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Leslee J. Shaw

Researcher at Cornell University

Publications -  871
Citations -  70793

Leslee J. Shaw is an academic researcher from Cornell University. The author has contributed to research in topics: Coronary artery disease & Myocardial infarction. The author has an hindex of 116, co-authored 808 publications receiving 61598 citations. Previous affiliations of Leslee J. Shaw include Saint Louis University & Cedars-Sinai Medical Center.

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Frequency, Predictors, and Consequences of Crossing Over to Revascularization Within 12 Months of Randomization to Optimal Medical Therapy in the Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation (COURAGE) Trial

TL;DR: Among COURAGE patients assigned to OMT alone, patients’ angina, dissatisfaction with their current treatment, and, to a lesser extent, their health system were associated with early revascularization, support an initial trial of OMT in stable ischemic heart disease with close follow-up of the most symptomatic patients.
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Obesity distribution and reproductive hormone levels in women: a report from the NHLBI-sponsored WISE Study.

TL;DR: Different relationships between blood estrogen levels and obesity distribution in a cohort of postmenopausal women with chest pain undergoing coronary angiography demonstrate differing levels by general and central obesity, which may help explain in part observed epidemiological relationships between obesity and disease.
Journal Article

Noninvasive cardiac imaging.

TL;DR: Although guidelines can help with treating patients, treatment ultimately should be tailored to each person based on clinical judgment of the a priori risk of a cardiac event, symptoms, and the cardiac risk profile.
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Pericoronary Adipose Tissue Attenuation, Low-Attenuation Plaque Burden, and 5-Year Risk of Myocardial Infarction.

TL;DR: In this paper , the authors investigated the relationship between the future risk of fatal or nonfatal myocardial infarction and attenuation measured from coronary computed tomography angiography (CTA) using multivariable Cox regression models including plaque burden, obstructive coronary disease, and cardiac risk score (incorporating age, sex, diabetes, smoking, hypertension, hyperlipidemia, and family history).