Pediatric Palliative Care Patients: A Prospective Multicenter Cohort Study
Bibliographic record
Abstract
OBJECTIVE: To describe demographic and clinical characteristics and outcomes of patients who received hospital-based pediatric palliative care (PPC) consultations. DESIGN, SETTING, AND PATIENTS: Prospective observational cohort study of all patients served by 6 hospital-based PPC teams in the United States and Canada from January to March 2008. RESULTS: There were 515 new (35.7%) or established (64.3%) patients who received care from the 6 programs during the 3-month enrollment interval. Of these, 54.0% were male, and 69.5% were identified as white and 8.1% as Hispanic. Patient age ranged from less than one month (4.7%) to 19 years or older (15.5%). Of the patients, 60.4% lived with both parents, and 72.6% had siblings. The predominant primary clinical conditions were genetic/congenital (40.8%), neuromuscular (39.2%), cancer (19.8%), respiratory (12.8%), and gastrointestinal (10.7%). Most patients had chronic use of some form of medical technology, with gastrostomy tubes (48.5%) being the most common. At the time of consultation, 47.2% of the patients had cognitive impairment; 30.9% of the cohort experienced pain. Patients were receiving many medications (mean: 9.1). During the 12-month follow-up, 30.3% of the cohort died; the median time from consult to death was 107 days. Patients who died within 30 days of cohort entry were more likely to be infants and have cancer or cardiovascular conditions. CONCLUSIONS: PPC teams currently serve a diverse cohort of children and young adults with life-threatening conditions. In contrast to the reported experience of adult-oriented palliative care teams, most PPC patients are alive for more than a year after initiating PPC.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".