Towards a harmonized bronchopulmonary dysplasia definition: a study protocol for an international Delphi procedure
Bibliographic record
Abstract
INTRODUCTION: Bronchopulmonary dysplasia (BPD) remains the most common complication of preterm birth with lifelong consequences. Multiple BPD definitions are currently used in daily practice. Uniformity in defining BPD is important for clinical care, research and benchmarking. The aim of this Delphi procedure is to determine what clinicians and researchers consider the key features for defining BPD. With the results of this study, we hope to advance the process of reaching consensus on the diagnosis of BPD. METHODS AND ANALYSIS: A Delphi procedure will be used to establish why, when and how clinicians propose BPD should be diagnosed. This semi-anonymous iterative technique ensures an objective approach towards gaining these insights. An international multidisciplinary panel of clinicians and researchers working with preterm infants and/or patients diagnosed with BPD will participate. Steering committee members will recruit potential participants in their own region or network following eligibility guidelines to complete a first round survey online. This round will collect demographic information and opinions on key features of BPD definitions. Subsequent rounds will provide participants with the results from the previous round, for final acceptance or rejection of key features. Statements will be rated using a 5-point Likert scale. After completing the Delphi procedure, an (online) consensus meeting will be organised to discuss the results. ETHICS AND DISSEMINATION: For this study, ethical approval a waiver has been provided. However, all participants will be asked to provide consent for the use of personal data. After the Delphi procedure is completed, it will be published in a peer-reviewed journal and disseminated at international conferences.
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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 | 0.217 | 0.146 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.042 | 0.013 |
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".