Kidney Stones Research Today is a free monthly online journal that collates and summarizes the latest research about Kidney Stones, including details on causes, symptoms, treatment, diagnosis of nephrolithiasis, calculi. | ||||||||
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External validation of outcome prediction model for ureteral/renal calculi.Parekattil SJ, Kumar U, Hegarty NJ, Williams C, Allen T, Teloken P, Leitão VA, Netto NR, Haber GP, Ballereau C, Villers A, Streem SB, White MD, Moran ME Cleveland Clinic Foundation, Cleveland, Ohio, USA. sijo_p@hotmail.com PURPOSE: We externally validated a previously designed neural network model to predict outcome and duration of passage for ureteral/renal calculi. The model was also evaluated using a 6 mm largest stone dimension cutoff in predicting stone outcome. MATERIALS AND METHODS: The model was previously designed on 301 patients at Albany Medical Center (free shareware from www.uroengineering.com). The model had a prediction accuracy of 86% for passage outcome and 87% for passage duration. In this study we tested the model on a separate 384 patients from 6 different external institutions to assess the prediction accuracy. All patients had a single renal/ureteral calculus by evaluation in an emergency room setting or by primary physicians and were then referred for further treatment. Model accuracy was also compared to using a 6 mm largest stone dimension cutoff in predicting the need for intervention. RESULTS: Testing on the 384 patients from all 6 external institutions revealed an outcome prediction accuracy of 88%. The area under the ROC curve was 0.9. Using a 6 mm stone size cutoff provided 79% (ROC 0.8) accuracy. The model duration of passage prediction accuracy was 80% (133 patients passed the stone, area under ROC of 0.8). CONCLUSIONS: The model provided high stone outcome prediction accuracy (ROC of 0.9 and 0.8) at the 6 external institutions, comparable to that of the design institution. The model provided higher accuracy than using only the largest stone dimension as a cutoff. Increasing experience will further assess the model's accuracy. Published 12 January 2006 in J Urol, 175(2): 575-9.
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