The Final 30 Days of Life
Bibliographic record
Abstract
BACKGROUND: Studies have reported overly aggressive end-of-life care (EOLC) in many cancers. We investigate trends in, and factors associated with, aggressive EOLC among patients who died of gastrointestinal (GI) cancers in Ontario, Canada. METHODS: All patients with primary cause of death from esophageal, gastric, colon, and anorectal cancer from January 2003 to December 2013 were identified through the Ontario Cancer Registry, and information was collected from linked databases. Outcomes representing aggressive EOLC were assessed: administration of chemotherapy, any emergency department (ED) visits, hospital admissions, intensive care unit (ICU) admissions (all within 30 days of death), death in hospital and in ICU, and a composite outcome representing any aggressive EOLC. Temporal trends were analyzed using the Cochran-Armitage test. RESULTS: There were 34 630 patients in the cohort: 43% colon, 26% anorectal, 19% gastric, and 12% esophageal cancers. Aggressive EOLC was delivered to 65%, with a significantly decreasing trend from 64.8% in 2003 to 62.5% in 2013 ( P = .001). Utilization of specific elements of aggressive EOLC included 8% chemotherapy, 46% ED visits, 49% hospital admissions, 6% ICU admissions, 45% death in hospital, and 5% death in ICU. Trends over the study period showed that ED visits (from 43% to 46.9%; P = .0001) and death in ICU (from 3.7% to 4.9%; P = .04) significantly increased; hospital admissions (from 48.9% to 47.8%; P = .02) and death in hospital (from 46.6% to 38.9%; P < .0001) significantly decreased. CONCLUSIONS: Two-thirds of patients with GI cancer had aggressive EOLC in the last 30 days of life.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".