Are we offering palliative care and employing shared decision making in the neonatal intensive care unit? A 10-year retrospective chart review
Bibliographic record
Abstract
Objective: Perinatal palliative care (PPC) supports families with a fetal diagnosis of a life-limiting condition or who are facing preterm labour at the limits of viability. Shared decision making (SDM) is the gold standard approach in PPC. The objectives of this study were to describe the Neonatal Intensive Care Unit (NICU) team's involvement in PPC and the extent of SDM at an academic hospital in southeastern Ontario, and the frequency with which PPC was offered, accepted and received for live births. Methods: We retrospectively reviewed charts for births from January 2010-January 2020 where a life-limiting condition (LLC) had been prenatally diagnosed or there was threatened preterm labour (TPTL) at the limits of viability. Frequency distributions were used to summarize the NICU team's involvement, extent of SDM, and data related to PPC provision. Results: The LLC group included 73 patients. The NICU team was consulted for 26 (36 %). Among the 10 consults that involved decision making, SDM was documented in 9 instances (90 %). PPC was offered to 9 of 60 LLC families (15 %) with a live birth and was accepted by 8 (89 %). The TPTL Group included 112 patients. Seventy (62 %) received a consult with the NICU team. SDM was documented in 34 of 39 consults (87 %) that involved decision making. PPC was offered to 28 of 90 families (31 %) who experienced a live birth and was accepted by 16 (57 %). Conclusion: Our results demonstrate the need for standardized consultation and palliative care referral protocols to advance access to and quality of neonatal end-of-life 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.002 | 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".