Intra- and Interrater Reliability of Ultrasound Assessment of Gastric Volume
Bibliographic record
Abstract
BACKGROUND: Gastric sonography can provide information about gastric content and volume that can help determine aspiration risk at the bedside. The primary objective of this study is to assess the intrarater and interrater reliability of a previously validated method of gastric volume assessment based on gastric antral area. The secondary objective is to evaluate the agreement between two different methods to measure gastric antral area. METHODS: Three independent raters performed a standardized gastric ultrasound assessment in healthy subjects who had been randomly allocated to ingest a predetermined volume of clear fluid (apple juice) from 0 to 400 ml. Each rater measured the gastric antral area, using twice the two-diameter method and twice the free-tracing method. The rater order was allocated at random and raters were unaware of the volume ingested and of one-another's measurements. The Guidelines for Reporting Reliability and Agreement Studies were followed for conducting and reporting this study. RESULTS: Twenty-two volunteers were studied. Ultrasound assessment of antral cross-sectional area and volume was found to have "nearly perfect" intrarater and interrater reliability (correlation coefficient >0.8) with maximum differences within 13%. A Bland-Altman analysis suggests that the free-tracing method and the two-diameter method are essentially equivalent, within a clinically acceptable level of agreement. CONCLUSIONS: Ultrasound assessment of gastric volume by clinical anesthesiologists is highly reproducible with high intrarater and interrater reliability. The free-tracing method to measure antral cross-sectional area is equivalent to the two-diameter method.
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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 | 0.053 | 0.113 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".