A Core Outcome Set for Pediatric Critical Care*
Bibliographic record
Abstract
OBJECTIVES: More children are surviving critical illness but are at risk of residual or new health conditions. An evidence-informed and stakeholder-recommended core outcome set is lacking for pediatric critical care outcomes. Our objective was to create a multinational, multistakeholder-recommended pediatric critical care core outcome set for inclusion in clinical and research programs. DESIGN: A two-round modified Delphi electronic survey was conducted with 333 invited research, clinical, and family/advocate stakeholders. Stakeholders completing the first round were invited to participate in the second. Outcomes scoring greater than 69% "critical" and less than 15% "not important" advanced to round 2 with write-in outcomes considered. The Steering Committee held a virtual consensus conference to determine the final components. SETTING: Multinational survey. PATIENTS: Stakeholder participants from six continents representing clinicians, researchers, and family/advocates. MEASUREMENTS AND MAIN RESULTS: Overall response rates were 75% and 82% for each round. Participants voted on seven Global Domains and 45 Specific Outcomes in round 1, and six Global Domains and 30 Specific Outcomes in round 2. Using overall (three stakeholder groups combined) results, consensus was defined as outcomes scoring greater than 90% "critical" and less than 15% "not important" and were included in the final PICU core outcome set: four Global Domains (Cognitive, Emotional, Physical, and Overall Health) and four Specific Outcomes (Child Health-Related Quality of Life, Pain, Survival, and Communication). Families (n = 21) suggested additional critically important outcomes that did not meet consensus, which were included in the PICU core outcome set-extended. CONCLUSIONS: The PICU core outcome set and PICU core outcome set-extended are multistakeholder-recommended resources for clinical and research programs that seek to improve outcomes for children with critical illness and their families.
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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 | 0.055 | 0.097 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".