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Retinal vascular caliber, diabetes, and retinopathy. 2007

Annette Kifley, and Jie Jin Wang, and Sudha Cugati, and Tien Y Wong, and Paul Mitchell
Centre for Vision Research, Department of Ophthalmology, University of Sydney, Australia.

OBJECTIVE To assess the relationship of retinal vessel caliber with diabetes and diabetic retinopathy (DR). METHODS Population-based cross-sectional analysis of the Blue Mountains Eye Study, Australia (n = 3,654, age >or=49 years). METHODS Diabetes was defined as physician-diagnosed or fasting blood glucose >or= 7.0 mmol/l; impaired fasting glucose as fasting glucose 6.1 to 6.9 mmol/l. DR was graded from retinal photographs. Retinal vessel caliber was measured from digitized images. RESULTS After controlling for age, gender, blood pressure, and other factors, mean retinal venular caliber was significantly wider in participants with moderate-severe nonproliferative DR (severe 262.7 microm; moderate 236.7 microm) than in nondiabetic participants (221.9 microm) or participants with diabetes but no DR (221.2 microm) (P < .0001). Mean retinal arteriolar caliber was significantly wider in participants with diabetes (193.5 microm) than in nondiabetic participants (190.2 microm) (P < .01). CONCLUSIONS Increasing severity of DR in persons with diabetes is associated with widening of retinal venular caliber.

UI MeSH Term Description Entries
D007091 Image Processing, Computer-Assisted A technique of inputting two-dimensional or three-dimensional images into a computer and then enhancing or analyzing the imagery into a form that is more useful to the human observer. Biomedical Image Processing,Computer-Assisted Image Processing,Digital Image Processing,Image Analysis, Computer-Assisted,Image Reconstruction,Medical Image Processing,Analysis, Computer-Assisted Image,Computer-Assisted Image Analysis,Computer Assisted Image Analysis,Computer Assisted Image Processing,Computer-Assisted Image Analyses,Image Analyses, Computer-Assisted,Image Analysis, Computer Assisted,Image Processing, Biomedical,Image Processing, Computer Assisted,Image Processing, Digital,Image Processing, Medical,Image Processings, Medical,Image Reconstructions,Medical Image Processings,Processing, Biomedical Image,Processing, Digital Image,Processing, Medical Image,Processings, Digital Image,Processings, Medical Image,Reconstruction, Image,Reconstructions, Image
D008297 Male Males
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D009517 New South Wales A state in southeastern Australia. Its capital is Sydney. It was discovered by Captain Cook in 1770 and first settled at Botany Bay by marines and convicts in 1788. It was named by Captain Cook who thought its coastline resembled that of South Wales. (From Webster's New Geographical Dictionary, 1988, p840 & Room, Brewer's Dictionary of Names, 1992, p377)
D010781 Photography Method of making images on a sensitized surface by exposure to light or other radiant energy. Photographies
D001786 Blood Glucose Glucose in blood. Blood Sugar,Glucose, Blood,Sugar, Blood
D001794 Blood Pressure PRESSURE of the BLOOD on the ARTERIES and other BLOOD VESSELS. Systolic Pressure,Diastolic Pressure,Pulse Pressure,Pressure, Blood,Pressure, Diastolic,Pressure, Pulse,Pressure, Systolic,Pressures, Systolic
D003430 Cross-Sectional Studies Studies in which the presence or absence of disease or other health-related variables are determined in each member of the study population or in a representative sample at one particular time. This contrasts with LONGITUDINAL STUDIES which are followed over a period of time. Disease Frequency Surveys,Prevalence Studies,Analysis, Cross-Sectional,Cross Sectional Analysis,Cross-Sectional Survey,Surveys, Disease Frequency,Analyses, Cross Sectional,Analyses, Cross-Sectional,Analysis, Cross Sectional,Cross Sectional Analyses,Cross Sectional Studies,Cross Sectional Survey,Cross-Sectional Analyses,Cross-Sectional Analysis,Cross-Sectional Study,Cross-Sectional Surveys,Disease Frequency Survey,Prevalence Study,Studies, Cross-Sectional,Studies, Prevalence,Study, Cross-Sectional,Study, Prevalence,Survey, Cross-Sectional,Survey, Disease Frequency,Surveys, Cross-Sectional
D003924 Diabetes Mellitus, Type 2 A subclass of DIABETES MELLITUS that is not INSULIN-responsive or dependent (NIDDM). It is characterized initially by INSULIN RESISTANCE and HYPERINSULINEMIA; and eventually by GLUCOSE INTOLERANCE; HYPERGLYCEMIA; and overt diabetes. Type II diabetes mellitus is no longer considered a disease exclusively found in adults. Patients seldom develop KETOSIS but often exhibit OBESITY. Diabetes Mellitus, Adult-Onset,Diabetes Mellitus, Ketosis-Resistant,Diabetes Mellitus, Maturity-Onset,Diabetes Mellitus, Non-Insulin-Dependent,Diabetes Mellitus, Slow-Onset,Diabetes Mellitus, Stable,MODY,Maturity-Onset Diabetes Mellitus,NIDDM,Diabetes Mellitus, Non Insulin Dependent,Diabetes Mellitus, Noninsulin Dependent,Diabetes Mellitus, Noninsulin-Dependent,Diabetes Mellitus, Type II,Maturity-Onset Diabetes,Noninsulin-Dependent Diabetes Mellitus,Type 2 Diabetes,Type 2 Diabetes Mellitus,Adult-Onset Diabetes Mellitus,Diabetes Mellitus, Adult Onset,Diabetes Mellitus, Ketosis Resistant,Diabetes Mellitus, Maturity Onset,Diabetes Mellitus, Slow Onset,Diabetes, Maturity-Onset,Diabetes, Type 2,Ketosis-Resistant Diabetes Mellitus,Maturity Onset Diabetes,Maturity Onset Diabetes Mellitus,Non-Insulin-Dependent Diabetes Mellitus,Noninsulin Dependent Diabetes Mellitus,Slow-Onset Diabetes Mellitus,Stable Diabetes Mellitus
D003930 Diabetic Retinopathy Disease of the RETINA as a complication of DIABETES MELLITUS. It is characterized by the progressive microvascular complications, such as ANEURYSM, interretinal EDEMA, and intraocular PATHOLOGIC NEOVASCULARIZATION. Diabetic Retinopathies,Retinopathies, Diabetic,Retinopathy, Diabetic

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