1.Establishment and validation of a column chart risk prediction model for aspiration in early enteral nutrition therapy of ICU patients
Haixia WANG ; Fei HE ; Congmei ZHU ; Jing WANG
Tianjin Medical Journal 2025;53(10):1037-1042
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.
2.Establishment and validation of a column chart risk prediction model for aspiration in early enteral nutrition therapy of ICU patients
Haixia WANG ; Fei HE ; Congmei ZHU ; Jing WANG
Tianjin Medical Journal 2025;53(10):1037-1042
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.
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