A Qualitative Study of Physician Perspectives on Prognostication in Neonatal Hypoxic Ischemic Encephalopathy
Bibliographic record
Abstract
Hypoxic ischemic encephalopathy is the most frequent cause of neonatal encephalopathy and yields a great degree of morbidity and mortality. From an ethical and clinical standpoint, neurological prognosis is fundamental in the care of neonates with hypoxic ischemic encephalopathy. This qualitative study explores physician perspectives about neurological prognosis in neonatal hypoxic ischemic encephalopathy. This study aimed, through semistructured interviews with neonatologists and pediatric neurologists, to understand the practice of prognostication. Qualitative thematic content analysis was used for data analysis. The authors report 2 main findings: (1) neurological prognosis remains fundamental to quality-of-life predictions and considerations of best interest, and (2) magnetic resonance imaging is presented to parents with a greater degree of certainty than actually exists. Further research is needed to explore both the parental perspective and, prospectively, the impact of different clinical approaches and styles to prognostication for neonatal hypoxic ischemic encephalopathy.
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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 | 0.030 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".