Automated real-time collection of pathogen-specific diagnostic data: Syndromic infectious disease epidemiology

© Lindsay Meyers, Christine C Ginocchio, Aimie N Faucett, Frederick S Nolte, Per H Gesteland, Amy Leber, Diane Janowiak,. Background: Health care and public health professionals rely on accurate, real-time monitoring of infectious diseases for outbreak preparedness and response. Early detection of outbreaks is improved by systems that are comprehensive and specific with respect to the pathogen but are rapid in reporting the data. It has proven difficult to implement these requirements on a large scale while maintaining patient privacy. Objective: The aim of this study was to demonstrate the automated export, aggregation, and analysis of infectious disease diagnostic test results from clinical laboratories across the United States in a manner that protects patient confidentiality. We hypothesized that such a system could aid in monitoring the seasonal occurrence of respiratory pathogens and may have advantages with regard to scope and ease of reporting compared with existing surveillance systems. Methods: We describe a system, BioFire Syndromic Trends, for rapid disease reporting that is syndrome-based but pathogen-specific. Deidentified patient test results from the BioFire FilmArray multiplex molecular diagnostic system are sent directly to a cloud database. Summaries of these data are displayed in near real time on the Syndromic Trends public website. We studied this dataset for the prevalence, seasonality, and coinfections of the 20 respiratory pathogens detected in over 362,000 patient samples acquired as a standard-of-care testing over the last 4 years from 20 clinical laboratories in the United States. Results: The majority of pathogens show influenza-like seasonality, rhinovirus has fall and spring peaks, and adenovirus and the bacterial pathogens show constant detection over the year. The dataset can also be considered in an ecological framework; the viruses and bacteria detected by this test are parasites of a host (the human patient). Interestingly, the rate of pathogen codetections, on average 7.94% (28,741/362,101), matches predictions based on the relative abundance of organisms present. Conclusions: Syndromic Trends preserves patient privacy by removing or obfuscating patient identifiers while still collecting much useful information about the bacterial and viral pathogens that they harbor. Test results are uploaded to the database within a few hours of completion compared with delays of up to 10 days for other diagnostic-based reporting systems. This work shows that the barriers to establishing epidemiology systems are no longer scientific and technical but rather administrative, involving questions of patient privacy and data ownership. We have demonstrated here that these barriers can be overcome. This first look at the resulting data stream suggests that Syndromic Trends will be able to provide high-resolution analysis of circulating respiratory pathogens and may aid in the detection of new outbreaks

Behavioral determinants as predictors of return to work after long-term sickness absence: an application of the theory of planned behavior

Background The aim of this prospective, longitudinal cohort study was to analyze the association between the three behavioral determinants of the theory of planned behavior (TPB) model-attitude, subjective norm and self-efficacy-and the time to return-to-work (RTW) in employees on long-term sick leave. Methods The study was based on a sample of 926 employees on sickness absence (maximum duration of 12 weeks). The employees filled out a baseline questionnaire and were subsequently followed until the tenth month after listing sick. The TPB-determinants were measured at baseline. Work attitude was measured with a Dutch language version of the Work Involvement Scale. Subjective norm was measured with a self-structured scale reflecting a person's perception of social support and social pressure. Self-efficacy was measured with the three subscales of a standardised Dutch version of the general self-efficacy scale (ALCOS): willingness to expend effort in completing the behavior, persistence in the face of adversity, and willingness to initiate behavior. Cox proportional hazards regression analyses were used to identify behavioral determinants of the time to RTW. Results Median time to RTW was 160 days. In the univariate analysis, all potential prognostic factors were significantly associated (P < 0.15) with time to RTW: work attitude, social support, and the three subscales of self-efficacy. The final multivariate model with time to RTW as the predicted outcome included work attitude, social support and willingness to expend effort in completing the behavior as significant predictive factors. Conclusions This prospective, longitudinal cohort-study showed that work attitude, social support and willingness to expend effort in completing the behavior are significantly associated with a shorter time to RTW in employees on long-term sickness absence. This provides suggestive evidence for the relevance of behavioral characteristics in the prediction of duration of sickness absence. It may be a promising approach to address the behavioral determinants in the development of interventions focusing on RTW in employees on long-term sick leave

Pion-nucleus elastic scattering on 12C, 40Ca, 90Zr, and 208Pb at 400 and 500 MeV

Pion-nucleus elastic scattering at energies above the Delta(1232) resonance is studied using both pi+ and pi- beams on 12C, 40Ca, 90Zr, and 208Pb. The present data provide an opportunity to study the interaction of pions with nuclei at energies where second-order corrections to impulse approximation calculations should be small. The results are compared with other data sets at similar energies, and with four different first-order impulse approximation calculations. Significant disagreement exists between the calculations and the data from this experiment

The effects of pause software on the temporal characteristics of computer use.

The study investigated the natural work-pause pattern of computer users and the possible effects of imposing pause regimes on this pattern. Hereto, the precise timing of computer events was recorded across a large number of days. It was found that the distribution of the pause durations was extremely skewed and that pauses with twice the duration are twice less likely to occur. The effects of imposing pause regimes were studied by performing a simulation of commercially available pause software. It was found that depending on the duration of the introduced pause, the software added 25-57% of the pauses taken naturally. Analysis of the timing of the introduced pauses revealed that a large number of spontaneous pauses were taken close to the inserted pause. Considering the disappointing results of studies investigating the effects of introducing (active) pauses during computer work, this study has cast doubt on the usefulness of introducing short duration pauses

Modelling Survival Events with Longitudinal Covariates Measured with Error

In survival analysis, time-dependent covariates are usually present as longitudinal data collected periodically and measured with error. The longitudinal data can be assumed to follow a linear mixed effect model and Cox regression models may be used for modelling of survival events. The hazard rate of survival times depends on the underlying time-dependent covariate measured with error, which may be described by random effects. Most existing methods proposed for such models assume a parametric distribution assumption on the random effects and specify a normally distributed error term for the linear mixed effect model. These assumptions may not be always valid in practice. In this article, we propose a new likelihood method for Cox regression models with error-contaminated time-dependent covariates. The proposed method does not require any parametric distribution assumption on random effects and random errors. Asymptotic properties for parameter estimators are provided. Simulation results show that under certain situations the proposed methods are more efficient than the existing methods. © 2013 Copyright Taylor and Francis Group, LLC

The Role of Parental Cognitive, Behavioral, and Motor Profiles in Clinical Variability in Individuals with Chromosome 16p11.2 Deletions

Importance Most disorders caused by copy number variants (CNVs) display significant clinical variability, often referred to as incomplete penetrance and variable expressivity. Genetic and environmental sources of this variability are not well understood. Objectives To investigate the contributors to phenotypic variability in probands with CNVs involving the same genomic region; to measure the effect size for de novo mutation events; and to explore the contribution of familial background to resulting cognitive, behavioral, and motor performance outcomes in probands with de novo CNVs. Design, Setting, and Participants Family-based study design with a volunteer sample of 56 individuals with de novo 16p11.2 deletions and their noncarrier parents and siblings from the Simons Variation in Individuals Project. Main Outcomes and Measures We used linear mixed-model analysis to measure effect size and intraclass correlation to determine the influence of family background for a de novo CNV on quantitative traits representing the following 3 neurodevelopmental domains: cognitive ability (Full-Scale IQ), social behavior (Social Responsiveness Scale), and neuromotor performance (Purdue Pegboard Test). We included an anthropometric trait, body mass index, for comparison. Results A significant deleterious effect of the 16p11.2 deletion was demonstrated across all domains. Relative to the biparental mean, the effect sizes were −1.7 SD for cognitive ability, 2.2 SD for social behavior, and −1.3 SD for neuromotor performance (P \u3c .001). Despite large deleterious effects, significant positive correlations between parents and probands were preserved for the Full-Scale IQ (0.42 [P = .03]), the verbal IQ (0.53 [P = .004]), and the Social Responsiveness Scale (0.52 [P = .009]) scores. We also observed a 1-SD increase in the body mass index of probands compared with siblings, with an intraclass correlation of 0.40 (P = .07). Conclusions and Relevance Analysis of families with de novo CNVs provides the least confounded estimate of the effect size of the 16p11.2 deletion on heritable, quantitative traits and demonstrates a 1- to 2-SD effect across all neurodevelopmental dimensions. Significant parent-proband correlations indicate that family background contributes to the phenotypic variability seen in this and perhaps other CNV disorders and may have implications for counseling families regarding their children’s developmental and psychiatric prognoses. Use of biparental mean scores rather than general population mean scores may be more relevant to examine the effect of a mutation or any other cause of trait variation on a neurodevelopmental outcome and possibly on systems of diagnosis and trait ascertainment for developmental disorders

Joint modeling of longitudinal outcomes and survival using latent growth modeling approach in a mesothelioma trial

Joint modeling of longitudinal and survival data can provide more efficient and less biased estimates of treatment effects through accounting for the associations between these two data types. Sponsors of oncology clinical trials routinely and increasingly include patient-reported outcome (PRO) instruments to evaluate the effect of treatment on symptoms, functioning, and quality of life. Known publications of these trials typically do not include jointly modeled analyses and results. We formulated several joint models based on a latent growth model for longitudinal PRO data and a Cox proportional hazards model for survival data. The longitudinal and survival components were linked through either a latent growth trajectory or shared random effects. We applied these models to data from a randomized phase III oncology clinical trial in mesothelioma. We compared the results derived under different model specifications and showed that the use of joint modeling may result in improved estimates of the overall treatment effect

The cost-effectiveness of the RSI QuickScan intervention programme for computer workers: Results of an economic evaluation alongside a randomised controlled trial

<p>Abstract</p> <p>Background</p> <p>The costs of arm, shoulder and neck symptoms are high. In order to decrease these costs employers implement interventions aimed at reducing these symptoms. One frequently used intervention is the RSI QuickScan intervention programme. It establishes a risk profile of the target population and subsequently advises interventions following a decision tree based on that risk profile. The purpose of this study was to perform an economic evaluation, from both the societal and companies' perspective, of the RSI QuickScan intervention programme for computer workers. In this study, effectiveness was defined at three levels: exposure to risk factors, prevalence of arm, shoulder and neck symptoms, and days of sick leave.</p> <p>Methods</p> <p>The economic evaluation was conducted alongside a randomised controlled trial (RCT). Participating computer workers from 7 companies (N = 638) were assigned to either the intervention group (N = 320) or the usual care group (N = 318) by means of cluster randomisation (N = 50). The intervention consisted of a tailor-made programme, based on a previously established risk profile. At baseline, 6 and 12 month follow-up, the participants completed the RSI QuickScan questionnaire. Analyses to estimate the effect of the intervention were done according to the intention-to-treat principle. To compare costs between groups, confidence intervals for cost differences were computed by bias-corrected and accelerated bootstrapping.</p> <p>Results</p> <p>The mean intervention costs, paid by the employer, were 59 euro per participant in the intervention and 28 euro in the usual care group. Mean total health care and non-health care costs per participant were 108 euro in both groups. As to the cost-effectiveness, improvement in received information on healthy computer use as well as in their work posture and movement was observed at higher costs. With regard to the other risk factors, symptoms and sick leave, only small and non-significant effects were found.</p> <p>Conclusions</p> <p>In this study, the RSI QuickScan intervention programme did not prove to be cost-effective from the both the societal and companies' perspective and, therefore, this study does not provide a financial reason for implementing this intervention. However, with a relatively small investment, the programme did increase the number of workers who received information on healthy computer use and improved their work posture and movement.</p> <p>Trial registration</p> <p>Trial registration number: NTR1117</p

The LANSCE RICE control system upgrade.

The LANSCE (Los Alamos Neutron Science Center) control system upgrade program continues with the impending replacement of the RICE (Remote Instrumentation and Control Equipment) subsystem. The RICE subsystem upgrade is a challenge because of its technology (late 1960s), number of channels (&gt;10,000), and unique characteristics (all-modules data takes, timed/flavored data takes). The plan is to replace at least the non-timed data and the command portions of the subsystem with Programmable Logic Controllers (PLCs). We discuss motivations, technological challenges, proof-of-principle, and planning. The boundary condition, as usual, is that we must implement these major changes on a running accelerator