Distinct two different ages associated with clinical profiles of acute onset type 1 diabetes in Chinese patients
Bibliographic record
Abstract
Abstract Background There are abundant variations in the phenotypes and genetics of type 1 diabetes (T1D) patients across different races. This study aimed to assess differences between juvenile acute onset (JAO) and adult acute onset in Chinese T1D patients. Methods Seven hundred and fifty‐one acute onset T1D patients were divided into two groups by the patient onset age as follows: the juvenile acute onset group (≤20 years, JAO group) and the adult acute onset group (>20 years, AAO group). Clinical characteristics, islet autoantibodies, and HLA class II haplotypes and genotypes were compared between these two groups. Results In comparison with AAO patients, JAO patients had significantly lower relative weights and lower triglyceride levels (P < .001, P < .01, respectively) but higher frequency of ketoacidosis (P < .001), higher daily insulin dosage (Pc < .001), higher HbA1c (Pc < .05), and higher HDL‐cholesterol levels (Pc < .01). The JAO group showed a higher prevalence of IA‐2A, ZnT8A, and multiple autoantibodies than that in the AAO group (P < .001, P < .01, P < .001, respectively). Haplotypes for DRB1*0301‐DQA1*03‐DQB1*0201, DR3, DR4, DR9, and DR3/DR9 genotypes are highly associated with JAO susceptibility, whereas only DR3 and DR9 genotypes confer risk for AAO. In the JAO group but not the AAO group, DR3 is related to ZnT8A, and DR3/DR9 is related to IA‐2A and multiple autoantibodies. Conclusions These observations suggest that JAO patients markedly differ from AAO patients in their clinical manifestations and genetics in the Chinese T1D population. Notably, the DR3/DR9 genotype can facilitate the appearance of IA‐2A or multiple autoantibodies in JAO patients.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".