Sex-Based Analysis of Quality Indicators of End-of-Life Care in Gastrointestinal Malignancies
Bibliographic record
Abstract
Indices of aggressive or supportive end-of-life (EOL) care are used to evaluate health services quality. Disparities according to sex were previously described, with studies showing that male sex is associated with aggressive EOL care. This is a secondary analysis of 69,983 patients who died of a GI malignancy in Ontario between 2006 and 2018. Quality indices from the last 14-30 days of life and aggregate measures for aggressive and supportive EOL care were derived from administrative data. Hospitalizations, emergency department use, intensive care unit admissions, and receipt of chemotherapy were considered indices of aggressive care, while physician house call and palliative home care were considered indices of supportive care. Overall, a smaller proportion of females experienced aggressive care at EOL (14.3% vs. 19.0%, standardized difference = 0.13, where ≥0.1 is a meaningful difference). Over time, rates of aggressive care were stable, while rates of supportive care increased for both sexes. Logistic regression showed that younger females (ages 18-39) had increased odds of experiencing aggressive EOL care (OR 1.71, 95% CI 1.30-2.25), but there was no such association for males. Quality of EOL care varies according to sex, with a smaller proportion of females experiencing aggressive EOL care.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".