ArticleJournal of cardiovascular translational research2015
A Robust e-Epidemiology Tool in Phenotyping Heart Failure with Differentiation for Preserved and Reduced Ejection Fraction: the Electronic Medical Records and Genomics (eMERGE) Network.
Article in Journal of cardiovascular translational research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
35 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic review of current natural language processing methods and applications in cardiology.Heart (British Cardiac Society) · 2022Pooled it
- Association of Common Ancestry-Enriched Variants With Cardiomyopathy and Arrhythmias.Circulation · 2026Article
- Prevalence and Clinical Impact of Pathogenic Variants in Cardiomyopathy Genes Among Individuals with Cardiac Conduction Disorders.medRxiv : the preprint server for health sciences · 2026Article
- Galectin-1 Is a Marker but Not a Mediator of Heart Failure With Preserved Ejection Fraction.Hypertension (Dallas, Tex. : 1979) · 2026Article
- Weight Trajectory Impacts Risk for 10 Distinct Cardiometabolic Diseases.The Journal of clinical endocrinology and metabolism · 2025Article
- Large-scale multi-omics identifies drug targets for heart failure with reduced and preserved ejection fraction.Nature cardiovascular research · 2025Article
- Oral hygiene, quality of life, and risk of heart failure.Frontiers in oral health · 2025Article
- Patient-specific Predictors of Haemolysis with Percutaneous Ventricular Assist Devices.Cardiac failure review · 2025Article
- Artificial intelligence approaches for phenotyping heart failure in U.S. Veterans Health Administration electronic health record.ESC heart failure · 2024Article
- An Online Tool for Correcting Performance Measures of Electronic Phenotyping Algorithms for Verification Bias.ACI open · 2024Article
- Volumetric brain MRI signatures of heart failure with preserved ejection fraction in the setting of dementia.Magnetic resonance imaging · 2024Article
- Article
- Harnessing Electronic Medical Records in Cardiovascular Clinical Practice and Research.Journal of cardiovascular translational research · 2023Review
- Article
- Diagnostic signature for heart failure with preserved ejection fraction (HFpEF): a machine learning approach using multi-modality electronic health record data.BMC cardiovascular disorders · 2022Article
- A multicenter program for electronic health record screening for patients with heart failure with preserved ejection fraction: Lessons from the DELIVER-EHR initiative.Contemporary clinical trials · 2022Review
- Deep Learning Analysis of Polish Electronic Health Records for Diagnosis Prediction in Patients with Cardiovascular Diseases.Journal of personalized medicine · 2022Article
- Characterizing a Clinical Trial - Representative, Real-World Population with Heart Failure with Reduced Ejection Fraction.Clinical epidemiology · 2022Article
- Heart failure clinical care analysis uncovers risk reduction opportunities for preserved ejection fraction subtype.Scientific reports · 2021Article
- FIBER: enabling flexible retrieval of electronic health records data for clinical predictive modeling.JAMIA open · 2021Article
Corrections and comments
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Authors and funding
27 authors.
Funding
Abstract
Identifying populations of heart failure (HF) patients is paramount to research efforts aimed at developing strategies to effectively reduce the burden of this disease. The use of electronic medical record (EMR) data for this purpose is challenging given the syndromic nature of HF and the need to distinguish HF with preserved or reduced ejection fraction. Using a gold standard cohort of manually abstracted cases, an EMR-driven phenotype algorithm based on structured and unstructured data was developed to identify all the cases. The resulting algorithm was executed in two cohorts from the Electronic Medical Records and Genomics (eMERGE) Network with a positive predictive value of >95 %. The algorithm was expanded to include three hierarchical definitions of HF (i.e., definite, probable, possible) based on the degree of confidence of the classification to capture HF cases in a whole population whereby increasing the algorithm utility for use in e-Epidemiologic research.
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Registered trials
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