Implementation of Video Laryngoscope-Assisted Coaching Reduces Adverse Tracheal Intubation-Associated Events in the PICU*
Bibliographic record
Abstract
OBJECTIVES: To evaluate implementation of a video laryngoscope (VL) as a coaching device to reduce adverse tracheal intubation associated events (TIAEs). DESIGN: Prospective multicenter interventional quality improvement study. SETTING: Ten PICUs in North America. PATIENTS: Patients undergoing tracheal intubation in the PICU. INTERVENTIONS: VLs were implemented as coaching devices with standardized coaching language between 2016 and 2020. Laryngoscopists were encouraged to perform direct laryngoscopy with video images only available in real-time for experienced supervising clinician-coaches. MEASUREMENTS AND MAIN RESULTS: The primary outcome was TIAEs. Secondary outcomes included severe TIAEs, severe hypoxemia (oxygen saturation < 80%), and first attempt success. Of 5,060 tracheal intubations, a VL was used in 3,580 (71%). VL use increased from baseline (29.7%) to implementation phase (89.4%; p < 0.001). VL use was associated with lower TIAEs (VL 336/3,580 [9.4%] vs standard laryngoscope [SL] 215/1,480 [14.5%]; absolute difference, 5.1%; 95% CI, 3.1-7.2%; p < 0.001). VL use was associated with lower severe TIAE rate (VL 3.9% vs SL 5.3%; p = 0.024), but not associated with a reduction in severe hypoxemia (VL 15.7% vs SL 16.4%; p = 0.58). VL use was associated with higher first attempt success (VL 71.8% vs SL 66.6%; p < 0.001). In the primary analysis after adjusting for site clustering, VL use was associated with lower adverse TIAEs (odds ratio [OR], 0.61; 95% CI, 0.46-0.81; p = 0.001). In secondary analyses, VL use was not significantly associated with severe TIAEs (OR, 0.72; 95% CI, 0.44-1.19; p = 0.20), severe hypoxemia (OR, 0.95; 95% CI, 0.73-1.25; p = 0.734), or first attempt success (OR, 1.28; 95% CI, 0.98-1.67; p = 0.073). After further controlling for patient and provider characteristics, VL use was independently associated with a lower TIAE rate (adjusted OR, 0.65; 95% CI, 0.49-0.86; p = 0.003). CONCLUSIONS: Implementation of VL-assisted coaching achieved a high level of adherence across the PICUs. VL use was associated with reduced adverse TIAEs.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".