Abstract
Background . Nowadays dissolution of uric acid kidney stones is the first line treatment according to existing clinical guidelines. Besides dual-energy CT, which is costly, there is no non-invasive tool to predict uric acid stone composition. Aim . To develop a new tool for uric acid stones prediction which will improve patient selection for oral stone dissolution therapy. Materials and methods . We retrospectively analyzed treatment results of 189 patients which were distributed to two groups: with pure uric acid stones - 59 patients and with other composition - 130 patients. Demographic data, results of 24 hour urine analysis and CT scans were analyzed. Results . Among above mentioned parameters the following had the highest significance: body mass, body mass index, urine pH and stone density in Hounsfield Units (p<0.01). Product of multiplication of urine pH and CT-stone density called «Urate index» yielded highest AUC (0.96) which permitted with high accuracy diagnose uric acid stones. Conclusion . «Urate-index» is simple to obtain and has high predictive value which might help choosing target population for kidney stone dissolution.
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