OBJECTIVE: Premature @entity301 ( @entity301 ) significantly affects morbidity and mortality in @entity1252 ( @entity1252 ). Several studies have detected factors influencing the atherosclerotic process, as well as methods to quantify the @entity731 in subclinical stages. The aim of this systematic review was to identify the minimum investigations to optimally monitor @entity301 risk in @entity1252 . METHODS: English-restricted literature review was performed using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines through Ovid Medline, Embase, and Cochrane Central databases, from inception until May 2014 (Medline until October 2014). Specific search terms included, among others, " @entity1252 ," " @entity731 ," " @entity301 ," " @entity741 ," " @entity1187 ," " @entity583 ," and " @entity951 ." We identified 101 eligible articles, 23 with cardiovascular events (CVE) as endpoints and 78 with measures of subclinical @entity731 . The Newcastle-Ottawa scale was used for quality assessment. RESULTS: Certain traditional and disease-specific factors were identified as independent predictors for @entity301 . Among the former were age (particularly postmenopausal state), male sex, arterial @entity101 , @entity2299 , and smoking. Disease activity and duration, cumulative damage, antiphospholipid antibodies, high sensitivity C-reactive protein, and @entity8 were the most consistent disease-related factors. Corticosteroids were linked to increased @entity301 risk whereas antimalarials were protective. Concerning imaging techniques, carotid ultrasonography (intima-media thickness and plaque) was shown to independently predict CVE. CONCLUSION: Premature @entity301 in @entity1252 is multifactorial; modifiable variables should be monitored at frequent intervals to ensure prompt management. Disease-specific factors also affect the atherogenic process and should be evaluated regularly. Carotid ultrasonography may hold promise in predicting CVE in selected high-risk @entity1 .

Optimal Monitoring For Coronary Heart Disease Risk in @entity1 with XXXX : A Systematic Review.

@entity1 :: ('9606', 'Species') :: ['patients'] @entity1187 :: ('MESH:D054058', 'Disease') :: ['acute coronary syndrome'] @entity8 :: ('MESH:D007674', 'Disease') :: ['renal disease'] @entity583 :: ('MESH:D009203', 'Disease') :: ['myocardial infarction'] @entity101 :: ('MESH:D006973', 'Disease') :: ['hypertension'] @entity301 :: ('MESH:D003327', 'Disease') :: ['CHD', 'coronary heart disease'] @entity2299 :: ('MESH:D050171', 'Disease') :: ['dyslipidemia'] @entity1252 :: ('MESH:D008180', 'Disease') :: ['SLE', 'systemic lupus erythematosus'] @entity951 :: ('MESH:D000787', 'Disease') :: ['angina pectoris'] @entity741 :: ('MESH:D017202', 'Disease') :: ['myocardial ischemia'] @entity731 :: ('MESH:D050197', 'Disease') :: ['atherosclerotic burden', 'atherosclerosis']
@entity1252 :: (MESH:D008180,Disease) :: ['Systemic Lupus Erythematosus']
