Risk predict model using multi-drug resistant organism infection from Neuro-ICU patients: a retrospective cohort study

Abstract

The aim of this study was to analyze the current situation and risk factors of multi-drug-resistant organism (MDRO) infection in Neuro-intensive care unit (ICU) patients, and to develop the risk predict model. The data was collected from the patients discharged from Neuro-ICU of grade-A tertiary hospital at Guizhou province from January 2018 to April 2020. Binary Logistics regression was used to analyze the data. The model was examined by receiver operating characteristic curve (ROC). The grouped data was used to verify the sensitivity and specificity of the model. A total of 297 patients were included, 131 patients infected with MDRO. The infection rate was 44.11%. The results of binary Logistics regression showed that tracheal intubation, artery blood pressure monitoring, fever, antibiotics, pneumonia were independent risk factors for MDRO infection in Neuro-ICU (P < 0.05), AUC = 0.887. The sensitivity and specificity of ROC curve was 86.3% and 76.9%. The risk prediction model had a good predictive effect on the risk of MDRO infection in Neuro ICU, which can evaluate the risk and provide reference for preventive treatment and nursing intervention.