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Objective: To build a prediction model for uveitis in children with JIA for use in current clinical practice., Methods: Data from the international observational Pharmachild registry were used. Adjusted risk factors as well as predictors for JIA-associated uveitis (JIA-U) were determined using multivariable logistic regression models. The prediction model was selected based on the Akaike information criterion. Bootstrap resampling was used to adjust the final prediction model for optimism., Results: JIA-U occurred in 1102 of 5529 JIA patients (19.9%). The majority of patients that developed JIA-U were female (74.1%), ANA positive (66.0%) and had oligoarthritis (59.9%). JIA-U was rarely seen in patients with systemic arthritis (0.5%) and RF positive polyarthritis (0.2%). Independent risk factors for JIA-U were ANA positivity [odds ratio (OR): 1.88 (95% CI: 1.54, 2.30)] and HLA-B27 positivity [OR: 1.48 (95% CI: 1.12, 1.95)] while older age at JIA onset was an independent protective factor [OR: 0.84 (9%% CI: 0.81, 0.87)]. On multivariable analysis, the combination of age at JIA onset [OR: 0.84 (95% CI: 0.82, 0.86)], JIA category and ANA positivity [OR: 2.02 (95% CI: 1.73, 2.36)] had the highest discriminative power among the prediction models considered (optimism-adjusted area under the receiver operating characteristic curve = 0.75)., Conclusion: We developed an easy to read model for individual patients with JIA to inform patients/parents on the probability of developing uveitis., (© The Author(s) 2020. Published by Oxford University Press on behalf of the British Society for Rheumatology.)

The authors comment on D. Frasca's article on the continuous noninvasive hemoglobin monitoring (CNHM). They say that the use of CNHM in patients who are critically ill has strong merit. They add that trend monitoring can serve as a useful alternative to serial in vitro testing especially when improving the cost-effectiveness of transfusions, enhancing the timeliness of decision making and reducing iatrogenic blood loss.

Machine learning (ML) approaches have been widely applied to medical data in order to find reliable classifiers to improve diagnosis and detect candidate biomarkers of a disease. However, as a powerful, multivariate, data-driven approach, ML can be misled by biases and outliers in the training set, finding sample-dependent classification patterns. This phenomenon often occurs in biomedical applications in which, due to the scarcity of the data, combined with their heterogeneous nature and complex acquisition process, outliers and biases are very common. In this work we present a new workflow for biomedical research based on ML approaches, that maximizes the generalizability of the classification. This workflow is based on the adoption of two data selection tools: an autoencoder to identify the outliers and the Confounding Index, to understand which characteristics of the sample can mislead classification. As a study-case we adopt the controversial research about extracting brain structural biomarkers of Autism Spectrum Disorders (ASD) from magnetic resonance images. A classifier trained on a dataset composed by 86 subjects, selected using this framework, obtained an area under the receiver operating characteristic curve of 0.79. The feature pattern identified by this classifier is still able to capture the mean differences between the ASD and Typically Developing Control classes on 1460 new subjects in the same age range of the training set, thus providing new insights on the brain characteristics of ASD. In this work, we show that the proposed workflow allows to find generalizable patterns even if the dataset is limited, while skipping the two mentioned steps and using a larger but not well designed training set would have produced a sample-dependent classifier. [ABSTRACT FROM AUTHOR]

Coffee is one of the most popular beverages worldwide. Its effect on health is generally regarded as beneficial in many studies. However, there are growing concerns about the adverse effect of coffee consumption on cardiovascular disease (CVD) due to the potential aggravating impact on the cardiovascular system attributed to various compounds within coffee. This review is focused on deteriorative effects of coffee consumption on CVDs with possible mechanisms. Patients with risk factors of CVDs should prudently consider heavy consumption of coffee as it may exacerbate hypertension, dyslipidemia, and atherosclerosis, and increase the odds of cardiovascular events. J-shaped or U-shaped dose-response graphs of coffee consumption and CVD parameters partially explain the inconsistency of conclusions between coffee studies on CVD, highlighting a moderate intake of coffee. Moreover, there are discrepancies in results from clinical studies elucidating considerable influences of confounding factors including gender and smoking status on outcomes of those conducted to reveal the actual impact of coffee consumption on CVDs. Physical features of subjects including genetic variations and body mass index (BMI) make it difficult to determine moderate intake of coffee for individuals in terms of caffeine metabolism. Further epidemiological studies with consideration about characteristics of the study population are needed to determine the exact effect of coffee consumption on CVD. [ABSTRACT FROM AUTHOR]

Clustering is a form of unsupervised learning that aims to uncover latent groups within data based on similarity across a set of features. A common application of this in biomedical research is in delineating novel cancer subtypes from patient gene expression data, given a set of informative genes. However, it is typically unknown a priori what genes may be informative in discriminating between clusters, and what the optimal number of clusters are. Few methods exist for performing unsupervised clustering of RNA-seq samples, and none currently adjust for between-sample global normalization factors, select cluster-discriminatory genes, or account for potential confounding variables during clustering. To address these issues, we propose the Feature Selection and Clustering of RNA-seq (FSCseq): a model-based clustering algorithm that utilizes a finite mixture of regression (FMR) model and the quadratic penalty method with a Smoothly-Clipped Absolute Deviation (SCAD) penalty. The maximization is done by a penalized Classification EM algorithm, allowing us to include normalization factors and confounders in our modeling framework. Given the fitted model, our framework allows for subtype prediction in new patients via posterior probabilities of cluster membership, even in the presence of batch effects. Based on simulations and real data analysis, we show the advantages of our method relative to competing approaches.

Aims: Recent technical developments have allowed the study of the human microbiome to accelerate at an unprecedented pace. Methodological differences may have considerable impact on the results obtained. Thus, we investigated how different storage, isolation, and DNA extraction methods can influence the characterization of the intestinal microbiome, compared to the impact of true biological signals such as intraindividual variability, nutrition, health, and demographics., Methods and Results: An observative cohort study in 27 healthy subjects was performed. Participants were instructed to collect stool samples twice spaced by a week, using six different methods (naive and Zymo DNA/RNA Shield on dry ice, OMNIgene GUT, RNALater, 95% ethanol, Zymo DNA/RNA Shield at room temperature). DNA extraction from all samples was performed comparatively using QIAamp Power Fecal and ZymoBIOMICS DNA Kits. 16S rRNA sequencing of the gut microbiota as well as qPCRs were performed on the isolated DNA. Metrics included alpha diversity as well as multivariate and univariate comparisons of samples, controlling for covariate patterns computationally. Interindividual differences explained 7.4% of overall microbiome variability, whereas the choice of DNA extraction method explained a further 5.7%. At phylum level, the tested kits differed in their recovery of Gram-positive bacteria, which is reflected in a significantly skewed enterotype distribution., Conclusion: DNA extraction methods had the highest impact on observed microbiome variability, and were comparable to interindividual differences, thus may spuriously mimic the microbiome signatures of various health and nutrition factors. Conversely, collection methods had a relatively small influence on microbiome composition. The present study provides necessary insight into the technical variables which can lead to divergent results from seemingly similar study designs. We anticipate that these results will contribute to future efforts towards standardization of microbiome quantification procedures in clinical research., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2020. For permissions, please email: journals.permissions@oup.com.)

Background: Roux-en-Y gastric bypass (RYGB) has been recommended as the bariatric procedure of choice for morbidly obese patients with Barrett's esophagus (BE)., Objectives: To systematically review the effect of RYGB on BE., Setting: University hospital, Melbourne, Australia., Methods: A systematic review was performed. Studies were included of patients who had BE who underwent RYGB and had minimum 1 follow-up gastroscopy postoperatively. English language full-text articles were included, with case reports excluded. Endoscopic assessment methods of BE were compared to the American College of Gastroenterology (ACG) clinical guideline recommendations. A novel methodological quality assessment tool to assess risk of bias was developed. For each study, potential confounders for the effect of RYGB on BE were analyzed., Results: Of 28 articles, 5 publications met inclusion criteria. Quality assessment did not demonstrate any high-quality publications. Of 63 patients, no cases showed progression of BE. Overall, regression rates of BE assessed at the postoperative endoscopy varied from 36%-62%. There was a lack of consensus between authors on definition of regression and short- versus long-segment BE. Eighty percent of patients with dysplasia had regression of dysplasia. Both studies that provided all required endoscopic information had poor compliance with ACG recommendations. Potential confounding factors for the effect of RYGB on BE included preoperative risk factors, selection bias based on length of BE, type of RYGB (resectional or nonresectional), concomitant hiatus hernia repair, postoperative use of proton pump inhibitor, and amount of weight loss., Conclusion: RYGB has been shown to be associated with regression of BE and dysplasia in some patients, with no cases of progression after short-term postoperative endoscopic assessment. A clearer definition of regression of BE and following ACG recommendations is necessary to allow standardized reporting and comparison of future results. Long-term, larger, multicenter high-quality studies, including assessment of all potential contributing factors for BE regression, are required., (Copyright © 2020 American Society for Bariatric Surgery. All rights reserved.)

Purpose: To address confounding issues that have been noted in planning and conducting studies to identify biomarkers of radiation injury, develop animal models to simulate these injuries, and test potential medical countermeasures to mitigate/treat damage caused by radiation exposure., Methods: The authors completed an intensive literature search to address several key areas that should be considered before embarking on studies to assess efficacy of medical countermeasure approaches in mouse models of radiation injury. These considerations include: (1) study variables; (2) animal selection criteria; (3) animal husbandry; (4) medical management; and (5) radiation attributes., Results: It is important to select mouse strains that are capable of responding to the selected radiation exposure (e.g. genetic predispositions might influence radiation sensitivity and proclivity to certain phenotypes of radiation injury), and that also react in a manner similar to humans. Gender, vendor, age, weight, and even seasonal variations are all important factors to consider. In addition, the housing and husbandry of the animals (i.e. feed, environment, handling, time of day of irradiation and animal restraint), as well as the medical management provided (e.g. use of acidified water, antibiotics, routes of administration of drugs, consideration of animal numbers, and euthanasia criteria) should all be addressed. Finally, the radiation exposure itself should be tightly controlled, by ensuring a full understanding and reporting of the radiation source, dose and dose rate, shielding and geometry of exposure, while also providing accurate dosimetry. It is important to understand how all the above factors contribute to the development of radiation dose response curves for a given animal facility with a well-defined murine model., Conclusions: Many potential confounders that could impact the outcomes of studies to assess efficacy of a medical countermeasure for radiation-induced injuries are addressed, and recommendations are made to assist investigators in carrying out research that is robust, reproducible, and accurate.

Propensity score methods are commonly used in statistical analyses of observational data to reduce the impact of confounding bias in estimations of average treatment effect. While the propensity score is defined as the conditional probability of a subject being in the treatment group given that subject's covariates, the most precise estimation of average treatment effect results from specifying the propensity score as a function of true confounders and predictors only. This property has been demonstrated via simulation in multiple prior research articles. However, we have seen no theoretical explanation as to why this should be so. This paper provides that theoretical proof. Furthermore, this paper presents a method for performing the necessary variable selection by means of elastic net regression, and then estimating the propensity scores so as to obtain optimal estimates of average treatment effect. The proposed method is compared against two other recently introduced methods, outcome-adaptive lasso and covariate balancing propensity score. Extensive simulation analyses are employed to determine the circumstances under which each method appears most effective. We applied the proposed methods to examine the effect of pre-cardiac surgery coagulation indicator on mortality based on a linked dataset from a retrospective review of 1390 patient medical records at Jewish Hospital (Louisville, KY) with the Society of Thoracic Surgeons database.

Background: Several studies have shown that maternal HIV infection is associated with adverse pregnancy outcomes such as low birth weight and perinatal mortality. However, the association is conflicted with the effect of antiretroviral therapy (ART) on the pregnancy outcomes and it remains unexamined. If the association is confirmed then it would guide policy makers towards more effective prevention of mother to child HIV transmission interventions. Using methods for matching possible confounders, the objectives of the study were to assess the effect of maternal HIV infection on birth weight and perinatal mortality and to investigate the effect of ART on these two pregnancy outcomes in HIV-infected women., Methods: Data on 4111 and 4759 children, born within five years of the 2010 and 2015-16 Malawi Demographic and Health Surveys (MDHS) respectively, whose mothers had an HIV test result, were analysed. A best balancing method was chosen from a set of covariate balance methods namely, the 1:1 nearest neighbour (NN) matching, matching on the propensity score (PS) and inverse weighting on the PS. HIV and ART data were only available in the MDHS 2010, permitting an assessment of the moderating effect of ART on the association between maternal HIV infection and birth weight and perinatal mortality., Results: The overall average birth weight was 3227.9g (95% CI: 3206.4, 3249.5) in 2010 and 3226.4g (95%: 3205.6, 3247.2) in 2015-16 and perinatal mortality was 3.8% (95%: 3.2, 4.3) in 2010 and 3.5% (95%: 2.8, 3.8) in 2015-16. The prevalence of HIV among the mothers was 11.1% (95%: 10.1, 12.0) and 9.2% (95% CI: 8.4, 10.1) in 2010 and 2015-16, respectively. In 2010, maternal HIV infection was negatively associated with birth weight (mean= -25.3g, 95% CI:(-95.5, -7.4)) and in 2015-16 it was positively associated with birth weight (mean= 116.3g, 95% CI:(27.8, 204.7)). Perinatal mortality was higher in infants of HIV-infected mothers compared to infants of HIV-uninfected mothers (OR = 1.5, 95% CI:(1.1 - 3.1)) in 2010, while there was no difference in the rate in 2015-16 (OR = 1.0, 95% CI:(0.4, 1.6)). ART was not associated with birth weight, however, it was associated with perinatal mortality (OR=3.9, 95% CI:(1.1, 14.8))., Conclusion: The study has found that maternal HIV infection had an adverse effect on birth weight and perinatal mortality in 2010. Birth weight was not dependent on ART uptake but perinatal mortality was higher among infants of HIV-infected mothers who were not on ART. The higher birth weight among HIV-infected mothers and similarity in perinatal mortality with HIV-uninfected mothers in 2015-16 may be indicative of successes of interventions within the PMTCT program in Malawi.

Background: Although shoulder arthroplasty is less common than knee or hip arthroplasty, the number of procedures being performed is increasing rapidly. The treatment effect is a simple method to measure outcome of joint replacement. The method was applied to measure results of total hip/knee arthroplasty but not yet for shoulder arthroplasty., Methods: Included were patients with unilateral cuff arthropathy (Hamada grades > = 2) treated with reversed total shoulder arthroplasty (RSA) in this prospective multicenter study. The patients were assessed with the ASES questionnaire. The treatment effects (TE) was calculated for each patient. TE = score reduction/baseline score. A positive TE means amelioration, TE = 0 unchanged, and a negative TE means worse. The primary aim was to calculate the TE's for RSA at 6, 12, 24, and 60 months postoperatively. The secondary aim was to analyze the influence of confounders (preoperative Hamada grade, age, gender, dominance, side of the affected shoulder, general co-morbidities measured using ASA grade)., Results: Two hundred three patients were included for this analysis of whom 183 patients had a complete 2 year follow up. Two years postoperatively the mean ASES score augmented significant from 20.5 to 78.7 (p < 0.001). The 2 year TE's ranged from 1 to 0.09. We had no patient with a negative TE. A higher Hamada grade was associated with better TE's (Hamada grade 4+ vs. 2, p-value 0.042). For age and dominant side there were weak associations where those aged 80+ and dominant side had better TE's. The patients with higher ASA grade had lower TE's (ASA grade 4+ vs. 1, p-value 0.013). The mean TE's were 0.77 at 6-months, 0.81 at 1 year, 0.76 at 2 years and 0.73 at 5 years., Conclusions: The outcome for reverse shoulder arthroplasty can be measured with the treatment effect method; the 2 years TE's vary from 1 to 0.09. The mean treatment effects change little in the first five postoperative years (from 0.73 to 0.81). The confounders for better TE's were: higher severity of cuff arthropathy (Hamada grade 3, 4 and 5), less co-morbidities (ASA Grade 1), higher age (80+) and dominant side. Gender did not influence the 2-year TE's., Trial Registration: Comité intercantonal d'éthique (Jura, Fribourg, Neuchâtel), number 01/2008, 24.09.2008.

Background: With the explosion in the number of methods designed to analyze bulk and single-cell RNA-seq data, there is a growing need for approaches that assess and compare these methods. The usual technique is to compare methods on data simulated according to some theoretical model. However, as real data often exhibit violations from theoretical models, this can result in unsubstantiated claims of a method's performance., Results: Rather than generate data from a theoretical model, in this paper we develop methods to add signal to real RNA-seq datasets. Since the resulting simulated data are not generated from an unrealistic theoretical model, they exhibit realistic (annoying) attributes of real data. This lets RNA-seq methods developers assess their procedures in non-ideal (model-violating) scenarios. Our procedures may be applied to both single-cell and bulk RNA-seq. We show that our simulation method results in more realistic datasets and can alter the conclusions of a differential expression analysis study. We also demonstrate our approach by comparing various factor analysis techniques on RNA-seq datasets., Conclusions: Using data simulated from a theoretical model can substantially impact the results of a study. We developed more realistic simulation techniques for RNA-seq data. Our tools are available in the seqgendiff R package on the Comprehensive R Archive Network: https://cran.r-project.org/package=seqgendiff.

Objectives: Retrospective data including subgroup analyses in clinical studies have sparked strong interest in developing tumor mutational burden (TMB) as a predictive biomarker for immune checkpoint blockade. While individual factors influencing panel sequencing based measurement of TMB (psTMB) have been discussed in the recent literature, an integrative study quantifying, comparing and combining all potential confounders is still missing., Material and Methods: We separated different potential confounders of psTMB measurement including "panel size", "germline mutation filtering", "biological variance" and "technical variance" and developed a specific error model for each of these factors. Published experimental psTMB data were fitted to the error models to quantify the contribution of each of the confounders. The total psTMB variance was obtained as sum over the variance contributions of each of the confounders., Results: Using a typical large panel (size 1-1.5 Mbp) total errors of 57 %, 42 %, 34 % and 28 % were observed for tumors with psTMB of 5, 10, 20 and 40 muts/Mbp. Even for large panels, the stochastic error connected to the panel size represented the largest of all contributions to the total psTMB variance, especially for tumors with TMB up to 20 muts/Mbp. Other sources of psTMB variability could be kept under control, but rigorous quality control, best practice laboratory workflows and optimized bioinformatics pipelines are essential., Conclusion: A statistical framework for the analysis of complex, genomic biomarkers was developed and applied to the analysis of psTMB variability. The methods developed here can support the analysis of other quantitative biomarkers and their implementation in clinical practice., Competing Interests: Declaration of Competing Interest Dr. Budczies has nothing to disclose. Dr. Kazdal reports personal fees from Pfizer Pharma GmbH, outside the submitted work. Dr. Allgäuer has nothing to disclose. Dr. Christopoulos reports personal fees from Roche, personal fees from Chugai, grants and personal fees from Novartis, grants from Takeda, outside the submitted work. Dr. Rempel has nothing to disclose. Mrs. Pfarr has nothing to disclose. Dr. Weichert reports personal fees from Roche, MSD, BMS, AstraZeneca, Pfizer, Merck, Lilly, Boehringer, Novartis, Takeda, Amgen, Astellas and grants from Roche, MSD, BMS, Bruker outside the submitted work. Dr. Fröhling reports personal fees from Amgen, grants from AstraZeneca, personal fees from Eli Lilly, grants from Pfizer, grants from PharmaMar, personal fees from Roche, personal fees from Bayer, outside the submitted work;. Dr. Thomas reports personal fees from AbbVie, grants, personal fees and non-financial support from BMS, personal fees and non-financial support from Boehringer, grants and personal fees from Celgene, personal fees from Lilly, personal fees and non-financial support from MSD, personal fees and non-financial support from Novartis, grants and personal fees from Roche, personal fees from Takeda, grants from AstraZeneca, outside the submitted work. Dr. Peters reports personal fees from Abbvie, personal fees from Amgen, personal fees from AstraZeneca, personal fees from Bayer, personal fees from Biocartis, personal fees from Boehringer-Ingelheim, personal fees from Bistrol-Myers Squibb, personal fees from Clovis, personal fees from Daiichi Sankyo, personal fees from Debiopharm, personal fees from Eli Lilly, personal fees from F. Hoffmann-La Roche, personal fees from Foundation Medicine, personal fees from Illumina, personal fees from Janssen, personal fees from Merck Sharp and Dohme, personal fees from Merck Serono, personal fees from Merrimack, personal fees from Novartis, personal fees from Pharma Mar, personal fees from Pfizer, personal fees from Regeneron, personal fees from Sanofi, personal fees from Seattle Genetics and Takeda, personal fees from AstraZeneca, personal fees from Boehringer-Ingelheim, personal fees from Bristol-Myers Squibb, personal fees from Eli Lilly, personal fees from F. Hoffmann-La Roche, personal fees from Merck Sharp and Dohme, personal fees from Novartis, personal fees from Pfizer, personal fees from Takeda, non-financial support from Sponsored by Amgen, non-financial support from AstraZeneca, non-financial support from Boehringer-Ingelheim, non-financial support from Bristol-Meyers Squibb, non-financial support from Clovis, non-financial support from F. Hoffmann-La Roche, non-financial support from Illumina, non-financial support from Merck Sharp and Dohme, non-financial support from Merck Serono, non-financial support from Novartis, non-financial support from Pfizer, personal fees from Sanofi, personal fees from Bioinvent, personal fees from Blueprint Medicine, outside the submitted work. Dr. Endris reports personal fees from Thermo Fisher, personal fees from Astra Zeneca, outside the submitted work. Dr. Schirmacher reports grants from QuIP, during the conduct of the study; grants and personal fees from BMS, grants and personal fees from MSD, grants and personal fees from Roche, grants and personal fees from AstraZeneca, grants and personal fees from Novartis, personal fees from Chugai, personal fees from AbbVie, grants from Sanofi-Aventis, personal fees from Ipsen, grants and personal fees from Pfizer, grants from Illumina, grants from Thermo Fisher, outside the submitted work. Dr. Stenzinger reports other from Ilumina, during the conduct of the study; personal fees from AstraZeneca, grants and personal fees from Bristol-Myers Squibb, personal fees from Novartis, personal fees from Thermo Fisher Scientific, personal fees from Illumina, personal fees from MSD, personal fees from Roche, grants from Chugai, outside the submitted work., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Methodologies employed in the production of systematic reviews used to inform policy must be robust. In formulating the recent World Health Organisation (WHO) Environmental Noise Guidelines for the European Region, seven systematic reviews of evidence were commissioned to assess the relationship between environmental noise exposure and a range of health outcomes, six of which were nonauditory. Within the methodological guidance document devised for these reviews, inclusion and exclusion criteria for individual studies and existing reviews were applied in accordance with the Population-Exposure-Comparator-Outcome-Study (PECOS) framework for the evaluation of evidence. Specific criteria were defined for "populations" and source-specific "exposure", but no criteria were defined for the treatment of potential "effect modifiers". Furthermore, no criteria were set for the treatment of combined exposures. Employing a custom-designed assessment matrix, we assess the treatment of potential effect modifiers in the formulation of the aforementioned systematic reviews, all published in a Special Issue of the International Journal of Environmental Research and Public Health (IJERPH), titled "WHO Noise and Health Evidence Reviews". We identify substantial methodological variation in their treatment and propose the differentiation of "moderators" and "mediators" from "confounders" as the basis for criteria development-including combined exposures-for future systematic reviews.

Competing Interests: The authors have each completed and submitted an ICMJE form for disclosure of potential conflicts of interest. The authors declare that they have no competing interests, financial or otherwise, related to the current work. Both authors report services from RAI Services Company, during the conduct of the study.

The goal of the study was to investigate the quantitative impact of region of interest (ROI), software choice, muscle fiber orientation and preload tension on shear wave velocity (SWV). First, SWV was assessed in an isotropic elasticity phantom and ex vivo porcine muscle using a commercially available clinical ultrasound system. Secondly, SWV was acquired in relaxed and stretched calf muscles of healthy volunteers (dorsal extension of the talocrural joint), for both parallel and transverse probe direction to the fibers, as well as for different ROIs and software versions. The effect of intermediate probe-fiber alignments was also analyzed. Finally, the impact of confounding factors on SWV reproducibility was minimized with a second force-controlled volunteer study, in which the calf was isometrically loaded, and fiber orientation and ROI were well-defined. 2046 in vivoSWE images were acquired to analyze SWV reproducibility with different confounder settings. In healthy volunteers, the main variance-contributing factors were in order of importance muscle tension, fiber orientation, horizontal ROI size and insertion depth. Regression analysis showed significantly reduced SWV with increasing insertion depth for each study material. Parallel probe-fiber orientation, muscle stretch and increasing horizontal ROI size led to significantly higher SWV. Based on the results of the study, we provide recommendations to minimize the impact of confounders in musculoskeletal elastography and discuss the main confounding mechanisms and trade-offs between confounding variables. Coefficients of variation can be significantly reduced with a controlled protocol, if the confounders are clinically taken into account., (Copyright © 2019 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.)

Background: The aim of this study was to review the clinical data on the effectiveness of the pharmacotherapy of HIV-associated neurocognitive disorders (HANDs)., Methods: A literature search of PubMed was performed (from January 1996 to October 2018) using the terms: 'HIV-associated neurocognitive disorders', 'HIV-associated dementia', 'mild neurocognitive disorder (MND)', 'asymptomatic neurocognitive impairment (ANI)', 'adjuvant therapies', 'antiretroviral treatment (cART)', 'neurotoxicity', 'cART intensification', 'fluid markers', 'cerebrospinal fluid', 'protease inhibitors', 'nonnucleoside reverse transcriptase inhibitor', 'nucleoside reverse transcriptase inhibitors', and 'integrase strand transfer inhibitors'. Additional references were identified from a review of literature citations. All English language clinical studies of adjunctive therapies and neuronal markers were selected in order to evaluate a closer relationship between the early involvement and the onset of cognitive decline. We identified 407 relevant studies, of which 248 were excluded based on abstract analysis. Finally, we analyzed 35 articles, organizing the results by cART, adjuvant and neuronal markers (total of 7716 participants)., Results: It is important to inform clinicians about the importance of accurate phenotyping of HIV patients, incorporating an array of markers relevant to HAND pathophysiology, in order to assess the individual's risk and potential response to future personalized antiretroviral treatment., Conclusion: So far, no clinical trials of HAND therapies are effective beyond optimal suppression of HIV replication in the central nervous system. Combination of validated neuronal markers should be used to distinguish between milder HAND subtypes and improve efficiency of clinical trials, after strict control of confounders., Competing Interests: Conflict of interest statement: The authors declare that there is no conflict of interest.

Functional Class Scoring (FCS) is a network-based approach previously demonstrated to be powerful in missing protein prediction (MPP). We update its performance evaluation using data derived from new proteomics technology (SWATH) and also checked for reproducibility using two independent datasets profiling kidney tissue proteome. We also evaluated the objectivity of the FCS p -value, and followed up on the value of MPP from predicted complexes. Our results suggest that (1) FCS p -values are non-objective, and are confounded strongly by complex size, (2) best recovery performance do not necessarily lie at standard p -value cutoffs, (3) while predicted complexes may be used for augmenting MPP, they are inferior to real complexes, and are further confounded by issues relating to network coverage and quality and (4) moderate sized complexes of size 5 to 10 still exhibit considerable instability, we find that FCS works best with big complexes. While FCS is a powerful approach, blind reliance on its non-objective p -value is ill-advised.

OBJECTIVE: Low birth weight children are unusual among well-off families. However, in Brazil, low birth weight rate was higher in a more developed city than in a less developed one. The study objective was to find out the reasons to explain this paradox. METHODS: A study was carried out in two municipalities, Ribeirão Preto (Southeastern Brazil) and São Luís (Northeastern Brazil), which low birth weight rates were 10.7% and 7.6% respectively. Data from two birth cohorts were analyzed: 2,839 newborns in Ribeirão Preto in 1994 and 2,439 births in São Luís in 1997-1998. Multiple logistic regression analysis was performed, adjusted for confounders. RESULTS: Low birth weight risk factors in São Luís were primiparity, maternal smoking and maternal age less than 18 years. In Ribeirão Preto, the associated variables were family income between one and three minimum wages, maternal age less than 18 and equal to or more than 35 years, maternal smoking and cesarean section. In a combined model including both cohorts, Ribeirão Preto presented a 45% higher risk of low birth weight than São Luís. When adjusted for maternal smoking habit, the excess risk for low birth weight in Ribeirão Preto compared to São Luís was reduced by 49%, but the confidence interval was marginally significant. Differences in cesarean section rates between both cities contributed to partially explain the paradox. CONCLUSIONS: Maternal smoking was the most important risk factor for explaining the difference in low birth weight between both cities. The other factors contributed little to explain the difference in low birth weight rates.

Numerous studies suggest 'social gradient' in health, but it is less clear whether every step up the socio-economic ladder improves health by the same degree. Based on 4326 households, the present study examines the relationship between household income and psychological distress while identifying specific risk factor in different income groups. Overall, 26.5% of sampled households were reported for being distressed. Work pressure (OR 2.0, p < 0.01) and reducing time for family/friends (OR 1.79, p < 0.01) in high-income group; overcrowding (OR 3.1, p < 0.001), lacking drinking water (OR 2.27, p < 0.001) and indoor noise pollution (OR 1.76, p < 0.001) in low income group and overcrowding (OR 3.1, p < 0.001), lacking affordable health care (OR 2.58, p < 0.001), and indoor noise pollution (OR 1.6, p < 0.001) in medium income group were significant predictors of psychological distress. People in lower income group are at greater risk of becoming distressed, but the higher income is not always the guarantor of psychological well-being.

Psychotic experiences (PEs), including hallucination- and delusion-like experiences, are robustly associated with self-injurious thoughts and behaviours (SITB) in the general population. However, it remains unclear as to why there is an association. The purpose of this systematic review was to elucidate the role of other factors that influence the association between PEs and SITB and, in doing so, highlight potential mechanisms underlying the relationship. A search of electronic international databases was undertaken, including PubMed, PsycINFO and EMBASE, and eligible studies were grouped according to seven confounder categories: sociodemographics, mental disorders, alcohol and substance use, environmental, psychological, intervention and family history/genetic factors. The systematic search strategy identified 41 publications reporting on 1 39 427 participants from 16 different countries. In the majority of studies, where adjustment for other variables occurred, the association between PEs and SITB persisted, suggesting PEs have an independent role. Common mental disorders, psychological distress and negative environmental exposures explained a substantial amount of the variance and therefore need to be considered as potential underlying mechanisms. There was high variability in the variables adjusted for in these studies, and so the question still remains as to whether the association between PEs and self-harm/suicidality can be attributed (fully or in part) to confounding and mediating factors or directly causal mechanisms. Regardless of causality, the now extensive literature reporting an association between these two clinical phenomena supports the broad usefulness of PEs as an indicator of risk for SITB.

Random allocation of treatment or intervention is the key feature of clinical trials and divides patients into treatment groups that are approximately balanced for baseline, and therefore comparable covariates except for the variable treatment of the study. However, in observational studies, where treatment allocation is not random, patients in the treatment and control groups often differ in covariates that are related to intervention variables. These imbalances in covariates can lead to biased estimates of the treatment effect. However, randomized clinical trials are sometimes not feasible for ethical, logistical, economic or other reasons. To resolve these situations, interest in the field of clinical research has grown in designing studies that are most similar to randomized experiments using observational (i.e. non-random) data. Observational studies using propensity score analysis methods have been increasing in the scientific papers of Intensive Care. Propensity score analyses attempt to control for confounding in non-experimental studies by adjusting for the likelihood that a given patient is exposed. However, studies with propensity indexes may be confusing, and intensivists are not familiar with this methodology and may not fully understand the importance of this technique. The objectives of this review are: to describe the fundamentals of propensity index methods; to present the techniques to adequately evaluate propensity index models; to discuss the advantages and disadvantages of these techniques., (Copyright © 2018 Elsevier España, S.L.U. y SEMICYUC. All rights reserved.)

Background: Evidence suggests that dietary microRNAs (miRs) are bioavailable and regulate gene expression across species boundaries. Concerns were raised that the detection of dietary miRs in plasma might have been due to sample contamination or lack of assay specificity. Objectives: The objectives of this study were to assess potential confounders of plasma miR analysis and to detect miRs from bovine milk in human plasma., Methods: Potential confounders of plasma miR analysis (circadian rhythm, sample collection and storage, calibration, and erythrocyte hemolysis) were assessed by quantitative reverse transcriptase polymerase chain reaction (PCR) by using blood from healthy adults (7 men, 6 women; aged 23-57 y). Bovine miRs were analyzed by RNase H2-dependent PCR (rhPCR) in plasma collected from a subcohort of 11 participants before and 6 h after consumption of 1.0 L of 1%-fat bovine milk., Results: The use of heparin tubes for blood collection resulted in a complete loss of miRs. Circadian variations did not affect the concentrations of 8 select miRs. Erythrocyte hemolysis caused artifacts for some miRs if plasma absorbance at 414 nm was >0.300. The stability of plasma miRs depended greatly on the matrix in which the miRs were stored and whether the plasma was frozen before analysis. Purified miR-16, miR-200c, and cel-miR-39 were stable for ≤24 h at room temperature, whereas losses equaled ≤80% if plasma was frozen, thawed, and stored at room temperature for as little as 4 h. rhPCR distinguished between bovine and human miRs with small variations in the nucleotide sequence; plasma concentrations of Bos taurus (bta)-miR-21-5p and bta-miR-30a-5p were >100% higher 6 h after milk consumption than before milk consumption., Conclusions: Confounders in plasma miR analysis include the use of heparin tubes, erythrocyte hemolysis, and storage of thawed plasma at room temperature. rhPCR is a useful tool to detect dietary miRs., (© 2018 American Society for Nutrition. All rights reserved.)

Aim: To determine the degree of influence of the confounders on the outcome of ischemic stroke (IS)., Material and Methods: One hundred and eight patients were included in the prospective clinical cohort study. Based on disease outcomes, two groups of patients were singled out: 1st group - survivors (n=93), 2nd group - patients with fatal outcomes (n=15)., Results: Concomitant diseases were found in 80 (74.1%) patients. Twenty-eight (25.9%) patients had no concomitant pathology (without taking into account atherosclerosis, arterial hypertension, diabetes mellitus and coronary heart disease). The Pearson χ 2 test was 0.005 (p=0.944), which indicated that there was no significant association between the fatal outcome and the presence of confounders. The relative risk (RR) was 0.963 (95% CI 0.333-2.779), indicating that the likelihood of a favorable or fatal outcome was almost equal., Conclusion: Therefore, the presence or absence of confounders noted in patients of our cohort does not affect the likelihood of a favorable or fatal outcome.

The authors discuss the study by Naimi and colleagues regarding the protective impact of alcohol. The authors mention that observational studies on the consumption of alcohol show that moderate use is protective against many conditions such as liver cirrhosis. The authors state that reasonable doubt can be dismissed and discouraged by meta-analyses.

Aim: To highlights the problems of assessing cognitive deficits in schizophrenia, relevant to the epigenetic, as well as a wide range of other approaches to the search for biological bases of cognition., Material and Methods: The literature on the weaknesses in the evaluation of cognitive functions in patients with schizophrenia are summarized and discussed. The analysis is illustrated by our experience in developing a cognitive battery and a sample to examine relationships between DNA methylation in blood cells and cognitive deficits in schizophrenia., Results and Conclusion: It has been shown that to assess cognitive deficits in patients and to reduce the influence of confounders in epigenetic analysis it is necessary (1) to use a battery with the existing co-normative data in the target population, which allows to evaluate representativeness of control and patients included in the study sample, (2) to verify the theoretically driven battery structure using normative population and a cohort of patients, (3) to balance groups of cases and controls on the number, age and sex, for which an individual matching of cases and controls is best suited, (4) to conduct an additional statistical analysis controlling for education and smoking.

Objective: To investigate the potential association between serum folate levels and colorectal adenoma (CRA) occurrence and recurrence., Methods: This prospective study measured baseline serum folate levels in outpatients who were screened for CRA using colonoscopy. Participants were then randomly selected to produce one group with CRA and one without CRA. These two subgroups underwent further follow-up observations of colonoscopy to determine the occurrence of new and recurrent CRA., Results: A total of 1310 participants were screened at baseline: 888 were healthy subjects without CRA; and 422 had CRA. Two subgroups were randomly selected (n = 200 per group) for follow-up. In the overall population, baseline serum folate levels were significantly lower in patients with CRA or advanced CRA (A-CRA) compared with healthy participants without CRA. Similar findings were shown for the follow-up study in terms of the association between CRA and A-CRA occurrence and recurrence and baseline serum folate levels. After controlling for confounders, increased serum folate was associated with a reduced risk of occurrence of CRA (odds ratio [OR] 0.993, 95% confidence interval [CI] 0.924, 1.066) and recurrence of CRA (OR 0.749, 95% CI 0.322, 1.742)., Conclusions: Higher serum folate levels may be protective against CRA and/or A-CRA., (© The Author(s) 2016.)

Background: Few large epidemiologic studies have used rigorous case criteria, individual-level exposure measurements, and appropriate control for confounders to examine associations between workplace psychosocial and biomechanical factors and carpal tunnel syndrome (CTS)., Methods: Pooling data from five independent research studies, we assessed associations between prevalent CTS and personal, work psychosocial, and biomechanical factors while adjusting for confounders using multivariable logistic regression., Results: Prevalent CTS was associated with personal factors of older age, obesity, female sex, medical conditions, previous distal upper extremity disorders, workplace measures of peak forceful hand activity, a composite measure of force and repetition (ACGIH Threshold Limit Value for Hand Activity Level), and hand vibration., Conclusions: In this cross-sectional analysis of production and service workers, CTS prevalence was associated with workplace and biomechanical factors. The findings were similar to those from a prospective analysis of the same cohort with differences that may be due to recall bias and other factors., (© 2015 Wiley Periodicals, Inc.)

To discuss methods of preservation of treatment fidelity in health behavior change trials conducted in public health contexts. The treatment fidelity framework provided by the National Institutes of Health's Behavioral Change Consortium includes five domains of treatment fidelity (Study Design, Training, Delivery, Receipt, and Enactment). A measure of treatment fidelity was previously developed and validated using these categories. Strategies for assessment, monitoring, and enhancing treatment fidelity within each of the five treatment fidelity domains are discussed. The previously created measure of treatment fidelity is updated to include additional items on selecting providers, additional confounders, theory testing, and multicultural considerations. Implementation of a treatment fidelity plan may require extra staff time and costs. However, the economic and scientific costs of lack of attention to treatment fidelity are far greater than the costs of treatment fidelity implementation. Maintaining high levels of treatment fidelity with flexible adaptation according to setting, provider, and patient is the goal for public health trials. [ABSTRACT FROM AUTHOR]

This paper focuses on the problem of partially matched samples in the presence of confounders. We propose using propensity score matching to adjust for confounding factors for the subset of data with incomplete pairs, followed by integrating the P-values computed from the complete and incomplete paired samples, respectively. Several simulations and a case study on DNA methylation are considered to evaluate the operating characteristics of the proposed method.