Development and validation of a nomogram for predicting enteral feeding intolerance in critically ill patients (NOFI): Mixed retrospective and prospective cohort study

OBJECTIVE: Developing and validating a clinical prediction nomogram of enteral feeding intolerance (NOFI) in critically ill patients. So as to help clinicians implement pre-intervention for patients with high risk of enteral feeding intolerance (FI), formulate individualized feeding strategies, and reduce the probability of FI occurrence. METHODS: From March 2018 to April 2023, patients who met the inclusion criteria but did not meet the exclusion criteria constituted the development cohort for retrospective analysis, and NOFI was developed. Patients recruited consecutively between May 2023 and July 2023 constituted the validation cohort for the prospective analysis for independent external validation of NOFI. Initially, a backward stepwise method was employed to conduct a multivariate logistic regression analysis in the development cohort, aiming to identify the optimal-fit model. Subsequently, a nomogram was derived from this model. The validation of the nomogram was carried out in an independent external validation cohort, where discrimination and calibration were evaluated. Additionally, a decision curve analysis was conducted to assess the net benefit of utilizing the nomogram for decision-making. RESULTS: A total of 628 and 143 patients, 49.0 % and 51.7 % of patients occurred FI, were included in the development and validation cohort, respectively. We developed a NOFI in severely ill patients and the primary diagnosis, Acute gastrointestinal injury (AGI) grade, and APACHE II score were independent predictors of FI, with the OR of the primary diagnosis of circulatory disease being 2.281 (95 % CI, 1.364-3.816; P = 0.002); The OR of respiratory diseases was 0.424 (95 % CI, 0.259-0.594; P = 0.001); The OR of AGI grade was 4.920 (95 % CI, 3.773-6.416; P < 0.001), OR of APACHE II score was 1.100 (95 % CI, 1.059-1.143; P < 0.001). Independent external validation of the prediction model was performed. This model has good discrimination and calibration. The decision curve analysis of the nomogram provided better net benefit than the alternate options (full early enteral nutrition or delayed enteral nutrition). CONCLUSIONS: The prediction of enteral feeding intolerance can be conveniently facilitated by the NOFI that integrates primary diagnosis, AGI grade, and APACHE II score in critically ill patients.