Risk factors for bladder spasms after radical prostatectomy for prostate cancer: A prospective study

Author:

Yu Chen1,Chaoyu Liao1,Siyue Li1,Luqiang Zhou1,Fang Guo1,Ji Zheng1,Caiping Song1

Affiliation:

1. Xinqiao Hospital, Third Military Medical University (Army Medical University)

Abstract

Abstract

Background Postoperative bladder spasms in prostate cancer patients have the potential to significantly impact their quality of life following surgery. It is essential to investigate the risk factors associated with bladder spasms in this patient population post-radical surgery to develop effective prevention strategies. Methods A prospective selection was conducted on 281 patients who underwent radical prostatectomy in our hospital from March 2022 to March 2024. They were divided into two groups based on whether bladder spasms occurred after surgery: the occurrence group (n = 130) and the non occurrence group (n = 151). Logistic regression analysis was performed on possible related factors to construct a column chart risk model. Another 43 prostate cancer patients who underwent radical surgery were selected to validate the model. Results The results of multivariate logistic regression analysis showed that preoperative anxiety, postoperative body temperature above 37.4, and flushing fluid speed > 150 drops/min were independent risk factors for bladder spasms in prostate cancer patients after radical surgery (OR > 1), while robotic surgery were independent protective factors (OR = 0.563). A column chart prediction model was established based on the risk factors affecting postoperative bladder spasms, and internal validation was performed using Bootstrap method with 1000 repeated samples. The predicted values of the calibration curve were basically consistent with the actual values, and the Hosmer Lemeshow goodness of fit test was performed χ2 = 7.802, P = 0.453, the area under the ROC curve is 0.688 (95%CI: 0.626–0.750). Conclusions The occurrence of bladder spasms in prostate cancer patients after radical surgery is influenced by multiple factors, and the risk warning model established based on these factors has good predictive performance.

Publisher

Research Square Platform LLC

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