ArticleJournal of cardiac failure2014
Prevalence of heart failure signs and symptoms in a large primary care population identified through the use of text and data mining of the electronic health record.
Article in Journal of cardiac failure, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 4 of them syntheses that pooled it.
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Who cites it
45 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Natural language processing with machine learning methods to analyze unstructured patient-reported outcomes derived from electronic health records: A systematic review.Artificial intelligence in medicine · 2023Pooled it
- Natural language processing of symptoms documented in free-text narratives of electronic health records: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2019Pooled it
- Factors influencing the development of primary care data collection projects from electronic health records: a systematic review of the literature.BMC medical informatics and decision making · 2017Pooled it
- Clinical Natural Language Processing in 2014: Foundational Methods Supporting Efficient Healthcare.Yearbook of medical informatics · 2015Pooled it
- Article
- Article
- Assessment of Bendopnea and Its Association With Clinical and Para-Clinical Findings in Systolic Heart Failure: A Cross-Sectional Study.Health science reports · 2025Article
- Compression wraps as adjuvant therapy in the management of acute systolic heart failure.Heliyon · 2023Article
- Congestion and Use of Diuretics in Heart Failure and Cardiomyopathies: a Practical Guide.Current cardiology reports · 2023Review
- A cross-institutional evaluation on breast cancer phenotyping NLP algorithms on electronic health records.Computational and structural biotechnology journal · 2023Article
- Interpretable machine learning text classification for clinical computed tomography reports - a case study of temporal bone fracture.Computer methods and programs in biomedicine update · 2023Article
- The clinical value of hepatojugular reflux on congestive heart failure: A meta-analysis.Journal of general and family medicine · 2022Article
- Data-driven identification of heart failure disease states and progression pathways using electronic health records.Scientific reports · 2022Article
- Echocardiographic Parameters Associated with Bendopnea in Patients with Systolic Heart Failure.The journal of Tehran Heart Center · 2022Article
- A Holistic View of Advanced Heart Failure.Life (Basel, Switzerland) · 2022Review
- A literature review on the analysis of symptom-based clinical pathways: Time for a different approach?PLOS digital health · 2022Article
- A Deep Language Model for Symptom Extraction From Clinical Text and its Application to Extract COVID-19 Symptoms From Social Media.IEEE journal of biomedical and health informatics · 2022Article
- Advances in Machine Learning Approaches to Heart Failure with Preserved Ejection Fraction.Heart failure clinics · 2022Review
- Artificial Intelligence in Cardiovascular Medicine: Historical Overview, Current Status, and Future Directions.Texas Heart Institute journal · 2022Article
- Application of Artificial Intelligence in Community-Based Primary Health Care: Systematic Scoping Review and Critical Appraisal.Journal of medical Internet research · 2021Article
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Authors and funding
10 authors.
Funding
Abstract
backgroundThe electronic health record (EHR) contains a tremendous amount of data that if appropriately detected can lead to earlier identification of disease states such as heart failure (HF). Using a novel text and data analytic tool we explored the longitudinal EHR of over 50,000 primary care patients to identify the documentation of the signs and symptoms of HF in the years preceding its diagnosis. METHODS AND
resultsRetrospective analysis consisted of 4,644 incident HF cases and 45,981 group-matched control subjects. Documentation of Framingham HF signs and symptoms within encounter notes were carried out with the use of a previously validated natural language processing procedure. A total of 892,805 affirmed criteria were documented over an average observation period of 3.4 years. Among eventual HF cases, 85% had ≥1 criterion within 1 year before their HF diagnosis, as did 55% of control subjects. Substantial variability in the prevalence of individual signs and symptoms were found in both case and control subjects.
conclusionsHF signs and symptoms are frequently documented in a primary care population as identified through automated text and data mining of EHRs. Their frequent identification demonstrates the rich data available within EHRs that will allow for future work on automated criterion identification to help develop predictive models for HF.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.