Portal de Periódicos da CAPES

Initial Experience and Evaluation of a Nomogram for Outcome Prediction in Management of Medium-sized (1–2 cm) Kidney Stones

2021; Elsevier BV; Volume: 8; Issue: 1 Linguagem: Inglês

10.1016/j.euf.2020.12.012

2405-4569

Salvatore Micali, Maria Chiara Sighinolfi, A. Iseppi, Elena Morini, Tommaso Calcagnile, Mattia Benedetti, M. Ticonosco, Shaniko Kaleci, Luigi Bevilacqua, Stefano Puliatti, Cosimo De Nunzio, Raphael B. Arada, Francesco Chiancone, Davide Campobasso, Ahmed Eissa, Giulia Bonfante, Elisa Simonetti, Michele Cotugno, Riccardo Galli, Pierpaolo Curti, Luigi Schips, Pasquale Ditonno, Luca Villa, Stefania Ferretti, F. Bergamaschi, Giorgio Bozzini, Ahmed Zoeir, Ahmed El Sherbiny, Antonio Frattini, Paolo Fedelini, Zhamshid Okhunov, Andrea Tubaro, Jaime Landman, Giampaolo Bianchi, Bernardo Rocco,

Paleopathology and ancient diseases

Background The gold standard treatment for solitary medium-sized (1–2 cm) renal stones is not defined by recent guidelines, since management modalities including shockwave lithotripsy (SWL), retrograde intrarenal surgery (RIRS), and percutaneous nephrolithotomy (PNL) are recommended. Improved ability to predict patient outcomes would aid in patients' counseling and decision-making. Objective To develop a nomogram predicting treatment failure, based on preoperative clinical variables, to be used in the preplanning setting. Design, setting, and participants We recruited 2605 patients from 14 centers and carried out a multicenter retrospective analysis of 699 SWL, 1290 RIRS, and 616 PN L procedures performed as first-line treatment for 1–2-cm kidney stones. The variables evaluated included age, gender, previous renal surgery, body mass index, stone size, location, stone density, skin-to-stone distance, presence of urinary tract infections (UTIs), and hydronephrosis. Outcome measurements and statistical analysis Multivariate logistic regression was fitted to predict treatment failure, defined as the presence of residual fragments >4 mm. A nomogram was developed based on the coefficients of the logit function. Results and limitations A total of 2431 (93.3%) patients were stone free; 174 (6.7%) treatment failures were recorded and considered the event to be predicted. On univariate analysis, type of procedure, preoperative hydronephrosis, stone density, stone location, and laterality turned out to be statistically significant. Skin-to-stone distance, UTIs, and previous renal surgery were predictors of failure on multivariate analysis. Each variable was given a score based on statistical relevance. The main limitation of the current study is its retrospective nature. Conclusions This nomogram provides a prediction of treatment failure and need of reintervention for medium-sized kidney stones. External validation is needed to determine its reproducibility and validity. Patient summary We developed a preoperative model of treatment outcomes for 1–2-cm kidney stones. Its application may assist urologists to counsel patients with regard to stone management modality.