Modalities and Complications Associated With the Use of High-Flow Nasal Cannula: Experience in a Pediatric ICU
Bibliographic record
Abstract
BACKGROUND: High-flow nasal cannula (HFNC) therapy is increasingly used in pediatric ICUs as an intermediate level of support between conventional oxygen delivery and noninvasive ventilation (NIV). The safety of HFNC has seldom been studied, and some cases of barotrauma have been reported. This retrospective study aims to describe HFNC use in a tertiary care pediatric ICU, with a focus on the complications associated with this therapy. METHODS: Between January 2013 and January 2014, all children <18 y old treated with HFNC in the pediatric ICU were included. Demographic data, HFNC settings, chest radiograph reports, and blood gas values were gathered from the electronic medical records. Episodes of pneumothorax, pneumomediastinum, and significant epistaxis were noted. Pneumothorax was distinguished from chest tube-related air leak (frequent after cardiac surgery), which was defined as a small pneumothorax with no clinical impact that resolved spontaneously after chest tube removal. RESULTS: During the 1-y study period, there were 177 HFNC episodes, involving 145 subjects with a median (interquartile range) age of 8 (2-28) months. HFNC was used as primary support in 31% of episodes, after extubation in 36% and after NIV in 18%. HFNC was administered exclusively for nitric oxide delivery in 16% of episodes. Two children (1%) developed new pneumothoraces that required chest tube insertion, whereas 5 (3%) chest tube-related air leaks were noted. One (0.6%) episode of significant epistaxis was noted. Among 6 preexisting pneumothoraces, none worsened under HFNC. Failure of HFNC occurred in 32 episodes, requiring transition to NIV in 28 cases and endotracheal intubation in 5 cases. CONCLUSIONS: Support with HFNC following a clinical protocol in pediatric ICUs was associated with a relatively low rate of complications. Since HFNC use is increasing, further evidence is needed to confirm its efficacy and safety.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".