Evaluation of the discrepancy between clinical diagnostic hypotheses and anatomopathological diagnoses resulting from autopsies

OBJECTIVES: An objective of clinical autopsies is to determine the final cause of death and the pathological changes that may have triggered it. Despite advances in Medicine, the level of discrepancy between clinical and autopsy diagnoses remains significant. The aim of this study was to compare the data obtained from autopsies carried out at the Sa˜o Bernardo do Campo/SP Death Verification Section with clinical diagnostic hypotheses proposed during medical care. METHOD: This was a retrospective study involving the comparison of necroscopic reports issued by the Sa˜o Bernardo do Campo/Sa˜o Paulo Death Verification Section in 2014 and 2015 and the Cadaver Referral Guides completed by attending physicians prior to the necroscopic examination. RESULTS: A total of 465 cases were analyzed. In general, discrepancies between the clinical diagnostic hypothesis and the autopsy diagnosis occurred in 28% of the cases. A logistic regression model, with diagnostic discrepancy as a response variable and sex, age, duration of care, type of institution providing medical care and organ system as explanatory variables, was fit to the data; the results indicated that all explanatory variables with the exception of organ system are not significant (p40.132). CONCLUSIONS: Discrepancies between clinical diagnostic hypotheses and autopsy diagnoses continue to occur, despite new developments in complementary examinations and therapies. The odds of a discrepancy when patients present with diseases of the cardiac system are greater than those when there are problems in the vascular, endocrine and neurological systems

Verifying compliance with ballast water standards : a decision-theoretic approach

We construct credible intervals to estimate the mean organism (zooplankton and phytoplankton) concentration in ballast water via a decision-theoretic approach. To obtain the required optimal sample size, we use a total cost minimization criterion defined as the sum of the sampling cost and the Bayes risk either under a Poisson or a negative binomial model for organism counts, both with a gamma prior distribution. Such credible intervals may be employed to verify whether the ballast water discharged from a ship is in compliance with international standards. We also conduct a simulation study to evaluate the credible interval lengths associated with the proposed optimal sample sizes

UU-tests for variance components in one-way random effects models

We consider a test for the hypothesis that the within-treatment variance component in a one-way random effects model is null. This test is based on a decomposition of a $U$-statistic. Its asymptotic null distribution is derived under the mild regularity condition that the second moment of the random effects and the fourth moment of the within-treatment errors are finite. Under the additional assumption that the fourth moment of the random effect is finite, we also derive the distribution of the proposed $U$-test statistic under a sequence of local alternative hypotheses. We report the results of a simulation study conducted to compare the performance of the $U$-test with that of the usual $F$-test. The main conclusions of the simulation study are that (i) under normality or under moderate degrees of imbalance in the design, the $F$-test behaves well when compared to the $U$-test, and (ii) when the distribution of the random effects and within-treatment errors are nonnormal, the $U$-test is preferable even when the number of treatments is small.Comment: Published in at http://dx.doi.org/10.1214/193940307000000149 the IMS Collections (http://www.imstat.org/publications/imscollections.htm) by the Institute of Mathematical Statistics (http://www.imstat.org

Prediction of failure probability of oil wells

We consider parametric accelerated failure time models with random effects to predict the probability of possibly correlated failures occurring in oil wells. In this context, we first consider empirical Bayes predictors (EBP) based on aWeibull distribution for the failure times and on a Gaussian distribution for the random effects.We also obtain empirical best linear unbiased predictors (EBLUP) using a linear mixed model for which the form of the distribution of the random effects is not specified. We compare both approaches using data obtained from an oil-drilling company and suggest how the results may be employed in designing a preventive maintenance program

Competing regression models for longitudinal data

The choice of an appropriate family of linear models for the analysis of longitudinal data is often a matter of concern for practitioners. To attenuate such difficulties, we discuss some issues that emerge when analyzing this type of data via a practical example involving pretestposttest longitudinal data. In particular, we consider log-normal linear mixed models (LNLMM), generalized linear mixed models (GLMM), and models based on generalized estimating equations (GEE). We show how some special features of the data, like a nonconstant coefficient of variation, may be handled in the three approaches and evaluate their performance with respect to the magnitude of standard errors of interpretable and comparable parameters. We also show how different diagnostic tools may be employed to identify outliers and comment on available software. We conclude by noting that the results are similar, but that GEE-based models may be preferable when the goal is to compare the marginal expected responses.Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP), Brazi

Dark Patterns after the GDPR: Scraping Consent Pop-ups and Demonstrating their Influence

New consent management platforms (CMPs) have been introduced to the web to conform with the EU's General Data Protection Regulation, particularly its requirements for consent when companies collect and process users' personal data. This work analyses how the most prevalent CMP designs affect people's consent choices. We scraped the designs of the five most popular CMPs on the top 10,000 websites in the UK (n=680). We found that dark patterns and implied consent are ubiquitous; only 11.8% meet the minimal requirements that we set based on European law. Second, we conducted a field experiment with 40 participants to investigate how the eight most common designs affect consent choices. We found that notification style (banner or barrier) has no effect; removing the opt-out button from the first page increases consent by 22--23 percentage points; and providing more granular controls on the first page decreases consent by 8--20 percentage points. This study provides an empirical basis for the necessary regulatory action to enforce the GDPR, in particular the possibility of focusing on the centralised, third-party CMP services as an effective way to increase compliance.Comment: 13 pages, 3 figures. To appear in the Proceedings of CHI '20 CHI Conference on Human Factors in Computing Systems, April 25--30, 2020, Honolulu, HI, US

The Multifunctional LigB Adhesin Binds Homeostatic Proteins with Potential Roles in Cutaneous Infection by Pathogenic Leptospira interrogans

Leptospirosis is a potentially fatal zoonotic disease in humans and animals caused by pathogenic spirochetes, such as Leptospira interrogans. The mode of transmission is commonly limited to the exposure of mucous membrane or damaged skin to water contaminated by leptospires shed in the urine of carriers, such as rats. Infection occurs during seasonal flooding of impoverished tropical urban habitats with large rat populations, but also during recreational activity in open water, suggesting it is very efficient. LigA and LigB are surface localized proteins in pathogenic Leptospira strains with properties that could facilitate the infection of damaged skin. Their expression is rapidly induced by the increase in osmolarity encountered by leptospires upon transition from water to host. In addition, the immunoglobulin-like repeats of the Lig proteins bind proteins that mediate attachment to host tissue, such as fibronectin, fibrinogen, collagens, laminin, and elastin, some of which are important in cutaneous wound healing and repair. Hemostasis is critical in a fresh injury, where fibrinogen from damaged vasculature mediates coagulation. We show that fibrinogen binding by recombinant LigB inhibits fibrin formation, which could aid leptospiral entry into the circulation, dissemination, and further infection by impairing healing. LigB also binds fibroblast fibronectin and type III collagen, two proteins prevalent in wound repair, thus potentially enhancing leptospiral adhesion to skin openings. LigA or LigB expression by transformation of a nonpathogenic saprophyte, L. biflexa, enhances bacterial adhesion to fibrinogen. Our results suggest that by binding homeostatic proteins found in cutaneous wounds, LigB could facilitate leptospirosis transmission. Both fibronectin and fibrinogen binding have been mapped to an overlapping domain in LigB comprising repeats 9–11, with repeat 11 possibly enhancing binding by a conformational effect. Leptospirosis patient antibodies react with the LigB domain, suggesting applications in diagnosis and vaccines that are currently limited by the strain-specific leptospiral lipopolysaccharide coats

Lifetime Doctor-Diagnosed Mental Health Conditions and Current Substance Use Among Gay and Bisexual Men Living in Vancouver, Canada

BackgroundStudies have found that gay, bisexual, and other men who have sex with men (GBM) have higher rates of mental health conditions and substance use than heterosexual men, but are limited by issues of representativeness.ObjectivesTo determine the prevalence and correlates of mental health disorders among GBM in Metro Vancouver, Canada.MethodsFrom 2012 to 2014, the Momentum Health Study recruited GBM (≥16 years) via respondent-driven sampling (RDS) to estimate population parameters. Computer-assisted self-interviews (CASI) collected demographic, psychosocial, and behavioral information, while nurse-administered structured interviews asked about mental health diagnoses and treatment. Multivariate logistic regression using manual backward selection was used to identify covariates for any lifetime doctor diagnosed: (1) alcohol/substance use disorder and (2) any other mental health disorder.ResultsOf 719 participants, 17.4% reported a substance use disorder and 35.2% reported any other mental health disorder; 24.0% of all GBM were currently receiving treatment. A lifetime substance use disorder diagnosis was negatively associated with being a student (AOR = 0.52, 95% CI [confidence interval]: 0.27-0.99) and an annual income ≥$30,000 CAD (AOR = 0.38, 95% CI: 0.21-0.67) and positively associated with HIV-positive serostatus (AOR = 2.54, 95% CI: 1.63-3.96), recent crystal methamphetamine use (AOR = 2.73, 95% CI: 1.69-4.40) and recent heroin use (AOR = 5.59, 95% CI: 2.39-13.12). Any other lifetime mental health disorder diagnosis was negatively associated with self-identifying as Latin American (AOR = 0.25, 95% CI: 0.08-0.81), being a refugee or visa holder (AOR = 0.18, 95% CI: 0.05-0.65), and living outside Vancouver (AOR = 0.52, 95% CI: 0.33-0.82), and positively associated with abnormal anxiety symptomology scores (AOR = 3.05, 95% CI: 2.06-4.51).ConclusionsMental health conditions and substance use, which have important implications for clinical and public health practice, were highly prevalent and co-occurring