1440-P: C-Peptide Preservation and Diabetic Ketoacidosis (DKA) Risk in Type 1 Diabetes
Bibliographic record
Abstract
Introduction & Objective: Endogenous insulin production in T1D, as measured by detectable C-peptide, is associated with lower HbA1c and insulin dose, as well as lower hypoglycemia and retinopathy risk. We aimed to determine if detectable C-peptide is also associated with decreased risk of DKA. Methods: We accessed data from the Diabetes Control and Complications Trial (DCCT) from the NIDDK central repository to investigate the effects of detectable stimulated C-peptide measured annually (≥0.2 pmol/ml, exposure) on DKA incidence (outcome) over mean 6.5-year trial follow-up. Analysis was conducted using the Andersen-Gill model for recurrent DKA events with time-varying covariates; crude unadjusted models and models adjusted for age, sex, diabetes duration, and trial assignment (intensive vs. conventional) were fit. Sensitivity analysis also adjusted for HbA1c. Results: Of the 1441 participants with a median age of 27 years and median duration of diabetes of 49 months, 53% were male, 21% had detectable C-peptide levels (>0.2 pmol/ml) at baseline, and the median HbA1c level was 8.8%. During the trial, 129 participants (9%) had 180 DKA events. Only 1 of these 129 DKA events occurred in an individual with detectable C-peptide, while 128 events occurred in individuals after C-peptide became undetectable. In crude analysis, detectable C-peptide level had a 93% reduction in the hazard for recurrent DKA [hazard ratio (HR) 0.07, 95% CI 0.01 to 0.48, p=0.007]. Results were similar in the first adjusted model (HR 0.06, 95% CI 0.01 to 0.44, p=0.006) and in the final adjusted model (HR 0.08, 95% CI 0.01 to 0.60, p=0.012). Conclusion: In addition to previously identified clinical benefits, this analysis demonstrates that endogenous insulin production dramatically lowers the risk of DKA in T1D. This implies that therapies that may preserve insulin production - such as immune, cell-based, or other therapies - are likely to reduce the burden of DKA. Disclosure M.I. Abuabat: None. D.R. Budhram: None. P. Bapat: None. A.M.K. Bakhsh: None. N. Verhoeff: None. D. Mumford: None. A. Orszag: None. M. Fralick: Consultant; singal1, proofdx. A. Weisman: None. L. Lovblom: None. B.A. Perkins: Advisory Panel; Abbott. Other Relationship; Novo Nordisk. Advisory Panel; Insulet Corporation, Nephris. Other Relationship; Medtronic. Advisory Panel; Sanofi, Vertex Pharmaceuticals Incorporated, Dexcom, Inc. Funding Diabetes Canada (Operating Grant OG-3-21-5572-BP)
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".