The use of mechanical ventilation protocols in Canadian neonatal intensive care units
Bibliographic record
Abstract
OBJECTIVES: To identify the proportion of Canadian neonatal intensive care units with existing mechanical ventilation protocols and to determine the characteristics and respiratory care practices of units that have adopted such protocols. METHODS: A structured survey including 36 questions about mechanical ventilation protocols and respiratory care practices was mailed to the medical directors of all tertiary care neonatal units in Canada and circulated between December 2012 and March 2013. RESULTS: Twenty-four of 32 units responded to the survey (75%). Of the respondents, 91% were medical directors and 71% worked in university hospitals. Nine units (38%) had at least one type of mechanical ventilation protocol, most commonly for the acute and weaning phases. Units with pre-existing protocols were more commonly university-affiliated and had higher ratios of ventilated patients to physicians or respiratory therapists, although this did not reach statistical significance. The presence of a mechanical ventilation protocol was highly correlated with the coexistence of a protocol for noninvasive ventilation (P<0.001, OR 4.5 [95% CI 1.3 to 15.3]). There were overall wide variations in ventilation practices across units. However, units with mechanical ventilation protocols were significantly more likely to extubate neonates from the assist control mode (P=0.039, OR 8.25 [95% CI 1.2 to 59]). CONCLUSION: Despite the lack of compelling evidence to support their use in neonates, a considerable number of Canadian neonatal intensive care units have adopted mechanical ventilation protocols. More research is needed to better understand their role in reducing unnecessary variations in practice and improving short- and long-term outcomes.
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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 | 0.004 | 0.025 |
| 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 | 0.001 |
| Open science | 0.002 | 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".