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Computed Tomography-Based Novel Prediction Model for the Outcome of Shockwave Lithotripsy in Proximal Ureteral Stones

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dc.contributor.authorPark, Hong Seok-
dc.contributor.authorGong, Mi Kyung-
dc.contributor.authorYoon, Cheol Yong-
dc.contributor.authorMoon, Du Geon-
dc.contributor.authorCheon, Jun-
dc.contributor.authorChoi, Young Deuk-
dc.date.accessioned2021-09-03T22:13:01Z-
dc.date.available2021-09-03T22:13:01Z-
dc.date.created2021-06-18-
dc.date.issued2016-07-
dc.identifier.issn0892-7790-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/88122-
dc.description.abstractIntroduction and Objectives: Computed tomography (CT) is one of the most commonly used diagnostic modalities for urinary stone disease. In this study we developed a CT and clinical parameter-based prediction model for shockwave lithotripsy (SWL) outcome in proximal ureteral stones. Materials and Methods: Data from 223 patients with single proximal ureteral stones treated with SWL between January 2009 and January 2015 were reviewed retrospectively. Clinical parameters including age, sex, bodyweight, and bodymass index (BMI) were analyzed in combinationwith stone-related CTparameters (stone diameter, height, volume, location, Hounsfield units [HU], stone-to-skin distance [SSD]), and secondary signs (hydronephrosis, perinephric edema, and rim sign). Based on the cutoff values determined by c-statistics, a scoring system for the prediction of SWL outcome was developed. Results: The success rate was 65.9% (147/223), and in a univariate analysis body weight, BMI, SSD (vertical, horizontal), HU, stone diameter, height, volume, and all secondary signs were significantly associatedwith the success of SWL. However, on multivariate analysis only BMI (odds ratio [OR] = 1.322, confidence interval [CI] 1.156, 1.512, p = 0.00), stone diameter (OR= 1.397, CI 1.259, 1.551, p = 0.00), and perinephric edema (grade 0-1 vs 3-4, OR= 2.831, CI 1.032, 7.764, p = 0.043) were independent predictors of SWL success. The prediction model based on the logistic regression analysis was as follows: SWL success = 1/[1 + exp (-10.165 + 0.279x[BMI] + 0.334x[diameter] + 1.040 [perinephric edema])], having an area under the curve of 0.881. In the predictionmodel based on these parameters, scores of 0, 1, 2, and 3 correlated with SWLsuccess rates of 98.5%, 65.7%, 31.4%, and 0%, respectively. Conclusions: BMI, stone diameter, and perinephric edema were independent predictors of SWL outcome and a prediction model based on these parameters will facilitate decision-making for SWL in proximal ureteral stones.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherMARY ANN LIEBERT, INC-
dc.subjectWAVE LITHOTRIPSY-
dc.subjectMULTIVARIATE-ANALYSIS-
dc.subjectATTENUATION VALUE-
dc.subjectURINARY CALCULI-
dc.subjectDISTANCE-
dc.subjectSUCCESS-
dc.subjectFRAGMENTATION-
dc.subjectDENSITY-
dc.subjectPATIENT-
dc.subjectTRIAL-
dc.titleComputed Tomography-Based Novel Prediction Model for the Outcome of Shockwave Lithotripsy in Proximal Ureteral Stones-
dc.typeArticle-
dc.contributor.affiliatedAuthorPark, Hong Seok-
dc.contributor.affiliatedAuthorMoon, Du Geon-
dc.contributor.affiliatedAuthorCheon, Jun-
dc.identifier.doi10.1089/end.2016.0056-
dc.identifier.scopusid2-s2.0-84978786174-
dc.identifier.wosid000380139600013-
dc.identifier.bibliographicCitationJOURNAL OF ENDOUROLOGY, v.30, no.7-
dc.relation.isPartOfJOURNAL OF ENDOUROLOGY-
dc.citation.titleJOURNAL OF ENDOUROLOGY-
dc.citation.volume30-
dc.citation.number7-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaUrology & Nephrology-
dc.relation.journalWebOfScienceCategoryUrology & Nephrology-
dc.subject.keywordPlusWAVE LITHOTRIPSY-
dc.subject.keywordPlusMULTIVARIATE-ANALYSIS-
dc.subject.keywordPlusATTENUATION VALUE-
dc.subject.keywordPlusURINARY CALCULI-
dc.subject.keywordPlusDISTANCE-
dc.subject.keywordPlusSUCCESS-
dc.subject.keywordPlusFRAGMENTATION-
dc.subject.keywordPlusDENSITY-
dc.subject.keywordPlusPATIENT-
dc.subject.keywordPlusTRIAL-
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