Arash Safaie1,2, Mojdeh Mirzadeh2, Ehsan Aliniagerdroudbari3, Sepideh Babaniamansour4, Alireza Baratloo1,2

1Prehospital Emergency Research Center, Tehran University of Medical Sciences, Tehran, Iran
2Department of Emergency Medicine, Sina Hospital, Tehran University of Medical Sciences, Tehran, Iran
3School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
4School of Medicine, Islamic Azad University of Medical Sciences, Tehran, Iran

Keywords: Clinical prediction rules, Decision support techniques, Emergency department, Renal colic, Validation studies

Abstract

Introduction: Renal colic is one of the most common complaints in patients admitted to Emergency Department (ED). Computed Tomography (CT) is the reference standard for the diagnosis of any stones in the kidneys or ureters. However, CT has classical disadvantages, such as radiation exposure, cost and availability. Recently, STONE clinical prediction criteria were suggested to identify uncomplicated ureteral stone cases among patiens admitted to the ED with abdominal pain. Primary objective of this study was the external validation of the STONE criteria.

Methods: This was a diagnostic accuracy study conducted on a prospective, observational cohort. All consecutive patients who underwent a non-enhanced abdominopelvic CT scan in the ED with an initial diagnosis of ureteral stone disease were enrolled. Using a pre-prepared checklist, all data and the final diagnosis according to the CT scan were recorded. STONE score was calculated for all patients. The area under the curve (AUC) of the STONE Score and the CT, the reference standard, were compared using the ROC curve analysis.

Results: Totally, 237 patients (59.9% male) with an average age of 41.54 years (SD: 13.37) were evaluated, and 156 cases (65.8%) were proved to have renal stone. The mean (SD) STONE scores in the groups of patients with renal stone and in the group of patients without renal stone group were 9.1 (2.6) and 6.0 ( 2.8), respectively (p < 0.001). The area under the curve (AUC) for the STONE score was 0.789 (95% confidence interval (CI) 0.725 to 0.852). The optimum threshold value of the STONE score for the diagnosis of a renal stone was 8 or more, which had a sensitivity of 75.0% and a specificity of 70.4%.

Conclusion: Despite the acceptable diagnostic accuracy, further modifications and enhancements of the STONE score are needed to differentiate patients with low risk prior to imaging.