Multifactorial prognostic model for long-term infectiousinflammatory complications risk following transurethral surgery for benign prostatic hyperplasia

Introduction. Infectious and inflammatory complications (ICs) are a significant, potentially life-threatening condition developing during transurethral resection of the prostate (TURP) with a frequency of 0.5% to 20.0% of cases. Most studies provide data on immediate ICs. However, there are currently no studies in the literature with a comprehensive assessment of late ICs after TURP.

Objective. To analyse the significant predictors of ICs for the development of a prognostic model for the risks of developing remote infectious complications TURP.

Materials & methods. This single-center retrospective study includes data from 301 patients who underwent monoand bipolar TURP from 2016 to 2023. Inclusion criteria for the study: prostate volume (30–80 cc), no history of urinary tract infections (UTI) at the time of hospitalization and treatment with antibacterial drugs for at least one month before surgery, possible presence of latent UTI before surgery, absence of prostate cancer. The exclusion criterion was non-compliance with the inclusion criteria. The infectious complications assessed included upper and lower urinary tract infections, as well as epididymitis, orchitis and prostatitis, confirmed based on clinical and laboratory data.

Results. In the late period, 47 (15.6%) patients developed infectious and inflammatory complications: urethritis developed in 8 cases, epididymoorchitis in 18, acute prostatitis in 9, and cystitis was diagnosed in the remaining 12 cases. Regression analysis revealed three statistically significant predictors: baseline PSA density, dysuria at hospital discharge, and scrotal discomfort / pain during hospitalization. The explained variance in the incidence of late ICs was 37.4%; the area under the curve in ROC analysis was 0.83; 95% CI [0.75; 0.90].

Conclusion. Implementation of the developed predictive model into clinical practice can improve the safety of transurethral surgery for BPH, optimize resource allocation, and improve the effectiveness of clinical outcomes in the treatment of urological infections. The predictive model can be used when discharging a patient from the hospital after TURP.

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