Acidocétose euglycémique attribuable aux inhibiteurs du cotransporteur sodium-glucose de type 2 : savoir la prévenir, la reconnaître et la traiter
Bibliographic record
Abstract
Objectif : L’objectif du présent article est de discuter d’un effet indésirable rare, mais grave des inhibiteurs du cotransporteur sodium-glucose de type 2 (iSGLT2), soit l’acidocétose euglycémique. Nous passerons aussi en revue sa physiopathologie, sa détection, sa prise en charge et sa prévention. Sources des données et sélection des études : Une revue de la littérature scientifique publiée entre 2010 et 2024 dans des bases de données telles que PubMed et Google Scholar a été effectuée en utilisant et en reliant des mots clés comme diabetic ketoacidosis, diagnosis, euglycemic ketoacidosis, iSGLT2, management, non-diabetic ketoacidosis, normoglycemic ketoacidosis, prevention, SGLT2 inhibitors, sodium-glucose cotransporter-2 inhibitors. Revue du sujet traité : L’acidocétose euglycémique présente un défi diagnostique. De multiples facteurs précipitants associés à l’état de santé, aux habitudes de vie et à la prise concomitante de certains médicaments peuvent prédisposer au développement d’une acidocétose euglycémique. Le traitement hospitalier de l’acidocétose euglycémique repose sur trois axes principaux, soit la réplétion liquidienne, la correction de l’acidocétose et la prévention des hypoglycémies. La surveillance des cétones pourrait permettre une détection précoce de l’acidocétose euglycémique en contexte post-opératoire. La gestion des jours de maladie est un élément crucial à discuter avec les patients pour prévenir les acidocétoses euglycémiques attribuables aux iSGLT2. Conclusion: Le pharmacien, qu’il pratique en milieu hospitalier ou communautaire, joue un rôle clé dans la prise en charge globale de l’acidocétose euglycémique liée aux iSGLT2. Summary Objective: To discuss euglycemic ketoacidosis, a rare, but serious adverse effect of sodium-glucose cotransporter-2 (SGLT-2) inhibitors. Pathophysiology and detection, management, and prevention strategies are also reviewed. Data sources and study selection: A review of the scientific literature published between 2010 and 2024 in databases such as PubMed and Google Scholar was conducted using and linking keywords such as diabetic ketoacidosis, diagnosis, euglycemic ketoacidosis, iSGLT2, management, non-diabetic ketoacidosis, normoglycemic ketoacidosis, prevention, SGLT2 inhibitors, sodium-glucose cotransporter-2 inhibitors. Subject review: Euglycemic ketoacidosis is a diagnostic challenge. Multiple precipitating factors associated with health status, lifestyle habits, and the concomitant use of certain medications may predispose patients to the development of euglycemic ketoacidosis. Hospital treatment is based on three main principles: fluid resuscitation, correction of ketoacidosis, and prevention of hypoglycemia. Ketone monitoring could enable early detection of euglycemic ketoacidosis in the postoperative setting. Management of medication during sick days is a crucial element to be discussed with patients to prevent euglycemic ketoacidosis secondary to SGLT-2 inhibitor use. Conclusion: The pharmacist, whether working in the hospital or community setting, plays a key role in the management of SGLT-2 inhibitor-related euglycemic ketoacidosis.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 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".