Tianjin Medical Journal ›› 2025, Vol. 53 ›› Issue (10): 1037-1042.doi: 10.11958/20250625

• Clinical Research • Previous Articles     Next Articles

Establishment and validation of a column chart risk prediction model for aspiration in early enteral nutrition therapy of ICU patients

WANG Haixia(), HE Fei(), ZHU Congmei, WANG Jing   

  1. Intensive Care Unit, the Second People's Hospital of Hefei, Hefei 230011, China
  • Received:2025-02-20 Revised:2025-07-21 Published:2025-10-15 Online:2025-10-12
  • Contact: E-mail:1977335804@qq.com

Abstract:

Objective To investigate the risk factors of aspiration during early enteral nutrition (EEN) support treatment in patients in intensive care unit (ICU) and establish and validate the corresponding nomogram risk prediction model. Methods A total of 348 ICU patients who received EEN between June 2022 and May 2024 were enrolled and divided into the aspiration group (n=74) and the non-aspiration group (n=274) based on the occurrence of aspiration. Clinical data were collected included age, sex, body mass index (BMI), history of diabetes, endotracheal intubation/mechanical ventilation status, plasma albumin (ALB) levels within 24 h after admission to ICU, disease type (severe pneumonia/stroke/septic shock), consciousness level (Glasgow Coma Scale, GCS), APACHE Ⅱscore, nasogastric tube insertion depth, infusion volume, nutritional risk (NRS2002 score ≥3 indicating high risk), and nutrition mode (nasogastric/nasointestinal tube). Logistic regression was used to identify risk factors of aspiration, and a nomogram prediction model was constructed using R software. External validation was performed on 72 EEN-treated ICU patients admitted between June 2024 and January 2025. Results Logistic regression identified age (OR=2.701, 95% CI: 1.633-4.467), APACHE Ⅱ score (OR=2.125, 95%CI: 1.133-3.987), consciousness level (OR=2.826, 95%CI: 1.617-4.940), nasogastric tube insertion depth (OR=1.101, 95%CI: 1.006-1.136) and nutritional risk (OR=8.996, 95%CI: 5.017-16.132) were independent risk factors for aspiration (all P<0.05). A nomogram incorporating these factors was developed, converting cumulative scores into individualized aspiration risk probabilities. The model demonstrated strong predictive performance in internal validation (AUC=0.860, calibration curve slope=0.930) and external validation (AUC=0.831). Decision curve analysis (DCA) confirmed significant clinical net benefits across risk thresholds, supporting its practical utility. Conclusion The nomogram model exhibits good discrimination and accuracy, providing a valuable tool for individualized aspiration risk assessment in ICU patients receiving EEN.

Key words: enteral nutrition, respiratory, aspiration, nomogram, intensive care unit, predictive model

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