Construction and validation of a predictive model for the acceptance of kidney xenotransplantation among patients awaiting kidney transplantation: a cross-sectional study from China.

Background: Kidney xenotransplantation (KXTx) has the potential to address the shortage of kidney donations. To construct and validate a predictive model for the willingness to receive KXTx, data were collected from Chinese patients awaiting kidney transplantation.

Methods: The data were collected from 539 questionnaires from June 20, 2023, to April 3, 2024. A random allocation method was used to conduct univariate analysis and multiple logistic regression analysis to explore the factors that affect KXTx acceptance. A prediction model was constructed in the form of a nomogram, and the accuracy of the prediction model was evaluated using multiple methods.

Results: The results of multivariate logistic regression revealed that medical insurance (No vs. Yes, odds ratio [OR] 3.10, 95% confidence interval [CI] 1.52-6.12), religion (no belief as the reference group; Atheist: OR 2.56, 95% CI 1.26-5.33; Buddhism: OR 2.03, 95% CI 0.78-4.89; Taoism: OR 2.33, 95% CI 0.72-6.77; Islam: OR 5.78, 95% CI 1.38-21.10; Catholicism: OR 4.52, 95% CI 0.74-22.7; Christianity: OR 7.69, 95% CI 0.36-66.5; Other: OR 0.93, 95% CI 0.05-5.26), and knowing about KXTx (No vs. Yes, OR 3.39, 95% CI 1.89-6.08) were independent risk factors for KXTx acceptance. A nomogram was constructed based on the abovementioned factors, and the area under the curve was 0.717. The calibration curves decision curve analysis also revealed good performance. Additionally, previous research has shown that KXTx-related risk factors are the primary concern for these patients.

Conclusion: This study constructed a predictive model for the acceptance of KXTx among patients awaiting kidney transplantation. This model has significance for studying the acceptance and attitudes of this population.