91 Determinants of Death or Palliative Care in Children's Hospital NICUs
Bibliographic record
Abstract
Previous studies suggest that mortality is higher in neonates admitted to children's hospitals compared to perinatal centres, even after correction for severity of illness. We examined 625 admissions to two children's hospital neonatal intensive care units (NICUs) to ascertain if admission source (another NICU versus non-NICU) is a predictor of outcome after correction for severity of illess [Score for Neonatal Acute Physiology (SNAP-II) and SNAP Perinatal Extension (SNAPPE-II)]. Cases included all acute NICU admissions to Hospital for Sick Children from July to Dec. 2002 (n=338) and Montreal Children's Hospital in the year 2002 (n=287). Mean (SD) birth weight was 2654 g (1062), gestational age 36 wks (5), and 5-min Apgar 8 (2). Median (range) SNAP-II was 0 (0–65), SNAPPE-II 15 (0–84), age of admission 1 day (0–244), and length of stay 8 days (0–312). 183 (29%) admissions were transferred from another NICU, 254 (41%) had congenital anomalies that required admission, 234 (37%) required surgical intervention, and 63 (10%) died before discharge or were discharged on palliative care. Admissions from other NICUs had increased risk of death or palliative care [RR 2.20 (95% CI 1.38, 3.49)], congenital anomalies [1.30 (1.08, 1.58)], surgery [2.46 (2.03, 2.97)], and longer length of stay [mean (SD) 24 (48) vs 14 (33) days; p=0.0006)]. Binary analyses showed that admission from another NICU, SNAP-II, SNAPPE-II, and congenital anomalies were predictors of death or palliative care (all p's<0.01), while surgery was not (p=0.91). On logistic regression, independent predictors of death or palliative care were NICU source of admission [OR 2.85 (95% CI 1.53, 5.31); p=0.0010], SNAP-II [1.09 per point (1.06, 1.11); p<0.0001], and congenital anomalies [4.68 (2.46, 8.92); p<0.0001], while surgery was inversely associated [0.33 (0.17, 0.66); p=0.0015]. Results for SNAPPE-II were similar. These results suggest that comparisons of outcomes between NICUs should include source of admission and associated casemix (congenital anomalies, surgeries) as well as severity of illness for neonates admitted to children's hospitals.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".