Bleeding in cardiac patients prescribed antithrombotic drugs: Electronic health record phenotyping algorithms, incidence, trends and prognosis
Anoop D. Shah,
James TH Teo,
Riyaz S Patel,
Posted 01 Feb 2019
bioRxiv DOI: 10.1101/538249 (published DOI: 10.1186/s12916-019-1438-y)
Posted 01 Feb 2019
Background: Clinical guidelines and public health authorities lack recommendations on scalable approaches to defining and monitoring the occurrence and severity of bleeding in populations prescribed antithrombotic therapy. We aimed to develop electronic health record algorithms for different bleeding phenotypes, and to determine the incidence, time trends and prognosis of bleeding in patients with incident cardiac disorders indicated for antiplatelet and/or vitamin K antagonist (VKA) therapy. Methods: We examined linked primary care, hospital admission and death registry electronic health records (CALIBER 1998-2010, England) of patients with newly diagnosed atrial fibrillation, acute myocardial infarction, unstable angina or stable angina to develop algorithms for bleeding events. Kaplan-Meier plots were used to estimate the incidence of bleeding events and we used Cox regression models to assess prognosis for all-cause mortality, atherothrombotic events and further bleeding following bleeding events. Results: We present electronic health record phenotyping algorithms for bleeding based on bleeding diagnosis in primary or hospital care, symptoms, transfusion, surgical procedures, and haemoglobin values. In validation of the phenotype we estimated a positive predictive value of 0.88 (95% CI: 0.64, 0.99) for hospitalised bleeding. Amongst 128,815 patients, 27259 (21.2%) had at least one bleeding event, with 5 year risks of bleeding of 29.1%, 21.9%, 25.3% and 23.4% following diagnoses of atrial fibrillation, acute myocardial infarction, unstable angina and stable angina respectively. Rates of hospitalised bleeding per 1000 patients more than doubled from 1.02 (95% CI: 0.83, 1.22) in January 1998 to 2.68 (95% CI: 2.49, 2.88) in December 2009 coinciding with increased rates of antiplatelet and VKA prescribing. Patients with hospitalised bleeding and primary care bleeding, with or without markers of severity, were at increased risk of all-cause mortality and atherothrombotic events compared to those with no bleeding. For example the hazard ratio for all-cause mortality was 1.98 (95% CI: 1.86, 2.11) for primary care bleeding with markers of severity, and 1.99 (95% CI: 1.92, 2.05) for hospitalised bleeding without markers of severity, compared to patients with no bleeding. Conclusions: Electronic health record bleeding phenotyping algorithms offer a scalable approach to monitoring bleeding in the population. Incidence of bleeding has doubled in incidence since 1998, affects 1 in 4 cardiac patients, and is associated with poor prognosis. Efforts are required to tackle this iatrogenic epidemic.
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