Latent autoimmune diabetes in youth shows greater autoimmunity than latent autoimmune diabetes in adults: Evidence from a nationwide, multicenter, cross‐sectional study
Bibliographic record
Abstract
AIM: To investigate the prevalence and clinical features of latent autoimmune diabetes in youth (LADY) diagnosed between 15 and 29 years old as a component of an age-related autoimmune diabetes spectrum. RESEARCH DESIGN AND METHODS: This nationwide, multicenter, cross-sectional study continuously included 19,100 newly diagnosed diabetes patients over 15 years old across China. LADY patients were screened from 1803 subjects aged between 15 and 29 years old, with the type 2 diabetes (T2D) phenotype and positive autoantibodies against glutamic acid decarboxylase (GADA), insulinoma-associated-2 (IA-2A) or zinc transporter-8 (ZnT8A). The clinical features of LADY, including metabolic status, β-cell function and insulin resistance, were investigated and compared with those of latent autoimmune diabetes in adults (LADA) identified from 17,297 other subjects over 30 years old. The age-related characteristics of the latent autoimmune diabetes spectrum were explored. RESULTS: A total of 135 subjects were diagnosed as LADY, accounting for 9.0% of the T2D phenotypic youth. Compared with autoantibody-negative T2D patients, LADY patients had fewer metabolic syndrome, less insulin resistance and poorer β-cell function, which were closely related to their autoantibody status (all p < 0.05). After stratifying LADA according to age, the GADA titer decreased across the LADY, "Y-LADA" (young LADA, onset age < 60 years old) and "E-LADA" (elderly LADA, onset age ≥ 60 years old) groups, while the prevalence of metabolic syndrome and level of β-cell function increased (all p < 0.05). CONCLUSIONS: A high prevalence of LADY exists in youth with T2D phenotype. Latent autoimmune diabetes forms a continuous age-related spectrum from LADY to LADA, in which LADY shows greater autoimmunity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".