BACKGROUND Enteral nutrition(EN)is essential for critically ill patients.However,some patients will have enteral feeding intolerance(EFI)in the process of EN.AIM To develop a clinical prediction model to predict the r...BACKGROUND Enteral nutrition(EN)is essential for critically ill patients.However,some patients will have enteral feeding intolerance(EFI)in the process of EN.AIM To develop a clinical prediction model to predict the risk of EFI in patients receiving EN in the intensive care unit.METHODS A prospective cohort study was performed.The enrolled patients’basic information,medical status,nutritional support,and gastrointestinal(GI)symptoms were recorded.The baseline data and influencing factors were compared.Logistic regression analysis was used to establish the model,and the bootstrap resampling method was used to conduct internal validation.RESULTS The sample cohort included 203 patients,and 37.93%of the patients were diagnosed with EFI.After the final regression analysis,age,GI disease,early feeding,mechanical ventilation before EN started,and abnormal serum sodium were identified.In the internal validation,500 bootstrap resample samples were performed,and the area under the curve was 0.70(95%CI:0.63-0.77).CONCLUSION This clinical prediction model can be applied to predict the risk of EFI.展开更多
Objective:The objective of this study was to construct an early warning system(EWS)to facilitate risk assessment,early identification,and appropriate treatment of enteral nutrition feeding intolerance(FI)in patients w...Objective:The objective of this study was to construct an early warning system(EWS)to facilitate risk assessment,early identification,and appropriate treatment of enteral nutrition feeding intolerance(FI)in patients with stroke,so as to provide a reference for risk classification standards and interventions toward a complete EWSs for nursing care of stroke.Materials and Methods:Based on evidence and clinical nursing practice,a structured expert consultation method was adopted on nine experts over two rounds of consultation.Statistical analysis was used to determine the early warning index for FI in patients with stroke.Results:The expert authority coefficient was 0.89;the coefficients of variation for the two rounds of consultation were 0.088-0.312 and 0.096-0.214,respectively.There were significant differences in the Kendall’s concordance coefficient(P<0.05).Finally,22 items in five dimensions of patient age,disease,treatment,biochemical,and enteral nutrition-related factors were identified.Conclusion:The early warning index for FI in patients with a history of stroke is valid and practical.It provides a reference for the early clinical identification of FI risk.展开更多
文摘BACKGROUND Enteral nutrition(EN)is essential for critically ill patients.However,some patients will have enteral feeding intolerance(EFI)in the process of EN.AIM To develop a clinical prediction model to predict the risk of EFI in patients receiving EN in the intensive care unit.METHODS A prospective cohort study was performed.The enrolled patients’basic information,medical status,nutritional support,and gastrointestinal(GI)symptoms were recorded.The baseline data and influencing factors were compared.Logistic regression analysis was used to establish the model,and the bootstrap resampling method was used to conduct internal validation.RESULTS The sample cohort included 203 patients,and 37.93%of the patients were diagnosed with EFI.After the final regression analysis,age,GI disease,early feeding,mechanical ventilation before EN started,and abnormal serum sodium were identified.In the internal validation,500 bootstrap resample samples were performed,and the area under the curve was 0.70(95%CI:0.63-0.77).CONCLUSION This clinical prediction model can be applied to predict the risk of EFI.
基金supported by the Young Teacher Project of the Beijing University of Chinese Medicine(No.:2018-JYB-JS155).
文摘Objective:The objective of this study was to construct an early warning system(EWS)to facilitate risk assessment,early identification,and appropriate treatment of enteral nutrition feeding intolerance(FI)in patients with stroke,so as to provide a reference for risk classification standards and interventions toward a complete EWSs for nursing care of stroke.Materials and Methods:Based on evidence and clinical nursing practice,a structured expert consultation method was adopted on nine experts over two rounds of consultation.Statistical analysis was used to determine the early warning index for FI in patients with stroke.Results:The expert authority coefficient was 0.89;the coefficients of variation for the two rounds of consultation were 0.088-0.312 and 0.096-0.214,respectively.There were significant differences in the Kendall’s concordance coefficient(P<0.05).Finally,22 items in five dimensions of patient age,disease,treatment,biochemical,and enteral nutrition-related factors were identified.Conclusion:The early warning index for FI in patients with a history of stroke is valid and practical.It provides a reference for the early clinical identification of FI risk.