ORIGINAL RESEARCH article
Front. Surg.
Sec. Visceral Surgery
This article is part of the Research TopicExploring kidney pathology in transplantation: Spotlight on non-neoplastic conditions and DCD donor qualityView all 4 articles
Influencing factors and risk prediction nomogram model construction of Hyperkalemia during kidney transplantation
Provisionally accepted
Guanmiao Chen
Yongyuan Jian
Ruiling Su
Junze ChenCheng ZhangKaiyong HuangXuelin Tan
Bo PengPing Huang
Chunqiang Dong*Kun Dong*- The First Affiliated Hospital of Guangxi Medical University, Nanning, China
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Objective To analyze the risk factors of hyperkalemia during kidney transplantation, and to construct the prediction model of nomogram. Methods 162 cases of renal transplant patients in our hospital from January 2020 to September 2024 were included. The clinical data of the patients were retrospectively analyzed. According to whether hyperkalemia occurred during the operation, the patients were divided into non hyperkalemia group and hyperkalemia group. The related factors of hyperkalemia in renal transplant patients were analyzed by multivariate logistic regression, and the nomogram model was constructed. Results Among 162 renal transplant patients, 59 cases (36.42%) had high potassium during operation. Univariate analysis showed that the pre-operative blood potassium, pulse pressure, and hemodialysis time of the high potassium group were higher than those of the non high potassium group, and the pH value of the high potassium group was lower than that of the non high potassium group, the difference was statistically significant (P < 0.05). The results of logistic regression analysis showed that high preoperative blood potassium, low preoperative pH value, large pulse pressure, and long hemodialysis time were risk factors for Hyperkalemia during kidney transplantation surgery (P<0.05). The area under the ROC curve for the training set and validation set of the nomogram model constructed based on the aforementioned risk factors was 0.933 (95% CI: 0.885-0.981, P<0.05), 0.798 (95% CI: 0.662-0.935, P<0.05). The sensitivity, specificity, logit value, and cutoff value were 0.892, 0.872, -0.625, 0.6 and 0.862, 0.700, -0.159, 0.5, respectively. The calibration curve and decision curve results indicate that the model has high predictive performance and clinical application value. Conclusions High preoperative serum potassium, low preoperative pH,high pulse pressure, and long hemodialysis time are the risk factors of hyperkalemia in renal transplantation. According to the risk factors, constructing nomogram model to predict hyperkalemia in renal transplantation has high clinical value.
Keywords: hyperkalaemia, Kidney Transplantation, Risk factors, nomogram, predictive model
Received: 01 Jul 2025; Accepted: 28 Oct 2025.
Copyright: © 2025 Chen, Jian, Su, Chen, Zhang, Huang, Tan, Peng, Huang, Dong and Dong. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Chunqiang Dong, dongchunqiang@163.com
Kun Dong, dongkun007@163.com
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