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Article Abstract
Introduction: Currently, percutaneous nephrolithotomy (PCNL) is a first-line treatment method for large and staghorn kidney stones. Predicting the efficiency of the performed surgical procedure is relevant at the stage of preoperative counseling of patients.
Aim: To develop a universal nomogram for predicting the efficiency of mini-PCNL taking into account the baseline characteristics and features of the patient.
Materials And Methods: A total of 251 patients with kidney stones who underwent mini-PCNL in the prone position according to the standard method through a single access were included in the study. The preoperative characteristics of patients and their impact on the outcome were evaluated. An achievement of the stone-free rate (SFR) was assessed by the computed tomography (CT).
Results: The analysis revealed factors significantly influencing the achievement of the SFR, such as stone volume >1.39 cm3 (p=0.001), stone area >189.03 mm2 (p=0.001), distance from the lowest point of the Th12 to the lower part of the lower pole calyx (T12-LP) <85.81 mm (p=0.050), distances from the lower calyx to the most cranial part of the iliac crest (ICLP) >49.1 mm (p=0.029), stone size >18.2 mm (p=0.001), number of involved calyxes >3 (p=0.001), number of involved calyxes for staghorn stones >4 (p=0.001), and staghorn stone (p=0.001). Correlation, logistic regression, and ROC analysis were performed for these factors. The area under the curve (AUC) was 0.897. A nomogram has been developed. The sensitivity of the model is 94.4%, specificity is 59.2%, and overall accuracy is 84.4%. A certificate of state registration of a computer program in the IBM SPSS Statistics syntax language "A model for predicting the SFR of mini-PCNL in patients with kidney stones" was obtained.
Conclusion: The nomogram developed on the basis of our data showed a high predictive ability in relation to the SFR with sensitivity of 94%. This nomogram is easy to use and interpret, which makes it convenient for routine practice, however, external validation is necessary to objectify the predictive ability.
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