International Journal of Cardiovascular Sciences. 21/Mar/2024;37:e20230198.

Editorial

Risk Stratification in Patients Hospitalized With Infective Endocarditis Undergoing Cardiac Surgery: How Sharp Are We?

DOI: 10.36660/ijcs.20230198

This Editorial is referred by the Research article "Analysis of the SHARPEN Score in the Prediction of In-Hospital Mortality of Patients With Infective Endocarditis Undergoing Cardiac Surgery".

Infective endocarditis (IE) is an infrequent yet life-threatening and disabling condition, with an estimated incidence between 3 and 12 cases per 100,000 subjects per year.^, Recent epidemiological studies have suggested a rising trend in the incidence of IE, potentially attributable to factors such as an aging population and a growing group of susceptible patients with congenital heart disease, intracardiac prosthesis or devices, and chronic renal failure on dialysis. Limited information is available concerning Brazil’s temporal trends on IE incidence and clinical outcomes. The primary source of evidence regarding the IE scenario in Brazil stems from single or multicenter observational studies.^– Analyzing available data, it appears that IE predominantly affects younger male patients in Brazil. The most prevalent microbial culprits are Staphylococcus, followed by Enterococcus and Streptococcus species; rheumatic heart disease is an important underlying heart condition as well.

The diverse clinical spectrum of IE, coupled with the substantial risk of complications and the limited availability of randomized clinical trials on IE, justify that it continues to be a prognostic challenge. Despite the unquestionable diagnostic and therapeutic advances in the management of IE in recent decades, its prognosis is still marked by high rates of complications and significant in-hospital mortality. In developed countries, IE is associated with mortality rates of approximately 20%,^,, whereas in low- and middle-income countries, the mortality of IE ranges from 15% to 30%. The predominant focus in studies on IE has been the evaluation of clinical factors that may influence the course of the disease. In one of these studies, a machine learning-based analysis identified peripheral stigmata, nosocomial IE, the absence of vegetation, and surgery in the presence of neurologic complications as characteristics associated with higher in-hospital mortality.