Respiratory Dysfunction Criteria in Critically Ill Children: The PODIUM Consensus Conference
Bibliographic record
Abstract
CONTEXT: Respiratory dysfunction is a component of every organ failure scoring system developed, reflecting the significance of the lung in multiple organ dysfunction syndrome. However, existing systems do not reflect current practice and are not consistently evidence based. OBJECTIVE: We aimed to review the literature to identify the components of respiratory failure associated with outcomes in children, with the purpose of developing an operational and evidence-based definition of respiratory dysfunction. DATA SOURCES: Electronic searches of PubMed and Embase were conducted from 1992 to January 2020 by using a combination of medical subject heading terms and text words to define respiratory dysfunction, critical illness, and outcomes. STUDY SELECTION: We included studies of critically ill children with respiratory dysfunction that evaluated the performance of metrics of respiratory dysfunction and their association with patient-centered outcomes. Studies in adults, studies in premature infants (≤36 weeks' gestational age), animal studies, reviews and commentaries, case series with sample sizes ≤10, and studies not published in English in which we were unable to determine eligibility criteria were excluded. DATA EXTRACTION: Data were abstracted into a standard data extraction form. RESULTS: We provided binary (no or yes) and graded (no, nonsevere, or severe) definitions of respiratory dysfunction, prioritizing oxygenation and respiratory support. The proposed criteria were approved by 82% of members in the first round, with a score of 8 of 9 (interquartile range 7-8). LIMITATIONS: Exclusion of non-English publications, heterogeneity across the pediatric age range, small sample sizes, and incomplete handling of confounders are limitations. CONCLUSIONS: We propose definitions for respiratory dysfunction in critically ill children after an exhaustive literature review.
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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 | 0.033 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".