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Can 24-Hour Urine Stone Risk Profiles Predict Urinary Stone Composition?

医学 尿酸 肾结石 草酸钙 优势比 尿 泌尿系统 置信区间 体质指数 内科学 草酸盐 胃肠病学 泌尿科 化学 有机化学
作者
Fábio César Miranda Torricelli,Shubha De,Xiaobo Liu,Juan Calle,Surafel Gebreselassie,Manoj Monga
出处
期刊:Journal of Endourology [Mary Ann Liebert, Inc.]
卷期号:28 (6): 735-738 被引量:19
标识
DOI:10.1089/end.2013.0769
摘要

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.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.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.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.

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