The first prospective assessment of S.T.O.N.E, Guy, CROES, S-RESC nomograms in the prediction of percutaneous nephrolithotomy outcomes
the 35th Annual EAU Congress Amsterdam (EAU20) • 2019
معلومات البحث
المؤلفون
Ahmed M. Al Adl, MD, MSc, PhD; Ahmed Mohey, MD, MSc, PhD; Ashraf Abdel Aal, MD, MSc, PhD; Hosam Abdel Fattah Abu-Elnasr, MD, MSc; Tarek El Karamany, MD, MSc, PhD; Yasser A. Noureldin, MD, MSc, PhD
الكلمات المفتاحية
kidney; urolithiasis; percutaneous nephrolithotomy, nomograms; Outcome.
المجلة العلمية
the 35th Annual EAU Congress Amsterdam (EAU20)
الناشر
European Urology Supplement
المجلد
Not Available
العدد
Not Available
الصفحات
Not Available
publication.type
International
رابط البحث
Not Available
المواد المرفقة
Not Available
الملخص
Introduction & Objectives To compare the clinical applicability and the time to calculate the famous four scoring systems used to predict the outcome of percutaneous nephrolithotomy (PCNL); S.T.O.N.E. Nephrolithometry (STONE), Guy’s Stone Score (GSS), Clinical Research Office of the Endourological Society Nephrolithometric Nomogram (CROES) and Seoul National University Renal Stone Complexity (S-ReSC).
Materials & Methods In this prospective study, patients undergoing PCNL between 2015 and 2018 were included after obtaining Institutional Ethics Committee approval and informed consents. The four scoring systems were calculated and correlated with the stone free status (SFS), postoperative complications, operative time (OT), fluoroscopy time (FT), estimated blood loss (EBL), and length of hospital stay (LOS). Regression analysis and ROC curves were performed to find out which is the best to predict outcomes and the fastest to calculate.
Results: In all, 162 PCNLs were accomplished. Overall SFS was 75.9% and the complication rate was 30.9%. The mean acquisition time (s) of scores revealed that the GSS had significantly lower time (52.9±0.5 sec) when compared to STONE (105.1±0.3 sec), CROES (224±3.1 sec) and S-ReSC score (102.6±3.5 sec). The four scores had comparable predictive accuracy for detection of SFS in ROC curves. The best correlation for SFS was recorded with CROES grade, and the best association with complications, using Clavien grade, was found with STONE score. Furthermore, the best association with EBL and OT was observed with S-ReSC score, and the best correlation with FT discovered with GSS. However, univariate analysis revealed that essence of stone and tract length are insignificantly different in cases with residual stones. The other potential factors were entered in regression analysis and the significant predictors were basically the number of involved calyces which had significant negative impact (OR: 0.1366 [0.068-0.270], p value
Materials & Methods In this prospective study, patients undergoing PCNL between 2015 and 2018 were included after obtaining Institutional Ethics Committee approval and informed consents. The four scoring systems were calculated and correlated with the stone free status (SFS), postoperative complications, operative time (OT), fluoroscopy time (FT), estimated blood loss (EBL), and length of hospital stay (LOS). Regression analysis and ROC curves were performed to find out which is the best to predict outcomes and the fastest to calculate.
Results: In all, 162 PCNLs were accomplished. Overall SFS was 75.9% and the complication rate was 30.9%. The mean acquisition time (s) of scores revealed that the GSS had significantly lower time (52.9±0.5 sec) when compared to STONE (105.1±0.3 sec), CROES (224±3.1 sec) and S-ReSC score (102.6±3.5 sec). The four scores had comparable predictive accuracy for detection of SFS in ROC curves. The best correlation for SFS was recorded with CROES grade, and the best association with complications, using Clavien grade, was found with STONE score. Furthermore, the best association with EBL and OT was observed with S-ReSC score, and the best correlation with FT discovered with GSS. However, univariate analysis revealed that essence of stone and tract length are insignificantly different in cases with residual stones. The other potential factors were entered in regression analysis and the significant predictors were basically the number of involved calyces which had significant negative impact (OR: 0.1366 [0.068-0.270], p value
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