To explore the risk factors of the occurrence of antibiotic-associated encephalopathy (AAE) in patients with chronic renal failure (CRF) and establish a prediction model.

The clinical data of 784 patients with CRF were retrospectively analyzed. All the patients had received treatment of antibiotics. According to whether the patients had AAE or not, they were divided into AAE group (n=103) and non-AAE group (n=681). The clinical indicators with statistical differences between the two groups were included in logistic regression analysis to obtain the independent risk factors of AAE and establish a prediction model which was shown by the nomogram. Receiver operating characteristic (ROC) curve and calibration curve were used to assess the discrimination and calibration of the model, and Bootstrap method was used for internal validation.

The multivariate logistic regression analysis showed that aging(OR 1.033, 95%CI: 1.012-1.054), low plasma albumin(OR 0.852, 95%CI: 0.802-0.905), low GFR(OR 0.963, 95%CI: 0.940-0.988), separate use of β-lactamase inhibitor compound preparation antibiotic (OR 3.827, 95%CI: 1.528-9.584), combination of two or more antibiotics(OR 2.913, 95%CI: 1.187-7.149), and use of antibiotics without dose reduction (OR 343, 95%CI: 0.212-0.553) were all independent influencing factors for the occurrence of AAE in CRF patients. The area under the ROC curve (AUC) of the nomogram model was 0.808(95%CI: 0.770-0.846)with an internal verification C-index of 0.808.

The prediction model established in this study may provide some reference value for the early identification of AAE risk and the implementation of preventive measures in CRF.