Percutaneous nephrolithotripsy in high-risk patients

• Grant number: 15/21843-1
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: June 01, 2016
• End date: May 31, 2017
• Field of knowledge: Health Sciences - Medicine - Surgery
• Principal Investigator: Fábio César Miranda Torricelli
• Grantee: Guilherme Kazuo Marchi Ogawa
• Host Institution: Faculdade de Medicina (FM). Universidade de São Paulo (USP). São Paulo , SP, Brazil

Abstract

Percutaneous nephrolithotripsy (PN) is the treatment of choice for patients with stones larger than 2.0 cm, but a number of complications inherent to the procedure may occur. Due to its potential morbidity, the NLP in high surgical risk patients (immunosuppressed and the elderly) is always a challenging surgery.Objective: To evaluate the safety of NLP (complication rate) in immunocompromised patients and the elderly served by the Division of Urology at the Hospital das Clinicas, Faculty of Medicine, University of São Paulo (HC-FMUSP) between January 2007 and December 2014 .Patients and methods: It will be developed a retrospective study of case-control design, using as variables for pairing the guy's score (evaluates the complexity of the calculation), the age and body mass index (BMI) of patients. Of interest data will be: age, sex, BMI, comorbidities, in use medications, prior surgeries, size calculation, Guy's score, patient's position on the operating table (supine versus prone), fee-free patients calculations, volume Bleeding estimated by the change in hemoglobin and hematocrit levels, rate of blood transfusion, complication rate, nephrostomy time and hospital stay.Result analysis: univariate analysis will be performed with the Student's t test or Mann-Whitney test for continuous variables and chi-square and Fisher for categorical variables. Will be compared between groups: age, sex, BMI, Guy's score, position on the operating table, fee-free patients calculations, volume of blood loss, rate of blood transfusion, complication rate, nephrostomy time and length of stay hospital. After univariate analysis, a multivariate analysis (logistic regression) will be held to analyze which variables influence the rate of complications.