ArticlePloS one2022
Assessment of medical management in Coronary Type 2 Diabetic patients with previous percutaneous coronary intervention in Spain: A retrospective analysis of electronic health records using Natural Language Processing.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 14 citations in OpenAlex.
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- Toward a Better Paradigm for Head and Neck Cancer Treatment Applying AI (HNC-TACTIC): Protocol for an International Cohort Study of Electronic Health Records.JMIR research protocols · 2026Observational
- Article
- Impact of Advanced Age on the Incidence of Major Adverse Cardiovascular Events in Patients with Type 2 Diabetes Mellitus and Stable Coronary Artery Disease in a Real-World Setting in Spain.Journal of clinical medicine · 2023Article
- Symptoms timeline and outcomes in amyotrophic lateral sclerosis using artificial intelligence.Scientific reports · 2023Article
- How can artificial intelligence optimize value-based contracting?Journal of pharmaceutical policy and practice · 2022Article
- Major Adverse Cardiovascular Events in Coronary Type 2 Diabetic Patients: Identification of Associated Factors Using Electronic Health Records and Natural Language Processing.Journal of clinical medicine · 2022Article
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Authors and funding
21 authors at 18 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
INTRODUCTION AND
objectivesPatients with type 2 diabetes (T2D) and stable coronary artery disease (CAD) previously revascularized with percutaneous coronary intervention (PCI) are at high risk of recurrent ischemic events. We aimed to provide real-world insights into the clinical characteristics and management of this clinical population, excluding patients with a history of myocardial infarction (MI) or stroke, using Natural Language Processing (NLP) technology.
methodsThis is a multicenter, retrospective study based on the secondary use of 2014-2018 real-world data captured in the Electronic Health Records (EHRs) of 1,579 patients (0.72% of the T2D population analyzed; n = 217,632 patients) from 12 representative hospitals in Spain. To access the unstructured clinical information in EHRs, we used the EHRead® technology, based on NLP and machine learning. Major adverse cardiovascular events (MACE) were considered: MI, ischemic stroke, urgent coronary revascularization, and hospitalization due to unstable angina. The association between MACE rates and the variables included in this study was evaluated following univariate and multivariate approaches.
resultsMost patients were male (72.13%), with a mean age of 70.5±10 years. Regarding T2D, most patients were non-insulin-dependent T2D (61.75%) with high prevalence of comorbidities. The median (Q1-Q3) duration of follow-up was 1.2 (0.3-4.5) years. Overall, 35.66% of patients suffered from at least one MACE during follow up. Using a Cox Proportional Hazards regression model analysis, several independent factors were associated with MACE during follow up: CAD duration (p < 0.001), COPD/Asthma (p = 0.021), heart valve disease (p = 0.031), multivessel disease (p = 0.005), insulin treatment (p < 0.001), statins treatment (p < 0.001), and clopidogrel treatment (p = 0.039).
conclusionsOur results showed high rates of MACE in a large real-world series of PCI-revascularized patients with T2D and CAD with no history of MI or stroke. These data represent a potential opportunity to improve the clinical management of these patients.
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