confounding variable
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2021 ◽  
pp. 1-8
Author(s):  
Kimberly Virginin Cruz Correia da Silva ◽  

Background: There are emerging concerns that the COVID-19 pandemic may specifically increase suicide. Methods: Scoping Review in the MEDLINE/PubMed, SCOPUS, Web of Science, PsycINFO, Science Direct databases and in the medRxiv, bioRxiv and PsyArXiv preprint servers, using the descriptors “Covid-19”, “coronavirus infection”, “coronavirus”, “2019-nCoV”, “2019 new coronavirus disease”, “SARS-CoV-2”, “Suicide”, “General Public” and “Mental Health”. Results: A total of 62 studies were included in this review, where 10 studies were reported to have been conducted between March and May 2021; 39 in 2020; 4 in 2019; 3 in 2018; 1 in 2015; 2 in 2014; 2 in 2010 and 1 in 2004, all were conducted via online platforms. Limitations: We have interpreted our study findings in the context of the overall significant risk of exposure to suicide in our study population, while recognizing that individual level data of exposure to COVID-19 is a significant confounding variable. Conclusions: Being one of the first reviews in this context, the findings are anticipated to be helpful to predict the possible solutions for reducing the number of suicides in and facilitate further studies on strategies of how to alleviate such a stressful situation in COVID-19.


Author(s):  
Kimberly Virginin Cruz Correia da Silva ◽  

Background: There are emerging concerns that the COVID-19 pandemic may specifically increase suicide. Methods: Scoping Review in the MEDLINE/PubMed, SCOPUS, Web of Science, PsycINFO, Science Direct databases and in the medRxiv, bioRxiv and PsyArXiv preprint servers, using the descriptors “Covid-19”, “coronavirus infection”, “coronavirus”, “2019-nCoV”, “2019 new coronavirus disease”, “SARS-CoV-2”, “Suicide”, “General Public” and “Mental Health”. Results: A total of 62 studies were included in this review, where 10 studies were reported to have been conducted between March and May 2021; 39 in 2020; 4 in 2019; 3 in 2018; 1 in 2015; 2 in 2014; 2 in 2010 and 1 in 2004, all were conducted via online platforms. Limitations: We have interpreted our study findings in the context of the overall significant risk of exposure to suicide in our study population, while recognizing that individual level data of exposure to COVID-19 is a significant confounding variable. Conclusions: Being one of the first reviews in this context, the findings are anticipated to be helpful to predict the possible solutions for reducing the number of suicides in and facilitate further studies on strategies of how to alleviate such a stressful situation in COVID-19.


Author(s):  
Nicole M Brossier ◽  
Jennifer M Strahle ◽  
Samuel J Cler ◽  
Michael Wallendorf ◽  
David H Gutmann

Summary Tumor location has been proposed as a prognostic factor for pilocytic astrocytoma (PA), but since resection status varies by CNS location, these two variables are difficult to separate on multivariate analysis. To eliminate resection status as a confounding variable, we analyzed the outcomes of children with subtotally resected PA by brain location. We found that individuals with PA in the supratentorial midline region had an increased likelihood of multiple progression events. These children also exhibited more neurologic deficits over time compared to those with brainstem PA, frequently due to worsening vision and the acquisition of new endocrinopathies or weakness.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Céline Labouesse ◽  
Bao Xiu Tan ◽  
Chibeza C. Agley ◽  
Moritz Hofer ◽  
Alexander K. Winkel ◽  
...  

AbstractStudies of mechanical signalling are typically performed by comparing cells cultured on soft and stiff hydrogel-based substrates. However, it is challenging to independently and robustly control both substrate stiffness and extracellular matrix tethering to substrates, making matrix tethering a potentially confounding variable in mechanical signalling investigations. Moreover, unstable matrix tethering can lead to poor cell attachment and weak engagement of cell adhesions. To address this, we developed StemBond hydrogels, a hydrogel in which matrix tethering is robust and can be varied independently of stiffness. We validate StemBond hydrogels by showing that they provide an optimal system for culturing mouse and human pluripotent stem cells. We further show how soft StemBond hydrogels modulate stem cell function, partly through stiffness-sensitive ERK signalling. Our findings underline how substrate mechanics impact mechanosensitive signalling pathways regulating self-renewal and differentiation, indicating that optimising the complete mechanical microenvironment will offer greater control over stem cell fate specification.


2021 ◽  
pp. 201010582110405
Author(s):  
Mostafa Saadat

Introduction Accumulating evidence recommends that infectious diseases including coronavirus disease 2019 (COVID-19) are often associated with oxidative stress and inflammation. Paraoxonase 1 ( PON1, OMIM: 168,820), a member of the paraoxonase gene family, has antioxidant properties. Enzyme activity of paraoxonase depends on a variety of influencing factors such as polymorphisms of PON1, ethnicity, gender, age, and a number of environmental variables. The PON1 has two common functional polymorphisms, namely, Q192R (rs662) and L55M (rs854560). The R192 and M55 alleles are associated with increase and decrease in enzyme activity, respectively. Objective The present study was conducted to investigate the possible association of rs662 and rs854560 polymorphisms with morbidity and mortality of COVID-19. Methods Data for the prevalence, mortality, and amount of accomplished diagnostic test (per 106 people) on 25 November 2020 from 48 countries were included in the present study. The Human Development Index (HDI) was used as a potential confounding variable. Results The frequency of M55 was positively correlated with the prevalence (partial r = 0.487, df = 36, p = 0.002) and mortality of COVID-19 (partial r = 0.551, df = 36, p < 0.001), after adjustments for HDI and amount of the accomplished diagnostic test as possible confounders. Conclusions This means that countries with higher M55 frequency have higher prevalence and mortality of COVID-19.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Emily Goren ◽  
Chong Wang ◽  
Zhulin He ◽  
Amy M. Sheflin ◽  
Dawn Chiniquy ◽  
...  

Abstract Background Microbiome studies have uncovered associations between microbes and human, animal, and plant health outcomes. This has led to an interest in developing microbial interventions for treatment of disease and optimization of crop yields which requires identification of microbiome features that impact the outcome in the population of interest. That task is challenging because of the high dimensionality of microbiome data and the confounding that results from the complex and dynamic interactions among host, environment, and microbiome. In the presence of such confounding, variable selection and estimation procedures may have unsatisfactory performance in identifying microbial features with an effect on the outcome. Results In this manuscript, we aim to estimate population-level effects of individual microbiome features while controlling for confounding by a categorical variable. Due to the high dimensionality and confounding-induced correlation between features, we propose feature screening, selection, and estimation conditional on each stratum of the confounder followed by a standardization approach to estimation of population-level effects of individual features. Comprehensive simulation studies demonstrate the advantages of our approach in recovering relevant features. Utilizing a potential-outcomes framework, we outline assumptions required to ascribe causal, rather than associational, interpretations to the identified microbiome effects. We conducted an agricultural study of the rhizosphere microbiome of sorghum in which nitrogen fertilizer application is a confounding variable. In this study, the proposed approach identified microbial taxa that are consistent with biological understanding of potential plant-microbe interactions. Conclusions Standardization enables more accurate identification of individual microbiome features with an effect on the outcome of interest compared to other variable selection and estimation procedures when there is confounding by a categorical variable.


2021 ◽  
Vol 1 (3) ◽  
pp. 303-313
Author(s):  
Muhammad Ihsan Fadillah ◽  
Ilmiawati Ilmiawati ◽  
Eka Fithra Elfi

Background. Cigarette smoke may cause harm not only to active smokers but also to those in their vicinity (passive smokers). Cigarettes contain nicotine, which triggers the release of catecholamines, affecting lipid metabolism. Exposure to cigarette smoke may increase serum LDL cholesterol levels in active and passive smokers. Objective. This study aimed to analyze the correlation between serum cotinine (a metabolite of nicotine) and LDL cholesterol levels in young adults. Methods. A cross-sectional study was performed, the analysis included 122 Andalas University students, aged 17.5 - 25.9 years. Demographic data, smoking degree, serum cotinine, and LDL cholesterol levels were collected. Bivariate analysis was carried out individually on each independent and confounding variables to the dependent variable, followed by multiple hierarchical regressions analysis. Results. Serum cotinine levels in this study was 10,5 ± 6.8 ng/ml (mean±SD), and serum LDL cholesterol levels were 65,5±18,5 mg/dl (mean±SD). There was no significant correlation between serum cotinine and LDL cholesterol levels in bivariate analysis. However, serum cotinine levels had a nonlinear correlation with serum LDL cholesterol levels in the regression model that included body mass index (BMI) as the confounding variable. The adjusted r2 value in this study is 0,066, the standardized β coefficient for the BMI is 0,197 (p = 0.028), for the serum cotinine levels is -0,830 (p = 0.007), and for the squared serum cotinine levels is 0,753 (p = 0.014).


Diagnostics ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 820
Author(s):  
Martina Faraldi ◽  
Laura Gerosa ◽  
Marta Gomarasca ◽  
Veronica Sansoni ◽  
Silvia Perego ◽  
...  

Circulating miRNAs are ideal diagnostics and prognostics biomarkers in cancer since altered levels of specific miRNAs have been associated to development/progression of several cancers. Physical activity is a recognized preventive strategy against several cancers, but it may also modify the baseline levels of cancer-associated miRNAs and, hence, may act as a confounding pre-analytical variable. This study aimed at understanding whether physical activity-dependent changes in cancer-associated circulating miRNAs profile could act as a confounding variable. A panel comprising 179 miRNAs was assayed in plasma from 20 highly trained and 10 sedentary men. RT-qPCR data were analyzed with the 2−2ΔΔCT methods and normalized on hsa-miR-320d, as determined by bioinformatics analysis. miRNAs associated with the diagnosis of the most prevalent cancers were considered. Only those miRNAs, relevantly associated with cancers, found ≥2-fold up- or downregulated in highly trained subjects compared to sedentary were disclosed. The results reveal that chronic physical activity determined modifications altering the baseline level of several cancer-associated miRNAs and, hence, their diagnostic and prognostic potential. In conclusion, based on our results, a physically active status emerges as an important pre-analytical variable able to alter the basal level of circulating miRNAs, and these alterations might be considered as potentially misleading the analytical output.


2021 ◽  
pp. 014920632110064
Author(s):  
John R. Busenbark ◽  
Hyunjung (Elle) Yoon ◽  
Daniel L. Gamache ◽  
Michael C. Withers

Management research increasingly recognizes omitted variables as a primary source of endogeneity that can induce bias in empirical estimation. Methodological scholarship on the topic overwhelmingly advocates for empirical researchers to employ two-stage instrumental variable modeling, a recommendation we approach with trepidation given the challenges associated with this analytic procedure. Over the course of two studies, we leverage a statistical technique called the impact threshold of a confounding variable (ITCV) to better conceptualize what types of omitted variables might actually bias causal inference and whether they have appeared to do so in published management research. In Study 1, we apply the ITCV to published studies and find that a majority of the causal inference is unlikely biased from omitted variables. In Study 2, we respecify an influential simulation on endogeneity and determine that only the most pervasive omitted variables appear to substantively impact causal inference. Our simulation also reveals that only the strongest instruments (perhaps unrealistically strong) attenuate bias in meaningful ways. Taken together, we offer guidelines for how scholars can conceptualize omitted variables in their research, provide a practical approach that balances the tradeoffs associated with instrumental variable models, and comprehensively describe how to implement the ITCV technique.


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