Palliative care intervention and aggressive care at end-of-life in patients with advanced pancreatic adenocarcinoma.
Bibliographic record
Abstract
244 Background: Unresectable pancreatic cancer carries one of the worst prognoses amongst malignancies. For these patients, their treatment at end-of-life represents some of the most expensive care they will receive. Resource-intensive care at the end of life contrasts with the preferences of many patients and their family members. We have examined the intensity of end-of-life care in patients diagnosed with unresectable pancreatic adenocarcinoma using a previously published aggressiveness score. Methods: The surveillance and epidemiology unit of the program of care for cancer identified all patients diagnosed with unresectable pancreatic adenocarcinoma in Nova Scotia between January 1, 2011 and December 31, 2014. Charts were then reviewed for demographic data, Charlson Comorbidity Index, and consultation with Palliative Care. An aggressiveness of end-of-life care score, which has been previously described in the literature, was employed. Briefly, scores ranged from 0 to 6, with higher scores representing more aggressive care. One point was assigned for each of the following events in the last 30 days of life: two or more emergency department visits, two or more hospitalizations, 14 or more inpatient days, chemotherapy, intensive care unit admission, death in hospital. One-way ANOVA was then performed to determine factors associated with more aggressive end-of-life care. Results: In total, 264 patients met inclusion criteria. Mean aggressiveness of end-of-life care was 0.92 (95% CI 0.8 – 1.03). On average, patients seen by Palliative Care at any point in their illness had less aggressive treatment than those never seen by Palliative Care (0.83 vs 1.38, p = 0.001). Conclusions: In patients diagnosed with unresectable pancreatic cancer, less aggressive end-of-life care Further work, including prospective studies, is needed to identify a true association between palliative care intervention and less aggressive care at end-of-life. Such an association could lead to benefits for the patient and reduce costly resource-intensive 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 | 0.000 |
| 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 | 0.000 |
| 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".