Patients with ankylosing spondylitis have increased sick leave—a registry-based case–control study over 7 yrs

Objectives. Using prospectively collected registry data to investigate sick leave (sickness benefit and sickness compensation) over a 7-yr period in patients with AS in comparison with population-based controls matched for age, sex and residential area

Estimation of Genetic Parameters for Growth, Feed Consumption, and Conformation Traits for Double-Muscled Belgian Blue Bulls Performance-Tested in Belgium

For 1,442 Belgian Blue bulls performance- tested at the Centre de Selection de la Race Blanc-Bleue Belge, nine traits were observed: height at withers at 7 mo, height at withers at 13 mo, weight at 7 mo, weight at 13 mo, average feed consumption of concentrates, average daily gain, average feed consumption of concentrates per average daily gain, average feed consumption of concentrates per mean metabolic weight, and price per kilogram of live weight. This price is based on muscle conformation and is therefore used as muscle conformation score. Restricted maximum likelihood with a derivative-free algorithm was used to estimate (co)variance components because there were different models and missing values per trait. Estimates of heritabilities were above .50 except for average feed consumption per average daily gain (.16) and average feed consumption per mean metabolic weight (.33). Estimates of genetic and phenotypic correlations between height at withers and weight traits were positive and moderate to high. Average daily gain showed a negative genetic correlation with weight at 7 mo ( -.68) but had positive correlations with height at withers at 13 mo and weight at 13 mo (.22 and .43). Muscle conformation expressed as price per kilogram of live weight was related to low average feed consumption per average daily gain. Average feed consumption showed high correlations with weight at 7 mo and weight at 13 mo. Average feed consumption per average daily gain had a high negative genetic correlation with average daily gain ( -.89)

ASAS/WHO ICF Core Sets for ankylosing spondylitis (AS): how to classify the impact of AS on functioning and health

Objective: To report on the results of a standardised consensus process agreeing on concepts typical and/or relevant when classifying functioning and health in patients with ankylosing spondylitis (AS) based on the International Classification of Functioning and Health (ICF).Methods: Experts in AS from different professional and geographical backgrounds attended a consensus conference and were divided into three working groups. Rheumatologists were selected from members of the Assessment of SpondyloArthritis international Society (ASAS). Other health professionals were recommended by ASAS members. The aim was to compose three working groups with five to seven participants to allow everybody's contribution in the discussions. Experts selected ICF categories that were considered typical and/or relevant for AS during a standardised consensus process by integrating evidence from preceding studies in alternating working group and plenary discussions. A Comprehensive ICF Core Set was selected for the comprehensive classification of functioning and a Brief ICF Core Set for application in trials.Results: The conference was attended by 19 experts from 12 countries. Eighty categories were included in the Comprehensive Core Set, which included 23 Body functions, 19 Body structures, 24 Activities and participation and 14 Environmental factors. Nineteen categories were selected for the Brief Core Set, which included 6 Body functions, 4 Body structures, 7 Activities and participation and 2 Environmental factors.Conclusion: The Comprehensive and Brief ICF Core Sets for AS are now available and aim to represent the external reference to define consequences of AS on functioning

Genetic fuzzy system predicting contractile reactivity patterns of small arteries

Monitoring of physiological surrogate end points in drug development generates dynamic time-domain data reflecting the state of the biological system. Conventional data analysis often reduces the information in these data by extracting specific data points, thereby discarding potentially useful information. We developed a genetic fuzzy system (GFS) algorithm that is capable of learning all information in time-domain physiological data. Data on isometric force development of isolated small arteries were used as a framework for developing and optimizing a GFS. GFS performance was improved by several strategies. Results show that optimized fuzzy systems (OFSs) predict contractile reactivity of arteries accurately. In addition, OFSs identified significant differences that were undetectable using conventional analysis in the responses of arteries between groups. We concluded that OFSs may be used in clustering or classification tasks as aids in the objective identification or prediction of dynamic physiological behavior