Trying an Accused Serial Sexual Harasser for Libel in a US Civil Court

The goal of this article is to provide a class of MeToo# victims of a high-profile serial sexual harasser with a non-invasive method for civil action, when the accused publicly dismisses the victims’ claims as lies. When these libelous claims do occur, the victims can be assembled into a class-action libel/defamation case, which in most US states must be mounted within two years of the claim. Because under current civil methods, the plaintiffs would be subject to intense cross-examination in a civil jury trial, class-action lawsuits with small numbers of plaintiffs (e.g. 5–8) have proven impossible to conduct. This article provides a blueprint to create a collaboration amongst the victims, credibility-assessment (lie-detector) experts, statisticians, and MeToo# attorneys to litigate libel suits, which will likely produce out-of-court settlements. Once the first case is successfully completed, precedent will be set to bring other perpetrators to justice, and act as a deterrent to future exploitation. The evidentiary basis would be based on testing the null hypothesis that all plaintiffs are lying, to compare the inferred lying rates of the plaintiffs to similar population controls, who would be known liars, to a “Yes” answer to “Did X sexually harass you?

Chronic Cocaine Administration Is Associated with Behavioral Sensitization and Time-Dependent Changes in Striatal Dopamine Transporter Binding1

ABSTRAC

The Effect of EHR-Integrated Patient Reported Outcomes on Satisfaction with Chronic Pain Care

Objective Given its complexity, chronic noncancer pain presents an opportunity to use health information technology (IT) to improve care experiences. The objective of this study was to assess whether integrating patient-reported outcomes (PRO) data in an electronic health record (EHR) affects providers and patient satisfaction with chronic noncancer pain care. Study Design We conducted a pragmatic cluster randomized trial involving four family medicine clinics. Methods We enrolled primary care providers (PCPs) and their patients with chronic noncancer pain. In the first seven months (education phase), PCPs in intervention practices received education on how to use PROs for pain care. In the second seven months (PRO phase), patients in intervention practices reported pain-related outcomes upon arrival at their visits. PROs were immediately reported to PCPs through the EHR. Control group PCPs provided usual care. We compared intervention and control practices in terms of provider and patient satisfaction with care. Results During the education phase, patients’ mean ratings of their visits did not differ between control and intervention (9.33 vs. 9.08, p=0.20). During the PRO phase, patients’ mean ratings did not differ between control and intervention (9.28 vs 9.01, p=0.20). Similarly, there were no differences between the intervention and control groups in terms of provider satisfaction. Conclusion Delivering EHR-integrated PROs did not consistently improve patient or provider satisfaction. Positively, we found no evidence that the PRO tools negatively affected satisfaction. Future studies and technological innovations are needed to translate point-of-care health IT tools to improvements in patient and provider experiences

A randomized, placebo-controlled trial of late Na current inhibition (ranolazine) in coronary microvascular dysfunction (CMD): impact on angina and myocardial perfusion reserve.

AimsThe mechanistic basis of the symptoms and signs of myocardial ischaemia in patients without obstructive coronary artery disease (CAD) and evidence of coronary microvascular dysfunction (CMD) is unclear. The aim of this study was to mechanistically test short-term late sodium current inhibition (ranolazine) in such subjects on angina, myocardial perfusion reserve index, and diastolic filling.Materials and resultsRandomized, double-blind, placebo-controlled, crossover, mechanistic trial in subjects with evidence of CMD [invasive coronary reactivity testing or non-invasive cardiac magnetic resonance imaging myocardial perfusion reserve index (MPRI)]. Short-term oral ranolazine 500-1000 mg twice daily for 2 weeks vs. placebo. Angina measured by Seattle Angina Questionnaire (SAQ) and SAQ-7 (co-primaries), diary angina (secondary), stress MPRI, diastolic filling, quality of life (QoL). Of 128 (96% women) subjects, no treatment differences in the outcomes were observed. Peak heart rate was lower during pharmacological stress during ranolazine (-3.55 b.p.m., P < 0.001). The change in SAQ-7 directly correlated with the change in MPRI (correlation 0.25, P = 0.005). The change in MPRI predicted the change in SAQ QoL, adjusted for body mass index (BMI), prior myocardial infarction, and site (P = 0.0032). Low coronary flow reserve (CFR <2.5) subjects improved MPRI (P < 0.0137), SAQ angina frequency (P = 0.027), and SAQ-7 (P = 0.041).ConclusionsIn this mechanistic trial among symptomatic subjects, no obstructive CAD, short-term late sodium current inhibition was not generally effective for SAQ angina. Angina and myocardial perfusion reserve changes were related, supporting the notion that strategies to improve ischaemia should be tested in these subjects.Trial registrationclinicaltrials.gov Identifier: NCT01342029

Antithymocyte Globulin Plus G-CSF Combination Therapy Leads to Sustained Immunomodulatory and Metabolic Effects in a Subset of Responders With Established Type 1 Diabetes.

Low-dose antithymocyte globulin (ATG) plus pegylated granulocyte colony-stimulating factor (G-CSF) preserves β-cell function for at least 12 months in type 1 diabetes. Herein, we describe metabolic and immunological parameters 24 months following treatment. Patients with established type 1 diabetes (duration 4-24 months) were randomized to ATG and pegylated G-CSF (ATG+G-CSF) (N = 17) or placebo (N = 8). Primary outcomes included C-peptide area under the curve (AUC) following a mixed-meal tolerance test (MMTT) and flow cytometry. "Responders" (12-month C-peptide ≥ baseline), "super responders" (24-month C-peptide ≥ baseline), and "nonresponders" (12-month C-peptide < baseline) were evaluated for biomarkers of outcome. At 24 months, MMTT-stimulated AUC C-peptide was not significantly different in ATG+G-CSF (0.49 nmol/L/min) versus placebo (0.29 nmol/L/min). Subjects treated with ATG+G-CSF demonstrated reduced CD4+ T cells and CD4+/CD8+ T-cell ratio and increased CD16+CD56hi natural killer cells (NK), CD4+ effector memory T cells (Tem), CD4+PD-1+ central memory T cells (Tcm), Tcm PD-1 expression, and neutrophils. FOXP3+Helios+ regulatory T cells (Treg) were elevated in ATG+G-CSF subjects at 6, 12, and 18 but not 24 months. Immunophenotyping identified differential HLA-DR expression on monocytes and NK and altered CXCR3 and PD-1 expression on T-cell subsets. As such, a group of metabolic and immunological responders was identified. A phase II study of ATG+G-CSF in patients with new-onset type 1 diabetes is ongoing and may support ATG+G-CSF as a prevention strategy in high-risk subjects

UIML: an appliance-independent xml user interface language

Abstract Today's Internet appliances feature user interface technologies almost unknown a few years ago: touch screens, styli, handwriting and voice recognition, speech synthesis, tiny screens, and more. This richness creates problems. First, different appliances use different languages: WML for cell phones; SpeechML, JSML, and VoxML for voice enabled devices such as phones; HTML and XUL for desktop computers, and so on. Thus, developers must maintain multiple source code families to deploy interfaces to one information system on multiple appliances. Second, user interfaces differ dramatically in complexity (e.g, PC versus cell phone interfaces). Thus, developers must also manage interface content. Third, developers risk writing appliance-specific interfaces for an appliance that might not be on the market tomorrow. A solution is to build interfaces with a single, universal language free of assumptions about appliances and interface technology. This paper introduces such a language, the User Interface Markup Language (UIML), an XML-compliant language. UIML insulates the interface designer from the peculiarities of different appliances through style sheets. A measure of the power of UIML is that it can replace hand-coding of Java AWT or Swing user interfaces

On variance estimate for covariate adjustment by propensity score analysis: On variance estimate for covariate adjustment by propensity score analysis

Propensity score (PS) methods have been used extensively to adjust for confounding factors in the statistical analysis of observational data in comparative effectiveness research. There are four major PS-based adjustment approaches: PS matching, PS stratification, covariate adjustment by PS, and PS-based inverse probability weighting (IPW). Though covariate adjustment by PS is one of the most frequently used PS-based methods in clinical research, the conventional variance estimation of the treatment effects estimate under covariate adjustment by PS is biased. As Stampf et al. have shown, this bias in variance estimation is likely to lead to invalid statistical inference and could result in erroneous public health conclusions (e.g. food and drug safety, adverse events surveillance). To address this issue, we propose a two-stage analytic procedure to develop a valid variance estimator for the covariate adjustment by PS analysis strategy. We also carry out a simple empirical bootstrap resampling scheme. Both proposed procedures are implemented in an R function for public use. Extensive simulation results demonstrate the bias in the conventional variance estimator, and show that both proposed variance estimators offer valid estimates for the true variance and they are robust to complex confounding structures. The proposed methods are illustrated for a post-surgery pain study

On model selections for repeated measurement data in clinical studies: On model selections for repeated measurement data in clinical studies

Repeated measurement designs have been widely used in various randomized controlled trials for evaluating long term intervention efficacies. For some clinical trials, the primary research question is to compare two treatments at a fixed time, using a t-test. Though simple, robust, and convenient, this type of analysis fails to utilize a large amount of collected information. Alternatively, the mixed effects model is commonly used for repeated measurement data. It models all available data jointly and allows explicit assessment of the overall treatment effects across the entire time spectrum. In this paper, we propose an analytic strategy for longitudinal clinical trial data where the mixed effects model is coupled with a model selection scheme. The proposed test statistics not only make full use of all available data but also utilize the information from the optimal model deemed for the data. The performance of the proposed method under various setups, including different data missing mechanisms, is evaluated via extensive Monte Carlo simulations. Our numerical results demonstrate that the proposed analytic procedure is more powerful than the t-test when the primary interest is to test for the treatment effect at the last time point. Simulations also reveal that the proposed method outperforms the usual mixed effects model for testing the overall treatment effects across time. In addition, the proposed framework is more robust and flexible in dealing with missing data compared to several competing methods. The utility of the proposed method is demonstrated by analyzing a clinical trial on the cognitive effect of testosterone in geriatric men with low baseline testosterone levels