Consensus definition and diagnostic criteria for neonatal encephalopathy—study protocol for a real-time modified delphi study
Bibliographic record
Abstract
BACKGROUND: 'Neonatal encephalopathy' (NE) describes a group of conditions in term infants presenting in the earliest days after birth with disturbed neurological function of cerebral origin. NE is aetiologically heterogenous; one cause is peripartum hypoxic ischaemia. Lack of uniformity in the terminology used to describe NE and its diagnostic criteria creates difficulty in the design and interpretation of research and complicates communication with families. The DEFINE study aims to use a modified Delphi approach to form a consensus definition for NE, and diagnostic criteria. METHODS: Directed by an international steering group, we will conduct a systematic review of the literature to assess the terminology used in trials of NE, and with their guidance perform an online Real-time Delphi survey to develop a consensus diagnosis and criteria for NE. A consensus meeting will be held to agree on the final terminology and criteria, and the outcome disseminated widely. DISCUSSION: A clear and consistent consensus-based definition of NE and criteria for its diagnosis, achieved by use of a modified Delphi technique, will enable more comparability of research results and improved communication among professionals and with families. IMPACT: The terms Neonatal Encephalopathy and Hypoxic Ischaemic Encephalopathy tend to be used interchangeably in the literature to describe a term newborn with signs of encephalopathy at birth. This creates difficulty in communication with families and carers, and between medical professionals and researchers, as well as creating difficulty with performance of research. The DEFINE project will use a Real-time Delphi approach to create a consensus definition for the term 'Neonatal Encephalopathy'. A definition formed by this consensus approach will be accepted and utilised by the neonatal community to improve research, outcomes, and parental experience.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".