Intensive Care Unit, Jiangmen Central Hospital, Jiangmen, China.
Nursing Department, Jiangmen Central Hospital, Jiangmen, China.
JPEN J Parenter Enteral Nutr. 2023 May;47(4):563-571. doi: 10.1002/jpen.2501. Epub 2023 Apr 10.
The aim of this study was to build and validate a risk prediction model for diarrhea in patients in the intensive care unit (ICU) receiving enteral nutrition (EN) by identifying risk factors for diarrhea in these patients.
The risk factors for diarrhea were analyzed to build a prediction model for EN diarrhea in patients in the ICU based on the data collected from 302 patients receiving EN in the ICU. Subsequently, the model was validated by the area under the curve.
In this study, the collected data were divided into two groups: a derivation cohort and a validation cohort. The results showed that 54.03% (114) of patients had diarrhea in the derivation cohort and 56.04% (51) of patients had diarrhea in the validation cohort. Moreover, days of EN, high urea nitrogen levels, probiotics, respiratory system disease, and daily doses of nutrient solution were included as predictive factors for diarrhea in patients receiving EN in the ICU. The predictive power of the model was 0.81 (95% CI, 0.7520.868) in the derivation cohort and 0.736 (95% CI, 0.6340.837) in the validation cohort.
In accordance with the predictive factors, the model, characterized by excellent discrimination and high accuracy, can be used to clinically identify patients in the ICU with a high risk of EN diarrhea.
本研究旨在通过确定 ICU 接受肠内营养（EN）患者腹泻的风险因素，建立并验证一种预测 ICU 患者 EN 相关腹泻风险的模型。
分析腹泻的风险因素，基于 ICU 中 302 例接受 EN 的患者的数据，建立 ICU 患者 EN 腹泻预测模型。随后通过曲线下面积验证模型。
在本研究中，收集的数据分为两组：推导队列和验证队列。结果显示，推导队列中 54.03%（114）的患者出现腹泻，验证队列中 56.04%（51）的患者出现腹泻。此外，EN 天数、高尿素氮水平、益生菌、呼吸系统疾病和每日营养液剂量被纳入 ICU 接受 EN 的患者腹泻的预测因素。该模型在推导队列中的预测能力为 0.81（95%CI，0.7520.868），在验证队列中的预测能力为 0.736（95%CI，0.6340.837）。
根据预测因素，该模型具有出色的区分度和高准确性，可以用于临床识别 ICU 中存在高风险发生 EN 腹泻的患者。
