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Predictors of health care use among patients with or at high risk of atherothrombotic disease: two-year follow-up data

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  • REACH Registry Investigators
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<mark>Journal publication date</mark>15/07/2014
<mark>Journal</mark>International Journal of Cardiology
Issue number1
Volume175
Number of pages6
Pages (from-to)72-77
Publication statusPublished
Original languageEnglish

Abstract

Background
Atherothrombotic diseases are the leading health problems in the world, both in terms of morbidity and mortality. This study aimed to identify and quantify the predictors of medication, hospital and outpatient service use among patients with or at high risk of atherothrombotic disease.

Methods
Two-year follow-up data were analyzed for 2873 Australian participants of the Reduction of Atherothrombosis for Continued Health (REACH) registry. The analysis was performed using generalized linear models with Poisson and Gamma distributions and log link function.

Results
Participants with hypercholesterolemia, diabetes, hypertension, atrial fibrillation (AF), and history of coronary artery disease (CAD) used more medications (p < 0.0001). The presence of diabetes predicted higher number of outpatient visits (RR = 1.09, 95% CI: 1.07–1.11), as did AF (RR = 1.10, 95% CI: 1.08–1.12). The presence of peripheral artery disease (PAD) regardless of ankle brachial index (ABI) status (abnormal or normal) increased the use of outpatient visits (RR = 1.24, 95% CI: 1.20–1.29 and RR = 1.12, 95% CI: 1.08–1.15), compared to those without PAD. Similarly, the presence of PAD regardless of ABI status increased the risk of vascular interventions, including coronary angioplasty, carotid surgery, amputation affecting lower-limb and peripheral bypass graft (RR = 3.64, 95% CI: 2.01–6.60) (RR = 2.8, 95% CI: 1.6–4.92) compared to patients without PAD.

Conclusions
The presence of PAD regardless of ABI status predicts a higher number of outpatient visits, non-fatal cardiovascular endpoints and vascular-interventions, while diabetes predicts higher pharmaceutical use and outpatient visits. AF predicts the higher number of outpatient visits and non-fatal cardiovascular events.