2012 ACCF/AHA/ACR/SCAI/SIR/STS/SVM/SVN/SVS Key data elements and definitions for peripheral atherosclerotic vascular disease: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Clinical Data Standards (Writing Committee to develop Clinical Data Standards for peripheral atherosclerotic vascular disease).

Journal of the American College of Cardiology (Impact Factor: 16.5). 12/2011; 59(3):294-357. DOI: 10.1016/j.jacc.2011.10.860
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Available from: Edward I Bluth, Sep 26, 2015
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    • "We defined hypercholesterolemia, high LDL-cholesterol, low HDL-cholesterol, hypertriglyceridemia, respectively, as serum cholesterol levels greater than 190 mg/L (4.9 mmol/L), LDL-cholesterol greater than 100 mg/dL (2.50 mmol/L), HDL-cholesterol levels less than 40 mg/L (1.03 mmol/L), and serum triglyceride levels greater than 200 mg/L (2.26 mmol/L) respectively [26]. We defined mild PAD as an ABI ≥ 0.71 but ≤ 0.90, moderate PAD as an ABI ≥ 0.40 but ≤ 0.70, and severe PAD as an ABI < 0.40 [20]. We considered a patient with PAD as being on PAD-appropriate medical therapy if they reported taking either aspirin or clopidigrel. "
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    ABSTRACT: Background Peripheral artery disease (PAD) is a major complication of atherosclerosis. PAD can be diagnosed with low-cost diagnostic techniques and is associated with significant morbidity and mortality. While the major epidemiologic risk factors for PAD have been established in the western world, data from resource-poor countries are limited. We performed a cross-sectional study to determine the prevalence and correlates of PAD among patients with diabetes at Mbarara Referral Hospital in southwestern Uganda. Methods We consecutively enrolled diabetes patients aged 50 years or greater presenting to the outpatient clinic. We collected blood for fasting lipid profile, HIV serology, and glycosylated hemoglobin, measured blood pressure and ankle brachial index, and administered the Edinburgh Claudication Questionnaire (ECQ). We also surveyed patients for other PAD risk factors. We used logistic regression to determine correlates of PAD. Results We enrolled 229 diabetes patients. The median age of 60 years (IQR 55–66), and 146 (63.7%) were female. Fifty five patients (24%) had PAD (ABI of ≤ 0.9). Of these, 48 /55 (87.27%) had mild PAD (ABI 0.71-0.9) while 7/55 (12.73%) had moderate to severe PAD (ABI < 0.7). Amongst those with PAD, 24/55 (43.64%) reported claudication by the ECQ. Correlates of PAD included female sex (AOR 2.25, 95% CI 1.06 - 4.77, p = 0.034), current high blood pressure (AOR 2.59, 95% CI 1.25-5.33, p = 0.01), and being on a sulfonylurea–glibenclamide (AOR 3.47, 95% CI 1.55 - 7.76, p = 0.002). Conclusion PAD was common in diabetic patients in southwestern Uganda. Given its low cost and ease of measurement, ABI deserves further assessment as a screening tool for both PAD and long term cardiovascular risk amongst diabetics in this region.
    BMC Cardiovascular Disorders 06/2014; 14(1):75. DOI:10.1186/1471-2261-14-75 · 1.88 Impact Factor
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    Journal of the American College of Cardiology 01/2013; 61(9). DOI:10.1016/j.jacc.2012.10.005 · 16.50 Impact Factor
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    ABSTRACT: Background: The Walking Impairment Questionnaire (WIQ) is a subjective measure of patient-reported walking performance developed for peripheral arterial disease. The purpose of this study is to examine whether this simple tool can improve the predictive capacity of established risk models and whether the WIQ can be used in patients without peripheral arterial disease. Methods and results: At baseline we assessed the walking distance, stair-climbing, and walking speed WIQ category scores among individuals who were undergoing coronary angiography. During a median follow-up of 5.0 years, there were 172 mortalities among 1417 study participants. Adjusted Cox proportional hazards models showed that all 3 WIQ categories independently predicted future all-cause and cardiovascular mortality, including among individuals without peripheral arterial disease (P<0.001). Compared with the cardiovascular risk factors model, we observed significantly increased risk discrimination with a C-index of 0.741 (change in C-index, 0.040; 95% confidence interval, 0.011-0.068) and 0.832 (change in C-index, 0.080; 95% confidence interval, 0.034-0.126) for all-cause and cardiovascular mortality, respectively. Examination of risk reclassification using the net reclassification improvement index showed a 48.4% (P<0.001) improvement for all-cause mortality and a 77.4% (P<0.001) improvement for cardiovascular mortality compared with the cardiovascular risk factors model. Conclusions: All 3 WIQ categories independently predicted future all-cause and cardiovascular mortality. Importantly, we found that this subjective measure of walking ability could be extended to patients without peripheral arterial disease. The addition of the WIQ scores to established cardiovascular risk models significantly improved risk discrimination and reclassification, suggesting broad clinical use for this simple, inexpensive test.
    Circulation Cardiovascular Quality and Outcomes 04/2013; 6(3). DOI:10.1161/CIRCOUTCOMES.111.000070 · 5.66 Impact Factor
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