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Substantial controversy surrounds the use of estimated glomerular filtration rate (eGFR) and albuminuria to define chronic kidney disease and assign its stages. We undertook a meta-analysis to assess the independent and combined associations of eGFR and albuminuria with mortality. In this collaborative meta-analysis of general population cohorts, we pooled standardised data for all-cause and cardiovascular mortality from studies containing at least 1000 participants and baseline information about eGFR and urine albumin concentrations. Cox proportional hazards models were used to estimate hazard ratios (HRs) for all-cause and cardiovascular mortality associated with eGFR and albuminuria, adjusted for potential confounders. The analysis included 105 872 participants (730 577 person-years) from 14 studies with urine albumin-to-creatinine ratio (ACR) measurements and 1 128 310 participants (4 732 110 person-years) from seven studies with urine protein dipstick measurements. In studies with ACR measurements, risk of mortality was unrelated to eGFR between 75 mL/min/1·73 m 2 and 105 mL/min/1·73 m 2 and increased at lower eGFRs. Compared with eGFR 95 mL/min/1·73 m 2, adjusted HRs for all-cause mortality were 1·18 (95% CI 1·05–1·32) for eGFR 60 mL/min/1·73 m 2, 1·57 (1·39–1·78) for 45 mL/min/1·73 m 2, and 3·14 (2·39–4·13) for 15 mL/min/1·73 m 2. ACR was associated with risk of mortality linearly on the log-log scale without threshold effects. Compared with ACR 0·6 mg/mmol, adjusted HRs for all-cause mortality were 1·20 (1·15–1·26) for ACR 1·1 mg/mmol, 1·63 (1·50–1·77) for 3·4 mg/mmol, and 2·22 (1·97–2·51) for 33·9 mg/mmol. eGFR and ACR were multiplicatively associated with risk of mortality without evidence of interaction. Similar findings were recorded for cardiovascular mortality and in studies with dipstick measurements. eGFR less than 60 mL/min/1·73 m 2 and ACR 1·1 mg/mmol (10 mg/g) or more are independent predictors of mortality risk in the general population. This study provides quantitative data for use of both kidney measures for risk assessment and definition and staging of chronic kidney disease. Kidney Disease: Improving Global Outcomes (KDIGO), US National Kidney Foundation, and Dutch Kidney Foundation.

In this study, patients with type 2 diabetes, albuminuria, and mild-to-moderate renal dysfunction received losartan followed by lisinopril or placebo. The study was stopped early because of increased risks of hyperkalemia and acute kidney injury with combination therapy. Diabetic nephropathy is the leading cause of end-stage renal disease (ESRD) in the United States. 1 Persons with diabetes and proteinuria are at high risk for progression to ESRD. 2 Blockade of the renin–angiotensin system decreases the progression of proteinuric kidney disease, 3 – 5 and the degree of reduction in proteinuria correlates with the extent to which the decrease in the glomerular filtration rate (GFR) is slowed. 2 , 6 Given these observations, it has been hypothesized that interventions that further lower proteinuria will further reduce the risk of progression. 6 Combination therapy with an angiotensin-converting–enzyme (ACE) inhibitor and an angiotensin II–receptor blocker (ARB) results in . . .

Foot infections are a common and serious problem in persons with diabetes. Diabetic foot infections (DFIs) typically begin in a wound, most often a neuropathic ulceration. While all wounds are colonized with microorganisms, the presence of infection is defined by ≥2 classic findings of inflammation or purulence. Infections are then classified into mild (superficial and limited in size and depth), moderate (deeper or more extensive), or severe (accompanied by systemic signs or metabolic perturbations). This classification system, along with a vascular assessment, helps determine which patients should be hospitalized, which may require special imaging procedures or surgical interventions, and which will require amputation. Most DFIs are polymicrobial, with aerobic gram-positive cocci (GPC), and especially staphylococci, the most common causative organisms. Aerobic gram-negative bacilli are frequently copathogens in infections that are chronic or follow antibiotic treatment, and obligate anaerobes may be copathogens in ischemic or necrotic wounds. Wounds without evidence of soft tissue or bone infection do not require antibiotic therapy. For infected wounds, obtain a post-debridement specimen (preferably of tissue) for aerobic and anaerobic culture. Empiric antibiotic therapy can be narrowly targeted at GPC in many acutely infected patients, but those at risk for infection with antibiotic-resistant organisms or with chronic, previously treated, or severe infections usually require broader spectrum regimens. Imaging is helpful in most DFIs; plain radiographs may be sufficient, but magnetic resonance imaging is far more sensitive and specific. Osteomyelitis occurs in many diabetic patients with a foot wound and can be difficult to diagnose (optimally defined by bone culture and histology) and treat (often requiring surgical debridement or resection, and/or prolonged antibiotic therapy). Most DFIs require some surgical intervention, ranging from minor (debridement) to major (resection, amputation). Wounds must also be properly dressed and off-loaded of pressure, and patients need regular follow-up. An ischemic foot may require revascularization, and some nonresponding patients may benefit from selected adjunctive measures. Employing multidisciplinary foot teams improves outcomes. Clinicians and healthcare organizations should attempt to monitor, and thereby improve, their outcomes and processes in caring for DFIs.

Nonhealing diabetic foot ulcers (DFUs) are a common and costly complication of diabetes. Microbial burden, or “bioburden,” is believed to underlie delayed healing, although little is known of those clinical factors that may influence microbial load, diversity, and/or pathogenicity. We profiled the microbiomes of neuropathic nonischemic DFUs without clinical evidence of infection in 52 individuals using high-throughput sequencing of the bacterial 16S ribosomal RNA gene. Comparatively, wound cultures, the standard diagnostic in the clinic, vastly underrepresent microbial load, microbial diversity, and the presence of potential pathogens. DFU microbiomes were heterogeneous, even in our tightly restricted study population, but partitioned into three clusters distinguished primarily by dominant bacteria and diversity. Ulcer depth was associated with ulcer cluster, positively correlated with abundance of anaerobic bacteria, and negatively correlated with abundance of Staphylococcus. Ulcer duration was positively correlated with bacterial diversity, species richness, and relative abundance of Proteobacteria, but was negatively correlated with relative abundance of Staphylococcus. Finally, poor glycemic control was associated with ulcer cluster, with poorest median glycemic control concentrating to Staphylococcus-rich and Streptococcus-rich ulcer clusters. Analyses of microbial community membership and structure may provide the most useful metrics in prospective studies to delineate problematic bioburden from benign colonization that can then be used to drive clinical treatment.

Aims/hypothesis Outcome data on individuals with diabetic foot ulcers are scarce, especially in those with peripheral arterial disease (PAD). We therefore examined the clinical characteristics that best predict poor outcome in a large population of diabetic foot ulcer patients and examined whether such predictors differ between patients with and without PAD. Methods Analyses were conducted within the EURODIALE Study, a prospective cohort study of 1,088 diabetic foot ulcer patients across 14 centres in Europe. Multiple logistic regression modelling was used to identify independent predictors of outcome (i.e. non-healing of the foot ulcer). Results After 1 year of follow-up, 23% of the patients had not healed. Independent baseline predictors of non-healing in the whole study population were older age, male sex, heart failure, the inability to stand or walk without help, end-stage renal disease, larger ulcer size, peripheral neuropathy and PAD. When analyses were performed according to PAD status, infection emerged as a specific predictor of non-healing in PAD patients only. Conclusions/interpretation Predictors of healing differ between patients with and without PAD, suggesting that diabetic foot ulcers with or without concomitant PAD should be defined as two separate disease states. The observed negative impact of infection on healing that was confined to patients with PAD needs further investigation.

Obstructive sleep apnea (OSA), a treatable sleep disorder that is associated with alterations in glucose metabolism in individuals without diabetes, is a highly prevalent comorbidity of type 2 diabetes. However, it is not known whether the severity of OSA is a predictor of glycemic control in patients with diabetes. To determine the impact of OSA on hemoglobin A1c (HbA1c), the major clinical indicator of glycemic control, in patients with type 2 diabetes. We performed polysomnography studies and measured HbA1c in 60 consecutive patients with diabetes recruited from outpatient clinics between February 2007 and August 2009. A total of 77% of patients with diabetes had OSA (apnea-hypopnea index [AHI] > or =5). Increasing OSA severity was associated with poorer glucose control, after controlling for age, sex, race, body mass index, number of diabetes medications, level of exercise, years of diabetes and total sleep time. Compared with patients without OSA, the adjusted mean HbA1c was increased by 1.49% (P = 0.0028) in patients with mild OSA, 1.93% (P = 0.0033) in patients with moderate OSA, and 3.69% (P < 0.0001) in patients with severe OSA (P < 0.0001 for linear trend). Measures of OSA severity, including total AHI (P = 0.004), rapid eye movement AHI (P = 0.005), and the oxygen desaturation index during total and rapid eye movement sleep (P = 0.005 and P = 0.008, respectively) were positively correlated with increasing HbA1c levels. In patients with type 2 diabetes, increasing severity of OSA is associated with poorer glucose control, independent of adiposity and other confounders, with effect sizes comparable to those of widely used hypoglycemic drugs.

Intervention in the renin-angiotensin-aldosterone-system (RAAS) is associated with slowing the progressive loss of renal function. During initiation of therapy, however, there may be an acute fall in glomerular filtration rate (GFR). We tested whether this initial fall in GFR reflects a renal hemodynamic effect and whether this might result in a slower decline in long-term renal function. We performed a post hoc analysis of the Reduction of Endpoints in Non-Insulin-Dependent Diabetes Mellitus with the Angiotensin II Antagonist Losartan (RENAAL) trial. Patients assigned to losartan had a significantly greater acute fall in estimated (eGFR) during the first 3 months compared to patients assigned to placebo, but a significantly slower long-term mean decline of eGFR thereafter. A large interindividual difference, however, was noticed in the acute eGFR change. When patients were divided into tertiles of initial fall in eGFR, the long-term eGFR slope calculated from baseline was significantly higher in patients with an initial fall compared to those with an initial rise. When eGFR decline was calculated from 3 months to the final visit, excluding the initial effect, patients with a large initial fall in eGFR had a significant lower long-term eGFR slope compared to those with a moderate fall or rise. This relationship was independent of other risk markers or change in risk markers for progression of renal disease such as blood pressure and albuminuria. Thus, the greater the acute fall in eGFR, during losartan treatment, the slower the rate of long-term eGFR decline. Hence, interpretation of trial results relying on slope-based GFR outcomes should separate the initial drug-induced GFR change from the subsequent long-term effect on GFR.

Diabetic nephropathy (DN) is a progressive kidney disease, a well-known complication of long-standing diabetes. DN is the most frequent reason for dialysis in many Western countries. Early detection may enable development of specific drugs and early initiation of therapy, thereby postponing/preventing the need for renal replacement therapy. We evaluated urinary proteome analysis as a tool for prediction of DN. Capillary electrophoresis–coupled mass spectrometry was used to profile the low–molecular weight proteome in urine. We examined urine samples from a longitudinal cohort of type 1 and 2 diabetic patients (n = 35) using a previously generated chronic kidney disease (CKD) biomarker classifier to assess peptides of collected urines for signs of DN. The application of this classifier to samples of normoalbuminuric subjects up to 5 years prior to development of macroalbuminuria enabled early detection of subsequent progression to macroalbuminuria (area under the curve [AUC] 0.93) compared with urinary albumin routinely used to determine the diagnosis (AUC 0.67). Statistical analysis of each urinary CKD biomarker depicted its regulation with respect to diagnosis of DN over time. Collagen fragments were prominent biomarkers 3–5 years before onset of macroalbuminuria. Before albumin excretion starts to increase, there is a decrease in collagen fragments. Urinary proteomics enables noninvasive assessment of DN risk at an early stage via determination of specific collagen fragments.

Aims/hypothesis The aim of this meta-analysis is to determine the predictive value of diabetic retinopathy in differentiating diabetic nephropathy from non-diabetic renal diseases in patients with type 2 diabetes and renal disease. Methods Medline and Embase databases were searched from inception to February 2012. Renal biopsy studies of participants with type 2 diabetes were included if they contained data with measurements of diabetic retinopathy. Pooled sensitivity, specificity, positive predictive value, negative predictive value and other diagnostic indices were evaluated using a random-effects model. Results The meta-analysis investigated 26 papers with 2012 patients. The pooled sensitivity and specificity of diabetic retinopathy to predict diabetic nephropathy were 0.65 (95% CI 0.62, 0.68) and 0.75 (95% CI 0.73, 0.78), respectively. The pooled positive and negative predictive value of diabetic retinopathy to predict diabetic nephropathy were 0.72 (95% CI 0.68, 0.75) and 0.69 (95% CI 0.67, 0.72), respectively. The area under the summary receiver operating characteristic curve was 0.75, and the diagnostic odds ratio was 5.67 (95% CI 3.45, 9.34). For proliferative diabetic retinopathy, the pooled sensitivity was 0.25 (95% CI 0.16, 0.35), while the specificity was 0.98 (95% CI 0.92, 1.00). There was heterogeneity among studies ( p <  0.001), and no publishing bias was identified. Conclusions/interpretation Diabetic retinopathy is useful in diagnosing or screening for diabetic nephropathy in patients with type 2 diabetes and renal disease. Proliferative diabetic retinopathy may be a highly specific indicator for diabetic nephropathy.

Urinary exosomes are 40–100nm vesicles containing protein, mRNA, and microRNA that may serve as biomarkers of renal dysfunction and structural injury. Currently, there is a need for more sensitive and specific biomarkers of renal injury and disease progression. Here we sought to identify the best exosome isolation methods for both proteomic analysis and RNA profiling as a first step for biomarker discovery. We used six different protocols; three were based on ultracentrifugation, one used a nanomembrane concentrator–based approach, and two utilized a commercial exosome precipitation reagent. The highest yield of exosomes was obtained using a modified exosome precipitation protocol, which also yielded the highest quantities of microRNA and mRNA and, therefore, is ideal for subsequent RNA profiling. This method is likewise suitable for downstream proteomic analyses if an ultracentrifuge is not available and/or a large number of samples are to be processed. Two of the ultracentrifugation methods, however, are better options for exosome isolation if an ultracentrifuge is available and few samples will be processed for proteomic analysis. Thus, our modified exosome precipitation method is a simple, fast, highly scalable, and effective alternative for the isolation of exosomes, and may facilitate the identification of exosomal biomarkers from urine.