TY - JOUR
T1 - Using 24-hour urinalysis to predict stone type
AU - Moreira, Daniel M.
AU - Friedlander, Justin I.
AU - Hartman, Christopher
AU - Elsamra, Sammy E.
AU - Smith, Arthur D.
AU - Okeke, Zeph
PY - 2013/12
Y1 - 2013/12
N2 - 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.
AB - 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.
KW - Calcium oxalate
KW - Calcium phosphate
KW - Kidney calculi
KW - Uric acid
KW - Urinalysis
UR - https://www.scopus.com/pages/publications/84888638497
UR - https://www.scopus.com/pages/publications/84888638497#tab=citedBy
U2 - 10.1016/j.juro.2013.05.115
DO - 10.1016/j.juro.2013.05.115
M3 - Article
C2 - 23764079
SN - 0022-5347
VL - 190
SP - 2106
EP - 2111
JO - Journal of Urology
JF - Journal of Urology
IS - 6
ER -