Title: Which Is More Important in Predicting the Outcome of Extracorporeal Shockwave Lithotripsy of Solitary Renal Stones: Stone Location or Stone Burden?
Abstract: Purpose: To assess the effect of stone location and burden on the outcome of extracorporeal shockwave lithotripsy (SWL) as a primary treatment of solitary renal stone. Patients and Methods: The study included 438 patients with a solitary renal stone who underwent SWL as a primary treatment for their stones. All were evaluated by plain radiography of the kidneys, ureters, and bladder (KUB), ultrasonography, intravenous urography, or noncontrast enhanced CT before SWL and followed up for 3 months after treatment by KUB radiography and/or ultrasongraphy. Patients were classified into four groups according to stone location (renal pelvis, lower, middle, and upper calix) and three groups according to stone burden (≤1 cm2, 1.1–2 cm2, and >2 cm2). Treatment outcome was considered successful if no residual fragments (stone free) or clinically insignificant nonobstructing residuals less than 4 mm remained after 3 months of follow-up. Results: The mean age of the patients was 45.1±12.5 years. The mean stone burden, number of sessions, and shockwaves for the whole study were 1.3±0.49 cm2, 2.1±0.7 sessions, and 5616.6±2017.4 shockwaves, respectively. The stone-free rate of the study was 65.1%. The stone-free rates of the stones in the renal pelvis, lower, middle, and upper calices were 72.4%, 56%, 55.6%, and 69%, respectively. The stone-free rate of the stones ≤1 cm2, 1.1 to 2 cm2, and >2 cm2 was 50.2%, 39.6%, and 10.2%, respectively (P<0.05). Conclusion: Stone burden rather than stone location is considered as a predicting factor for the outcome of SWL in a solitary renal stone, especially in the renal pelvis and lower calix.
Publication Year: 2012
Publication Date: 2012-05-01
Language: en
Type: article
Indexed In: ['crossref', 'pubmed']
Access and Citation
Cited By Count: 12
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot