Attitudes of <scp>A</scp>ustralian neonatologists to resuscitation of extremely preterm infants
Bibliographic record
Abstract
AIM: We aimed to investigate how Australian neonatologists made decisions when incompetent patients of different ages needed resuscitation. METHODS: A survey including vignettes of eight incompetent patients requiring resuscitation was sent to 140 neonatologists. Patients ranged from a very preterm infant to 80 years old. While some had existing impairments, all faced risk of death or neurological sequelae. Respondents indicated whether they would resuscitate, whether they believed resuscitation was in the patients' best interests, whether they would want intervention for a family member and whether they would comply with families' wishes to withhold resuscitation. They were also asked how they would rank the eight patients in a triage situation. RESULTS: Seventy-eight per cent of specialists completed the survey. The majority of respondents gave priority to the resuscitation of children over adults. Less than 40% would agree to withhold resuscitation at families' request for all children except for the preterm infant, where 96% would comply with families' wishes to withhold intensive care despite 77% believing resuscitation to be in the infant's best interest. CONCLUSION: This study found inconsistencies between physicians' perceptions of the patient's best interest regarding resuscitation and their willingness to comply with families' wishes to withhold resuscitation and give comfort care. Accepting a family's refusal of resuscitation was more marked for the premature infant, even among respondents who thought that resuscitation was in the patient's best interest. These findings are consistent with other international studies.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".