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Bayesian comparative assessment of diagnostic accuracy of low-dose CT scan and ultrasonography in the diagnosis of urolithiasis after the application of the STONE score

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Abstract

Objective

The objective of our study was to assess the diagnostic quality of low-dose computed tomography (CT) when compared to ultrasound (US) in diagnosis of urolithiasis using STONE score as a predictor of pre-test probability and the Bayesian statistical model to calculate post-test probabilities (POST) for both diagnostic tests.

Methods

STONE score was used to form risk groups to obtain pre-test probabilities. Likelihood ratios (LR) were calculated from external data for low-dose CT and US. POST were obtained using pre-test probabilities and likelihood ratios with Bayesian nomogram. Absolute (ADG) and relative (RDG) gains in diagnostic value were calculated.

Results

Calculated +LR for US was 12 and −LR was 0.32; for CT, +LR was 19 and −LR 0.04. +LR and low STONE for US yielded POST 57% and RDG 470%; intermediate STONE POST 92% and RDG 84%; and high STONE POST 99% and RDG 10%. −LR and low STONE for US POST 3% and RDG −70%; intermediate POST 24% and RDG −52%; and high STONE POST 74% and RDG −17.7%. +LR and low STONE for CT POST 68% and RDG 580%; moderate STONE POST 95% and RDG 90%; and high STONE POST 99% and RDG 10%. −LR and low STONE for CT POST 0% and RDG −100%; intermediate POST 4% and RDG −92%; and high STONE POST 26% and RDG −71.1%. ANOVA calculations comparing CT vs US for +LR showed no statistical significance (P value = 0.9893; LR− P value = 0.5488).

Conclusion

Bayesian statistical analysis demonstrated slight superiority of CT scan over US on STONE score low- and moderate-risk stratified subtypes, whereas no significant advantage was seen when evaluating high-probability patients.

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References

  1. Dalrymple NC, Verga M, Anderson KR, Bove P, Covey AM, Rosenfield AT, Smith RC (1998) The value of unenhanced helical computerized tomography in the management of acute flank pain. J Urol 159(3):735–740

    Article  CAS  PubMed  Google Scholar 

  2. Sheafor DH, Hertzberg BS, Freed KS, Carroll BA, Keogan MT, Paulson EK, DeLong DM, Nelson RC (2000) Nonenhanced helical CT and US in the emergency evaluation of patients with renal colic: prospective comparison. Radiology 217(3):792–797. doi:10.1148/radiology.217.3.r00dc41792

    Article  CAS  PubMed  Google Scholar 

  3. Vieweg J, Teh C, Freed K, Leder RA, Smith RH, Nelson RH, Preminger GM (1998) Unenhanced helical computerized tomography for the evaluation of patients with acute flank pain. J Urol 160(3 Pt 1):679–684

    Article  CAS  PubMed  Google Scholar 

  4. Coursey CA, Casalino DD, Remer EM, Arellano RS, Bishoff JT, Dighe M, Fulgham P, Goldfarb S, Israel GM, Lazarus E, Leyendecker JR, Majd M, Nikolaidis P, Papanicolaou N, Prasad S, Ramchandani P, Sheth S, Vikram R (2012) ACR appropriateness criteria (R) acute onset flank pain—suspicion of stone disease. Ultrasound quarterly 28(3):227–233. doi:10.1097/RUQ.0b013e3182625974

    Article  PubMed  Google Scholar 

  5. Fulgham PF, Assimos DG, Pearle MS, Preminger GM (2013) Clinical effectiveness protocols for imaging in the management of ureteral calculous disease: AUA technology assessment. J Urol 189(4):1203–1213. doi:10.1016/j.juro.2012.10.031

    Article  PubMed  Google Scholar 

  6. Turk C, Petrik A, Sarica K, Seitz C, Skolarikos A, Straub M, Knoll T (2016) EAU guidelines on diagnosis and conservative management of urolithiasis. Eur Urol 69(3):468–474. doi:10.1016/j.eururo.2015.07.040

    Article  PubMed  Google Scholar 

  7. Ferraro PM, Curhan GC, D’Addessi A, Gambaro G (2016) Risk of recurrence of idiopathic calcium kidney stones: analysis of data from the literature. Journal of nephrology. doi:10.1007/s40620-016-0283-8

    PubMed Central  Google Scholar 

  8. Broder J, Bowen J, Lohr J, Babcock A, Yoon J (2007) Cumulative CT exposures in emergency department patients evaluated for suspected renal colic. The Journal of emergency medicine 33(2):161–168. doi:10.1016/j.jemermed.2006.12.035

    Article  PubMed  Google Scholar 

  9. National Research Council Committee on Health Effects of Exposure to Low Levels of Ionizing R (1998). In: Health effects of exposure to low levels of ionizing radiations: time for reassessment? National Academies Press (US), Washington (DC). doi:10.17226/6230

  10. Ray AA, Ghiculete D, Pace KT, Honey RJ (2010) Limitations to ultrasound in the detection and measurement of urinary tract calculi. Urology 76(2):295–300. doi:10.1016/j.urology.2009.12.015

    Article  PubMed  Google Scholar 

  11. Ulusan S, Koc Z, Tokmak N (2007) Accuracy of sonography for detecting renal stone: comparison with CT. Journal of clinical ultrasound : JCU 35(5):256–261. doi:10.1002/jcu.20347

    Article  PubMed  Google Scholar 

  12. Gottlieb RH, La TC, Erturk EN, Sotack JL, Voci SL, Holloway RG, Syed L, Mikityansky I, Tirkes AT, Elmarzouky R, Zwemer FL, Joseph JV, Davis D, DiGrazio WJ, Messing EM (2002) CT in detecting urinary tract calculi: influence on patient imaging and clinical outcomes. Radiology 225(2):441–449. doi:10.1148/radiol.2252020101

    Article  PubMed  Google Scholar 

  13. Westphalen AC, Hsia RY, Maselli JH, Wang R, Gonzales R (2011) Radiological imaging of patients with suspected urinary tract stones: national trends, diagnoses, and predictors. Acad Emerg Med Off J Soc Acad Emerg Med 18(7):699–707. doi:10.1111/j.1553-2712.2011.01103.x

    Article  Google Scholar 

  14. Passerotti C, Chow JS, Silva A, Schoettler CL, Rosoklija I, Perez-Rossello J, Cendron M, Cilento BG, Lee RS, Nelson CP, Estrada CR, Bauer SB, Borer JG, Diamond DA, Retik AB, Nguyen HT (2009) Ultrasound versus computerized tomography for evaluating urolithiasis. J Urol 182(4 Suppl):1829–1834. doi:10.1016/j.juro.2009.03.072

    Article  PubMed  Google Scholar 

  15. Moore CL, Bomann S, Daniels B, Luty S, Molinaro A, Singh D, Gross CP (2014) Derivation and validation of a clinical prediction rule for uncomplicated ureteral stone—the STONE score: retrospective and prospective observational cohort studies. BMJ (Clinical research ed) 348:g2191. doi:10.1136/bmj.g2191

    Google Scholar 

  16. Baez AA, Cochon L (2016) Acute Care Diagnostics Collaboration: assessment of a Bayesian clinical decision model integrating the prehospital sepsis score and point-of-care lactate. Am J Emerg Med 34(2):193–196. doi:10.1016/j.ajem.2015.10.007

    Article  PubMed  Google Scholar 

  17. Baez AA, Esin J, Cochon L Bayesian comparative model of CT scan and ultrasonography in the assessment of acute appendicitis: results from the ACDC project. The American journal of emergency medicine. doi:10.1016/j.ajem.2016.07.012

  18. Baez AA, Cochon L 133 Improved rule-out diagnostic gain with a combined aortic dissection detection risk score and D-dimer Bayesian decision support scheme. Annals of emergency medicine 64 (4):S48. doi:10.1016/j.annemergmed.2014.07.159

  19. Cochon L, Baez AA, Ovalle A 59 Bayesian model for comparative assessment of lactate and procalcitonin using CURB 65 risk score as predictor for ICU admission. Annals of emergency medicine 64 (4):S21-S22. doi:10.1016/j.annemergmed.2014.07.084

  20. Cochon L, Peña M, Baez A Evidence of incremental diagnostic quality gain in the assessment of pulmonary embolism with computed tomography angiography versus ventilation perfusion scan using Wells score and Bayesian statistical modeling. Annals of emergency medicine 62 (4):S38. doi:10.1016/j.annemergmed.2013.07.384

  21. Niemann T, Kollmann T, Bongartz G (2008) Diagnostic performance of low-dose CT for the detection of urolithiasis: a meta-analysis. AJR Am J Roentgenol 191(2):396–401. doi:10.2214/ajr.07.3414

    Article  PubMed  Google Scholar 

  22. DerSimonian R, Laird N (1986) Meta-analysis in clinical trials. Control Clin Trials 7(3):177–188

    Article  CAS  PubMed  Google Scholar 

  23. Kanno T, Kubota M, Sakamoto H, Nishiyama R, Okada T, Higashi Y, Yamada H (2014) The efficacy of ultrasonography for the detection of renal stone. Urology 84(2):285–288. doi:10.1016/j.urology.2014.04.010

    Article  PubMed  Google Scholar 

  24. Fagan TJ (1975) Letter: nomogram for Bayes theorem. N Engl J Med 293(5):257. doi:10.1056/nejm197507312930513

    CAS  PubMed  Google Scholar 

  25. Papa L, Stiell IG, Wells GA, Ball I, Battram E, Mahoney JE (2005) Predicting intervention in renal colic patients after emergency department evaluation. Cjem 7(2):78–86

    Article  PubMed  Google Scholar 

  26. Prina LD, Rancatore E, Secic M, Weber RE (2002) Comparison of stone size and response to analgesic treatment in predicting outcome of patients with renal colic. European journal of emergency medicine : official journal of the European Society for Emergency Medicine 9(2):135–139

    Article  CAS  Google Scholar 

  27. Fowler KA, Locken JA, Duchesne JH, Williamson MR (2002) US for detecting renal calculi with nonenhanced CT as a reference standard. Radiology 222(1):109–113. doi:10.1148/radiol.2221010453

    Article  PubMed  Google Scholar 

  28. Sidhu R, Bhatt S, Dogra VS (2008) Renal colic. Ultrasound Clinics 3(1):159–170

    Article  Google Scholar 

  29. Chen TT, Wang C, Ferrandino MN, Scales CD, Yoshizumi TT, Preminger GM, Lipkin ME (2015) Radiation exposure during the evaluation and management of nephrolithiasis. J Urol 194(4):878–885. doi:10.1016/j.juro.2015.04.118

    Article  PubMed  Google Scholar 

  30. Uribarri J, Oh MS, Carroll HJ (1989) The first kidney stone. Ann Intern Med 111(12):1006–1009

    Article  CAS  PubMed  Google Scholar 

  31. Pearle MS, Calhoun EA, Curhan GC (2005) Urologic diseases in America project: urolithiasis. J Urol 173(3):848–857. doi:10.1097/01.ju.0000152082.14384.d7

    Article  PubMed  Google Scholar 

  32. Antonelli JA, Maalouf NM, Pearle MS, Lotan Y (2014) Use of the National Health and Nutrition Examination Survey to calculate the impact of obesity and diabetes on cost and prevalence of urolithiasis in 2030. Eur Urol 66(4):724–729. doi:10.1016/j.eururo.2014.06.036

    Article  PubMed  PubMed Central  Google Scholar 

  33. Medow MA, Lucey CR (2011) A qualitative approach to Bayes’ theorem. Evidence-based medicine 16(6):163–167. doi:10.1136/ebm-2011-0007

    Article  PubMed  Google Scholar 

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Authors and Affiliations

  1. Universitat de Barcelona, Barcelona, Spain

    Laila Cochon

  2. Miller School of Medicine, University of Miami, Miami, FL, USA

    Jeffrey Smith

  3. Department of Emergency Medicine, Jackson Memorial Hospital, Miami, FL, USA

    Amado Alejandro Baez

Authors
  1. Laila Cochon
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  2. Jeffrey Smith
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  3. Amado Alejandro Baez
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Corresponding author

Correspondence to Laila Cochon.

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Appendix

Appendix

Table 1 Values of sensitivity, specificity, and likelihood ratios for ultrasound and low-dose CT in detecting urolithiasis
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Table 2 Post-test probabilities and diagnostic gains based on positive ultrasound result in detection of urolithiasis
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Table 3 Post-test probabilities and diagnostic gains based on negative ultrasound result in detection of urolithiasis
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Table 4 Post-test probabilities and diagnostic gains based on positive CT result in detection of urolithiasis
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Table 5 Post-test probabilities and diagnostic gains based on negative CT result in detection of urolithiasis
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Cochon, L., Smith, J. & Baez, A.A. Bayesian comparative assessment of diagnostic accuracy of low-dose CT scan and ultrasonography in the diagnosis of urolithiasis after the application of the STONE score. Emerg Radiol 24, 177–182 (2017). https://doi.org/10.1007/s10140-016-1471-5

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