Waist-to-Hip Ratio, Cardiovascular Outcomes, and Death in Peritoneal Dialysis Patients

Objectives. The primary objective of this study was to determine the relationship between waist-to-hip ratio (WHR), cardiovascular (CV) events, and mortality in peritoneal dialysis (PD) patients. A secondary objective was to investigate the association between abdominal obesity and systemic inflammatory markers. Methods. This is a prospective study of 22 prevalent PD patients. WHR was measured at baseline. C-reactive protein (CRP), tumour necrosis factor-α (TNF-α), and interleukin-6 (IL-6) were measured. Main outcomes were first CV event and death from all causes. Survival analysis was used to examine the relationship between anthropomorphic measures and clinical outcomes. Results. Mean follow-up period was 3.1 years. In Kaplan-Meier analysis, survival was lower in those with higher WHR (P = .002). In Cox regression, WHR independently predicted mortality and first CV event after adjustment for known ischemic heart disease (hazard ratio [HR] 1.17, confidence interval [CI] 1.05–1.30 for death; HR 1.13, CI 1.01–1.26 for CV event). WHR correlated with serum TNF-α (r = 0.45; P = .05). Conclusion. The results of this study suggest WHR may be a risk factor for increased CV events and mortality in PD patients. Abdominal obesity is also associated with inflammatory markers. Larger studies are warranted to confirm these findings

An internet-based intervention with brief nurse support to manage obesity in primary care (POWeR+): a pragmatic, parallel-group, randomised controlled trial

Background The obesity epidemic has major public health consequences. Expert dietetic and behavioural counselling with intensive follow-up is effective, but resource requirements severely restrict widespread implementation in primary care, where most patients are managed. We aimed to estimate the effectiveness and cost-effectiveness of an internet-based behavioural intervention (POWeR+) combined with brief practice nurse support in primary care. Methods We did this pragmatic, parallel-group, randomised controlled trial at 56 primary care practices in central and south England. Eligible adults aged 18 years or older with a BMI of 30 kg/m2 or more (or ≥28 kg/m2 with hypertension, hypercholesterolaemia, or diabetes) registered online with POWeR+—a 24 session, web-based, weight management intervention lasting 6 months. After registration, the website automatically randomly assigned patients (1:1:1), via computer-generated random numbers, to receive evidence-based dietetic advice to swap foods for similar, but healthier, choices and increase fruit and vegetable intake, in addition to 6 monthly nurse follow-up (control group); web-based intervention and face-to-face nurse support (POWeR+Face-to-face [POWeR+F]; up to seven nurse contacts over 6 months); or web-based intervention and remote nurse support (POWeR+Remote [POWeR+R]; up to five emails or brief phone calls over 6 months). Participants and investigators were masked to group allocation at the point of randomisation; masking of participants was not possible after randomisation. The primary outcome was weight loss averaged over 12 months. We did a secondary analysis of weight to measure maintenance of 5% weight loss at months 6 and 12. We modelled the cost-effectiveness of each intervention. We did analysis by intention to treat, with multiple imputation for missing data. This trial is registered as an International Standard Randomised Controlled Trial, number ISRCTN21244703. Findings Between Jan 30, 2013, and March 20, 2014, 818 participants were randomly assigned to the control group (n=279), the POWeR+F group (n=269), or the POWeR+R group (n=270). Weight loss averaged over 12 months was recorded in 666 (81%) participants. The control group lost almost 3 kg over 12 months (crude mean weight: baseline 104·38 kg [SD 21·11; n=279], 6 months 101·91 kg [19·35; n=136], 12 months 101·74 kg [19·57; n=227]). The primary imputed analysis showed that compared with the control group, patients in the POWeR+F group achieved an additional weight reduction of 1·5 kg (95% CI 0·6–2·4; p=0·001) averaged over 12 months, and patients in the POWeR+R group achieved an additional 1·3 kg (0·34–2·2; p=0·007). 21% of patients in the control group had maintained a clinically important 5% weight reduction at month 12, compared with 29% of patients in the POWeR+F group (risk ratio 1·56, 0·96–2·51; p=0·070) and 32% of patients in the POWeR+R group (1·82, 1·31–2·74; p=0·004). The incremental overall cost to the health service per kg weight lost with the POWeR+ interventions versus the control strategy was £18 (95% CI −129 to 195) for POWeR+F and –£25 (−268 to 157) for POWeR+R; the probability of being cost-effective at a threshold of £100 per kg lost was 88% and 98%, respectively. No adverse events were reported. Interpretation Weight loss can be maintained in some individuals by use of novel written material with occasional brief nurse follow-up. However, more people can maintain clinically important weight reductions with a web-based behavioural program and brief remote follow-up, with no increase in health service costs. Future research should assess the extent to which clinically important weight loss can be maintained beyond 1 year

Dietary intakes of individual flavanols and flavonols are inversely associated with incident type 2 diabetes in European populations.

Dietary flavanols and flavonols, flavonoid subclasses, have been recently associated with a lower risk of type 2 diabetes (T2D) in Europe. Even within the same subclass, flavonoids may differ considerably in bioavailability and bioactivity. We aimed to examine the association between individual flavanol and flavonol intakes and risk of developing T2D across European countries. The European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct case-cohort study was conducted in 8 European countries across 26 study centers with 340,234 participants contributing 3.99 million person-years of follow-up, among whom 12,403 incident T2D cases were ascertained and a center-stratified subcohort of 16,154 individuals was defined. We estimated flavonoid intake at baseline from validated dietary questionnaires using a database developed from Phenol-Explorer and USDA databases. We used country-specific Prentice-weighted Cox regression models and random-effects meta-analysis methods to estimate HRs. Among the flavanol subclass, we observed significant inverse trends between intakes of all individual flavan-3-ol monomers and risk of T2D in multivariable models (all P-trend < 0.05). We also observed significant trends for the intakes of proanthocyanidin dimers (HR for the highest vs. the lowest quintile: 0.81; 95% CI: 0.71, 0.92; P-trend = 0.003) and trimers (HR: 0.91; 95% CI: 0.80, 1.04; P-trend = 0.07) but not for proanthocyanidins with a greater polymerization degree. Among the flavonol subclass, myricetin (HR: 0.77; 95% CI: 0.64, 0.93; P-trend = 0.001) was associated with a lower incidence of T2D. This large and heterogeneous European study showed inverse associations between all individual flavan-3-ol monomers, proanthocyanidins with a low polymerization degree, and the flavonol myricetin and incident T2D. These results suggest that individual flavonoids have different roles in the etiology of T2D.The EPIC-InterAct Study was supported by the European Union (Integrated Project LSHM-CT-2006-037197 in the Framework Programme 6 of the European Community). In addition, InterAct investigators acknowledge funding from the following agencies: R.Z.-R. was supported by a postdoctoral program Fondo de Investigación Sanitaria (FIS; no. CD09/00133) from the Spanish Ministry of Science; R.Z.-R. and C.A.G. were supported by the Health Research Fund (FIS) of the Spanish Ministry of Health (RTICC DR06/0020/0091); core support from the Medical Research Council (MRC) Epidemiology Unit is acknowledged for program MC_UU_12015/1 and MC_UU_12015/5; Y.T.v.d.S. was supported by NL Agency grant IGE05012 and an Incentive Grant from the Board of the UMC Utrecht (Netherlands); A.M.W.S. and D.L.v.d.A. were supported by the Dutch Ministry of Public Health, Welfare, and Sports, Netherlands Cancer Registry, LK Research Funds, Dutch Prevention Funds, Dutch ZON, World Cancer Research Fund, and Statistics Netherlands; T.J.K. and K.-T.K. were supported by Cancer Research UK; G.F., M.T., and F.P. were supported by Ligue contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale, INSERM; G.M. was supported by Ministero della Salute Regione Toscana Progetto Integrato Oncologia–PIO; P.W.F. was supported by the Swedish Research Council, Novo Nordisk, the Swedish Heart Lung Foundation, and the Swedish Diabetes Association; L.B., K.O., N.R., and A.T. were supported by the Danish Cancer Society; V.K. and T.K. were supported by Deutsche Krebshilfe; A.M. was supported by Associazione Italiana per la Ricerca sul Cancro; M.L.R. was supported by the Asturias Regional Government; M.G., P.A., E.M.-M., and M.J.T. were supported by the Health Research Fund of the Spanish Ministry of Health, CIBER Epidemiology and Public Health (Spain); M.J.T. was supported by the Murcia Regional Government; and R.T. was supported by AIRE-ONLUS Ragusa, AVIS-Ragusa, the Sicilian Regional Government.This is the final published version distributed under a Creative Commons Attribution Licence, which can also be found on the publisher's website at: http://jn.nutrition.org/content/144/3/335.ful

A combination of plasma phospholipid fatty acids and its association with incidence of type 2 diabetes: The EPIC-InterAct case-cohort study.

BACKGROUND: Combinations of multiple fatty acids may influence cardiometabolic risk more than single fatty acids. The association of a combination of fatty acids with incident type 2 diabetes (T2D) has not been evaluated. METHODS AND FINDINGS: We measured plasma phospholipid fatty acids by gas chromatography in 27,296 adults, including 12,132 incident cases of T2D, over the follow-up period between baseline (1991-1998) and 31 December 2007 in 8 European countries in EPIC-InterAct, a nested case-cohort study. The first principal component derived by principal component analysis of 27 individual fatty acids (mole percentage) was the main exposure (subsequently called the fatty acid pattern score [FA-pattern score]). The FA-pattern score was partly characterised by high concentrations of linoleic acid, stearic acid, odd-chain fatty acids, and very-long-chain saturated fatty acids and low concentrations of γ-linolenic acid, palmitic acid, and long-chain monounsaturated fatty acids, and it explained 16.1% of the overall variability of the 27 fatty acids. Based on country-specific Prentice-weighted Cox regression and random-effects meta-analysis, the FA-pattern score was associated with lower incident T2D. Comparing the top to the bottom fifth of the score, the hazard ratio of incident T2D was 0.23 (95% CI 0.19-0.29) adjusted for potential confounders and 0.37 (95% CI 0.27-0.50) further adjusted for metabolic risk factors. The association changed little after adjustment for individual fatty acids or fatty acid subclasses. In cross-sectional analyses relating the FA-pattern score to metabolic, genetic, and dietary factors, the FA-pattern score was inversely associated with adiposity, triglycerides, liver enzymes, C-reactive protein, a genetic score representing insulin resistance, and dietary intakes of soft drinks and alcohol and was positively associated with high-density-lipoprotein cholesterol and intakes of polyunsaturated fat, dietary fibre, and coffee (p < 0.05 each). Limitations include potential measurement error in the fatty acids and other model covariates and possible residual confounding. CONCLUSIONS: A combination of individual fatty acids, characterised by high concentrations of linoleic acid, odd-chain fatty acids, and very long-chain fatty acids, was associated with lower incidence of T2D. The specific fatty acid pattern may be influenced by metabolic, genetic, and dietary factors

Experimental systems to study the origin of the myofibroblast in peritoneal fibrosis

Peritoneal fibrosis is one of the major complications occurring in long-term peritoneal dialysis patients as a result of injury. Peritoneal fibrosis is characterized by submesothelial thickening and fibrosis which is associated with a decline in peritoneal membrane function. The myofibroblast has been identified as the key player involved in the development and progression of peritoneal fibrosis. Activation of the myofibroblast is correlated with expansion of the extracellular matrix and changes in peritoneal membrane integrity. Over the years, epithelial to mesenchymal transition (EMT) has been accepted as the predominant source of the myofibroblast. Peritoneal mesothelial cells have been described to undergo EMT in response to injury. Several animal and in vitro studies support the role of EMT in peritoneal fibrosis; however, emerging evidence from genetic fate-mapping studies has demonstrated that myofibroblasts may be arising from resident fibroblasts and pericytes/perivascular fibroblasts. In this review, we will discuss hypotheses currently surrounding the origin of the myofibroblast and highlight the experimental systems predominantly being used to investigate this

Transforming growth factor-beta and the glomerular filtration barrier

The increasing burden of chronic kidney disease worldwide and recent advancements in the understanding of pathologic events leading to kidney injury have opened up new potential avenues for therapies to further diminish progression of kidney disease by targeting the glomerular filtration barrier and reducing proteinuria. The glomerular filtration barrier is affected by many different metabolic and immune-mediated injuries. Glomerular endothelial cells, the glomerular basement membrane, and podocytes—the three components of the filtration barrier—work together to prevent the loss of protein and at the same time allow passage of water and smaller molecules. Damage to any of the components of the filtration barrier can initiate proteinuria and renal fibrosis. Transforming growth factor-beta (TGF-β) is a pleiotropic cytokine strongly associated with the fibrogenic response. It has a known role in tubulointerstitial fibrosis. In this review we will highlight what is known about TGF-β and how it interacts with the components of glomerular filtration barrier and causes loss of function and proteinuria

The pathophysiology of the peritoneal membrane

The development of peritoneal dialysis (PD) as a successful therapy has and still depends on experimental models to test and understand critical pieces of pathophysiology. To date, the majority of studies performed in rat and rabbit models derive mechanistic insights primarily on the basis of interventional pharmacologic agents, blocking antibodies, or transient expression systems. Because body size no longer limits the performance of in vivo studies of PD, genetic mouse models are increasingly available to investigate the molecular and pathophysiologic mechanisms of the peritoneal membrane. We illustrate in this review how these investigations are catching up with other areas of biomedical research and provide direct evidence for understanding transport and ultrafiltration, responses to infection, and structural changes including fibrosis and angiogenesis. These studies are relevant to mechanisms responsible not only for the major complications of PD but also for endothelial biology, host defense, inflammation, and tissue repair processes

The Gamma Test

The Gamma Test is a non-linear modelling analysis tool that allows us to quantify the extent to which a numerical input/output data set can be expressed as a smooth relationship. In essence, it allows us to efficiently calculate that part of the variance of the output that cannot be accounted for by the existence of any smooth model based on the inputs, even though this model is unknown. A key aspect of this tool is its speed: the Gamma Test has time complexity O(Mlog M), where M is the number of data-points. For data sets consisting of a few thousand points and a reasonable number of attributes, a single run of the Gamma Test typically takes a few seconds. In this chapter we will show how the Gamma Test can be used in the construction of predictive models and classifiers for numerical data. In doing so, we will demonstrate the use of this technique for feature selection, and for the selection of embedding dimension when dealing with a time-series