The Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) equation does not improve the underestimation of Glomerular Filtration Rate (GFR) in people with diabetes and preserved renal function

BackgroundOur hypothesis was that both the Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) equations would underestimate directly measured GFR (mGFR) to a similar extent in people with diabetes and preserved renal function.MethodsIn a cross-sectional study, bias (eGFR – mGFR) was compared for the CKD-EPI and MDRD equations, after stratification for mGFR levels. We also examined the ability of the CKD-EPI compared with the MDRD equation to correctly classify subjects to various CKD stages. In a longitudinal study of subjects with an early decline in GFR i.e., initial mGFR >60 ml/min/1.73 m2 and rate of decline in GFR (ΔmGFR) > 3.3 ml/min/1.73 m2 per year, ΔmGFR (based on initial and final values) was compared with ΔeGFR by the CKD-EPI and MDRD equations over a mean of 9 years.ResultsIn the cross-sectional study, mGFR for the whole group was 80 ± 2.2 ml/min/1.73 m2 (n = 199, 75 % type 2 diabetes). For subjects with mGFR >90 ml/min/1.73 m2 (mGFR: 112 ± 2.0, n = 76), both equations significantly underestimated mGFR to a similar extent: bias for CKD-EPI: -12 ± 1.4 ml/min/1.73 m2 (p < 0.001) and for MDRD: -11 ± 2.1 ml/min/1.73 m2 (p < 0.001). Using the CKD-EPI compared with the MDRD equation did not improve the number of subjects that were correctly classified to a CKD-stage. No biochemical or clinical patient characteristics were identified to account for the under estimation of mGFR values in the normal to high range by the CKD-EPI equation. In the longitudinal study (n = 30, 66 % type 1 diabetes), initial and final mGFR values were 102.8 ± 6 and 54.6 ± 6.0 ml/min/1.73 m2, respectively. Mean ΔGFR (ml/min/1.73 m2 per year) was 6.0 by mGFR compared with only 3.0 by MDRD and 3.2 by CKD-EPI (both p < 0.05 vs mGFR)ConclusionsBoth the CKD-EPI and MDRD equations underestimate reference GFR values >90 ml/min/1.73 m2 as well as an early decline in GFR to a similar extent in people with diabetes. There is scope to improve methods for estimating an early decline in GFR

MINMOD Millennium: A Computer Program to Calculate Glucose Effectiveness and Insulin Sensitivity From the Frequently Sampled Intravenous Glucose Tolerance Test

The Bergman Minimal Model enables estimation of two key indices of glucose/insulin dynamics: glucose effectiveness and insulin sensitivity. In this paper we describe MINMOD Millennium, the latest Windows-based version of minimal model software. Extensive beta testing of MINMOD Millennium has shown that it is user-friendly, fully automatic, fast, accurate, reproducible, repeatable, and highly concordant with past versions of MINMOD. It has a simple interface, a comprehensive help system, an input file editor, a file converter, an intelligent processing kernel, and a file exporter. It provides publication-quality charts of glucose and insulin and a table of all minimal model parameters and their error estimates. In contrast to earlier versions of MINMOD and some other minimal model programs, Millennium provides identified estimates of insulin sensitivity and glucose effectiveness for almost every subject

Relationships among Body Condition, Insulin Resistance and Subcutaneous Adipose Tissue Gene Expression during the Grazing Season in Mares

Obesity and insulin resistance have been shown to be risk factors for laminitis in horses. The objective of the study was to determine the effect of changes in body condition during the grazing season on insulin resistance and the expression of genes associated with obesity and insulin resistance in subcutaneous adipose tissue (SAT). Sixteen Finnhorse mares were grazing either on cultivated high-yielding pasture (CG) or semi-natural grassland (NG) from the end of May to the beginning of September. Body measurements, intravenous glucose tolerance test (IVGTT), and neck and tailhead SAT gene expressions were measured in May and September. At the end of grazing, CG had higher median body condition score (7 vs. 5.4, interquartile range 0.25 vs. 0.43; P=0.05) and body weight (618 kg vs. 572 kg +/- 10.21 (mean +/- SEM); P=0.02), and larger waist circumference (P=0.03) than NG. Neck fat thickness was not different between treatments. However, tailhead fat thickness was smaller in CG compared to NG in May (P=0.04), but this difference disappeared in September. Greater basal and peak insulin concentrations, and faster glucose clearance rate (P=0.03) during IVGTT were observed in CG compared to NG in September. A greater decrease in plasma non-esterified fatty acids during IVGTT (PPeer reviewe

Methods for the Detection of Seizure Bursts in Epilepsy

Background: Seizure clusters and “bursts” are of clinical importance. Clusters are reported to be a marker of antiepileptic drug resistance. Additionally, seizure clustering has been found to be associated with increased morbidity and mortality. However, there are no statistical methods described in the literature to delineate bursting phenomenon in epileptic seizures.Methods: We present three automatic burst detection methods referred to as precision constrained grouping (PCG), burst duration constrained grouping (BCG), and interseizure interval constrained grouping (ICG). Concordance correlation coefficients were used to confirm the pairwise agreement between common bursts isolated using these three automatic burst detection procedures. Additionally, three graphical methods were employed to demonstrate seizure bursts: modified scatter plots, staircase plots, and dropline plots. Burst detection procedures are demonstrated on data from continuous intracranial ambulatory EEG monitoring in a patient diagnosed with drug-refractory focal epilepsy.Results: We analyzed 1,569 seizures, from our assigned index patient, captured on ambulatory intracranial EEG monitoring. A total of 31, 32, and 32 seizure bursts were detected by the three quantitative methods (BCG, ICG, and PCG), respectively. The concordance correlation coefficient was ≥0.99 signifying considerably stronger than chance burst detector agreements with one another.Conclusions: Bursting is a quantifiable temporal phenomenon in epilepsy and seizure bursts can be reliably detected using our methodology

Invisible Diaspora?:English Ethnicity in the United States before 1920

The article presents an examination into the English population of the United States during the 19th and early 20th centuries, examining their ethnic identity as a diaspora community. Introductory details are given noting the relative lack of attention given to English Americans as an ethnic group. Topics addressed include reasons behind the invisibility of the English immigrant identity in the U.S., the existence of English ethnic organizations, and an overview of their activities

Saliva levels of Abeta1-42 as potential biomarker of Alzheimer's disease: a pilot study

<p>Abstract</p> <p>Background</p> <p>Simple, non-invasive tests for early detection of degenerative dementia by use of biomarkers are urgently required. However, up to the present, no validated extracerebral diagnostic markers for the early diagnosis of Alzheimer disease (AD) are available. The clinical diagnosis of probable AD is made with around 90% accuracy using modern clinical, neuropsychological and imaging methods. A biochemical marker that would support the clinical diagnosis and distinguish AD from other causes of dementia would therefore be of great value as a screening test. A total of 126 samples were obtained from subjects with AD, and age-sex-matched controls. Additionally, 51 Parkinson's disease (PD) patients were used as an example of another neurodegenerative disorder. We analyzed saliva and plasma levels of β amyloid (Aβ) using a highly sensitive ELISA kit.</p> <p>Results</p> <p>We found a small but statistically significant increase in saliva Aβ₄₂levels in mild AD patients. In addition, there were not differences in saliva concentration of Aβ₄₂between patients with PD and healthy controls. Saliva Aβ₄₀expression was unchanged within all the studied sample. The association between saliva Aβ₄₂levels and AD was independent of established risk factors, including age or Apo E, but was dependent on sex and functional capacity.</p> <p>Conclusions</p> <p>We suggest that saliva Aβ₄₂levels could be considered a potential peripheral marker of AD and help discrimination from other types of neurodegenerative disorders. We propose a new and promising biomarker for early AD.</p

Decision support systems for forest management: a comparative analysis and assessment

Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.compag.2013. 12.005.[EN] Decision Support Systems (DSS) are essential tools for forest management practitioners to help take account of the many environmental, economic, administrative, legal and social aspects in forest management. The most appropriate techniques to solve a particular instance usually depend on the characteristics of the decision problem. Thus, the objective of this article is to evaluate the models and methods that have been used in developing DSS for forest management, taking into account all important features to categorize the forest problems. It is interesting to know the appropriate methods to answer specific problems, as well as the strengths and drawbacks of each method. We have also pointed out new approaches to deal with the newest trends and issues. The problem nature has been related to the temporal scale, spatial context, spatial scale, number of objectives and decision makers or stakeholders and goods and services involved. Some of these problem dimensions are inter-related, and we also found a significant relationship between various methods and problem dimensions, all of which have been analysed using contingency tables. The results showed that 63% of forest DSS use simulation modelling methods and these are particularly related to the spatial context and spatial scale and the number of people involved in taking a decision. The analysis showed how closely Multiple Criteria Decision Making (MCDM) is linked to problem types involving the consideration of the number of objectives, also with the goods and services. On the other hand, there was no significant relationship between optimization and statistical methods and problem dimensions, although they have been applied to approximately 60% and 16% of problems solved by DSS for forest management, respectively. Metaheuristics and spatial statistical methods are promising new approaches to deal with certain problem formulations and data sources. Nine out of ten DSS used an associated information system (Database and/or Geographic Information System - GIS), but the availability and quality of data continue to be an important constraining issue, and one that could cause considerable difficulty in implementing DSS in practice. Finally, the majority of DSS do not include environmental and social values and focus largely on market economic values. The results suggest a strong need to improve the capabilities of DSS in this regard, developing and applying MCDM models and incorporating them in the design of DSS for forest management in coming years.The authors acknowledge the support received from European Cooperation in Science and Technology (COST Action FP0804 - Forest Management Decision Support Systems "FORSYS"), the Ministry of Economy and Competitiveness through the research project Multiple Criteria and Group Decision Making integrated into Sustainable Management, Ref. ECO2011-27369 and Ministry of Education (Training Plan of University Teaching). We also thank the editor and reviewers for their suggestions to improve the paper.Segura Maroto, M.; Ray, D.; Maroto Álvarez, MC. (2014). Decision support systems for forest management: a comparative analysis and assessment. Computers and Electronics in Agriculture. 101:55-67. https://doi.org/10.1016/j.compag.2013.12.005S556710

Potential applications of subseasonal-to-seasonal (S2S) predictions

While seasonal outlooks have been operational for many years, until recently the extended-range timescale referred to as subseasonal-to-seasonal (S2S) has received little attention. S2S prediction fills the gap between short-range weather prediction and long-range seasonal outlooks. Decisions in a range of sectors are made in this extended-range lead time; therefore, there is a strong demand for this new generation of forecasts. International efforts are under way to identify key sources of predictability, improve forecast skill and operationalize aspects of S2S forecasts; however, challenges remain in advancing this new frontier. If S2S predictions are to be used effectively, it is important that, along with science advances, an effort is made to develop, communicate and apply these forecasts appropriately. In this study, the emerging operational S2S forecasts are presented to the wider weather and climate applications community by undertaking the first comprehensive review of sectoral applications of S2S predictions, including public health, disaster preparedness, water management, energy and agriculture. The value of applications-relevant S2S predictions is explored, and the opportunities and challenges facing their uptake are highlighted. It is shown how social sciences can be integrated with S2S development, from communication to decision-making and valuation of forecasts, to enhance the benefits of ‘climate services’ approaches for extended-range forecasting. While S2S forecasting is at a relatively early stage of development, it is concluded that it presents a significant new window of opportunity that can be explored for application-ready capabilities that could allow many sectors the opportunity to systematically plan on a new time horizon