SAT-545 Improving inpatient management of SGLT2i associated Euglycemic Diabetic Ketoacidosis: Insights from The Ottawa Hospital
Bibliographic record
Abstract
Abstract Disclosure: Z.R. O'Neill: None. J.C. Malcolm: None. A. Arnaout: None. Background: The widespread use of sodium-glucose cotransporter-2 inhibitors (SGLT2i) in managing type 2 diabetes (T2D) has led to an increasing prevalence of euglycemic diabetic ketoacidosis (eDKA) (1). The overall incidence of eDKA among SGLT2i users is estimated at 0.1% (2), though a more recent cohort study reported a prevalence as high as 0.43% (3). DKA treatment benefits from standardized protocols, which, when well-formulated and physician-driven, have been shown to reduce both the time to DKA resolution and overall hospital stay (4). While general guidelines exist for managing eDKA—including insulin, fluids, electrolytes, and IV dextrose—the optimal management strategies for this specific cohort remain unclear. Furthermore, no large studies have systematically analyzed treatment outcomes for patients with eDKA. Methods: We conducted a retrospective chart review to evaluate the prevalence, characteristics, and management patterns of patients admitted to The Ottawa Hospital (TOH) with SGLT2i-associated eDKA. Time to resolution—defined as the interval from biochemical diagnosis to the resolution of metabolic acidosis—was recorded. Management decisions, including insulin infusion rates and choice of resuscitation fluids, were also analyzed. Results: 61 patients were admitted to TOH with eDKA in the context of recent SGLT2i use. The cohort consisted of 43% female patients, with an average age of 66 years. Empagliflozin was the most commonly prescribed SGLT2i (79%). Most patients presented with mild DKA with only 2 patients presenting with severe acidosis. The median time to resolution using a standard IV insulin protocol was 35 hours. The shortest time spent on an insulin infusion was 9 hours and the longest time was 121 hours. Conclusions: There is limited data guiding the management of SGLT2i-associated eDKA. Larger studies are needed to determine best practices for a condition that is expected to become more prevalent with the continued widespread use of SGLT2 inhibitors. Our data suggest some mild cases of eDKA may respond less intensive insulin treatment. Presentation: Saturday, July 12, 2025
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".