Development and validation of risk prediction model for refeeding syndrome in neurocritical patients

Abstract

BackgroundThe incidence of refeeding syndrome (RFS) in critically ill patients is high, which is detrimental to their prognoses. However, the current status and risk factors for the occurrence of RFS in neurocritical patients remain unclear. Elucidating these aspects may provide a theoretical basis for screening populations at high risk of RFS.MethodsA total of 357 patients from January 2021 to May 2022 in a neurosurgery ICU of a tertiary hospital in China were included using convenience sampling. Patients were divided into RFS and non-RFS groups, based on the occurrence of refeeding-associated hypophosphatemia. Risk factors for RFS were determined using univariate and logistic regression analyses, and a risk prediction model for RFS in neurocritical patients was developed. The Hosmer-Lemeshow test was used to determine the goodness of fit of the model, and the receiver operator characteristic curve was used to examine its discriminant validity.ResultsThe incidence of RFS in neurocritical patients receiving enteral nutrition was 28.57%. Logistic regression analyses showed that history of alcoholism, fasting hours, Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, Sequential Organ Failure Assessment (SOFA) scores, low serum albumin, and low baseline serum potassium were risk factors of RFS in neurocritical patients (p < 0.05). The Hosmer-Lemeshow test showed p = 0.616, and the area under the ROC curve was 0.791 (95% confidence interval: 0.745–0.832). The optimal critical value was 0.299, the sensitivity was 74.4%, the specificity was 77.7%, and the Youden index was 0.492.ConclusionThe incidence of RFS in neurocritical patients was high, and the risk factors were diverse. The risk prediction model in this study had good predictive effects and clinical utility, which may provide a reference for assessing and screening for RFS risk in neurocritical patients.