Should Extremely Premature Babies Get Ventilators During the COVID-19 Crisis?
Bibliographic record
Abstract
In a crisis, societal needs take precedence over a patient's best interests. Triage guidelines, however, differ on whether limited resources should focus on maximizing lives or life-years. Choosing between these two approaches has implications for neonatology. Neonatal units have ventilators, some adaptable for adults. This raises the question of whether, in crisis conditions, guidelines for treating extremely premature babies should be altered to free-up ventilators. Some adults who need ventilators will have a survival rate higher than some extremely premature babies. But surviving babies will likely live longer, maximizing life-years. Empiric evidence demonstrates that these babies can derive significant survival benefits from ventilation when compared to adults. When "triaging" or choosing between patients, justice demands fair guidelines. Premature babies do not deserve special consideration; they deserve equal consideration. Solidarity is crucial but must consider needs specific to patient populations and avoid biases against people with disabilities and extremely premature babies.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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".