OBJECTIVE: To determine the in vivo ability to predict uric acid stone composition by Hounsfield units (HU) with the addition of urine parameters. METHODS: We reviewed all consecutive stones sent for analysis during a 4-year period from our institution for patients with an in-house computed tomography (CT) scan within the prior 6 months and urinalysis within the prior week. CT scans were independently reviewed by a radiologist blinded to stone composition. RESULTS: Of the 507 patients with stones sent for analysis, 235 met the criteria for inclusion. Analysis showed 212 stones were predominantly calcium-based, and 22 were predominantly uric acid in composition. There was a significant difference between calcium stones and uric acid stones in mean HU (890 ± 20 vs 484 ± 44; P <.01) and urine pH (6.4 ± 0.8 vs 5.1 ± 0.2; P <.01). Receiver operating characteristic curve evaluation gave optimal predictive values of HU ≤494 (rounded to 500) and pH of ≤5.5 to predict uric acid stones. The combination of HU and pH criteria resulted in a sensitivity of 86% and a specificity of 98%, with a positive predictive value of 80%, which increased to 90% if we limited to stones >4 mm. CONCLUSION: Uric acid stones show a significant difference in HU and urine pH from calcium stones, and the use of both criteria is superior to either separately. For a stone >4 mm, a HU ≤500 and pH ≤5.5 has a positive predictive value of 90% for uric acid composition. Our prediction model gives a straightforward tool that can be easily measured to predict a uric acid stone.
OBJECTIVE: To determine the in vivo ability to predict uric acid stone composition by Hounsfield units (HU) with the addition of urine parameters. METHODS: We reviewed all consecutive stones sent for analysis during a 4-year period from our institution for patients with an in-house computed tomography (CT) scan within the prior 6 months and urinalysis within the prior week. CT scans were independently reviewed by a radiologist blinded to stone composition. RESULTS: Of the 507 patients with stones sent for analysis, 235 met the criteria for inclusion. Analysis showed 212 stones were predominantly calcium-based, and 22 were predominantly uric acid in composition. There was a significant difference between calcium stones and uric acid stones in mean HU (890 ± 20 vs 484 ± 44; P <.01) and urine pH (6.4 ± 0.8 vs 5.1 ± 0.2; P <.01). Receiver operating characteristic curve evaluation gave optimal predictive values of HU ≤494 (rounded to 500) and pH of ≤5.5 to predict uric acid stones. The combination of HU and pH criteria resulted in a sensitivity of 86% and a specificity of 98%, with a positive predictive value of 80%, which increased to 90% if we limited to stones >4 mm. CONCLUSION:Uric acid stones show a significant difference in HU and urine pH from calcium stones, and the use of both criteria is superior to either separately. For a stone >4 mm, a HU ≤500 and pH ≤5.5 has a positive predictive value of 90% for uric acid composition. Our prediction model gives a straightforward tool that can be easily measured to predict a uric acid stone.
Authors: Maria A Jepperson; Joseph G Cernigliaro; El-Sayed H Ibrahim; Richard L Morin; William E Haley; David D Thiel Journal: J Endourol Date: 2014-09-17 Impact factor: 2.942