Experiences from the first 10 years of a perinatal palliative care program: A retrospective chart review
Bibliographic record
Abstract
BACKGROUND: Perinatal palliative care is a relatively new component of paediatric palliative care which supports families who are expecting the birth of a child with a life-limiting condition. This study seeks to understand the characteristics of the infants and families referred for perinatal palliative care and the context for referrals in terms of diagnoses, referral characteristics, interventions, and outcomes. METHODS: A retrospective chart review of infants with prenatally diagnosed life-limiting conditions that were referred for perinatal palliative care. RESULTS: Eighty-five referrals were made for perinatal palliative care during the 10-year period, of which, 84 chose to continue with the service. Average gestational age at diagnosis was 23 weeks, and the mean time between diagnosis and referral to palliative care was 7 weeks. Stillbirths were common, occurring in 29% cases. Of livebirths, 59% of the infants survived for 2 days, and 80% died within 30 days. The most commonly referred conditions were trisomy 13 or 18 (24%), severe central nervous system malformations (20%), and severe congenital cardiac disease (16%). Referrals were most often made by neonatologists (39%), and maternal-fetal medicine specialists (36%). DISCUSSION: Our study confirms previously observed characteristics of diagnosis, referrals, and outcomes, while providing the most detailed account of lifespans for particular diagnoses to date. Our findings validate the need for perinatal palliative care, as 99% of those referred continued with the service. Future research should adopt a prospective approach to identify critical factors affecting decision making of families and physicians in the wake of a life-limiting diagnosis.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".