Ethics of Resuscitation at Different Stages of Life: A Survey of Perinatal Physicians
Bibliographic record
Abstract
OBJECTIVE: We surveyed US neonatologists and high-risk obstetricians about preferences for resuscitation in ethically difficult situations to determine whether (1) their responses adhered to traditional ethical principles of best interests and patient autonomy and (2) physician specialty seemed to influence the response. METHODS: In an electronic survey, we presented 8 vignettes with varying prognoses for survival and long-term outcome. Respondents were provided outcome data for mortality and morbidity in each vignette. We asked whether resuscitation was in the patient's best interest and whether the physician would accede to requests for nonresuscitation. RESULTS: We analyzed surveys for 587 neonatologists and 108 high-risk obstetricians (15% overall response rate, 75% of web site visitors). There were no statistically significant differences in responses between the 2 physician subspecialty groups. As expected, in most cases there were inverse relationships between valuation of best interest and deferred resuscitation at the family's request. For example, for the oldest patient (an 80-year-old), 9.9% found resuscitation to be in the patient's best interest and 94.3% would allow nonresuscitation; for a 2-month-old, 93.9% found resuscitation to be in the patient's best interest and 24.5% would allow nonresuscitation. However, this pattern was not observed in the 2 newborn cases, in which resuscitation and nonresuscitation were both acceptable. In the triage scenario, the 7-year-old with cerebral palsy and acute trauma was consistently resuscitated first despite others having equivalent or better short- and long-term prognoses. CONCLUSIONS: On the basis of our results, physicians' decisions to resuscitate seem to be context-specific, rather than based on prognosis or consistent application of best-interest or autonomy principles. Despite their different professional perspectives, neonatologists and high-risk obstetricians seemed to converge on these judgments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".