UTI (urinary tract infection) risk factors and microbiological profile in patients with COVID-19 interned in the HC-UNICAMP

• Grant number: 22/02411-7
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: May 01, 2022
• End date: April 30, 2023
• Field of knowledge: Health Sciences - Medicine - Surgery
• Principal Investigator: Cássio Luís Zanettini Riccetto
• Grantee: Caio di Donato Ribeiro
• Host Institution: Hospital de Clínicas (HC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

COVID-19 is a new disease that originated in Wuhan (China) and quickly became a pandemic in 2020. The first case of COVID-19 in Brazil was found in February 2020, and until November 2021 there were 21,939,196 confirmed cases with 610,491 deaths. Bacterial co-infections associated with hospitalized patients with COVID-19 have an incidence of 7% in hospitalized patients, increasing to 14% in ICU patients. Among non-respiratory coinfections, urinary tract infection (UTI) is identified as the most common, affecting up to 3% of patients hospitalized for COVID. Objectives: Identify risk factors for UTI in patients with COVID-19 admitted to the Hospital de Clínicas of UNICAMP and, as a secondary objective, describe the microbiological profile of UTIs associated with the infection by COVID-19. Methods: In the present study, with a retrospective cohort design, the medical records of the AGHUSE system of all patients hospitalized between March 2020 and August 2021 at the Hospital de Clínicas of UNICAMP diagnosed with COVID-19 by a positive PCR sample who had a urine sample collected will be analyzed. The independent variable will be the result of the urine culture and the dependent variables studied will be: age, sex, presence of comorbidities, leukopenia, need for ICU admission, orotracheal intubation, indwelling bladder catheterization, number of days of hospitalization, severity, outcome and microbial species detected in urine culture (if positive). Descriptive statistics of the data and linear and logistic regression analysis will be carried out from models determined by the researchers, in order to determine risk factors for UTI in the studied population.(AU)