Corticosteroid-Induced Diabetes in Palliative Care
Bibliographic record
Abstract
BACKGROUND: Corticosteroids are one of the most commonly used medications in palliative care. Although the benefit of corticosteroids generally outweighs the risk in the palliative population, side effects are common and necessitate careful consideration prior to prescribing. In March of 2010, a guideline for monitoring blood glucose values was implemented as part of our standard care within our two inpatient tertiary palliative care units. METHOD: A retrospective study was conducted, the aim of which was twofold. First, we hoped to determine a prevalence rate for steroid-induced diabetes mellitus (SDM) in palliative care and whether or not screening glucose levels twice weekly was appropriate or required. Second, we wanted to determine if possible predictors existed for the development of SDM in a palliative population, thereby identifying the patients most at risk who would benefit from ongoing glucose monitoring. RESULTS AND DISCUSSION: We found that SDM is more common in palliative care patients than previously thought. Our study showed a higher likelihood of developing hyperglycaemia with higher doses of dexamethasone. But although dose is correlated with hyperglycemia, patients without high doses were also at risk. Further study is currently underway with slight modifications to the guideline to more accurately assess the physical burden, as well as the emotional and financial cost of a hyperglycemia screening protocol.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".