John Kloke

Hydrogen inhalation ameliorates ventilator-induced lung injury

IntroductionMechanical ventilation (MV) can provoke oxidative stress and an inflammatory response, and subsequently cause ventilator-induced lung injury (VILI), a major cause of mortality and morbidity of patients in the intensive care unit. Inhaled hydrogen can act as an antioxidant and may be useful as a novel therapeutic gas. We hypothesized that, owing to its antioxidant and anti-inflammatory properties, inhaled hydrogen therapy could ameliorate VILI.MethodsVILI was generated in male C57BL6 mice by performing a tracheostomy and placing the mice on a mechanical ventilator (tidal volume of 30 ml/kg without positive end-expiratory pressure, FiO2 0.21). The mice were randomly assigned to treatment groups and subjected to VILI with delivery of either 2% nitrogen or 2% hydrogen in air. Sham animals were given same gas treatments for two hours (n = 8 for each group). The effects of VILI induced by less invasive and longer exposure to MV (tidal volume of 10 ml/kg, 5 hours, FiO2 0.21) were also investigated (n = 6 for each group). Lung injury score, wet/dry ratio, arterial oxygen tension, oxidative injury, and expression of pro-inflammatory mediators and apoptotic genes were assessed at the endpoint of two hours using the high-tidal volume protocol. Gas exchange and apoptosis were assessed at the endpoint of five hours using the low-tidal volume protocol.ResultsVentilation (30 ml/kg) with 2% nitrogen in air for 2 hours resulted in deterioration of lung function, increased lung edema, and infiltration of inflammatory cells. In contrast, ventilation with 2% hydrogen in air significantly ameliorated these acute lung injuries. Hydrogen treatment significantly inhibited upregulation of the mRNAs for pro-inflammatory mediators and induced antiapoptotic genes. In the lungs treated with hydrogen, there was less malondialdehyde compared with lungs treated with nitrogen. Similarly, longer exposure to mechanical ventilation within lower tidal volume (10 mg/kg, five hours) caused lung injury including bronchial epithelial apoptosis. Hydrogen improved gas exchange and reduced VILI-induced apoptosis.ConclusionsInhaled hydrogen gas effectively reduced VILI-associated inflammatory responses, at both a local and systemic level, via its antioxidant, anti-inflammatory and antiapoptotic effects.

Rank-Based Estimation and Associated Inferences for Linear Models With Cluster Correlated Errors

R estimators based on the joint ranks (JR) of all the residuals have been developed over the last 20 years for fitting linear models with independently distributed errors. In this article, we extend these estimators to estimating the fixed effects in a linear model with cluster correlated continuous error distributions for general score functions. We discuss the asymptotic theory of the estimators and standard errors of the estimators. For the related mixed model with a single random effect, we discuss robust estimators of the variance components. These are used to obtain Studentized residuals for the JR fit. A real example is discussed, which illustrates the efficiency of the JR analysis over the traditional analysis and the efficiency of a prudent choice of a score function. Simulation studies over situations similar to the example confirm the validity and efficiency of the analysis.

A review of the effectiveness of antidepressant medications for depressed nursing home residents

BACKGROUND Antidepressant medications are the most common psychopharmacologic therapy used to treat depressed nursing home (NH) residents. Despite a significant increase in the rate of antidepressant prescribing over the past several decades, little is known about the effectiveness of these agents in the NH population. OBJECTIVE To conduct a systematic review of the literature to examine and compare the effectiveness of antidepressant medications for treating major depressive symptoms in elderly NH residents. METHODS The following databases were searched with searches completed prior to January 2011 and no language restriction: MEDLINE, Embase, PsycINFO, CINHAL, CENTRAL, LILACS, ClinicalTrials.gov, International Standard Randomized Controlled Trial Number Register, and the WHO International Clinical Trial Registry Platform. Additional studies were identified from citations in evidence-based guidelines and reviews as well as book chapters on geriatric depression and pharmacotherapy from several clinical references. Studies were included if they described a clinical trial that assessed the effectiveness of any currently-marketed antidepressant for adults aged 65 years or older, who resided in the NH, and were diagnosed by DSM criteria and/or standardized validated screening instruments with Major Depressive Disorder, minor depression, dysthymic disorder, or Depression in Alzheimers disease. RESULTS A total of eleven studies, including four randomized and seven non-randomized open-label trials, met all inclusion and exclusion criteria. It was not feasible to conduct a meta-analysis because the studies were heterogeneous in terms of study design, operational definitions of depression, participant characteristics, pharmacologic interventions, and outcome measures. Of the four randomized trials, two had a control group and did not demonstrate a statistically-significant benefit for antidepressant pharmacotherapy over placebo. While six of the seven non-randomized studies identified a response to an antidepressant, their results must be interpreted with caution as they lacked a comparison group. CONCLUSIONS The limited amount of evidence from randomized and non-randomized open-label trials suggests that depressed NH residents have a modest response to antidepressant medications. Further research using rigorous study designs are needed to examine the effectiveness and safety of antidepressants in depressed NH residents, and to determine the various facility, provider, and patient factors associated with response to treatment.

Performance Characteristics of Endoscopic Ultrasound in the Staging of Pancreatic Cancer: A Meta-Analysis

CONTEXT The optimal approach to pre-operative imaging assessment of pancreatic cancer is unknown. OBJECTIVE The aim of this meta-analysis was to assess accuracy and performance characteristics of EUS in determining nodal staging, vascular invasion, and prediction of resectability of pancreatic cancer. A secondary aim was to perform head to head comparison of performance characteristics between EUS and CT for nodal staging, vascular invasion and resectability. DESIGN Data from EUS studies were pooled according to bivariate generalized random effects model. Pooled estimates for CT were obtained from studies which performed head to head comparison between EUS and CT. PATIENTS Patients with pancreatic cancer undergoing pre-operative imaging assessment. INTERVENTION EUS. MAIN OUTCOME MEASURE Pooled sensitivity, specificity, positive and negative predictive values of EUS for nodal staging, vascular invasion and resectability. RESULTS Forty-nine studies were considered of which 29 met inclusion criteria with a total of 1,330 patients. Pooled summary estimates for EUS-nodal staging were 69% for sensitivity and 81% for specificity. For vascular invasion, sensitivity was 85% and specificity was 91%. The sensitivity and specificity for resectability was 90% and 86%, respectively. CT scan showed lower sensitivity than EUS for nodal staging (24% vs. 58%) and vascular invasion (58% vs. 86%); however, the specificities for nodal staging (88% vs. 85%) and vascular invasion (95% vs. 93%) were comparable in studies where both imaging techniques were performed. The sensitivity and specificity of CT in determining resectability (90% and 69%) was similar to that of EUS (87% and 89%). CONCLUSIONS EUS is an accurate pre-operative tool in the assessment of nodal staging, vascular invasion and resectability in patients with pancreatic cancer.

Accuracy of Liver Surface Nodularity Quantification on MDCT as a Noninvasive Biomarker for Staging Hepatic Fibrosis.

OBJECTIVE The purpose of this study was to investigate objective semiautomated measurement of liver surface nodularity on MDCT for prediction of underlying hepatic fibrosis (stages F0-F4). MATERIALS AND METHODS Contrast-enhanced abdominal MDCT scans were assessed with an independently validated semiautomated surface nodularity tool. A series of 10 or more consecutive ROI measurements along the anterior aspect of the liver totaling a length of 80 cm or more were made with the left lateral segment as the default. All intermediate stages of fibrosis (F1-F3) were based on liver biopsy results within 1 year of MDCT. RESULTS The study participants were 367 patients (191 men, 176 women; mean age, 51.1 years) divided into a healthy (F0) control group (n = 118) and patients with fibrosis in stages F1 (n = 47), F2 (n = 38), F3 (n = 67), and F4, which constituted cirrhosis (n = 97). MDCT-based liver surface nodularity scores increased with stage of fibrosis: F0, 2.01 ± 0.28; F1, 2.34 ± 0.39; F2, 2.37 ± 0.39; F3, 2.88 ± 0.68; and F4, 4.11 ± 0.95. For discriminating significant fibrosis (≥ F2), advanced fibrosis (≥ F3), and cirrhosis (≥ F4), the ROC AUCs were 0.902, 0.932, and 0.959, respectively. The sensitivity and specificity for significant fibrosis (≥ F2; liver surface nodularity threshold, 2.38) were 80.2% and 80.0%, for advanced fibrosis (≥ F3; liver surface nodularity threshold, 2.53) were 89.0% and 84.2%, and for cirrhosis (≥ F4; liver surface nodularity threshold, 2.81) were 97.9% and 84.8%. CONCLUSION Objective quantification of liver surface nodularity at MDCT allows accurate discrimination between stages of hepatic fibrosis, especially at more advanced levels. Although the results are comparable to those of elastography, this simple semiautomated biomarker can be measured retrospectively without additional equipment or patient time.

Nonparametric statistical methods using R

Getting Started with R R Basics Reading External Data Generating Random Data Graphics Repeating Tasks User-Defined Functions Monte Carlo Simulation R Packages Basic Statistics Sign Test Signed-Rank Wilcoxon Bootstrap Robustness One- and Two-Sample Proportion Problems chi2 Tests Two-Sample Problems Introductory Example Rank-Based Analyses Scale Problem Placement Test for the Behrens-Fisher Problem Efficiency and Optimal Scores Adaptive Rank Scores Tests Regression I Simple Linear Regression Multiple Linear Regression Linear Models Aligned Rank Tests Bootstrap Nonparametric Regression Correlation ANOVA and ANCOVA One-Way ANOVA Multi-Way Crossed Factorial Design ANCOVA Methodology for Type III Hypotheses Testing Ordered Alternatives Multi-Sample Scale Problem Time-to-Event Analysis Kaplan-Meier and Log Rank Test Cox Proportional Hazards Models Accelerated Failure Time Models Regression II Robust Diagnostics Weighted Regression Linear Models with Skew Normal Errors A Hogg-Type Adaptive Procedure Nonlinear Time Series Cluster Correlated Data Friedmans Test Joint Rankings Estimator Robust Variance Component Estimators Multiple Rankings Estimator GEE-Type Estimator Bibliography Index Exercises appear at the end of each chapter.

Olfactory dysfunction and parasympathetic dysautonomia in Parkinson’s disease

ObjectiveOlfactory impairment occurs early in Parkinson’s disease (PD), as may dysautonomia. We investigated the relationship between olfaction and dysautonomia as well as other non-motor manifestations of PD.MethodsOlfaction [University of Pennsylvania Smell Identification Test (UPSIT)], autonomic function in the pupillary (constriction and redilation velocity) and cardiac systems (resting low- and high-frequency heart rate variability (LF and HF HRV), positional changes in systolic blood pressure), neuropsychiatric function [Mini-mental Status Exam (MMSE)], Hamilton Depression Scale, activities of daily living [(ADLs), Schwab and England ADLs scale], quality of life [Short Form-36 health survey, PD Questionnaire 39 (PDQ-39)], and other non-motor symptoms [Non-motor Symptoms Scale (NMSS)] were simultaneously assessed in 33 participants (15 PD, 18 controls). Group comparisons, Spearman’s coefficients and non-parametric rank-based regression were employed to characterize relationships between olfaction and non-motor features.ResultsSmell scores were lower in the PD group and correlated positively with pupil constriction velocity and HF HRV. Smell scores were correlated negatively with PDQ-39 and gastrointestinal items of the NMSS and positively with MMSE and Schwab and England ADLs. These correlated measures were not significant terms in regression models of smell scores in which age and PD diagnosis were significant and accounted for over half of the variability (R-squared 0.52–0.58).InterpretationThis study suggests olfactory involvement occurs with parasympathetic dysautonomia in the pupillary and cardiovascular systems, involving both age-related and PD-related processes. Other non-motor features are concurrently involved, supporting the notion that aging and PD have widespread effects involving discrete portions of the autonomic and olfactory systems.

Inhibitory Metabolic Drug Interactions with Newer Psychotropic Drugs: Inclusion in Package Inserts and Influences of Concurrence in Drug Interaction Screening Software

Background: Food and Drug Administration (FDA) regulations mandate that package inserts (Pls) include observed or predicted clinically significant drug-drug interactions (DDIs), as well as the results of pharmacokinetic studies that establish the absence of effect. Objective: To quantify how frequently observed metabolic inhibition DDIs affecting US-marketed psychotropics are present in FDA-approved Pls and what influence the source of DDI information has on agreement between 3 DDI screening programs. Methods: The scientific literature and Pls were reviewed to determine all drug pairs for which there was rigorous evidence of a metabolic inhibition interaction or noninteraction. The DDIs were tabulated noting the source of evidence and the strength of agreement over chance. Descriptive statistics were used to examine the influence of source of DDI information on agreement among 3 DDI screening tools. Logistic regression was used to assess the influence of drug class, indication, generic status, regulatory approval date, and magnitude of effect on agreement between the literature and PI as well as agreement among the DDI screening tools. Results: Thirty percent (13/44) of the metabolic inhibition DDIs affecting newer psychotropics were not mentioned in Pls. Drug class, indication, regulatory approval date, generic status, or magnitude of effect did not appear to be associated with more complete DDI information in Pls. DDIs found exclusively in Pls were 3.25 times more likely to be agreed upon by all 3 DDI screening tools than were those found exclusively in the literature. Generic status was inversely associated with agreement among the DDI screening tools (odds ratio 0.11; 95% CI 0.01 to 0.89). Conclusions: The presence in Pls of DDI information for newer psychotropics appears to have a strong influence on agreement among DDI screening tools. Users of DDI screening software should consult more than 1 source when considering interactions involving generic psychotropics.

R Estimates and Associated Inferences for Mixed Models With Covariates in a Multicenter Clinical Trial

Robust rank-based methods are proposed for the analysis of data from multicenter clinical trials using a mixed model (including covariates) in which the treatment effects are assumed to be fixed and the center effects are assumed to be random. These rank-based methods are developed under the usual mixed-model structure but without the normality assumption of the random components in the model. For this mixed model, our proposed estimation includes R estimation of the fixed effects, robust estimation of the variance componets, and studentized residuals. Our accompanying inference includes estimates of the standard errors of the fixed-effects estimators and tests of general linear hypotheses concerning fixed effects. While the development is for general scores function, the Wilcoxon linear scores are emphasized. A discussion of the relative efficiency results shows that the R estimates are highly efficient compared to the traditional maximum likelihood (ML) estimates. A small Monte Carlo study confirms the validity of the analysis and its gain in power over the ML analysis for heavy-tailed distributions. We further develop a rank-based test for center by treatment interactions. We discuss the results of our analysis for an example of a multicenter clinical trial which shows the robustness of our procedure.

Iterated reweighted rank-based estimates for GEE models

Repeated measurement designs occur in many areas of statistical research. In 1986, Liang and Zeger offered an elegant analysis of these problems based on a set of generalized estimating equations (GEEs) for regression parameters, that specify only the relationship between the marginal mean of the response variable and covariates. Their solution is based on iterated reweighted least squares fitting. In this paper, we propose a rank-based fitting procedure that only involves substituting a norm based on a score function for the Euclidean norm used by Liang and Zeger. Our subsequent fitting, while also an iterated reweighted least squares solution to GEEs, is robust to outliers in response space and the weights can easily be adapted for robustness in factor space. As with the fitting of Liang and Zeger, our rank-based fitting utilizes a working covariance matrix. We prove that our estimators of the regression coefficients are asymptotically normal. The results of a simulation study show that the our proposed estimators are empirically efficient and valid. We illustrate our analysis on a real data set drawn from a hierarchical (three-way nested) design.