Core Outcome Sets for Medium-Chain Acyl-CoA Dehydrogenase Deficiency and Phenylketonuria
Bibliographic record
Abstract
BACKGROUND: Evidence to guide treatment of pediatric medium-chain acyl-coenzyme A dehydrogenase (MCAD) deficiency and phenylketonuria (PKU) is fragmented because of large variability in outcome selection and measurement. Our goal was to develop core outcome sets (COSs) for these diseases to facilitate meaningful future evidence generation and enhance the capacity to compare and synthesize findings across studies. METHODS: Parents and/or caregivers, health professionals, and health policy advisors completed a Delphi survey and participated in a consensus workshop to select core outcomes from candidate lists of outcomes for MCAD deficiency and PKU. Delphi participants rated the importance of outcomes on a nine-point scale (1-3: not important, 4-6: important but not critical, 7-9: critical). Candidate outcomes were progressively narrowed down over 3 survey rounds. At the workshop, participants evaluated the remaining candidate outcomes using an adapted nominal technique, open discussion, and voting. After the workshop, we finalized the COSs and recommended measurement instruments for each outcome. RESULTS: There were 85, 61, and 53 participants across 3 Delphi rounds, respectively. The candidate core outcome lists were narrowed down to 20 outcomes per disease to be discussed at the consensus workshop. Voting by 18 workshop participants led to COSs composed of 8 and 9 outcomes for MCAD deficiency and PKU, respectively, with measurement recommendations. CONCLUSIONS: These are the first known pediatric COSs for MCAD deficiency and PKU. Adoption in future studies will help to ensure best use of limited research resources to ultimately improve care for children with these rare diseases.
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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 | 0.100 | 0.202 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".