936 resultados para Shlomo Ben Ami
Resumo:
Background: A preliminary review of the UK Renal Registry (UKRR) pre-RRT study data revealed results suggesting that, for some patients, the date of start of renal replacement therapy (RRT), as reported to the UKRR, was incorrect and often significantly later than the true date of start. A more detailed study then aimed to validate a set of criteria to identify patients with an incorrect start date. Methods: Pre-RRT laboratory data were electronically extracted from 8,810 incident RRT patients from 9 UK renal centres. Any patient with a low urea (<15 mmol/L) at the start of RRT or with a substantial improvement in kidney function (either a fall in urea >10 mmol/L or rise in eGFR >2 ml/min/1.73 m) within the two months prior to RRT were considered to potentially have an incorrect date of start. In 4
selected centres, the electronic patient records of all patients flagged were reviewed to validate these criteria.
Results: Of 8,810 patients, 1,616 (18.3%) were flagged by the identification criteria as having a potentially incorrect date of start of RRT, although a single centre accounted for 41% of the total flagged cohort. Of these flagged patients, 61.7% had been assigned an incorrect date of start of haemodialysis (HD), 5.7% had evidence of acute RRT being given before the reported date of start of HD
and 9.2% had evidence of starting peritoneal dialysis exchanges prior to the reported date of start. Of
those flagged, 10.7% had a correct date of start of RRT.
Conclusions: Accurate reporting of RRT episodes is vital for the analysis of time dependent studies such as survival or time to transplantation. A proportion of patients starting RRT were assigned an incorrect start date. In order to improve the accuracy of this reporting the UK Renal Registry
must work with renal centres and clinical staff on improving data input for the start of RRT.
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OBJECTIVE: To examine a panel of 28 biomarkers for prediction of cardiovascular disease (CVD) and non-CVD mortality in a population-based cohort of men.
METHODS: Starting in 1979, middle-aged men in Caerphilly underwent detailed medical examination. Subsequently 2171 men were re-examined during 1989-1993, and fasting blood samples obtained from 1911 men (88%). Fibrinogen, viscosity and white cell count (WCC), routine biochemistry tests and lipids were analysed using fresh samples. Stored aliquots were later analysed for novel biomarkers. Statistical analysis of CVD and non-CVD mortality follow-up used competing risk Cox regression models with biomarkers in thirds tested at the 1% significance level after covariate adjustment.
RESULTS: During an average of 15.4years follow-up, troponin (subhazard ratio per third 1.71, 95% CI 1.46-1.99) and B-natriuretic peptide (BNP) (subhazard ratio per third 1.54, 95% CI 1.34-1.78) showed strong trends with CVD death but not with non-CVD death. WCC and fibrinogen showed similar weaker findings. Plasma viscosity, growth differentiation factor 15 (GDF-15) and interleukin-6 (IL-6) were associated positively with both CVD death and non-CVD death while total cholesterol was associated positively with CVD death but negatively with non-CVD death. C-reactive protein (C-RP), alkaline phosphatase, gamma-glutamyltransferase (GGT), retinol binding protein 4 (RBP-4) and vitamin B6 were significantly associated only with non-CVD death, the last two negatively. Troponin, BNP and IL-6 showed evidence of diminishing associations with CVD mortality through follow-up.
CONCLUSION: Biomarkers for cardiac necrosis were strong, specific predictors of CVD mortality while many inflammatory markers were equally predictive of non-CVD mortality.
Resumo:
Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10(-3), n = 22,044), increased triglycerides (p = 2.6×10(-14), n = 93,440), increased waist-to-hip ratio (p = 1.8×10(-5), n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10(-3), n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10(-13), n = 96,748) and decreased BMI (p = 1.4×10(-4), n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.
Resumo:
Whole-grain foods are touted for multiple health benefits, including enhancing insulin sensitivity and reducing type 2 diabetes risk. Recent genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) associated with fasting glucose and insulin concentrations in individuals free of diabetes. We tested the hypothesis that whole-grain food intake and genetic variation interact to influence concentrations of fasting glucose and insulin. Via meta-analysis of data from 14 cohorts comprising ∼ 48,000 participants of European descent, we studied interactions of whole-grain intake with loci previously associated in GWAS with fasting glucose (16 loci) and/or insulin (2 loci) concentrations. For tests of interaction, we considered a P value <0.0028 (0.05 of 18 tests) as statistically significant. Greater whole-grain food intake was associated with lower fasting glucose and insulin concentrations independent of demographics, other dietary and lifestyle factors, and BMI (β [95% CI] per 1-serving-greater whole-grain intake: -0.009 mmol/l glucose [-0.013 to -0.005], P < 0.0001 and -0.011 pmol/l [ln] insulin [-0.015 to -0.007], P = 0.0003). No interactions met our multiple testing-adjusted statistical significance threshold. The strongest SNP interaction with whole-grain intake was rs780094 (GCKR) for fasting insulin (P = 0.006), where greater whole-grain intake was associated with a smaller reduction in fasting insulin concentrations in those with the insulin-raising allele. Our results support the favorable association of whole-grain intake with fasting glucose and insulin and suggest a potential interaction between variation in GCKR and whole-grain intake in influencing fasting insulin concentrations.
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1791/07/20 (N524).
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Collection : Théâtre contemporain illustré ; 96e et 97e livraisons
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Collection : Théâtre contemporain illustré ; 96e et 97e livraisons
Resumo:
Collection : Théâtre contemporain illustré ; 96e et 97e livraisons
Resumo:
Collection : Théâtre contemporain illustré ; 96e et 97e livraisons
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Collection : Les archives de la Révolution française ; 8.262
