OBJECTIVE To explore the influencing factors for antibiotic associated encephalopathy (AAE) in end-stage renal disease undergoing hemodialysis and construct a nomogram-based predictive model.

METHODS Data were collected from 143 patients with end-stage renal disease admitted to the Third Bethune Hospital of Jilin University from Jan. 2021 to Feb. 2024, all of whom received hemodialysis and antibiotics. According to AAE occurrence during the use of antibiotics, patients were divided into the occurrence group (n=31) and non-occurrence group (n=112). The possible influencing factors for AAE were analyzed for the construction of a nomogram-based predictive model.

RESULTS The initial comparison between the occurrence group and the non-occurrence group showed that age, use of β-lactam antibiotics, albumin (Alb), and blood phosphorus levels were the influencing factors for AAE occurrence (P < 0.05); based on which, a nomogram-based predictive model was constructed. The calibration curve of the model approached the ideal one, of which the area under the curve was 0.927. Within the threshold ranged 0.00 to 1.00, the net benefit rate for predicting the occurrence of AAE were always greater than 0, with a maximum 0.216.

CONCLUSION An AAE risk prediction model is constructed based on the influencing factors (age, use of β-lactam antibiotics, Alb and blood phosphorus levels), which can visualize the risks and improve early screening and prediction.