Background: Infective endocarditis is a life-threatening disease with diverse clinical presentations, making diagnosis challenging and requiring a range of complementary tests. The level of suspicion, based on clinical judgment, guides decisions regarding the initiation of empirical treatment and the selection of appropriate diagnostic tools. This study aimed to develop and validate the EndoPredict-Dx score for early prediction of infective endocarditis diagnosis.
Methods: Patients admitted to a specialized cardiovascular hospital emergency department with suspected infective endocarditis between January 2011 and January 2020 were included. The primary outcome was left-sided infective endocarditis according to the Duke criteria. Logistic regression was used to derive the scoring system, with internal validation performed through bootstrapping. Candidate variables were obtained from the admission medical history, physical examination, and laboratory parameters.
Results: Of the 805 individuals with suspected infective endocarditis (median age 56 years (40-73); 58.6% men), 530 confirmed the diagnosis based on the Duke criteria. The EndoPredict-Dx assigned points for male sex, previous endocarditis, petechiae, heart murmur, suspected embolism, symptoms lasting 14 or more days at the time of admission, hemoglobin level ≤ 12 g/dL, leukocyte level ≥ 10 × 109/L, C-reactive protein level ≥ 20 mg/L, and urine red blood cells ≥ 20,000 cells/mL. Patients were divided into three risk groups. The AUROC was 0.78 (95% CI 0.75-0.81) for the derivation cohort and 0.77 for the internal validation.
Conclusions: The EndoPredict-Dx score accurately predicted the likelihood of infective endocarditis using clinical and laboratory data collected at admission.
Keywords: decision making; heart valve disease; infective endocarditis; resource-limited settings.