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J Renal Inj Prev
. 2019;8(3): 221-224. doi:
10.15171/jrip.2019.41
Original
Impact of body mass index on success, complications and failure of extracorporeal shock wave lithotripsy
Faramarz Mohammad Ali Beigi
1
, Zahra Keivani Hafshejani
2
, Mohammadreza Aghahoseini
1
, Majid Shirani
1
Cited by CrossRef: 2
1- Noble P, Hamilton B, Gerber G, Eissa A. Stone decision engine accurately predicts stone removal and treatment complications for shock wave lithotripsy and laser ureterorenoscopy patients.
PLoS ONE
. 2024;19(5):e0301812
[Crossref]
2- Rashidi E, Langarizadeh M, Sayadi M, Sarkarian M. Machine Learning Models for Predicting the Type and Outcome of Ureteral Stones Treatments. 2023;12(1)
[Crossref]
3- Ipek O, Dincer E, Sevinc A, Sevinc B, Canakci C, Ozkaptan O. Predictive performance of Triple-D, Quadruple-D, and Mayo adhesive probability scores in ESWL for renal stones: a retrospective cohort study.
Urolithiasis
. 2025;53(1)
[Crossref]
, Zahra Keivani Hafshejani 2 , Mohammadreza Aghahoseini 1 , Majid Shirani 1