Mining free-text medical records for companion animal enteric syndrome surveillance.

Large amounts of animal health care data are present in veterinary electronic medical records (EMR) and they present an opportunity for companion animal disease surveillance. Veterinary patient records are largely in free-text without clinical coding or fixed vocabulary. Text-mining, a computer and information technology application, is needed to identify cases of interest and to add structure to the otherwise unstructured data. In this study EMR's were extracted from veterinary management programs of 12 participating veterinary practices and stored in a data warehouse. Using commercially available text-mining software (WordStat™), we developed a categorization dictionary that could be used to automatically classify and extract enteric syndrome cases from the warehoused electronic medical records. The diagnostic accuracy of the text-miner for retrieving cases of enteric syndrome was measured against human reviewers who independently categorized a random sample of 2500 cases as enteric syndrome positive or negative. Compared to the reviewers, the text-miner retrieved cases with enteric signs with a sensitivity of 87.6% (95%CI, 80.4-92.9%) and a specificity of 99.3% (95%CI, 98.9-99.6%). Automatic and accurate detection of enteric syndrome cases provides an opportunity for community surveillance of enteric pathogens in companion animals.

Using Informatics and the Electronic Medical Record to Describe Antimicrobial Use in the Clinical Management of Diarrhea Cases at 12 Companion Animal Practices

Antimicrobial drugs may be used to treat diarrheal illness in companion animals. It is important to monitor antimicrobial use to better understand trends and patterns in antimicrobial resistance. There is no monitoring of antimicrobial use in companion animals in Canada. To explore how the use of electronic medical records could contribute to the ongoing, systematic collection of antimicrobial use data in companion animals, anonymized electronic medical records were extracted from 12 participating companion animal practices and warehoused at the University of Calgary. We used the pre-diagnostic, clinical features of diarrhea as the case definition in this study. Using text-mining technologies, cases of diarrhea were described by each of the following variables: diagnostic laboratory tests performed, the etiological diagnosis and antimicrobial therapies. The ability of the text miner to accurately describe the cases for each of the variables was evaluated. It could not reliably classify cases in terms of diagnostic tests or etiological diagnosis; a manual review of a random sample of 500 diarrhea cases determined that 88/500 (17.6%) of the target cases underwent diagnostic testing of which 36/88 (40.9%) had an etiological diagnosis. Text mining, compared to a human reviewer, could accurately identify cases that had been treated with antimicrobials with high sensitivity (92%, 95% confidence interval, 88.1%-95.4%) and specificity (85%, 95% confidence interval, 80.2%-89.1%). Overall, 7400/15,928 (46.5%) of pets presenting with diarrhea were treated with antimicrobials. Some temporal trends and patterns of the antimicrobial use are described. The results from this study suggest that informatics and the electronic medical records could be useful for monitoring trends in antimicrobial use.

Risk factors for potentially avoidable readmissions due to end-of-life care issues

BACKGROUND Repeated hospitalizations are frequent toward the end of life, where each admission should be an opportunity to initiate advance-care planning to high-risk patients. OBJECTIVE To identify the risk factors for having a 30-day potentially avoidable readmission due to end-of-life care issues among all medical patients. DESIGN Nested case-control study. SETTING/PATIENTS All 10,275 consecutive discharges from any medical service of an academic tertiary medical center in Boston, Massachusetts between July 1, 2009 and June 30, 2010. MEASUREMENTS A random sample of all the potentially avoidable 30-day readmissions was independently reviewed by 9 trained physicians to identify the ones due to end-of-life issues. RESULTS Among 534, 30-day potentially avoidable readmission cases reviewed, 80 (15%) were due to an end-of-life care issue. In multivariable analysis, the following risk factors were significantly associated with a 30-day potentially avoidable readmission due to end-of-life care issues: number of admissions in the previous 12 months (odds ratio [OR]: 1.10 per admission, 95% confidence interval [CI]: 1.02-1.20), neoplasm (OR: 5.60, 95% CI: 2.85-10.98), opiate medications at discharge (OR: 2.29, 95% CI: 1.29-4.07), Elixhauser comorbidity index (OR: 1.16 per 5-point increase, 95% CI: 1.10-1.22). The discrimination of the model (C statistic) was 0.85. CONCLUSIONS In a medical population, we identified 4 main risk factors that were significantly associated with 30-day potentially avoidable readmission due to end-of-life care issues, producing a model with very good to excellent discrimination. Patients with these risk factors might benefit from palliative care consultation prior to discharge in order to improve end-of-life care and possibly reduce unnecessary rehospitalizations.

Überlegungen zum Berner Stichprobenplan

Fritschi, Meyer und Schweizer haben vor drei Jahrzehnten in der Schweizerischen Zeitschrift für Soziologie ein elegantes Stichprobenverfahren für ein gesamtschweizerisches Sample vorgeschlagen, bei dem die Befragungspersonen mit Hilfe kommunaler Wahl- oder Einwohnerregister bestimmt werden. Ungeachtet der Vorzüge dieser Methode beruhen heute die meisten Bevölkerungsumfragen in der Schweiz aber auf Telefonregisterstichproben, die bezüglich der Abdeckung der Grundgesamtheit als problematisch anzusehen sind. Sozusagen als Wiederbelebungsversuch möchte ich deshalb hier einige Überlegungen zum Stichprobenplan von Fritschi et al. präsentieren. Die theoretischen Eigenschaften des Stichprobenplans werden besprochen und ein vereinfachtes Verfahren, die ex ante geteilte Stichprobe, wird vorgeschlagen. Mit Hilfe einer Simulationsstudie werden sodann die Vorzüge des "Berner Stichprobenplans" gegenüber einer einfachen Klumpenstichprobe illustriert.

The Use of New Technology and Occupational Mobility: An Event History Analysis of the Swiss Labor Market

The investigation of the consequences of new technologies has a long standing tradition within economics. Particularly, labor economists are wondering how the introduction of new technologies, e.g. Personal Computers, have shaped labor markets. Former research has concentrated on the question of whether on-the-job use of PCs creates a wage bonus for employees. In this paper, we investigate whether the use of PCs increases employees’ probability of an upward shift in their employment status and whether it reduces the risk of involuntary labor market exits. We do so by applying event history analysis to the Swiss Labor Market Survey, a random sample of 3028 respondents, and by analyzing a Panel sub-sample of 650 respondents conducted recently in Switzerland. Our results show that on-the-job use of PCs was beneficial for employees in the past by increasing their probability of an upward shift by approximately 50%. The analysis also suggests that PC use reduces the risk and duration of unemployment. However, these latter results fail to reach statistical significance.

Longitudinal associations between causal sexual relationships and stressful life events in emerging adults

Findings on the consequences of casual sexual relationships (CSR) are inconsistent and range from positive to negative outcomes. The longitudinal association between stressful live events and CSR was investigated in a random sample of 2844 Swiss emerging adults. Cross-lagged panel models with baseline, two- and five-year follow-up data showed that life events predicted more subsequent CSR across emerging adulthood. In contrast, CSR predicted life events only from the first to the second wave. Results suggest that the link between stressful life events and CSR was mainly explained by romantic breakups as stressful life event. Environment-related life events were not substantially associated with casual sexual relationships. Thus, engaging in CSR did not seem to be a general emotion-focused coping strategy in the context of life events nor can the engagement in casual sex be seen as a result of stressful life events affecting general self-regulation.

What is the influence of randomisation sequence generation and allocation concealment on treatment effects of physical therapy trials? A meta-epidemiological study.

OBJECTIVE To determine if adequacy of randomisation and allocation concealment is associated with changes in effect sizes (ES) when comparing physical therapy (PT) trials with and without these methodological characteristics. DESIGN Meta-epidemiological study. PARTICIPANTS A random sample of randomised controlled trials (RCTs) included in meta-analyses in the PT discipline were identified. INTERVENTION Data extraction including assessments of random sequence generation and allocation concealment was conducted independently by two reviewers. To determine the association between sequence generation, and allocation concealment and ES, a two-level analysis was conducted using a meta-meta-analytic approach. PRIMARY AND SECONDARY OUTCOME MEASURES association between random sequence generation and allocation concealment and ES in PT trials. RESULTS 393 trials included in 43 meta-analyses, analysing 44 622 patients contributed to this study. Adequate random sequence generation and appropriate allocation concealment were accomplished in only 39.7% and 11.5% of PT trials, respectively. Although trials with inappropriate allocation concealment tended to have an overestimate treatment effect when compared with trials with adequate concealment of allocation, the difference was non-statistically significant (ES=0.12; 95% CI -0.06 to 0.30). When pooling our results with those of Nuesch et al, we obtained a pooled statistically significant value (ES=0.14; 95% CI 0.02 to 0.26). There was no difference in ES in trials with appropriate or inappropriate random sequence generation (ES=0.02; 95% CI -0.12 to 0.15). CONCLUSIONS Our results suggest that when evaluating risk of bias of primary RCTs in PT area, systematic reviewers and clinicians implementing research into practice should pay attention to these biases since they could exaggerate treatment effects. Systematic reviewers should perform sensitivity analysis including trials with low risk of bias in these domains as primary analysis and/or in combination with less restrictive analyses. Authors and editors should make sure that allocation concealment and random sequence generation are properly reported in trial reports.

Direct Democracy and Institutional Trust: Relationships and Differences across Personality Traits

Direct democracy plays a prominent role in the explanation of institutional trust. To date, however, empirical findings on the effects of direct democracy remain inconclusive. In this article, we argue that this inconclusiveness can be partly ascribed to the diverse effects direct democracy has on individuals. In other words, direct democracy influences institutional trust, but how and to what degree depends on individuals’ personality traits. Running hierarchical analyses of unique survey data from a random sample of eligible Swiss voters, we document three findings: First, we show that the number of ballot measures is not directly associated with institutional trust. Second, we demonstrate that the Big Five personality traits affect the propensity to trust. Third, some of these traits also alter the relationship between direct democracy and institutional trust, suggesting that certain personality types are more likely to be sensitive to popular votes than others and that not everyone is equally likely to respond to political stimuli, even in highly democratic environments.

Opting for an Open Society? Personality Traits and Attitudes toward the Openness of Switzerland

The tension between openness and closedness is one of the most important cleavages in Swiss political debates. In the present article, we study the psychological foundations of attitudes regarding this issue. More precisely, we examine the link between personality and attitudes toward the degree of openness of Switzerland as a general stance toward the cultural, economic and political alignment of the country. Personality is understood as a complex and multifaceted concept that forms the basis for consistent patterns of attitudes and behavior. We build on the Five-Factor Theory to explain the link between personality traits, contextual factors and political attitudes. Analyzing survey data from a random sample of Swiss citizens, we find clear evidence that personality traits affect political attitudes. Furthermore, we are able to demonstrate that the relationship between personality and attitudes toward the degree of openness of Switzerland is moderated by perceived ethnic diversity in the neighborhood.

Retinal slit lamp video mosaicking

Purpose To this day, the slit lamp remains the first tool used by an ophthalmologist to examine patient eyes. Imaging of the retina poses, however, a variety of problems, namely a shallow depth of focus, reflections from the optical system, a small field of view and non-uniform illumination. For ophthalmologists, the use of slit lamp images for documentation and analysis purposes, however, remains extremely challenging due to large image artifacts. For this reason, we propose an automatic retinal slit lamp video mosaicking, which enlarges the field of view and reduces amount of noise and reflections, thus enhancing image quality. Methods Our method is composed of three parts: (i) viable content segmentation, (ii) global registration and (iii) image blending. Frame content is segmented using gradient boosting with custom pixel-wise features. Speeded-up robust features are used for finding pair-wise translations between frames with robust random sample consensus estimation and graph-based simultaneous localization and mapping for global bundle adjustment. Foreground-aware blending based on feathering merges video frames into comprehensive mosaics. Results Foreground is segmented successfully with an area under the curve of the receiver operating characteristic curve of 0.9557. Mosaicking results and state-of-the-art methods were compared and rated by ophthalmologists showing a strong preference for a large field of view provided by our method. Conclusions The proposed method for global registration of retinal slit lamp images of the retina into comprehensive mosaics improves over state-of-the-art methods and is preferred qualitatively.

The temporal evolution of nonverbal synchrony in outpatient psychotherapy: An aggregation of single-case studies

Objective: The authors quantified nonverbal synchrony—the coordination of patient's and therapist's movement—in a random sample of same-sex psychotherapy dyads. The authors contrasted nonverbal synchrony in these dyads with a control condition and assessed its association with session-level and overall psychotherapy outcome. Method: Using an automated objective video analysis algorithm (Motion Energy Analysis; MEA), the authors calculated nonverbal synchrony in (n = 104) videotaped psychotherapy sessions from 70 Caucasian patients (37 women, 33 men, mean age = 36.5 years, SD = 10.2) treated at an outpatient psychotherapy clinic. The sample was randomly drawn from an archive (N = 301) of routinely videotaped psychotherapies. Patients and their therapists assessed session impact with self-report postsession questionnaires. A battery of pre- and postsymptomatology questionnaires measured therapy effectiveness. Results: The authors found that nonverbal synchrony is higher in genuine interactions contrasted with pseudointeractions (a control condition generated by a specifically designed shuffling procedure). Furthermore, nonverbal synchrony is associated with session-level process as well as therapy outcome: It is increased in sessions rated by patients as manifesting high relationship quality and in patients experiencing high self-efficacy. Higher nonverbal synchrony characterized psychotherapies with higher symptom reduction. Conclusions: The results suggest that nonverbal synchrony embodies the patients' self-reported quality of the relationship and further variables of therapy process. This hitherto overlooked facet of therapeutic relationships might prove useful as an indicator of therapy progress and outcome. (PsycINFO Database Record (c) 2015 APA, all rights reserved)

MOREMATA: Stata module (Mata) to provide various functions

This package includes various Mata functions. kern(): various kernel functions; kint(): kernel integral functions; kdel0(): canonical bandwidth of kernel; quantile(): quantile function; median(): median; iqrange(): inter-quartile range; ecdf(): cumulative distribution function; relrank(): grade transformation; ranks(): ranks/cumulative frequencies; freq(): compute frequency counts; histogram(): produce histogram data; mgof(): multinomial goodness-of-fit tests; collapse(): summary statistics by subgroups; _collapse(): summary statistics by subgroups; gini(): Gini coefficient; sample(): draw random sample; srswr(): SRS with replacement; srswor(): SRS without replacement; upswr(): UPS with replacement; upswor(): UPS without replacement; bs(): bootstrap estimation; bs2(): bootstrap estimation; bs_report(): report bootstrap results; jk(): jackknife estimation; jk_report(): report jackknife results; subset(): obtain subsets, one at a time; composition(): obtain compositions, one by one; ncompositions(): determine number of compositions; partition(): obtain partitions, one at a time; npartitionss(): determine number of partitions; rsubset(): draw random subset; rcomposition(): draw random composition; colvar(): variance, by column; meancolvar(): mean and variance, by column; variance0(): population variance; meanvariance0(): mean and population variance; mse(): mean squared error; colmse(): mean squared error, by column; sse(): sum of squared errors; colsse(): sum of squared errors, by column; benford(): Benford distribution; cauchy(): cumulative Cauchy-Lorentz dist.; cauchyden(): Cauchy-Lorentz density; cauchytail(): reverse cumulative Cauchy-Lorentz; invcauchy(): inverse cumulative Cauchy-Lorentz; rbinomial(): generate binomial random numbers; cebinomial(): cond. expect. of binomial r.v.; root(): Brent's univariate zero finder; nrroot(): Newton-Raphson zero finder; finvert(): univariate function inverter; integrate_sr(): univariate function integration (Simpson's rule); integrate_38(): univariate function integration (Simpson's 3/8 rule); ipolate(): linear interpolation; polint(): polynomial inter-/extrapolation; plot(): Draw twoway plot; _plot(): Draw twoway plot; panels(): identify nested panel structure; _panels(): identify panel sizes; npanels(): identify number of panels; nunique(): count number of distinct values; nuniqrows(): count number of unique rows; isconstant(): whether matrix is constant; nobs(): number of observations; colrunsum(): running sum of each column; linbin(): linear binning; fastlinbin(): fast linear binning; exactbin(): exact binning; makegrid(): equally spaced grid points; cut(): categorize data vector; posof(): find element in vector; which(): positions of nonzero elements; locate(): search an ordered vector; hunt(): consecutive search; cond(): matrix conditional operator; expand(): duplicate single rows/columns; _expand(): duplicate rows/columns in place; repeat(): duplicate contents as a whole; _repeat(): duplicate contents in place; unorder2(): stable version of unorder(); jumble2(): stable version of jumble(); _jumble2(): stable version of _jumble(); pieces(): break string into pieces; npieces(): count number of pieces; _npieces(): count number of pieces; invtokens(): reverse of tokens(); realofstr(): convert string into real; strexpand(): expand string argument; matlist(): display a (real) matrix; insheet(): read spreadsheet file; infile(): read free-format file; outsheet(): write spreadsheet file; callf(): pass optional args to function; callf_setup(): setup for mm_callf().

Evaluation of a Bayesian MCMC Random Effects Inference Methodology for Capture-Mark-Recapture Data

Monte Carlo simulation was used to evaluate properties of a simple Bayesian MCMC analysis of the random effects model for single group Cormack-Jolly-Seber capture-recapture data. The MCMC method is applied to the model via a logit link, so parameters p, S are on a logit scale, where logit(S) is assumed to have, and is generated from, a normal distribution with mean μ and variance σ2 . Marginal prior distributions on logit(p) and μ were independent normal with mean zero and standard deviation 1.75 for logit(p) and 100 for μ ; hence minimally informative. Marginal prior distribution on σ2 was placed on τ2=1/σ2 as a gamma distribution with α=β=0.001 . The study design has 432 points spread over 5 factors: occasions (t) , new releases per occasion (u), p, μ , and σ . At each design point 100 independent trials were completed (hence 43,200 trials in total), each with sample size n=10,000 from the parameter posterior distribution. At 128 of these design points comparisons are made to previously reported results from a method of moments procedure. We looked at properties of point and interval inference on μ , and σ based on the posterior mean, median, and mode and equal-tailed 95% credibility interval. Bayesian inference did very well for the parameter μ , but under the conditions used here, MCMC inference performance for σ was mixed: poor for sparse data (i.e., only 7 occasions) or σ=0 , but good when there were sufficient data and not small σ .

Random Sampling with Interspike-Intervals of the Exponential Integrate and Fire Neuron: A Computational Interpretation of UP-States

Oscillations between high and low values of the membrane potential (UP and DOWN states respectively) are an ubiquitous feature of cortical neurons during slow wave sleep and anesthesia. Nevertheless, a surprisingly small number of quantitative studies have been conducted only that deal with this phenomenon’s implications for computation. Here we present a novel theory that explains on a detailed mathematical level the computational benefits of UP states. The theory is based on random sampling by means of interspike intervals (ISIs) of the exponential integrate and fire (EIF) model neuron, such that each spike is considered a sample, whose analog value corresponds to the spike’s preceding ISI. As we show, the EIF’s exponential sodium current, that kicks in when balancing a noisy membrane potential around values close to the firing threshold, leads to a particularly simple, approximative relationship between the neuron’s ISI distribution and input current. Approximation quality depends on the frequency spectrum of the current and is improved upon increasing the voltage baseline towards threshold. Thus, the conceptually simpler leaky integrate and fire neuron that is missing such an additional current boost performs consistently worse than the EIF and does not improve when voltage baseline is increased. For the EIF in contrast, the presented mechanism is particularly effective in the high-conductance regime, which is a hallmark feature of UP-states. Our theoretical results are confirmed by accompanying simulations, which were conducted for input currents of varying spectral composition. Moreover, we provide analytical estimations of the range of ISI distributions the EIF neuron can sample from at a given approximation level. Such samples may be considered by any algorithmic procedure that is based on random sampling, such as Markov Chain Monte Carlo or message-passing methods. Finally, we explain how spike-based random sampling relates to existing computational theories about UP states during slow wave sleep and present possible extensions of the model in the context of spike-frequency adaptation.

On ANOVA Decompositions of Kernels and Gaussian Random Field Paths

The FANOVA (or “Sobol’-Hoeffding”) decomposition of multivariate functions has been used for high-dimensional model representation and global sensitivity analysis. When the objective function f has no simple analytic form and is costly to evaluate, computing FANOVA terms may be unaffordable due to numerical integration costs. Several approximate approaches relying on Gaussian random field (GRF) models have been proposed to alleviate these costs, where f is substituted by a (kriging) predictor or by conditional simulations. Here we focus on FANOVA decompositions of GRF sample paths, and we notably introduce an associated kernel decomposition into 4 d 4d terms called KANOVA. An interpretation in terms of tensor product projections is obtained, and it is shown that projected kernels control both the sparsity of GRF sample paths and the dependence structure between FANOVA effects. Applications on simulated data show the relevance of the approach for designing new classes of covariance kernels dedicated to high-dimensional kriging.