ArticleClinical and experimental immunology2019
Inflammatory biomarkers in infective endocarditis: machine learning to predict mortality.
Article in Clinical and experimental immunology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.
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Who cites it
20 citing papers in PubMed, 2 syntheses or guidelines pooled it, 34 citations in OpenAlex.
- Infective endocarditis: Do we have an effective risk score model? A systematic review.Frontiers in cardiovascular medicine · 2023Pooled it
- Clinical Prognosis of Right-Sided Infective Endocarditis not Associated with Cardiac Devices or Intravenous Drug use: a Cohort Study and Meta-Analysis.Scientific reports · 2020Pooled it
- Automatic Detection of Vegetations With Transesophageal Echocardiography in Infective Endocarditis Using Artificial Intelligence.Journal of imaging informatics in medicine · 2026Observational
- The impact of thrombocytopenia on mortality in infective endocarditis - aInternational journal of cardiology. Heart & vasculature · 2025Review
- Mortality predicting models for patients with infective endocarditis: a machine learning approach.BMC medical informatics and decision making · 2025Observational
- The ratio of blood urea nitrogen to high-density lipoprotein cholesterol: a novel risk-stratifying tool for infective endocarditis.Lipids in health and disease · 2025Article
- Integrated plasma and vegetation proteomic characterization of infective endocarditis for early diagnosis and treatment.Nature communications · 2025Article
- Change of Heart: Can Artificial Intelligence Transform Infective Endocarditis Management?Pathogens (Basel, Switzerland) · 2025Review
- Diagnostic work-up and current management strategies for infective endocarditis in the pediatric population.Indian journal of thoracic and cardiovascular surgery · 2024Review
- A decision support system to recommend appropriate therapy protocol for AML patients.Frontiers in artificial intelligence · 2024Article
- Hematologic Parameters as Predictors of Long-Term Mortality in Infective Endocarditis Patients.Medical science monitor : international medical journal of experimental and clinical research · 2023Article
- Prognostic Value of Blood Urea Nitrogen for Short-Term Mortality in Patients with Infective Endocarditis.Infectious diseases and therapy · 2023Article
- C-Reactive Protein: Pathophysiology, Diagnosis, False Test Results and a Novel Diagnostic Algorithm for Clinicians.Diseases (Basel, Switzerland) · 2023Review
- Prognostic implications of ultra-short heart rate variability indices in hospitalized patients with infective endocarditis.PloS one · 2023Article
- Prognostic Value of Lymphocyte-to-White Blood Cell Ratio for In-Hospital Mortality in Infective Endocarditis Patients.International journal of clinical practice · 2022Article
- Infective endocarditis in paediatric population.European journal of pediatrics · 2021Review
- Prognostic value of D-dimer for adverse outcomes in patients with infective endocarditis: an observational study.BMC cardiovascular disorders · 2021Observational
- Current Challenges in the Management of Infective Endocarditis.Frontiers in medicine · 2021Review
- C-Reactive Protein at Hospital Discharge and 1-Year Mortality in Acute Infective Endocarditis: A Prospective Observational Study.Frontiers in cardiovascular medicine · 2021Article
- Risk stratification biomarkers forClinical & translational immunology · 2020Article
Corrections and comments
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Authors and funding
13 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Infective endocarditis (IE) is the cardiac disease with the highest rates of mortality. New biomarkers that are able to identify patients at risk for death are required to improve patient management and outcome. This study aims to investigate if cytokines, chemokines and growth factors measured at IE diagnosis can predict mortality. Patients with definite IE, according to the Duke's modified criteria, were included. Using high-performance Luminex assay, 27 different cytokines, chemokines and growth factors were analyzed. Machine learning techniques were used for the prediction of death and subsequently creating a decision tree, in which the cytokines, chemokines and growth factors were analyzed together with C-reactive protein (CRP). Sixty-nine patients were included, 41 (59%) male, median age 54 [interquartile range (IQR) = 41-65 years] and median time between onset of the symptoms and diagnosis was 12 days (IQR = 5-30 days). The in-hospital mortality was 26% (n = 18). Proinflammatory cytokines interkeukin (IL)-15 and C-C motif chemokine ligand (CCL4) were found to predict death, adding value to CRP levels. The decision tree predicted correctly the outcome of 91% of the patients at hospital admission. The high-risk group, defined as CRP ≥ 72 mg/dL, IL-15 ≥ 5·6 fg/ml and CCL4 ≥ 6·35 fg/ml had an 88% in-hospital mortality rate, whereas the patients classified as low-risk had a mortality rate of 8% (P = < 0·001). Cytokines IL-15 and CCL4 were predictors of mortality in IE, adding prognostic value beyond that provided by CRP levels. Assessment of cytokines has potential value for clinical risk stratification and monitoring in IE patients.
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