PURPOSE: We determined the accuracy of 24-hour urinalysis in predicting stone type and identify the associations between 24-hour urine elements with stone type. MATERIALS AND METHODS: We performed a retrospective review of 503 stone formers with stone composition analysis and 24-hour urinalysis available. Analysis of 24-hour urine elements across stone types was performed using Fisher's exact test and ANOVA. Multinomial logistic regression was used to predict stone type based on 24-hour urinalysis. RESULTS: A total of 280 (56%) patients had predominantly calcium oxalate, 103 (20%) had uric acid, 93 (19%) had calcium phosphate, 16 (3%) had mixed and 11 (2%) had other stone types. There were several significant patient characteristics and 24-hour urinalysis differences across stone type groups. The statistical model predicted 371 (74%) calcium oxalate, 78 (16%) uric acid, 52 (10%) calcium phosphate, zero mixed and 2 (less than 1%) other stone types. The model correctly predicted calcium oxalate stones in 85%, uric acid in 51%, calcium phosphate in 31%, mixed in 0% and other stone types in 18% of the cases. Of the predicted stone types, correct predictions were 61%, 69%, 56% and 71% for calcium oxalate, uric acid, calcium phosphate and other stones types, respectively. The overall accuracy was 64%. Plots were used to explore the associations between each 24-hour urine element with each predicted stone type adjusted for all the others urinary elements. CONCLUSIONS: A 24-hour urinalysis alone does not accurately predict stone type. However, it may be used in conjunction with other variables to predict stone composition.
PURPOSE: We determined the accuracy of 24-hour urinalysis in predicting stone type and identify the associations between 24-hour urine elements with stone type. MATERIALS AND METHODS: We performed a retrospective review of 503 stone formers with stone composition analysis and 24-hour urinalysis available. Analysis of 24-hour urine elements across stone types was performed using Fisher's exact test and ANOVA. Multinomial logistic regression was used to predict stone type based on 24-hour urinalysis. RESULTS: A total of 280 (56%) patients had predominantly calcium oxalate, 103 (20%) had uric acid, 93 (19%) had calcium phosphate, 16 (3%) had mixed and 11 (2%) had other stone types. There were several significant patient characteristics and 24-hour urinalysis differences across stone type groups. The statistical model predicted 371 (74%) calcium oxalate, 78 (16%) uric acid, 52 (10%) calcium phosphate, zero mixed and 2 (less than 1%) other stone types. The model correctly predicted calcium oxalate stones in 85%, uric acid in 51%, calcium phosphate in 31%, mixed in 0% and other stone types in 18% of the cases. Of the predicted stone types, correct predictions were 61%, 69%, 56% and 71% for calcium oxalate, uric acid, calcium phosphate and other stones types, respectively. The overall accuracy was 64%. Plots were used to explore the associations between each 24-hour urine element with each predicted stone type adjusted for all the others urinary elements. CONCLUSIONS: A 24-hour urinalysis alone does not accurately predict stone type. However, it may be used in conjunction with other variables to predict stone composition.
Authors: Daniel M Moreira; Justin I Friedlander; Christopher Hartman; Boris Gershman; Arthur D Smith; Zeph Okeke Journal: Urolithiasis Date: 2015-11-16 Impact factor: 3.436
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