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. 2023 Nov 28;13(1):20943.
doi: 10.1038/s41598-023-47773-7.

Pathogen species are the risk factors for postoperative infection of patients with transurethral resection of the prostate: a retrospective study

Jiexiang Lin #  1   2 , Zesong Yang #  1   2 , Liefu Ye  1   2 , Yun Hong  1   2 , Wanghai Cai  1   2 , Honghong Pan  1   2 , Haishou Fu  3   4 , Jinfeng Wu  5   6
Affiliations

Pathogen species are the risk factors for postoperative infection of patients with transurethral resection of the prostate: a retrospective study

Jiexiang Lin et al. Sci Rep. .

Abstract

This study aimed to analyze the infection risk factors for transurethral resection of the prostate (TURP) and establish predictive models to help make personalized treatment plans. Our study was designed one-center and retrospectively enrolled 1169 benign prostatic hyperplasia (BPH) patients. Risk factors were explored for postoperative infection. A TURP-postoperative infection (TURP-PI) model with infection prediction values was created. The improved-TURP-PI (I-TURP-PI) model, including extra new factors (pathogens species), was also built to see whether it could optimize the prediction abilities. At last, we developed a nomogram for better clinical application. Operation time, preoperative indwelling urinary catheter (PIUC), and positive preoperative urine culture were independent risk factors (all P < 0.05). Interestingly, pathogens species in pre-surgery urine (PEnterococcus faecium = 0.014, PPseudomonas aeruginosa = 0.086) were also independent risk factors. Patients with positive Enterococcus faecium (37.50%) were most likely to have postoperative infection. We built two models with AUCTURP-PI = 0.709 (95% CI 0.656-0.763) and AUCI-TURP-PI = 0.705 (95% CI 0.650-0.760). The nomogram could help improve the prediction ability. To our knowledge, our study is the first to use pathogen species in urine before surgery as risk factors for infection prediction after TURP. TURP-PI and I-TURP-PI models have essential roles in predicting patients' postoperative infections and in better postoperative antibiotic decision-making.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
The wokflow of the study.
Figure 2
Figure 2
Distribution of urine pathogen. (A) Species accumulation curve. (B) Proportion of different pathogens in preoperative urine culture. (C) Incidence of postoperative infection in different pathogen-positive groups. (D) Comparison of detection rates of different pathogens in non_postoperative and postoperative infection groups.
Figure 3
Figure 3
Nomogram for two predictive models. (A) TURP-PI model; (B) ROC of TURP-PI model; (C) The calibration curve of TURP-PI model; (D) I-TURP-PI model; (E) The ROC of I-TURP-PI model; (F) The calibration curve of I-TURP-PI model; (G) The clinical impact curves of two models.
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