ArticlePloS one2019
Semantic computational analysis of anticoagulation use in atrial fibrillation from real world data.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.
- Systematic review of current natural language processing methods and applications in cardiology.Heart (British Cardiac Society) · 2022Pooled it
- Hospital-wide natural language processing summarising the health data of 1 million patients.PLOS digital health · 2023Article
- Challenges of Anticoagulant Therapy in Atrial Fibrillation-Focus on Gastrointestinal Bleeding.International journal of molecular sciences · 2023Review
- 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 survey on clinical natural language processing in the United Kingdom from 2007 to 2022.NPJ digital medicine · 2022Review
- Building a Precision Medicine Delivery Platform for Clinics: The University of California, San Francisco, BRIDGE Experience.Journal of medical Internet research · 2022Article
- Prognostic relevance of demographic factors in cardiac magnetic resonance-proven acute myocarditis: A cohort study.Frontiers in cardiovascular medicine · 2022Article
- Natural language word embeddings as a glimpse into healthcare language and associated mortality surrounding end of life.BMJ health & care informatics · 2021Article
- Pre-existing cardiovascular disease rather than cardiovascular risk factors drives mortality in COVID-19.BMC cardiovascular disorders · 2021Article
- Cardiovascular Imaging and Intervention Through the Lens of Artificial Intelligence.Interventional cardiology (London, England) · 2021Review
- A case-control and cohort study to determine the relationship between ethnic background and severe COVID-19.EClinicalMedicine · 2020Article
- The relationship between frequency and severity of vaso-occlusive crises and health-related quality of life and work productivity in adults with sickle cell disease.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2020Article
- Angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers are not associated with severe COVID-19 infection in a multi-site UK acute hospital trust.European journal of heart failure · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 4 institutions in 3 countries.
Funding
Abstract
Atrial fibrillation (AF) is the most common arrhythmia and significantly increases stroke risk. This risk is effectively managed by oral anticoagulation. Recent studies using national registry data indicate increased use of anticoagulation resulting from changes in guidelines and the availability of newer drugs. The aim of this study is to develop and validate an open source risk scoring pipeline for free-text electronic health record data using natural language processing. AF patients discharged from 1st January 2011 to 1st October 2017 were identified from discharge summaries (N = 10,030, 64.6% male, average age 75.3 ± 12.3 years). A natural language processing pipeline was developed to identify risk factors in clinical text and calculate risk for ischaemic stroke (CHA2DS2-VASc) and bleeding (HAS-BLED). Scores were validated vs two independent experts for 40 patients. Automatic risk scores were in strong agreement with the two independent experts for CHA2DS2-VASc (average kappa 0.78 vs experts, compared to 0.85 between experts). Agreement was lower for HAS-BLED (average kappa 0.54 vs experts, compared to 0.74 between experts). In high-risk patients (CHA2DS2-VASc ≥2) OAC use has increased significantly over the last 7 years, driven by the availability of DOACs and the transitioning of patients from AP medication alone to OAC. Factors independently associated with OAC use included components of the CHA2DS2-VASc and HAS-BLED scores as well as discharging specialty and frailty. OAC use was highest in patients discharged under cardiology (69%). Electronic health record text can be used for automatic calculation of clinical risk scores at scale. Open source tools are available today for this task but require further validation. Analysis of routinely collected EHR data can replicate findings from large-scale curated registries.
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Registered trials
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.