Persisting plasma proinsulin levels in a cohort of 482 individuals with long‐standing type 1 diabetes mellitus
Bibliographic record
Abstract
AIMS: As compared with C-peptide, plasma proinsulin levels in individuals with long-standing type 1 diabetes mellitus are relatively understudied, but may serve as a marker of stressed, yet alive β-cells. MATERIALS AND METHODS: We measured proinsulin and C-peptide levels (detection limit <0.15 pmol/L and <0.05 nmol/L, respectively) in a cross-sectional cohort of 482 individuals with type 1 diabetes mellitus and measured associations with diabetes duration, HLA haplotype and autoantibodies. RESULTS: Proinsulin showed a biphasic decline with an initial decrease over 15 years followed by a stabilisation period, whereas C-peptide showed a similar pattern but with an inflection point at ~8 years. Proinsulin and the proinsulin-to-C-peptide ratio did not associate with variables associated with insulin resistance (BMI, triglyceride levels, insulin/day/kg). Higher proinsulin- and C-peptide levels correlated with higher levels of anti-GAD antibodies (Spearman ρ = 0.18 and 0.23 respectively, p < 0.05), but not with anti-IA2. A high-risk DR3/3 HLA genotype associated with complete loss of C-peptide (OR 0.34, 95% CI 0.14-0.79) and proinsulin(OR 0.44, 95% CI 0.20-0.92). CONCLUSIONS/INTERPRETATION: In type 1 diabetes mellitus, proinsulin levels remain detectable long after diagnosis, also in the absence of C-peptide, implying the presence of stressed, yet alive β-cells.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".