The ‘ouR‐<scp>HOPE</scp>’ approach for ethics and communication about neonatal neurological injury
Bibliographic record
Abstract
Predicting neurological outcomes of neonates with acute brain injury is an essential component of shared decision-making, in order to guide the development of treatment goals and appropriate care plans. It can aid parents in imagining the child's future, and guide timely and ongoing treatment decisions, including shifting treatment goals and focusing on comfort care. However, numerous challenges have been reported with respect to evidence-based practices for prognostication such as biases about prognosis among clinicians. Additionally, the evaluation or appreciation of living with disability can differ, including the well-known disability paradox where patients self-report a good quality of life in spite of severe disability. Herein, we put forward a set of five practice principles captured in the "ouR-HOPE" approach (Reflection, Humility, Open-mindedness, Partnership, and Engagement) and related questions to encourage clinicians to self-assess their practice and engage with others in responding to these challenges. We hope that this proposal paves the way to greater discussion and attention to ethical aspects of communicating prognosis in the context of neonatal brain injury.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.007 |
| 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; both teacher heads agree on what is shown here.
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".