ArticleAnnals of medicine2023
A convenient machine learning model to predict full stomach and evaluate the safety and comfort improvements of preoperative oral carbohydrate in patients undergoing elective painless gastrointestinal endoscopy.
Article in Annals of medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.
- Preoperative oral carbohydrate administration in adult elective surgery: protocol heterogeneity, regional practice patterns and evidence gaps-a scoping review.Frontiers in nutrition · 2026Pooled it
- Gastric ultrasound assessment of gastric volume and related factors in patients undergoing gastrointestinal endoscopy under sedation.Journal of anesthesia · 2026Article
- Residual gastric content after holding of glucagon-like peptide-1 receptor agonists before elective surgery: a cross-sectional study - the RESIDUAL study.BMC anesthesiology · 2026Article
- Knowledge, attitude and practice of pre-operative fasting in gastrointestinal surgery: Post-operative complications.Bioinformation · 2026Article
- Ultrasound Assessment of Preoperative Gastric Contents for Predicting Aspiration Risk in Surgical Patients: A Scoping Review and Future Directions.Therapeutics and clinical risk management · 2026Review
- Prediction of postoperative nausea and vomiting in patients undergoing sedated gastrointestinal endoscopy based on machine learning.Annals of medicine · 2025Article
- Gastric ultrasound: Enhancing preoperative risk assessment and patient safety.Journal of perioperative practice · 2025Article
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
aimsAssessment of the patient's gastric contents is the key to avoiding aspiration incidents, however, there is no effective method to determine whether elective painless gastrointestinal endoscopy (GIE) patients have a full stomach or an empty stomach. And previous studies have shown that preoperative oral carbohydrates (POCs) can improve the discomfort induced by fasting, but there are different perspectives on their safety. This study aimed to develop a convenient, accurate machine learning (ML) model to predict full stomach. And based on the model outcomes, evaluate the safety and comfort improvements of POCs in empty- and full stomach groups.
methodsWe enrolled 1386 painless GIE patients between October 2022 and January 2023 in Nanjing First Hospital, and 1090 patients without POCs were used to construct five different ML models to identify full stomach. The metrics of discrimination and calibration validated the robustness of the models. For the best-performance model, we further interpreted it through SHapley Additive exPlanations (SHAP) and constructed a web calculator to facilitate clinical use. We evaluated the safety and comfort improvements of POCs by propensity score matching (PSM) in the two groups, respectively.
resultsRandom Forest (RF) model showed the greatest discrimination with the area under the receiver operating characteristic curve (AUROC) 0.837 [95% confidence interval (CI): 79.1-88.2], F1 71.5%, and best calibration with a Brier score of 15.2%. The web calculator can be visited at https://medication.shinyapps.io/RF_model/. PSM results demonstrated that POCs significantly reduced the full stomach incident in empty stomach group (
conclusionsThe developed convenient RF model predicted full stomach with high accuracy and interpretability. POCs were safe and comfortably improved in both groups, with more benefit in empty stomach group. These findings may guide the patients' gastrointestinal preparation.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.