Epidemiology of Noninvasive Ventilation in Pediatric Cardiac ICUs*
Bibliographic record
Abstract
OBJECTIVE: To describe the epidemiology of noninvasive ventilation therapy for patients admitted to pediatric cardiac ICUs and to assess practice variation across hospitals. DESIGN: Retrospective cohort study using prospectively collected clinical registry data. SETTING: Pediatric Cardiac Critical Care Consortium clinical registry. PATIENTS: Patients admitted to cardiac ICUs at PC4 hospitals. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We analyzed all cardiac ICU encounters that included any respiratory support from October 2013 to December 2015. Noninvasive ventilation therapy included high flow nasal cannula and positive airway pressure support. We compared patient and, when relevant, perioperative characteristics of those receiving noninvasive ventilation to all others. Subgroup analysis was performed on neonates and infants undergoing major cardiovascular surgery. To examine duration of respiratory support, we created a casemix-adjustment model and calculated adjusted mean durations of total respiratory support (mechanical ventilation + noninvasive ventilation), mechanical ventilation, and noninvasive ventilation. We compared adjusted duration of support across hospitals. The cohort included 8,940 encounters from 15 hospitals: 3,950 (44%) received noninvasive ventilation and 72% were neonates and infants. Medical encounters were more likely to include noninvasive ventilation than surgical. In surgical neonates and infants, 2,032 (55%) received postoperative noninvasive ventilation. Neonates, extracardiac anomalies, single ventricle, procedure complexity, preoperative respiratory support, mechanical ventilation duration, and postoperative disease severity were associated with noninvasive ventilation therapy (p < 0.001 for all). Across hospitals, noninvasive ventilation use ranged from 32% to 65%, and adjusted mean noninvasive ventilation duration ranged from 1 to 4 days (3-d observed mean). Duration of total adjusted respiratory support was more strongly correlated with duration of mechanical ventilation compared with noninvasive ventilation (Pearson r = 0.93 vs 0.71, respectively). CONCLUSIONS: Noninvasive ventilation use is common in cardiac ICUs, especially in patients admitted for medical conditions, infants, and those undergoing high complexity surgery. We observed wide variation in noninvasive ventilation use across hospitals, though the primary driver of total respiratory support time seems to be duration of mechanical ventilation.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".