BACKGROUND AND PURPOSE: Distinguishing calcium oxalate from uric acid stones is critical to identify those patients who may benefit from dissolution therapy and can also help direct preventive measures for stone growth. We aim to study whether 24-hour urine analysis may predict the urinary stone composition. PATIENTS AND METHODS: We retrospectively identified patients with calcium oxalate and uric acid stone compositions who also had a 24-hour urine collection within 3 months of stone analysis. Patients with calcium phosphate, cystine, and other stone compositions were excluded. Subjects were divided based on their stone type (calcium oxalate vs uric acid stones) and were compared according to demographic data and 24-hour urine analysis. Logistic regression analysis was performed to assess the association between stone composition and covariates. A nomogram was then constructed to predict uric acid stones over calcium oxalate stones. RESULTS: Of the 1163 patients identified, 1054 (90.6%) had calcium oxalate stones and 109 (9.4%) had uric acid stones. On logistic regression, body mass index (BMI) (odds ratio [OR] 1.351, 95% confidence interval [CI] 1.133-1.609; P<0.001), urinary sodium (OR 1.021, 95% CI 1.004-1.037; P=0.013), calcium (OR 0.987, 95% CI 0.979-0.996; P=0.003), oxalate (OR 0.890, 95% CI 0.804-0.985; P=0.024), and uric acid (OR 0.989, 95% CI 0.982-0.997; P=0.005) were significant predictors for urinary stone composition. The nomogram with the highest concordance index (c-index=0.855) was obtained using age, BMI, urinary sodium, calcium, oxalate, and uric acid as variables. CONCLUSION: Distinguishing uric acid from calcium oxalate stones can be performed with relative accuracy using parameters from the 24-hour urine stone risk profile and the patient's BMI and age.
BACKGROUND AND PURPOSE: Distinguishing calcium oxalate from uric acid stones is critical to identify those patients who may benefit from dissolution therapy and can also help direct preventive measures for stone growth. We aim to study whether 24-hour urine analysis may predict the urinary stone composition. PATIENTS AND METHODS: We retrospectively identified patients with calcium oxalate and uric acid stone compositions who also had a 24-hour urine collection within 3 months of stone analysis. Patients with calcium phosphate, cystine, and other stone compositions were excluded. Subjects were divided based on their stone type (calcium oxalate vs uric acid stones) and were compared according to demographic data and 24-hour urine analysis. Logistic regression analysis was performed to assess the association between stone composition and covariates. A nomogram was then constructed to predict uric acid stones over calcium oxalate stones. RESULTS: Of the 1163 patients identified, 1054 (90.6%) had calcium oxalate stones and 109 (9.4%) had uric acid stones. On logistic regression, body mass index (BMI) (odds ratio [OR] 1.351, 95% confidence interval [CI] 1.133-1.609; P<0.001), urinary sodium (OR 1.021, 95% CI 1.004-1.037; P=0.013), calcium (OR 0.987, 95% CI 0.979-0.996; P=0.003), oxalate (OR 0.890, 95% CI 0.804-0.985; P=0.024), and uric acid (OR 0.989, 95% CI 0.982-0.997; P=0.005) were significant predictors for urinary stone composition. The nomogram with the highest concordance index (c-index=0.855) was obtained using age, BMI, urinary sodium, calcium, oxalate, and uric acid as variables. CONCLUSION: Distinguishing uric acid from calcium oxalate stones can be performed with relative accuracy using parameters from the 24-hour urine stone risk profile and the patient's BMI and age.
Authors: Fabio Cesar Miranda Torricelli; Robert Brown; Fernanda C G Berto; Sarah Tarplin; Miguel Srougi; Eduardo Mazzucchi; Manoj Monga Journal: Can Urol Assoc J Date: 2015 Mar-Apr Impact factor: 1.862