Validation of sonographic assistance for placement of a nasogastric tube in pediatric patients
Bibliographic record
Abstract
PURPOSE: Enteral access via nasogastric tube (NGT) placement can be essential in the provision of care in pediatric patients. Methods exist to confirm correct placement with success rates between 80% and 85%. Radiographic confirmation remains the "gold-standard," however; it exposes patients to ionizing radiation and fails to provide "real-time" information. In this study, we determined the feasibility of using sonography to assist in the placement of NGT insertions in pediatric patients that have difficulty cooperating. METHODS: Thirty patients requiring NGT placement were stratified into three age groups. Upon NGT insertion, transverse and longitudinal ultrasound images were acquired to visualize tube progression through the esophagus. Subsequently, a focused ultrasonographic exam of the gastric antrum and body were performed. If amenable, an air bolus (1 mL/kg) was injected in the stomach if the NGT was not directly visualized. Following intubation, standard guidelines for NGT position confirmation were performed. RESULTS: The NGT was visualized in all esophageal views and 52% of gastric views. Subgroup analysis showed that successful visualization of tube placement in the stomach ranged from 40% (7-18 years) to 70% (3-6 years). Eighty percentage of air boluses injected were visualized. CONCLUSION: The use of ultrasonography may assist NGT placement in pediatric patients and reduce the incidence of suboptimal placement during insertion. We demonstrated successful NGT visualization through the esophagus regardless of age. NGT visualization in the stomach was challenging; however, injection of an air bolus may improve visualization. Further studies are required to improve the success rate of obtaining gastric views of the NGT.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".