Life and death decisions for incompetent patients: determining best interests – the Irish perspective
Bibliographic record
Abstract
AIMS: To determine whether healthcare providers apply the best interest principle equally to different resuscitation decisions. METHODS: An anonymous questionnaire was distributed to consultants, trainees in neonatology, paediatrics, obstetrics and 4th medical students. It examined resuscitation scenarios of critically ill patients all needing immediate resuscitation. Outcomes were described including survival and potential long-term sequelae. Respondents were asked whether they would intubate, whether resuscitation was in the patients best interest, would they accept surrogate refusal to initiate resuscitation and in what order they would resuscitate. RESULTS: The response rate was 74%. The majority would wish resuscitation for all except the 80-year-old. It was in the best interest of the 2-month-old and the 7-year-old to be resuscitated compared to the remaining scenarios (p value <0.05 for each comparison). Approximately one quarter who believed it was in a patient best interests to be resuscitated would nonetheless accept the family refusing resuscitation. Medical students were statistically more likely to advocate resuscitation in each category. CONCLUSION: These results suggest resuscitation is not solely related to survival or long-term outcome and the best interest principle is applied differently, more so at the beginning of life.
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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 | 0.000 | 0.008 |
| 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".