Noninvasive ventilation of air transported infants with respiratory distress in the Canadian Arctic
Bibliographic record
Abstract
Abstract Objectives Since 2016, use of nasal continuous positive airway pressure (nCPAP) in Nunavut for air transport in select patients has become common practice. This study examines the outcomes of patients transferred by air from the Qikiqtaaluk Region during air transport. We examined intubation rates, adverse events during transfer, and respiratory parameters at departure and upon arrival. Methods This was a retrospective review from September 2016 to December 2019 including patients under 2 years of age transferred by air on nCPAP from the Qikiqtaaluk Region of Nunavut. Results Data were collected for 40 transfers involving 34 unique patients. Six transfers were from remote communities in Nunavut to Iqaluit, and 33 transfers were from Iqaluit to CHEO. The primary outcome measure was whether the patient required intubation during transport, or urgent intubation upon arrival to CHEO. The median nCPAP setting during transport was 6 cm H2O (5–7 cm H2O) and at arrival to CHEO was 6 cm H2O (6–7 cm H2O). Six of the 33 (18.2%) patients required intubation during their hospital stay and five (15.2%) in a controlled ICU setting. There were no discernible adverse events that occurred during transport for 28 patients (84.5%). Four patients (12.1%) required a brief period of bag-mask ventilation and one patient had an episode of bradycardia. Conclusions nCPAP on air transport is a safe and useful method for providing ventilatory support to infants and young children with respiratory distress.
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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 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".