| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Oliveira, Ricardo
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (8/8 displayed)
- 2019Semantic computational analysis of anticoagulation use in atrial fibrillation from real world datacitations
- 2018Novel techniques and devices for optical communications and sensing technologies
- 2017Multiparameter POF Sensing Based on Multimode Interference and Fiber Bragg Gratingcitations
- 2015Smooth end face termination of microstructured, graded-index, and step-index polymer optical fiberscitations
- 2015Fabrication and characterization of polymer fiber Bragg gratings inscribed with KrF UV laser
- 2015Bragg Gratings Inscription in Highly Birefringent Microstructured POFscitations
- 2015New advances in polymer fiber Bragg gratingscitations
- 2015Bragg gratings in a few mode microstructured polymer optical fiber in less than 30 secondscitations
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article
Semantic computational analysis of anticoagulation use in atrial fibrillation from real world data
Abstract
<p>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 1<sup>st</sup> January 2011 to 1<sup>st</sup> 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 (CHA<sub>2</sub>DS<sub>2</sub>-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 CHA<sub>2</sub>DS<sub>2</sub>-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 (CHA<sub>2</sub>DS<sub>2</sub>-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 CHA<sub>2</sub>DS<sub>2</sub>-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.</p>