Diabetic ketoacidosis and hyperglycaemic hyperosmolar syndrome in patients with cancer: A multicentre study
Bibliographic record
Abstract
BACKGROUND: Diabetic ketoacidosis (DKA) and hyperglycaemic hyperosmolar syndrome (HHS) are life-threatening complications of diabetes mellitus. However, limited data about DKA and HHS are available in patients with cancer. The current study aimed to determine characteristics and outcomes of patients with cancer who were admitted with DKA/HHS in a mid-size Canadian city. METHODS: Consecutive adult patients with an active cancer who were admitted with DKA or HHS from January 2008 to December 2020 in the city of Saskatoon, Saskatchewan, Canada were retrospectively evaluated. A univariate logistic regression analysis was performed to examine the correlation of various clinical variables with hospital mortality. RESULTS: During the study period 6,555 patients with diabetes and cancer were admitted in one of the three tertiary care hospitals. Among them 33 (0.5 %) eligible patients with DKA or HHS with a median age of 60 years (range 36-94 years) were identified. In 36 % of patients, DKA or HHS was the presenting manifestation of newly diagnosed diabetes. Of all patients, 66 % developed DKA and 73 % had an advanced cancer. Overall, 52 % patients received a systemic cancer therapy prior to the admission, and 41 % received steroids. Ten (42 %) of 24 patients with an advanced cancer died, compared to none of the nine patients with an early-stage cancer (p = 0.032). No clinical factors significantly correlated with hospital mortality. CONCLUSIONS: Although DKA or HHS is uncommon in patients with diabetes and cancer, it is the manifestation of undiagnosed diabetes in about one-third of patients with cancer. It has been associated with high hospital mortality in patients with advanced cancer.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".