ABSTRACT 43
Bibliographic record
Abstract
Background and aims: Albeit promising lung-protective therapy, HFOV has not demonstrated any benefit over low-Vt conventional ventilation in pediatrics. Concerns have recently raised about HFOV safety in adults. Aims: This international web-based survey assess stated endpoints used by intensivists to start and stop HFOV in pediatric ARDS. Methods: We designed 3 clinical scenarios of pediatric ARDS varying by age and hemodynamic status. The case report form was elaborated and evaluated using the Delphi and Likert’s methods, respectively. For each scenario, the responder selected parameters (and their values) necessary to switch from conventional mechanical ventilation to HFOV, among those: pressure item (Positive end-expiratory pressure, Mean Airway Pressure, Peak Pressure, Plateau Pressure); Oxygenation item (PaO2, SpO2, FiO2, FiO2/PaO2 ratio, Oxygenation index); pH; PaCO2. The survey was sent 3 times to the mailing lists of the PALISI, ESPNIC and ANZICS networks. Descriptive statistical analysis was performed. The Ethical committee of Sainte-Justine Hospital, Montreal, Qc, Canada approved the study. Results: 213 intensivists (37,5%) fullfilled the survey. 51% consider HFOV to be an early therapy, versus a rescue therapy for 49%. More than 70 different patterns are reported to trigger HFOV initiation. Peak Pressure, Plateau Pressure, FiO2, SpO2, pH and PCO2 are the most reported parameters. Age or hemodynamic compromise does not influence mean value of any item. The statement « early HFOV versus rescue HFOV» does not influence the threshold to initiate oscillatory ventilation. Conclusions: Pediatric RCTs and guidelines are needed. Ventilation management should be protocolized in any trial about pediatric ARDS.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.608 | 0.453 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".