A Visual “STAGED” Nomogram to Predict the Risk of Full Stomach in Adult Outpatients Undergoing Elective Sedated Upper Endoscopy

Background: A full stomach during elective sedated upper endoscopy (UE) is highly associated with aspiration. Aspiration is related to increased morbidity and mortality. We aimed to develop a nomogram model to predict the risk of having a full stomach in adult outpatients undergoing elective sedated UE. Methods: Data of 1171 adult outpatients undergoing elective sedated UE were collected retrospectively between July 2021 and February 2022. Univariable analysis, multivariable logistic regression, and Boruta were used to identify independent risk factors associated with full stomach. Using the identified risk factors, a nomogram was developed. The area under the receiver operating characteristic (AUROC), decision curve analysis (DCA), and calibration curve (CC) were used to evaluate the model’s performance. Results: After exclusion, 990 patients were enrolled in this study. In the training set, 305 patients (38.5%) had a full stomach, and 71 patients (35.9%) had a full stomach for the testing set. The AUROC (95% Cl) was 0.819 (0.788-0.85) and 0.823(0.759-0.887) for the training and testing set, respectively. The variables incorporated in the development of our STAGED model were Sex = female (OR: 2.147), fasting Time (OR: 0.839), Age (OR: 0.971), GERD (OR: 15.61), diabEtes (OR: 8.614) and Diet (OR: 3.691). DCA and CIC analyses showed that our model had a significant net benefit compared to the "treat all or "treat none" strategies and had high predictive value, making it clinically useful. Conclusion: The “STAGED” nomogram model was successfully developed and made easily accessible online via a visual web-based calculator. Summary of the patient’s inclusion along with the study design, the methodology used for model development, the implementation of the model, and model performance.

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Publication Details

Journal
Asian Journal of Advanced Research and Reports
Published
2025-06-07
DOI
https://doi.org/10.9734/ajarr/2025/v19i61038
Primary Topic
Esophageal and GI Pathology
Type
article
Field-Weighted Citation Impact
0.00

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article

A Visual “STAGED” Nomogram to Predict the Risk of Full Stomach in Adult Outpatients Undergoing Elective Sedated Upper Endoscopy

Yanna Si, Jianjun Zou, X Zhang, Yuqing Yan et al.
1 links
Asian Journal of Advanced Research and Reports
Esophageal and GI Pathology
article

A Visual “STAGED” Nomogram to Predict the Risk of Full Stomach in Adult Outpatients Undergoing Elective Sedated Upper Endoscopy

Yanna Si, Jianjun Zou, X Zhang, Yuqing Yan, Yuzhan Jin, Asha Khatib Iddi, Chernor Sulaiman Bah, Bongani Mbambara, Rui Ding, Zhixiang Li, Ndagijimana Djuma
article en

Abstract

Background: A full stomach during elective sedated upper endoscopy (UE) is highly associated with aspiration. Aspiration is related to increased morbidity and mortality. We aimed to develop a nomogram model to predict the risk of having a full stomach in adult outpatients undergoing elective sedated UE. Methods: Data of 1171 adult outpatients undergoing elective sedated UE were collected retrospectively between July 2021 and February 2022. Univariable analysis, multivariable logistic regression, and Boruta were used to identify independent risk factors associated with full stomach. Using the identified risk factors, a nomogram was developed. The area under the receiver operating characteristic (AUROC), decision curve analysis (DCA), and calibration curve (CC) were used to evaluate the model’s performance. Results: After exclusion, 990 patients were enrolled in this study. In the training set, 305 patients (38.5%) had a full stomach, and 71 patients (35.9%) had a full stomach for the testing set. The AUROC (95% Cl) was 0.819 (0.788-0.85) and 0.823(0.759-0.887) for the training and testing set, respectively. The variables incorporated in the development of our STAGED model were Sex = female (OR: 2.147), fasting Time (OR: 0.839), Age (OR: 0.971), GERD (OR: 15.61), diabEtes (OR: 8.614) and Diet (OR: 3.691). DCA and CIC analyses showed that our model had a significant net benefit compared to the "treat all or "treat none" strategies and had high predictive value, making it clinically useful. Conclusion: The “STAGED” nomogram model was successfully developed and made easily accessible online via a visual web-based calculator. Summary of the patient’s inclusion along with the study design, the methodology used for model development, the implementation of the model, and model performance.

Asian Journal of Advanced Research and ReportsVol. 19(6)
China Pharmaceutical University (CN), Southeast University (CN), Nanjing Medical University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 77%
Esophageal and GI Pathology
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