Diagnostic accuracy of point‐of‐care ultrasound compared to standard‐of‐care methods for endotracheal tube placement in neonates
Bibliographic record
Abstract
INTRODUCTION: Point-of-care ultrasound (POCUS) is a valuable tool to determine endotracheal tube (ETT) placement; however, few studies have compared it with standard confirmation methods. We evaluated the diagnostic accuracy of POCUS and time-to-interpretation for correct identification of tracheal versus esophageal intubations compared to a composite of standard-of-care methods in neonates. METHODS: A cross-sectional study was conducted in the Neonatal Intensive Care Unit (NICU) at Aga Khan University Hospital Karachi, Pakistan. All required intubations were performed as per NICU guidelines. The clinical team simultaneously determined the ETT placement using standard-of-care methods (auscultation, colorimetric capnography, and chest X-ray) by POCUS. In addition, the clinical team was blinded to the POCUS images. Timings were recorded for each method by independent study staff. RESULTS: A total of 348 neonates were enrolled in the study. More than half (58%) of intubations were in an emergency scenario. POCUS user interpretation showed 100% sensitivity and 94% specificity using an expert as the reference standard. We found a 99.4% agreement (Kappa: 0.96; p < 0.001). Diagnostic accuracy of POCUS compared with at least two standard-of-care methods demonstrated 99.7% sensitivity, 91% specificity, and 98.9% agreement (Kappa:0.93; p < 0.001). The median time required for POCUS interpretation was 3.0 (interquartile range [IQR] 3.0-4.0) seconds for tracheal intubation. The time recorded for auscultation and capnography was 6.0 (IQR 5.0-7.0) and 3.0 (IQR 3.0-4.0), respectively. CONCLUSION: POCUS is a rapid and reliable method of identifying ETT placement in neonates. Early and correct identification of airway management is critical to save lives and prevent mortality and morbidity.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".