Predictors of Symptoms and Site of Death in Pediatric Palliative Patients With Cancer at End of Life
Bibliographic record
Abstract
OBJECTIVE: To describe how preferences and treatment influence symptoms at end of life and site of death in pediatric cancer. METHODS: We included 61 pediatric palliative patients with cancer whose parents previously participated in a study that elicited preferences for aggressive chemotherapy versus supportive care alone and who subsequently died. Main outcomes were severe pain and dyspnea proximal to death and site of death. RESULTS: Choice of aggressive chemotherapy predicted significantly more severe pain (odds ratio [OR] 3.1, 95% confidence interval [CI] 1.0-9.6; P = .049). Intravenous chemotherapy 4 weeks before death predicted severe dyspnea (OR 15.8, 95% CI 3.7-67.5; P < .001) and death outside the home (OR 0.3, 95% CI 0.1-0.9; P = .038). CONCLUSIONS: Parental choice of aggressive chemotherapy and more aggressive treatment proximal to death predicted more pain, dyspnea, and death in hospital. Strategies to improve quality of life are needed.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".