Impact of fasting on the gastric volume of critically ill patients before extubation: a prospective observational study using gastric ultrasound
Bibliographic record
Abstract
Background: A period of fasting before tracheal extubation of ventilated patients in the ICU is common practice, aiming to reduce gastric volume and aspiration risk. As the volume of gastric content is unknown at the time of extubation, the efficacy of this practice is uncertain. Methods: A prospective, observational study using gastric ultrasound was undertaken. Images were obtained at four time points: (i) at baseline, with gastric feeds running; (ii) after suctioning of gastric contents through a gastric tube; (iii) after a 4 h period with no gastric feed running; and (iv) after both a 4 h fasting period and gastric tube suctioning. The primary outcome was the proportion of patients classed as low risk of aspiration with each intervention, using qualitative and quantitative gastric ultrasound. Results: Fifty-four patients in the ICU were enrolled. Forty-four (81%) subjects had images that were suitable for analysis. Suctioning of stomach content through a gastric tube and fasting were equivalent with 39/44 (88.6%) and 5/44 (11.4%) subjects classified as low risk and at risk of aspiration, respectively. A period of fasting followed by suction resulted in 41/44 (93.2%) patients being at low risk. Conclusions: Suctioning of stomach contents through the gastric tube and a 4 h fasting period appear equivalent at reducing gastric volume below a safe threshold. A small percentage did not reach the threshold despite all interventions.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".