A b b re v i a t i o n s : AUC, area under the curve; 1st PH, first-phase insulin release; Gluc, plasma glucose concentration during the OGTT; HOMA, homeostasis model assessment; IGT, impaired glucose tolerance; Ins, plasma insulin concentration during the OGTT; IR, insulin resistance index; ISI, insulin sensitivity index; ISI(comp), composite insulin sensitivity index; MCR, metabolic clearance rate; NGT, normal glucose tolerance; OGTT, oral glucose tolerance test; 2nd PH, second-phase insulin release; Secr, insulin release index; SI, sensitivity index; S y x , residual error of re g ression; WHR, waist-to-hip ratio.A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances. Use of the Oral Glucose Tolerance Test to Assess Insulin Release and Insulin S e n s i t i v ity O R I G I N A L A R T I C L E O B J E C T I V E -The oral glucose tolerance test (OGTT) has often been used to evaluate a p p a rent insulin release and insulin resistance in various clinical settings. However, because insulin sensitivity and insulin release are interdependent, to what extent they can be pre d i c t e d f rom an OGTT is unclear.RESEARCH DESIGN AND METHODS -We studied insulin sensitivity using the euglycemic-hyperinsulinemic clamp and insulin release using the hyperglycemic clamp in 104 nondiabetic volunteers who had also undergone an OGTT. Demographic parameters (BMI, waist-to-hip ratio, age) and plasma glucose and insulin values from the OGTT were subjected to multiple linear re g ression to predict the metabolic clearance rate (MCR) of glucose, the insulin sensitivity index (ISI), and first-phase (1st PH) and second-phase (2nd PH) insulin release as measured with the respective clamps. R E S U LT S -The equations predicting MCR and ISI contained BMI, insulin (120 min), and glucose (90 min) and were highly correlated with the measured MCR (r = 0.80, P 0 . 0 0 0 0 5 ) and ISI (r = 0.79, P 0.00005). The equations predicting 1st PH and 2nd PH contained insulin (0 and 30 min) and glucose (30 min) and were also highly correlated with the measured 1st PH (r = 0.78, P 0.00005) and 2nd PH (r = 0.79, P 0.00005). The parameters predicted by our equations correlated better with the measured parameters than homeostasis model assessment for secretion and resistance, the 30-min insulin/ 30-min glucose ratio for secretion and insulin (120 min) for insulin resistance taken from the OGTT. C O N C L U S I O N S E p i d e m i o l o g y / H e a l t h S e r v i c e s / P s y c h o s o c i a l R e s e a r c h 296DIABETES CARE, VOLUME 23, NUMBER 3, MARCH 2000Insulin release and insulin sensitivity 0.5 kg/m 2 (19.7-45.8), and waist-to-hip ratio (WHR) 0.84 ± 0.10 (0.67-1.03); 65 had normal glucose tolerance (NGT), and the remainder had impaired glucose tolerance (IGT) according to the World Health O rganization criteria (1). Within 2 months, all subjects underwent a 75-g OGTT, a h y p e rglycemic clamp study in which the a rterialized venous plasma glucose concentration was increas...

Previous studies have suggested that living kidney donors maintain long-term renal function and experience no increase in cardiovascular or all-cause mortality. However, most analyses have included control groups less healthy than the living donor population and have had relatively short follow-up periods. Here we compared long-term renal function and cardiovascular and all-cause mortality in living kidney donors compared with a control group of individuals who would have been eligible for donation. All-cause mortality, cardiovascular mortality, and end-stage renal disease (ESRD) was identified in 1901 individuals who donated a kidney during 1963 through 2007 with a median follow-up of 15.1 years. A control group of 32,621 potentially eligible kidney donors was selected, with a median follow-up of 24.9 years. Hazard ratio for all-cause death was significantly increased to 1.30 (95% confidence interval 1.11-1.52) for donors compared with controls. There was a significant corresponding increase in cardiovascular death to 1.40 (1.03-1.91), while the risk of ESRD was greatly and significantly increased to 11.38 (4.37-29.6). The overall incidence of ESRD among donors was 302 cases per million and might have been influenced by hereditary factors. Immunological renal disease was the cause of ESRD in the donors. Thus, kidney donors are at increased long-term risk for ESRD, cardiovascular, and all-cause mortality compared with a control group of non-donors who would have been eligible for donation.

A consensus meeting was held in Vienna on September 8–9, 2013, to discuss diagnostic and therapeutic challenges surrounding development of diabetes mellitus after transplantation. The International Expert Panel comprised 24 transplant nephrologists, surgeons, diabetologists and clinical scientists, which met with the aim to review previous guidelines in light of emerging clinical data and research. Recommendations from the consensus discussions are provided in this article. Although the meeting was kidney-centric, reflecting the expertise present, these recommendations are likely to be relevant to other solid organ transplant recipients. Our recommendations include: terminology revision from new-onset diabetes after transplantation to posttransplantation diabetes mellitus (PTDM), exclusion of transient posttransplant hyperglycemia from PTDM diagnosis, expansion of screening strategies (incorporating postprandial glucose and HbA1c) and opinion-based guidance regarding pharmacological therapy in light of recent clinical evidence. Future research in the field was discussed with the aim of establishing collaborative working groups to address unresolved questions. These recommendations are opinion-based and intended to serve as a template for planned guidelines update, based on systematic and graded literature review, on the diagnosis and management of PTDM.

A key element in diabetic nephropathy (DN) is changes in the extracellular matrix (ECM) of several of the components in the kidney. From a clinical perspective, the changes seen in the ECM are important both in diagnostics and for prognostic and therapeutic purposes. In the current review, we present some of the central clinical issues related to DN, as well as the most relevant changes to the ECM from a diagnostic point of view, and also discuss some of the changes observed in one of the important ECM components, the proteoglycans (PGs). Our aim is not to cover all relevant research in this rather wide field, ranging from clinical trials to studies on microRNA and other important regulators of kidney function, but to focus particularly on some key issues related to PG changes in DN. Clinical Perspectives on DNAccording to estimates from the International Diabetes Federation, the worldwide prevalence of diabetes is estimated to increase from 285 million persons in 2010 to 439 millions in 2030, a relative increase of 50% (Shaw et al. 2010). Among patients with type 1 diabetes, the incidence of DN has apparently decreased from 30-35% in the cohorts who developed diabetes 40 to 50 years ago to 10-15% in recent cohorts (Bojestig et al. 1994;Hovind et al. 2003). However, due to the increase in type 2 diabetes, the absolute prevalence of DN has increased over the past two decades. In 2009, DN was reported to be the cause of 44% of all cases of end-stage renal disease (ESRD) in the United States (www.usrds.org), with an incidence of 155 diabetic patients developing ESRD per million each year. This fact was earlier announced as a "medical catastrophe of world-wide dimensions" (Ritz et al. 465073J HCXXX10.1369/0022155412465073Kolset et al.Extracellular Matrix and Diabetic Nephropathy 2012© The Author(s) 2010 Reprints and permission: sagepub.com/journalsPermissions. SummaryDiabetic nephropathy (DN) is a serious complication in diabetes. Major typical morphological changes are the result of changes in the extracellular matrix (ECM). Thus, basement membranes are thickened and the glomerular mesangial matrix and the tubulointerstitial space are expanded, due to increased amounts of ECM. One important ECM component, the proteoglycans (PGs), shows a more complex pattern of changes in DN. PGs in basement membranes are decreased but increased in the mesangium and the tubulointerstitial space. The amounts and structures of heparan sulfate chains are changed, and such changes affect levels of growth factors regulating cell proliferation and ECM synthesis, with cell attachment affecting endothelial cells and podocytes. Enzymes modulating heparan sulfate structures, such as heparanase and sulfatases, are implicated in DN. Other enzyme classes also modulate ECM proteins and PGs, such as matrix metalloproteinases (MMPs) and serine proteases, such as plasminogen activator, as well as their corresponding inhibitors. The levels of these enzymes and inhibitors are changed in plasma and in the kidneys in DN. Several growth factors, signali...