INTRODUCTION: To determine the association of the basic metabolic panel with stone type. METHODS: The present study was a retrospective review of 492 stone formers with both stone composition analysis and basic metabolic panel available. Analysis of a basic metabolic panel across stone types was carried out using Fisher's exact test and analysis of variance. Multinomial logistic regression was used to predict stone type based on a basic metabolic panel. RESULTS: A total of 272 (55%) patients had predominantly calcium oxalate stones, 100 (21%) had uric acid stones, 93 (19%) had calcium phosphate stones, 16 (3%) had mixed stones and 11 (2%) had other types of stones. Uric acid stone formers had the highest serum glucose, blood urea nitrogen and creatinine levels. Calcium oxalate stone formers had the highest serum sodium. No significant differences in mean serum calcium levels across different stone types were identified. The predicted risk of uric acid stone over the other stone types increased with an increase in serum glucose and decreased with an increase in carbon dioxide levels. The predicted risk of calcium oxalate stones increased with an increase in serum sodium and chloride levels. The predicted risk of calcium phosphate and oxalate stones over the other stone types increased with an increase in serum calcium levels. The overall accuracy of the basic metabolic panel alone to predict stone type was 59%. CONCLUSION: A basic metabolic panel alone or in combination with 24-h urinalysis and demographics does not accurately predict stone type. However, it can be used in combination with other variables to predict stone composition.
INTRODUCTION: To determine the association of the basic metabolic panel with stone type. METHODS: The present study was a retrospective review of 492 stone formers with both stone composition analysis and basic metabolic panel available. Analysis of a basic metabolic panel across stone types was carried out using Fisher's exact test and analysis of variance. Multinomial logistic regression was used to predict stone type based on a basic metabolic panel. RESULTS: A total of 272 (55%) patients had predominantly calcium oxalate stones, 100 (21%) had uric acid stones, 93 (19%) had calcium phosphate stones, 16 (3%) had mixed stones and 11 (2%) had other types of stones. Uric acid stone formers had the highest serum glucose, blood ureanitrogen and creatinine levels. Calcium oxalate stone formers had the highest serum sodium. No significant differences in mean serum calcium levels across different stone types were identified. The predicted risk of uric acid stone over the other stone types increased with an increase in serum glucose and decreased with an increase in carbon dioxide levels. The predicted risk of calcium oxalate stones increased with an increase in serum sodium and chloride levels. The predicted risk of calcium phosphate and oxalate stones over the other stone types increased with an increase in serum calcium levels. The overall accuracy of the basic metabolic panel alone to predict stone type was 59%. CONCLUSION: A basic metabolic panel alone or in combination with 24-h urinalysis and demographics does not accurately predict stone type. However, it can be used in combination 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