Risk factors for healthcare-associated infections and their relationship with waves of the COVID-19 pandemic in an intensive care unit: a nested case-control study.

Objective: To evaluate the risk factors for healthcare-related infections during the COVID-19 pandemic in intensive care units, to investigate the impact of COVID-19 on Central Line-Associated Bloodstream Infection, Catheter-Associated Urinary Tract Infection, and ventilator-associated pneumonia, and to describe healthcare-associated infections in the waves of the COVID-19 pandemic.

Methods: This nested case-control study was conducted in a 137-bed adult medical/surgical intensive care unit at a private hospital in São Paulo, Brazil, between January 11, 2019, and May 21, 2022. Case patients were identified using the Nosocomial Infection Control Committee database and control patients were identified using the intensive care unit's EPIMED system.

Cost analysis of endovascular treatment for unruptured intracranial aneurysms at a private hospital in Brazil.

Background: Intracranial aneurysms have a prevalence of 1-6% and significant rupture risks, leading to high morbidity and mortality. Endovascular therapy demands an understanding of its economic impacts. This study evaluates the costs and complications of unruptured intracranial aneurysm treatment in a private Latin American hospital.

Patient-level cost analysis of intensive care unit acquired infections: A prospective cohort study.

Introduction: Hospital-associated infections (HAIs) are associated with increased mortality and prolonged hospital length-of-stay (LOS). Although some studies have shown that HAIs are associated with increased costs, these studies only used cost estimates, were carried out in a small number of centres, or only in high-income countries.

Methods: We carried out a prospective cohort study in ten Brazilian intensive care units (ICUs) selected from a collaborative platform study (IMPACTO MR).

Is it possible to estimate the number of patients with COVID-19 admitted to intensive care units and general wards using clinical and telemedicine data?

Background: Gabaldi et al. utilized telemedicine data, web search trends, hospitalized patient characteristics, and resource usage data to estimate bed occupancy during the COVID-19 pandemic. The results showcase the potential of data-driven strategies to enhance resource allocation decisions for an effective pandemic response.