title: Developing a preoperative predictive model for ureteral length for ureteral stent insertion.
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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Urology, Yokohama City University, Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa, 2360004, Japan. takashi_tk2001@yahoo.co.jp.|Department of Urology, Ohguchi Higashi General Hospital, Yokohama, Japan. takashi_tk2001@yahoo.co.jp.
authors.forename: Takashi
authors.identifier: http://orcid.org/0000-0002-7049-3379
authors.initials: T
authors.lastname: Kawahara
authors.affiliation: Departments of Biostatistics, Yokohama City University Graduate School of Medicine, Yokohama, Japan.
authors.forename: Kentaro
authors.initials: K
authors.lastname: Sakamaki
authors.affiliation: Department of Urology, Yokohama City University, Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa, 2360004, Japan.|Department of Urology, Ohguchi Higashi General Hospital, Yokohama, Japan.
authors.forename: Hiroki
authors.initials: H
authors.lastname: Ito
authors.affiliation: Department of Urology, Ohguchi Higashi General Hospital, Yokohama, Japan.
authors.forename: Shinnosuke
authors.initials: S
authors.lastname: Kuroda
authors.affiliation: Department of Urology, Ohguchi Higashi General Hospital, Yokohama, Japan.
authors.forename: Hideyuki
authors.initials: H
authors.lastname: Terao
authors.affiliation: Department of Urology, Yokohama City University, Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa, 2360004, Japan.
authors.forename: Kazuhide
authors.initials: K
authors.lastname: Makiyama
authors.affiliation: Department of Urology, Yokohama City University, Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa, 2360004, Japan.
authors.forename: Hiroji
authors.initials: H
authors.lastname: Uemura
authors.affiliation: Department of Urology, Yokohama City University, Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa, 2360004, Japan.
authors.forename: Masahiro
authors.initials: M
authors.lastname: Yao
authors.affiliation: Departments of Pathology and Urology, Johns Hopkins University School of Medicine, Baltimore, USA.
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Miyamoto
authors.affiliation: Department of Urology, Ohguchi Higashi General Hospital, Yokohama, Japan.
authors.forename: Junichi
authors.initials: J
authors.lastname: Matsuzaki
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D005544:Forecasting; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009929:Organ Size; D057234:Preoperative Period; D019919:Prosthesis Implantation; D015607:Stents; D014513:Ureter / Q000033:anatomy & histology* / Q000601:surgery*
keywords: Predictive model; Ureter; Ureteral catheter; Ureteral length; Ureteral stent