912-P: The Minimum Frequency of Well-Day Capillary Blood Ketone Testing Needed for Future Diabetic Ketoacidosis (DKA) Prediction in T1D
Bibliographic record
Abstract
Introduction and Objective: Routine well-day surveillance of capillary ketone levels in T1D can predict future DKA risk, including in those using sodium glucose-linked transporter inhibitors (SGLTi). We assessed the impact of ketone testing frequency on prediction accuracy using data from the EASE trials. Methods: Data from 1685 participants assigned empagliflozin or placebo were analyzed. Ketone measurements were randomly selected to simulate less frequent testing than the protocol’s 2-3 tests/week. Maximum and other statistics of ketone levels were derived and categorized into 28-day intervals. Gradient Boosting Tree models were trained (80% of participants) and evaluated (remaining 20%) to predict DKA or severe ketosis in subsequent intervals. Areas Under the Receiver Operating Characteristic Curve (AUC) were compared using one-sided DeLong tests. Results: Out of the 11,218 intervals, 600 had DKA or severe ketosis events. Predictive performance decreased with less frequent testing: Biweekly compared to all data (2-3 tests per week) had slightly lower AUC (0.75 vs. 0.81, p = 0.081), but with testing at 21-day intervals, the AUC decreased significantly compared to biweekly (0.65, p = 0.027, Figure 1). Conclusion: To reasonably predict future ketoacidosis risk among T1D users or non-users of SGLTi, ketone testing on well-days every 2 weeks is the recommended strategy. Disclosure Y. Zhang: None. D.R. Budhram: None. P. Bapat: None. S. Dhaliwal: None. C. Song: None. D. Scarr: Employee; Medicenna Therapeutics. A.M.K. Bakhsh: Other Relationship; Sanofi. Advisory Panel; Ithanin. N. Verhoeff: None. A. Weisman: None. M. Fralick: None. N. Ivers: None. D. Cherney: Consultant; Boehringer Ingelheim-Lilly, Merck, AstraZeneca, Sanofi, Mitsubishi-Tanabe, Abbvie, Janssen, AMGEN, Bayer, Prometic, BMS, Maze, Gilead, CSL-Behring, Otsuka, Novartis, Youngene, Lexicon, Inversago, GSK. Research Support; Boehringer Ingelheim-Lilly, Merck, Janssen, Sanofi, AstraZeneca, CSL-Behring and Novo-Nordisk, Bayer. G.A. Tomlinson: None. D. Mumford: None. L. Lovblom: None. B.A. Perkins: Other Relationship; Abbott, Novo Nordisk, Sanofi. Advisory Panel; Abbott, Insulet Corporation, Sanofi, Novo Nordisk, Nephris, Vertex Pharmaceuticals Incorporated. Research Support; Novo Nordisk. Funding Diabetes Canada (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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".