Past, present and future of latent autoimmune diabetes in adults
Bibliographic record
Abstract
Latent autoimmune diabetes in adults (LADA) is the most common form of autoimmune diabetes diagnosed in adults. Similar to type 1 diabetes, the prevalence of LADA is impacted by ethnicity and geography. LADA is characterized by β cell loss due to autoimmunity and insulin resistance and has highly heterogeneous clinical features, autoimmunity, and genetics in a glutamic acid decarboxylase antibody (GADA) titre-dependent manner, suggesting LADA is part of a continuum spectrum between type 1 and type 2 diabetes. Although LADA is the most frequent form of autoimmune diabetes diagnosed in adults, clinical trials involving LADA are scarce. Here we review the recent advancements in LADA epidemiology, clinical features, pathogenesis, and interventions. We also highlight the environmental factors that are thought to play an important role in addition to genetics in the pathogenesis of LADA. In the future, high-throughput molecular profiles might shed light on the nature of LADA among the wide spectrum of diabetes and offer new opportunities to identify novel LADA-specific biomarkers.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".