End of life, death and dying in neonatal intensive care units in Latin America
Bibliographic record
Abstract
AIM: Most analyses of end of life decisions in Neonatal Intensive Care Units (NICUs) have come from Europe/English-speaking countries. Would decisions be different in Latin American NICUs? Therefore, we aim to evaluate the approach to dying infants/families in NICUs in Latin America. METHODS: Multinational descriptive study of all deaths in babies born at >22 weeks in eight NICUs in five Latin American countries. Deaths were categorized as: (i) no Cardiopulmonary Resuscitation (CPR) or life support offered; (ii) life support initiated but do not resuscitate (DNR) orders written or no CPR provided; (iii) full life support and CPR; and (iv) unclassifiable. RESULTS: There were 100 deaths, 81% in >27 weeks. Seventeen infants received no CPR/life support at birth, 10 died in DR and seven in NICU. There were 27 infants in group 2, 54 in group three and two in group 4. No baby had care withdrawn or care withdrawn/CPR withheld. Thirty-two infants had 'do not resuscitate' order. Decisions without parents' involvement in 15%, both parents present at death 24% and sedatives/narcotics documented 14%. CONCLUSIONS: Latin American NICUs differ from those in Northern Europe/English-speaking countries. More deaths are accompanied by full life support and CPR. DNR orders are rare. Withdrawal of life support is virtually non-existent. Latin American's doctors are more likely to make decisions without the objections of family about withholding life-sustaining treatment.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".