Developing a preoperative predictive model for ureteral length for ureteral stent insertion

Takashi Kawahara, Kentaro Sakamaki, Hiroki Ito, Shinnosuke Kuroda, Hideyuki Terao, Kazuhide Makiyama, Hiroji Uemura, Masahiro Yao, Hiroshi Miyamoto, Junichi Matsuzaki

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Ureteral stenting has been a fundamental part of various urological procedures. Selecting a ureteral stent of optimal length is important for decreasing the incidence of stent migration and complications. The aim of the present study was to develop and internally validate a model for predicting the ureteral length for ureteral stent insertion. Methods: This study included a total of 127 patients whose ureters had previously been assessed by both intravenous urography (IVU) and CT scan. The actual ureteral length was determined by direct measurement using a 5-Fr ureteral catheter. Multiple linear regression analysis with backward selection was used to model the relationship between the factors analyzed and actual ureteral length. Bootstrapping was used to internally validate the predictive model. Results: Patients all of whom had stone disease included 76 men (59.8%) and 51 women (40.2%), with the median and mean (± SD) ages of 60 and 58.7 (±14.2) years. In these patients, 53 (41.7%) right and 74 (58.3%) left ureters were analyzed. The median and mean (± SD) actual ureteral lengths were 24.0 and 23.3 (±2.0) cm, respectively. Using the bootstrap methods for internal validation, the correlation coefficient (R2) was 0.57 ± 0.07. Conclusion: We have developed a predictive model, for the first time, which predicts ureteral length using the following five preoperative characteristics: age, side, sex, IVU measurement, and CT calculation. This predictive model can be used to reliably predict ureteral length based on clinical and radiological factors and may thus be a useful tool to help determining the optimal length of ureteral stent.

Original languageEnglish (US)
Article number70
Pages (from-to)1-5
Number of pages5
JournalBMC Urology
Volume16
Issue number1
DOIs
StatePublished - Nov 30 2016

Keywords

  • Predictive model
  • Ureter
  • Ureteral catheter
  • Ureteral length
  • Ureteral stent

ASJC Scopus subject areas

  • Reproductive Medicine
  • Urology

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