Skin fluorescence as a clinical tool for non-invasive assessment of advanced glycation and long-term complications of diabetes

Glycation is important in the development of complications of diabetes mellitus and may have a central role in the well-described glycaemic memory effect in developing these complications. Skin fluorescence has emerged over the last decade as a non-invasive method for assessing accumulation of advanced glycation endproducts. Skin fluorescence is independently related to micro- and macrovascular complications in both type 1 and type 2 diabetes mellitus and is associated with mortality in type 2 diabetes. The relation between skin fluorescence and cardiovascular disease also extends to other conditions with increased tissue AGE levels, such as renal failure. Besides cardiovascular complications, skin fluorescence has been associated, more recently, with other prevalent conditions in diabetes, such as brain atrophy and depression. Furthermore, skin fluorescence is related to past long-term glycaemic control and clinical markers of cardiovascular disease. This review will discuss the technique of skin fluorescence, its validation as a marker of tissue AGE accumulation, and its use as a clinical tool for the prediction of long-term complications in diabetes mellitus

Skin Autofluorescence Based Decision Tree in Detection of Impaired Glucose Tolerance and Diabetes

<p>Aim: Diabetes (DM) and impaired glucose tolerance (IGT) detection are conventionally based on glycemic criteria. Skin autofluorescence (SAF) is a noninvasive proxy of tissue accumulation of advanced glycation endproducts (AGE) which are considered to be a carrier of glycometabolic memory. We compared SAF and a SAF-based decision tree (SAF-DM) with fasting plasma glucose (FPG) and HbA1c, and additionally with the Finnish Diabetes Risk Score (FINDRISC) questionnaire +/- FPG for detection of oral glucose tolerance test (OGTT)- or HbA1c-defined IGT and diabetes in intermediate risk persons.</p><p>Methods: Participants had >= 1 metabolic syndrome criteria. They underwent an OGTT, HbA1c, SAF and FINDRISC, in adition to SAF-DM which includes SAF, age, BMI, and conditional questions on DM family history, antihypertensives, renal or cardiovascular disease events (CVE).</p><p>Results: 218 persons, age 56 yr, 128M/90F, 97 with previous CVE, participated. With OGTT 28 had DM, 46 IGT, 41 impaired fasting glucose, 103 normal glucose tolerance. SAF alone revealed 23 false positives (FP), 34 false negatives (FN) (sensitivity (S) 68%; specificity (SP) 86%). With SAF-DM, FP were reduced to 18, FN to 16 (5 with DM) (S 82%; SP 89%). HbA1c scored 48 FP, 18 FN (S 80%; SP 75%). Using HbA1c-defined DM-IGT/suspicion >= 6%/42 mmol/mol, SAF-DM scored 33 FP, 24 FN (4 DM) (S76%; SP72%), FPG 29 FP, 41 FN (S71%; SP80%). FINDRISC >= 10 points as detection of HbA1c-based diabetes/suspicion scored 79 FP, 23 FN (S 69%; SP 45%).</p><p>Conclusion: SAF-DM is superior to FPG and non-inferior to HbA1c to detect diabetes/IGT in intermediate-risk persons. SAF-DM's value for diabetes/IGT screening is further supported by its established performance in predicting diabetic complications.</p>

Determinants of arterial stiffness in chronic kidney disease stage 3

Background: Early chronic kidney disease (CKD) is associated with increased cardiovascular (CV) risk but underlying mechanisms remain uncertain. Arterial stiffness (AS) is associated with increased CV risk in advanced CKD, but it is unclear whether AS is relevant to CV disease (CVD) in early CKD. Study Design: Cross-sectional. Setting and participants: 1717 patients with previous estimated glomerular filtration rate (eGFR) 59–30 mL/min/1.73 m2; mean age 7369y, were recruited from 32 general practices in primary care. Outcomes: Increased arterial stiffness. Measurements: Medical history was obtained and participants underwent clinical assessment, urine and serum biochemistry testing. Carotid to femoral pulse wave velocity (PWV) was determined as a measure of AS, using a VicorderTM device. Results: Univariate analysis revealed significant correlations between PWV and risk factors for CVD including age (r = 0.456; p,0.001), mean arterial pressure (MAP) (r = 0.228; p,0.001), body mass index (r = 20.122; p,0.001), log urinary albumin to creatinine ratio (r = 0.124; p,0.001), Waist to Hip ratio (r = 0.124, p,0.001), eGFR (r = 20.074; p = 0.002), log high sensitivity c-reactive protein (r = 0.066; p = 0.006), HDL (r = 20.062; p = 0.01) and total cholesterol (r = 20.057; p = 0.02). PWV was higher in males (9.6 m/sec vs.10.3 m/sec; p,0.001), diabetics (9.8 m/sec vs. 10.3 m/sec; p,0.001), and those with previous CV events (CVE) (9.8 m/s vs. 10.3 m/sec; p,0.001). Multivariable analysis identified age, MAP and diabetes as strongest independent determinants of higher PWV (adjusted R2 = 0.29). An interactive term indicated that PWV increased to a greater extent with age in males versus females. Albuminuria was a weaker determinant of PWV and eGFR did not enter the model. Limitations: Data derived from one study visit, with absence of normal controls. Conclusion: In this cohort, age and traditional CV risk factors were the strongest determinants of AS. Albuminuria was a relatively weak determinant of AS and eGFR was not an independent determinant. Long-term follow-up will investigate AS as an independent risk factor for CVE in this cohort