Identification of a distinct phenotype of elderly latent autoimmune diabetes in adults: LADA China Study 8
Bibliographic record
Abstract
BACKGROUND: Latent autoimmune diabetes in adults (LADA) exhibits significant clinical heterogeneity, but the underlying causes remain unclear. The aim of this study was to investigate whether age of onset of LADA contributes to the observed clinical heterogeneity by comparing the clinical, metabolic, and immunogenetic characteristics between elderly and young LADA patients. METHODS: The cross-sectional study included a total of 579 patients with LADA which was further divided into elderly LADA (E-LADA) group (n = 135, age of onset ≥60 years) and young LADA (Y-LADA) group (n = 444, age of onset <60 years). Age-matched subjects with type 2 diabetes were served as control (E-T2D group, n = 622). Clinical characteristics, serum autoantibodies, and HLA-DQ haplotypes were compared among these groups. RESULTS: Compared with patients with Y-LADA, patients with E-LADA have better residual beta-cell function and higher level of insulin resistance (both P < .01), more metabolic syndrome characteristics, similar proportion of islet autoantibody positivity, and strikingly different HLA-DQ genetic background. In comparison with E-T2D patients, E-LADA patients tend to have similar metabolic syndrome prevalence, comparable C-peptide levels, and insulin resistance levels and share similar HLA-DQ genetic characteristics. CONCLUSIONS: Elderly LADA differs phenotypically and genetically from Y-LADA but has a clinical and genetic profile more similar to that of E-T2D. These distinct phenotypes could potentially help physicians better manage patients with E-LADA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".