Abstract
This study aims to develop and validate a risk prediction model for enteral nutrition feeding intolerance (ENFI) in patients with severe traumatic brain injury (STBI), providing a foundation for the prevention and management of ENFI in this population. STBI is a prevalent acute and severe condition encountered in neurosurgery. STBI patients are prone to diarrhea, reflux, and other manifestations of feeding intolerance during enteral nutrition, which not only affects the patient's systemic therapy and prolongs hospital stay, but also increases the risk of infection. We conducted a retrospective cohort study. Clinical assessment and data collection were obtained through an electronic medical record system. Data were collected from January 2019 to July 2023, we conducted a retrospective analysis of patients with STBI who met the inclusion criteria but did not meet the exclusion criteria, formed the development cohort and validation cohort. The dynamic nomogram was constructed and validated in R software. A total of 302 patients in the development cohort and 107 patients in the validation cohort were included, with incidences of ENFI at 50.7% and 56.1%, respectively. We developed a dynamic nomogram in patients with STBI and the mean arterial pressure, mechanical ventilation, intake and output, and combined antibiotics were independent predictors of ENFI. The C-index and the Hosmer-Lemeshow indicated good calibration; The calibration curve showed strong consistency between actual and predicted outcomes. The decision curve analysis confirmed the model's clinical utility. The prediction of enteral feeding intolerance can be conveniently facilitated by the ENFI which integrates general information, condition monitoring, and therapeutic factors in patients with STBI. Based on the dynamic nomogram, medical and nursing staff in the intensive care unit can assess patients at high risk for ENFI at an early stage. This has the potential to prevent the occurrence of ENFI and enhance various clinical outcomes for patients.