An integral part of IDOR since its foundation, the intensive care area focuses on five main research lines: sepsis; evaluation of multidrug resistance of bacteria and other pathogens; cancer patients and intensive care; neurology and intensive care; quality and efficiency in intensive care.

Sepsis or generalized infection is one of the main challenges faced in intensive care units and, in Brazil, is responsible for high mortality rates. For this reason, IDOR scientists dedicate themselves to studying the relationship between sepsis and patients’ general health, investigating which comorbidities can increase the risk of death from generalized infection, and how to manage this risk. Bacterial resistance is another hot topic, as it is a growing public health challenge, impacting the outcome of already fragile patients in ICUs. IDOR scientists are investigating the problem by analyzing hospital records of antibiotic prescriptions and dispensing, combined with microbiology data.

The third line of research, linked to the care of cancer patients in ICUs, analyzed information from more than 30,000 patients, which enabled scientists to observe, among other things, that the outcomes of these patients have improved substantially in recent years: for patients with different types of cancer, there was a progressive reduction in mortality.

In the area of neurology and intensive care, one of the main objects of research is delirium, the acute and severe brain dysfunction that affects patients in ICUs. Since 2008, the IDOR team has been studying the problem and developing predictive models with the help of artificial intelligence to identify patients at greater risk of the condition.

Finally, the fifth line of research, which aims to evaluate care in intensive care services and propose strategies for improving their quality, uses large amounts of data obtained from RDSL hospitals and partner institutions to assess how certain interventions – for example, protocols for treating frequent conditions such as respiratory failure, or for preventing complications such as hospital-acquired infections – can change patient outcomes. Using information on 330,000 patients from around 100 hospitals, the researchers are developing predictive models capable of identifying high-risk patients or helping to reorganize ICU structures, intending to increase the efficiency of these services.