Studies focused on the clinical profile of native valve endocarditis are scarce and outdated. In addition, none of them analyzed differences depending on the causative microorganism. Our objectives are to describe the clinical profile at admission of patients with left-sided native valve infective endocarditis in a contemporary wide series of patients and to compare them among the most frequent etiologies. To do so, we conducted a prospective, observational cohort study including 569 patients with native left-sided endocarditis enrolled from 2006 to 2019. We describe the modes of presentation and the symptoms and signs at admission of these patients and compare them among the five more frequent microbiological etiologies. Coagulase-negative Staphylococci and Enterococci endocarditis patients were the oldest (71 ± 11 years), and episodes caused by Streptococci viridans were less frequently nosocomial (4%). The neurologic, cutaneous or renal modes of presentation were more typical in Staphylococcus aureus endocarditis (28%, p = 0.002), the wasting syndrome of Streptococcus viridans (49%, p < 0.001), and the cardiac in Coagulase-negative Staphylococci, Enterococci and unidentified microorganism endocarditis (45%, 49% and 56%, p < 0.001). The clinical signs agreed with the mode of presentation. In conclusion, the modes of presentation and the clinical picture at admission were tightly associated with the causative microorganism in patients with left-sided native valve endocarditis.

The CHA₂DS₂-VASc score is widely used to predict thromboembolic events in non-valvular atrial fibrillation (AF) and has also been linked to adverse outcomes in diverse clinical contexts. The latest published European Guidelines on AF recommend the simplified CHA₂DS₂-VA score. Embolic events (EEs) develop in up to 50% of patients with left-sided infective endocarditis (LSIE). Although several variables have been associated with in-hospital mortality and EEs, no standardized risk stratification tool is currently applied in daily practice. Therefore, we sought to assess the prognostic value of the CHA₂DS₂-VA score at admission for predicting both in-hospital mortality and EEs in LSIE. This study included a total of 1420 episodes of definite LSIE diagnosed across three tertiary centers. The CHA₂DS₂-VA score was calculated on admission for all patients. Only cases of clinical EEs occurring in the context of LSIE diagnosis and confirmed by imaging techniques were considered. In-hospital mortality was 28.8% with a stepwise increase according to the CHA₂DS₂-VA score (p < 0.001), regardless of AF history. Multivariable analysis identified this score as an independent predictor of mortality (OR 1.195: 95% CI 1.106–1.291). During hospitalization, 27.5% of patients experienced EEs, but no significant association was observed with the CHA₂DS₂-VA score (p = 0.753). In conclusion, the CHA₂DS₂-VA score emerges as a simple and widely available tool to identify LSIE patients at increased risk of in-hospital mortality, although it does not predict EEs.

Background/Objectives: Vegetation length is a guideline-endorsed criterion for surgery in left-sided infective endocarditis (LSIE). However, its measurement is highly variable with crucial implications for decision making. A standardized measurement system would not only facilitate decision making in these patients, but also cutoff-point optimization for improving clinical guidelines. For this purpose, this work introduces an Artificial Intelligence (AI)-based system capable of extracting vegetation length from standard transesophageal echocardiography (TEE). Methods: Five echocardiographers independently measured the vegetation length of 76 vegetations from 67 consecutive patients with LSIE using offline TEE images. The AI-based system was trained on a multicenter registry with 353 patients with LSIE, comprising 282,096 echocardiographic frames annotated by an independent expert. This system was applied to measure vegetation length as an independent observer. The variability and correlation between operators and the system were assessed. Results: Lin’s concordance correlation coefficient between the AI-based system and the mean of the measurements obtained by the echocardiographers was 0.74, comparable to the coefficient obtained between the echocardiographers themselves. Bland–Altman analysis showed a mean difference of −1.0 mm between the AI-based system and the mean of the measurements obtained by the echocardiographers. Conclusions: The AI-based system for vegetation measurement demonstrates a high level of correlation and agreement with experts, similar to the concordance between human operators themselves. This level of agreement suggests that the method has the potential to reduce inter-operator variability in the measurement process. Whether AI-based vegetation size improves embolism prediction has to be further investigated.

Background/Objectives: Prosthetic valve endocarditis (PVE) carries a high morbidity and mortality. Surgery is classically indicated for heart failure, uncontrolled infection, or prevention of embolic events; however, evidence supporting surgery for “non-classical” indications—such as Staphylococcus aureus infection, non-HACEK Gram-negative bacteria, or early PVE—remains limited. This study aimed to update the clinical and prognostic profile of PVE and assess the impact of surgery, particularly in patients with non-classical surgical indications. Methods: We prospectively included all definite left-sided PVE cases diagnosed between 2000 and 2024 at three tertiary centers. Clinical, microbiological, echocardiographic, and prognostic data were analyzed and compared. Predictors of in-hospital mortality were identified using multivariable logistic regression, and Kaplan–Meier curves were used to compare 1-year survival according to surgical indications. Results: Among 589 patients with left-sided PVE, 61% underwent surgery, and in-hospital mortality was 31%. Independent mortality predictors were chronic obstructive pulmonary disease, pulmonary hypertension, periannular complications, S. aureus infection, and poor clinical condition at admission. Non-classical surgical indications were present in 38% of patients, although only 28 (5%) of them had no other surgical indication. These patients exhibited lower mortality (14%) and no survival benefit from surgery (10% vs. 17%; p 0.999). Conclusions: PVE remains associated with high mortality. Surgery improves survival in patients with classical surgical indications but not in patients with non-classical indications, supporting individualized surgical decisions by a multidisciplinary endocarditis team.