen: None. L. DiMeglio: Research Support; Self; Amgen Inc., Caladrius Biosciences, Inc., Janssen Research & Development, Medtronic, Sanofi. Other Relationship; Self; Dexcom, Inc. E. Fröhlich-Reiterer: None. J.B. McGill: Advisory Panel; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Gilead Sciences, Inc., Novo Nordisk Inc., Sanofi US. Research Support; Self; Dexcom, Inc., Medtronic, Novartis AG, Sanofi US. Speaker's Bureau; Self; Aegerion Pharmaceuticals, Dexcom, Inc., Janssen Pharmaceuticals, Inc., MannKind Corporation. R.W. Holl: None. D.M. Maahs: Advisory Panel; Self; Novo Nordisk Inc. Consultant; Self; Abbott, Sanofi. Research Support; Self; Dexcom, Inc., Tandem Diabetes Care. Funding German Center for Diabetes Research; The Leona M. and Harry B. Helmsley Charitable Trust; German Center for Diabetes Research; German Diabetes Association; European Foundation for the Study of Diabetes; INNODIA

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.744

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)0.0000.001

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 head0.011
GPT teacher head0.257
Teacher spread0.246 · 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 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

Citations9
Published2019
Admission routes1
Has abstractyes

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