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| Systematic review of risk prediction models for enteral feeding intolerance in intensive care unit patients |
| LIU Tingting TANG Ling SUN Yan LU Jun LU Daozhen▲ |
| Department of Intensive Care Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province, Nanjing 210029, China |
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Abstract Objective To systematically review the research status of risk prediction models for enteral nutrition feeding intolerance in intensive care unit (ICU) patients. Methods PubMed, EMbase, Web of Science, Cochrane Library, CNKI, Wanfang Data, VIP, SinoMed were searched from the establishment of the inception to February 2023. Two researchers independently screened the literatures, extracted the data, and evaluated the quality of the included models using the prediction model risk of bias assessment tool. Results A total of ten literatures were included, including 14 prediction models. The area under the receiver operating characteristic curve of 12 models ranged from 0.60 to 0.94, and nine models had good accuracy. The model bias risk assessment results showed that the study had a high risk of bias and good applicability. Conclusion Future research should focus on the external validation and optimization of existing models, or the development of new models under the guidance of standardization to improve the applicability and feasibility of models in clinical application.
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