Proposal and validation of a predictive model of hospital mortality in patients with infective endocarditis.
Keywords:
infective endocarditis; in-hospital mortality; NAIPES ScoreAbstract
Introduction: Infective endocarditis is a lethal and difficult-to-diagnose disease. Despite advances in prevention, diagnosis, and treatment, its incidence and mortality have not shown a significant decrease in the last 30 years.
Objective: To develop a predictive model of in-hospital mortality in patients with infective endocarditis.
Method: An observational, analytical, retrospective cohort study was conducted at the Institute of Cardiology and Cardiovascular Surgery between January 2018 and December 2024.
Results: Eighty-one patients were studied, predominantly male (71.6%), and the most frequent age group was under 65 years. In-hospital mortality occurred in 29.6% of patients and was associated with systemic response and hemodynamic compromise. A risk stratification tool adapted to this population, the NAIPES Score, was created. It included six clinical and paraclinical variables and demonstrated high predictive capacity, explaining 76.2% of deaths with a sensitivity of 95.8%, a specificity of 59.6%, and an AUC of 0.937 (95% CI: 0.877–0.996; p < 0.001).
Conclusions: The NAIPES Score is a highly predictive tool, useful for identifying patients at high risk of death during initial triage.
Keywords: infective endocarditis, in-hospital mortality, NAIPES Score.
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