Construction of a nomogram for predicting catheter-related bladder discomfort in patients with end-stage renal disease after renal transplantation: a retrospective study

Author:

Liu Kao1,Liu Shengli1,Peng Zhiguo1,Li Na1,Sun Huaibin1

Affiliation:

1. Department of Organ Transplantation, Qilu Hospital of Shandong University, Jinan, China

Abstract

Background The incidence of catheter-related bladder discomfort (CRBD) is relatively high in the end-stage renal disease (ESRD) patients who underwent renal transplantation (RT). This study was designed to establish a nomogram for predicting CRBD after RT among ESRD patients. Methods In this retrospective study, we collected 269 ESRD patients who underwent RT between September 2019 and August 2023 in our hospital. The patients were divided into training set (n = 215) and test set (n = 54) based on a ratio of 8:2. Univariate and multivariate logistic regression analyses were utilized to identify the risk factors associated with CRBD after RT, and then a nomogram model was constructed. Receiver operating characteristic (ROC) and calibration curve were used to evaluate the predicting efficiency of the established nomogram. Results Multivariate logistic regression analysis showed that aberrant body mass index (BMI) (underweight: OR = 5.25; 95% CI [1.25–22.15], P = 0.024; overweight: OR = 2.75; 95% CI [1.17–6.49], P = 0.021), anuria (OR = 2.86; 95% CI [1.33–5.88]) and application of double J (DJ) stent with a diameter of >5Fr (OR = 15.88; 95% CI [6.47–39.01], P < 0.001) were independent risk factors for CRBD after RT. In contrast, sufentanil utilization (>100 µg) [OR = 0.39; 95% CI [0.17–0.88], P = 0.023] was associated with decreased incidence of CRBD. A nomogram was then established based on these parameters for predicting the occurrence of CRBD after RT. Area under the ROC curve (AUC) values and calibration curves confirmed the prediction efficiency of the nomogram. Conclusion A nomogram was established for predicting CRBD after RT in ESRD patients, which showed good prediction efficiency based on AUC and calibration curves.

Publisher

PeerJ

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