Medications to manage infant pain, distress and end-of-life symptoms in the immediate postpartum period
Bibliographic record
Abstract
INTRODUCTION: Perinatal palliative care (PnPC) is a growing field where healthcare providers from multiple disciplines are supporting families and providing holistic care for their babies with life-limiting illnesses. It is important to have an approach that includes the standardized management of end-of-life symptoms that are anticipated around the time of birth. AREAS COVERED: A need was identified to develop medication orders for the initial pharmacological management of symptoms at end-of-life for infants with life-limiting conditions intended for use outside of an intensive care setting. The choice of medications was based on a review of the literature, discussion with content experts and guided by their ease of use, accessibility and noninvasive route of delivery. The recommendations can be used as a guide for the initial management of common symptoms encountered in perinatal palliative care. EXPERT OPINION: There are studies looking at many qualitative aspects of perinatal palliative care including perceptions of care, decision-making, and bereavement; however, few specifically focus on symptom management in the delivery room and postpartum ward settings. There is a need for standardization of the medical management of infants born with life-limiting conditions whose parents choose to pursue palliative 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".