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Record W2526590448 · doi:10.1136/bcr-2016-216607

Euglycaemic ketoacidosis in a postoperative Whipple patient using canaglifozin

2016· article· en· W2526590448 on OpenAlex
Trevor Wood, Allison Pang, Julie Hallet, Paul D. Greig

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBMJ Case Reports · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsToronto General HospitalHealth Sciences CentreSunnybrook Health Science CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineDiabetic ketoacidosisKetoacidosisIntensive care medicineHypoglycemiaAdverse effectDiabetes mellitusWeight lossSurgeryInternal medicineObesityEndocrinologyType 1 diabetes

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.404

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.262
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it