Euglycaemic ketoacidosis in a postoperative Whipple patient using canaglifozin
Bibliographic record
Abstract
SGLT2 inhibitors are a new class of oral antihyperglycaemic agents that have garnered much attention for their attractive efficacy profile in glycaemic control along with the added benefit of weight loss. There has been increasing concern for the risk of euglycaemic (serum glucose 4-8 mmol/L) ketoacidosis with these agents. In the setting of a postoperative patient, the use of these drugs may exacerbate the normal physiological stresses of the body and increase the risk of developing euglycaemic ketoacidosis (euKDA). This case highlights a postoperative patient who was using an SGLT2 inhibitor and developed severe euKDA after a pancreaticoduodenectomy. The goal of this case report was to bring awareness to the possibility of this rare adverse event. In doing so, it may aid in preoperative planning of the diabetic patient and trigger appropriate management for those who develop euKDA.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".