关键词: 重症监护病房, 肠内营养, Meta分析, 预测模型, 循证护理学

Abstract:

Objective To explore the factors influencing enteral nutrition intolerance in critically ill patients and to develop a risk prediction model to provide medical staff with a tool for early identification of patient intolerance. Methods Domestic and international databases such as CNKI，PubMed and Web of Science were searched and supplemented by searching references and grey literature. The search period was from inception to November 2022. Data were independently screened and extracted by 2 systematically trained researchers，and the quality of the literature was evaluated. Meta-analysis was performed using Review Manager 5.4 software. The OR value of the comprehensive effect of the factors was taken as the coefficient of each factor in the formula，and the natural logarithm of the ratio of intolerance incidence and non-incidence was the constant term of the formula. From December 2022 to June 2023，360 patients who met the inclusion and exclusion criteria in the ICU of a tertiary hospital were collected as a model verification group by convenient sampling method，and the collected clinical data were substituted into the formula to evaluate the discrimination and calibration of the model. Results A total of 13 articles were included. 7 influencing factors with more than 3 times of reports and statistically significant results were obtained. For age[OR=0.97，95%CI（0.94，0.99），P=0.010]，Acute Physiology and Chronic Health Evaluation score Ⅱ[OR=1.17，95%CI（1.01，1.36），P=0.040]，comorbidity with diabetes[OR=1.21，95%CI（1.05，1.40），P=0.008]，comor-bidity with neurological diseases[OR=0.85，95%CI（0.74，0.98），P=0.020]，mechanical ventilation[OR=3.21，95%CI（1.82，5.66），P<0.001]，using sedative analgesics[OR=2.27，95%CI（1.66，3.10），P<0.001]，using gastric motility drugs[OR=0.23，95%CI（0.15，0.36），P<0.001]. The incidence of enteral nutrition intolerance was 35.00%. The risk prediction model for enteral nutrition intolerance in critically ill patients was logit（P）=-0.619-0.031×age+0.157×APACHE Ⅱ+0.191×comorbidity with diabetes-0.163×comorbidity with neurosurgery+0.820×using sedatives and analgesics+1.166×mechanical ventilation-1.470×using gastric dynamic drugs. The area under the receiver operating characteristic curve of the model was 0.864. The maximum Youden index was 0.589. The sensitivity was 0.922. The specificity was 0.667. The corresponding clinical diagnostic threshold was 0.536. Hosmer-Leme-show test χ²=13.410，P=0.098. Brier score was 0.195. Conclusion The risk prediction model of enteral nutrition intolerance in critically ill patients based on large sample evidence-based medicine is universal，scientific and practical. It provides a tool for medical staff to identify patients with enteral nutrition feeding intolerance in ICU.

Key words: Intensive Care Units, Enteral Nutrition, Meta-Analysis, Prediction Model, Evidence-Based Nursing