Aspiration risk prediction models in patients with nasogastric enteral nutrition: a systematic review and meta-analysis
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Updated: Sep 14, 2025

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Published on: September 22, 2023
Juan Chen1, Yushuang Su1, Tianlong Li2
1Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, No. 32, West Second Section, 1st Ring Road, Qingyang District, Chengdu, 610072, Sichuan Province, China.
Abstract:
In recent years, numerous researchers have developed risk prediction models for aspiration in patients with nasogastric enteral nutrition (EN). Nevertheless, comprehensive and systematic comparative studies are lacking. This study systematically review and evaluate the studies on aspiration risk prediction models in patients with nasogastric EN. A computer search was conducted from the database establishment to May 10, 2025. The Prediction Model Risk of Bias Assessment Tool (PROBAST) evaluation tool was used to assess the quality of the included studies, and the meta-analysis was conducted using Stata 17 software to analyze the prediction factors included in the models and the area under the curve (AUC) values of the validated models. Eleven studies were included, with a total of 22 aspiration risk prediction models for patients with nasogastric EN. The AUC ranged from 0.809 to 0.992. The PROBAST evaluation results showed that all 11 included studies had a high risk of bias. The most common predictive factors included the number of diseases, history of aspiration, use of sedative, depth of tube placement, amount of gastric residue, APACHE II score, consciousness disturbance, nutritional risk, age. The pooled AUC value of the four validated models was 0.92 (95% confidence interval: 0.90-0.93), indicating an excellent level of discrimination. The study protocol has been registered with PROSPERO (registration number: CRD42024594672).
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