# Influencing factors and risk prediction nomogram model construction of hyperkalemia during kidney transplantation

## TL;DR

This study identifies risk factors for high potassium levels during kidney transplants and builds a predictive model to help doctors prepare for this complication.

## Contribution

A novel nomogram model for predicting hyperkalemia during kidney transplantation based on preoperative risk factors.

## Key findings

- High preoperative blood potassium, low pH, high pulse pressure, and long hemodialysis time are significant risk factors for hyperkalemia during kidney transplantation.
- The nomogram model achieved high predictive accuracy with an area under the ROC curve of 0.933 in the training set.
- The model's calibration and decision curve analysis confirmed its strong clinical utility for predicting hyperkalemia.

## Abstract

To analyze the risk factors of hyperkalemia during kidney transplantation, and to construct the prediction model of nomogram.

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.

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.

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.