Development and Validation of a Risk Prediction Model for Gastric Retention in Patients Undergoing Sedated Gastroscopy

Condition(s) studied

Study summary

Gastric retention not only compromises the quality of endoscopic examination but also significantly increases the risk of reflux and aspiration in sedated patients. Aspiration of gastric contents represents a critical anesthesia-related complication during the perioperative period, carrying substantial implications for anesthetic management. With the growing volume of sedated gastroscopy procedures, predicting gastric retention has become an urgent clinical priority. This prospective study aims to establish a standardized gastric residual volume (GRV) grading system to evaluate both the volume of retained gastric contents and its contributing factors in patients undergoing upper gastrointestinal endoscopy. We will systematically assess the impact of demographic characteristics, comorbidities, and medication history on gastric emptying function. This study will facilitate establishment of an endoscopy-based simplified assessment system for gastric retention.

Eligibility

Primary outcome measure(s)

• Incidence of delayed gastric emptying (defined as endoscopic gastric residual volume ≥ Grade 2) assessed by standardized endoscopic grading system — Patients will be followed for the duration of hospital stay, an expected average about 2 hours
  Measurement Tool: Standardized endoscopic gastric residual volume grading system ： Grade 0：Stomach completely clean, no visible residue； Grade 1：Small amount of clear liquid (\<1.5 mL/kg or \<100 mL), no solid components； Grade 2：Liquid ≥1.5 mL/kg (or ≥100 mL) or small solid fragments (\<5 mm)； Grade 3：Large amount of liquid (\>200 mL) or significant solid residue (≥5 mm fragments) Grade 4：Visible undigested food chunks or intact food pieces Data Collection: Two physicians independently assessed gastric residue (liquid/solid), measuring volume using a graduated suction bottle, with video recordings archived for third-party review. Statistical Methods: The incidence (%) of gastric retention (≥Grade 2) was calculated. Multivariate logistic regression analyzed risk factors, and ROC curves evaluated the model's predictive performance (AUC).

Trial sites (3)

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