Analysis of Pediatric Direct Laryngoscopy and Bronchoscopy Operative Flow
Bibliographic record
Abstract
OBJECTIVE: To study pediatric direct laryngoscopy and bronchoscopy operative flow. DESIGN: Observational quality improvement initiative. SETTING: Two freestanding tertiary care children's hospitals. PATIENTS: Pediatric patients undergoing direct laryngoscopy and bronchoscopy. MAIN OUTCOME MEASURES: Trained medical students observed direct laryngoscopy and bronchoscopy operative flow. An audit tool containing 144 fields was completed during each encounter for the following domains: timing of the case, preoperative preparation, operative flow, and operating room personnel assessment. RESULTS: Forty-one cases were observed. The mean time between the patient entering the operating room and the beginning of the case was 12 minutes. In all the patients, a complete history was obtained, and a physical examination was performed. The equipment was ready for 31 cases (76%) and was checked before 32 cases (78%). Anesthesia equipment was checked before 36 cases (88%). Issues with intravenous access were recorded for 19 cases (46%). The operating room orientation needed to be changed to accommodate the procedure in 11 cases (27%). Preoperative preparation of the patient proceeded smoothly in 16 cases (39%), and the operative flow proceeded without disruption in 19 cases (46%). The scrub nurse left the operating room in 2 cases (5%), the circulating nurse left in 15 cases (37%), and the anesthesiologist left in 9 cases (22%). CONCLUSIONS: Although a common pediatric otolaryngology procedure, direct laryngoscopy and bronchoscopy operative flow is ideal in less than half the cases. Areas for improvement include obtaining intravenous access, reducing operating room personnel turnover, verifying equipment, and educating staff on operating room setup. To our knowledge, this is the first observational quality improvement initiative in otolaryngology to study the operative flow of a specific procedure and provide insight into areas of patient risk and opportunities for improvement in efficiency.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".