8,197 research outputs found
Missing covariates in competing risks analysis.
Studies often follow individuals until they fail from one of a number of competing failure types. One approach to analyzing such competing risks data involves modeling the cause-specific hazards as functions of baseline covariates. A common issue that arises in this context is missing values in covariates. In this setting, we first establish conditions under which complete case analysis (CCA) is valid. We then consider application of multiple imputation to handle missing covariate values, and extend the recently proposed substantive model compatible version of fully conditional specification (SMC-FCS) imputation to the competing risks setting. Through simulations and an illustrative data analysis, we compare CCA, SMC-FCS, and a recent proposal for imputing missing covariates in the competing risks setting
The effects of aluminium and selenium supplementation on brain and liver antioxidant status in the rat
This in vivo study was designed to investigate the potential of aluminium (Al), in the absence of added iron, to participate in either antioxidant or pro-oxidant events. Some markers of oxidative stress were determined in liver and brain of rats exposed to aluminium lactate, either alone or in the presence of dietary supplements of selenium (se) as selenite. Exposure to aluminium for 21 days resulted in a statistically significant (P0.05) was observed in the GSH content. Contrary to what is known, Al exposure resulted in statistically significant decrease (
Data processing of remotely sensed airborne hyperspectral data using the Airborne Processing Library (APL): Geocorrection algorithm descriptions and spatial accuracy assessment
This is the author's preprint. The final version is available from the publisher via the DOI in this record.The authors would like to thank Dr. Peter Land for useful discussions on reflectance spectra of ground targets. Fig. 9 contains Ordnance Survey OpenData © Crown copyright and database right 2013. The hyperspectral data used in this report were collected by the Natural Environment Research Council Airborne Research and Survey Facility.Remote sensing airborne hyperspectral data are routinely used for applications including algorithm development for satellite sensors, environmental monitoring and atmospheric studies. Single flight lines of airborne hyperspectral data are often in the region of tens of gigabytes in size. This means that a single aircraft can collect terabytes of remotely sensed hyperspectral data during a single year. Before these data can be used for scientific analyses, they need to be radiometrically calibrated, synchronised with the aircraft's position and attitude and then geocorrected. To enable efficient processing of these large datasets the UK Airborne Research and Survey Facility has recently developed a software suite, the Airborne Processing Library (APL), for processing airborne hyperspectral data acquired from the Specim AISA Eagle and Hawk instruments. The APL toolbox allows users to radiometrically calibrate, geocorrect, reproject and resample airborne data. Each stage of the toolbox outputs data in the common Band Interleaved Lines (BILs) format, which allows its integration with other standard remote sensing software packages. APL was developed to be user-friendly and suitable for use on a workstation PC as well as for the automated processing of the facility; to this end APL can be used under both Windows and Linux environments on a single desktop machine or through a Grid engine. A graphical user interface also exists. In this paper we describe the Airborne Processing Library software, its algorithms and approach. We present example results from using APL with an AISA Eagle sensor and we assess its spatial accuracy using data from multiple flight lines collected during a campaign in 2008 together with in situ surveyed ground control points. © 2013 Elsevier Ltd
What e-patients want from the doctor-patient relationship: content analysis of posts on discussion boards.
People with long-term conditions are encouraged to take control and ownership of managing their condition. Interactions between health care staff and patients become partnerships with sharing of expertise. This has changed the doctor-patient relationship and the division of roles and responsibilities that traditionally existed, but what each party expects from the other may not always be clear. Information that people with long-term conditions share on Internet discussion boards can provide useful insights into their expectations of health care staff. This paper reports on a small study about the expectations that people with a long-term condition (diabetes) have of their doctors using information gleaned from Internet discussion boards
Analysis of time-to-event for observational studies: Guidance to the use of intensity models
This paper provides guidance for researchers with some mathematical
background on the conduct of time-to-event analysis in observational studies
based on intensity (hazard) models. Discussions of basic concepts like time
axis, event definition and censoring are given. Hazard models are introduced,
with special emphasis on the Cox proportional hazards regression model. We
provide check lists that may be useful both when fitting the model and
assessing its goodness of fit and when interpreting the results. Special
attention is paid to how to avoid problems with immortal time bias by
introducing time-dependent covariates. We discuss prediction based on hazard
models and difficulties when attempting to draw proper causal conclusions from
such models. Finally, we present a series of examples where the methods and
check lists are exemplified. Computational details and implementation using the
freely available R software are documented in Supplementary Material. The paper
was prepared as part of the STRATOS initiative.Comment: 28 pages, 12 figures. For associated Supplementary material, see
http://publicifsv.sund.ku.dk/~pka/STRATOSTG8
IFN-gamma is associated with risk of Schistosoma japonicum infection in China.
Before the start of the schistosomiasis transmission season, 129 villagers resident on a Schistosoma japonicum-endemic island in Poyang Lake, Jiangxi Province, 64 of whom were stool-positive for S. japonicum eggs by the Kato method and 65 negative, were treated with praziquantel. Forty-five days later the 93 subjects who presented for follow-up were all stool-negative. Blood samples were collected from all 93 individuals. S. japonicum soluble worm antigen (SWAP) and soluble egg antigen (SEA) stimulated IL-4, IL-5 and IFN-gamma production in whole-blood cultures were measured by ELISA. All the subjects were interviewed nine times during the subsequent transmission season to estimate the intensity of their contact with potentially infective snail habitats, and the subjects were all re-screened for S. japonicum by the Kato method at the end of the transmission season. Fourteen subjects were found to be infected at that time. There was some indication that the risk of infection might be associated with gender (with females being at higher risk) and with the intensity of water contact, and there was evidence that levels of SEA-induced IFN-gamma production were associated with reduced risk of infection
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Protocol for a randomized controlled trial examining multilevel prediction of response to behavioral activation and exposure-based therapy for generalized anxiety disorder.
BACKGROUND:Only 40-60% of patients with generalized anxiety disorder experience long-lasting improvement with gold standard psychosocial interventions. Identifying neurobehavioral factors that predict treatment success might provide specific targets for more individualized interventions, fostering more optimal outcomes and bringing us closer to the goal of "personalized medicine." Research suggests that reward and threat processing (approach/avoidance behavior) and cognitive control may be important for understanding anxiety and comorbid depressive disorders and may have relevance to treatment outcomes. This study was designed to determine whether approach-avoidance behaviors and associated neural responses moderate treatment response to exposure-based versus behavioral activation therapy for generalized anxiety disorder. METHODS/DESIGN:We are conducting a randomized controlled trial involving two 10-week group-based interventions: exposure-based therapy or behavioral activation therapy. These interventions focus on specific and unique aspects of threat and reward processing, respectively. Prior to and after treatment, participants are interviewed and undergo behavioral, biomarker, and neuroimaging assessments, with a focus on approach and avoidance processing and decision-making. Primary analyses will use mixed models to examine whether hypothesized approach, avoidance, and conflict arbitration behaviors and associated neural responses at baseline moderate symptom change with treatment, as assessed using the Generalized Anxiety Disorder-7 item scale. Exploratory analyses will examine additional potential treatment moderators and use data reduction and machine learning methods. DISCUSSION:This protocol provides a framework for how studies may be designed to move the field toward neuroscience-informed and personalized psychosocial treatments. The results of this trial will have implications for approach-avoidance processing in generalized anxiety disorder, relationships between levels of analysis (i.e., behavioral, neural), and predictors of behavioral therapy outcome. TRIAL REGISTRATION:The study was retrospectively registered within 21 days of first participant enrollment in accordance with FDAAA 801 with ClinicalTrials.gov, NCT02807480. Registered on June 21, 2016, before results
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