A nomogram clinical prediction model for predicting urinary infection stones: development and validation in a retrospective study
Author:
Funder
Xuzhou Key Research and Development Project
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00345-024-04904-7.pdf
Reference30 articles.
1. Zhang D, Li S, Zhang Z et al (2021) Urinary stone composition analysis and clinical characterization of 1520 patients in central China. Sci Rep 11(1):6467. https://doi.org/10.1038/s41598-021-85723-3
2. Espinosa-Ortiz EJ, Eisner BH, Lange D et al (2019) Current insights into the mechanisms and management of infection stones. Nat Rev Urol 16(1):35–53. https://doi.org/10.1038/s41585-018-0120-z
3. Rahman NU, Meng MV, Stoller ML (2003) Infections and urinary stone disease. Curr Pharm Des 9(12):975–981. https://doi.org/10.2174/1381612033455125
4. Gao X, Lu C, Xie F et al (2020) Risk factors for sepsis in patients with struvite stones following percutaneous nephrolithotomy. World J Urol 38(1):219–229. https://doi.org/10.1007/s00345-019-02748-0
5. Koras O, Bozkurt IH, Yonguc T et al (2015) Risk factors for postoperative infectious complications following percutaneous nephrolithotomy: a prospective clinical study. Urolithiasis 43(1):55–60. https://doi.org/10.1007/s00240-014-0730-8
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