Abstract: Ｏｂｊｅｃｔｉｖｅ：To investigate the risk factors of hyperkalemia in patients with secondary hyperparathyroidism （SHPT） after parathyroidectomy （PTX） and construct a risk prediction model.
Ｍｅｔｈｏｄｏｌｏｇｙ：A single-centre retrospective study that included dialysis patients who underwent parathyroidectomy in Guangdong Provincial Peoples Hospital from 2015 to 2021， and the patients were divided into hyperkalemia group （>5.3 mmol／L） and non-hyperkalemia group （≤5.3 mmol／L） according to the postoperative serum potassium. The clinical data of the two groups were compared. The influencing factors of hyperkalemia in patients with secondary hyperparathyroidism after parathyroidectomy were analyzed by binary multivariate Logistic regression analysis. The discrimination， calibration， and effectiveness of the model were evaluated by plotting the receiver operating characteristic （ROC） curve，calibration curve， and decision curve.
Ｒｅｓｕｌｔｓ：A total of 392 patients were enrolled， 98 in the hyperkalemia group and 294 in the non-hyperkalemia group. Through multivariate Logistic regression analysis， preoperative serum potassium， preoperative blood albumin， dialysis mode， and blood urea nitrogen creatinine ratio were predictors for postoperative hyperkalemia （P<0.05）. The predictors screened by multivariate Logistic regression analysis were included to establish a risk prediction model. The ROC curve showed that the area under the curve （AUC） of the model was 0.747， and the predictive model was internally validated and confirmed by repeated sampling 1000 times by Bootstrap method， and the AUC of the internal validation was 0.733. The results of Hosmer-Lemeshow goodness-of-fit test was P=0.723， the calibration curve of the model was close to the ideal curve. The decision curve （DCA） indicated that when the probability threshold predicted by the model was 0.06-0.60， the model has clinical utility.
Ｃｏｎｃｌｕｓｉｏｎ：Preoperative serum potassium， preoperative blood albumin， dialysis mode， and preoperative blood urea nitrogen creatinine ratio are predictors of hyperkalemia after parathyroidectomy， and the prediction model has a good predictive ability.

Key words: secondary hyperparathyroidism, parathyroidectomy, hyperkalemia, nomogram