Systematic review of risk prediction models for enteral feeding intolerance in ICU patients
10.3760/cma.j.cn115682-20240925-05314
- VernacularTitle:ICU患者肠内营养喂养不耐受风险预测模型的系统评价
- Author:
Yubing LI
1
;
Qian LU
;
Fan LI
;
Lichuan ZHANG
;
Xiaoge HE
;
Aihui LIU
;
Longfei YANG
;
Di JIANG
Author Information
1. 北京大学护理学院，北京 100191
- Publication Type:Journal Article
- Keywords:
Intensive care unit;
Patients;
Enteral nutrition;
Feeding intolerance;
Prediction models
- From:
Chinese Journal of Modern Nursing
2025;31(13):1705-1712
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To conduct a systematic review of risk prediction models for enteral feeding intolerance in ICU patients.Methods:Relevant literature was searched in China National Knowledge Infrastructure, Wanfang Data, China Biology Medicine disc, VIP, PubMed, Web of Science, Cochrane Library, Embase, CINAHL, and Scopus, with search limits from the establishment of the databases up to July 24, 2024. Two researchers independently screened the literature and extracted data, using Prediction model Risk Of Bias ASsessment Tool to evaluate the quality of the included studies.Results:A total of 12 studies were included, which included 20 prediction models. The area under the receiver operating characteristic curve or C-index for these models ranged from 0.70 to 0.94. The overall bias risk of the 12 studies was high, with three studies having good applicability. The bias risk primarily stemmed from issues such as measurement of prediction factors, variable handling, sample size, outcome definition, and model performance evaluation.Conclusions:Existing risk prediction models for enteral feeding intolerance in ICU patients exhibit a high risk of bias. Further validation, optimization, or development of new models is required in the future.
