scholarly journals Prevalence of Worldwide Neonatal Calf Diarrhoea Caused by Bovine Rotavirus in Combination with Bovine Coronavirus, Escherichia coli K99 and Cryptosporidium spp.: A Meta-Analysis

Animals ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 1014
Author(s):  
Michael Brunauer ◽  
Franz-Ferdinand Roch ◽  
Beate Conrady
Keyword(s):  
Escherichia Coli ◽  
Meta Analysis ◽  
Influencing Factor ◽  
Diagnostic Methods ◽  
Mixed Infections ◽  
Bovine Coronavirus ◽  
Bovine Rotavirus ◽  
Cryptosporidium Spp ◽  
Calf Diarrhoea ◽  
Meta Analyses

Multiple enteropathogens such as bovine rotavirus (BRV), bovine coronavirus (BCoV), Escherichia coli K99 (ETEC) and Cryptosporidium spp. (Crypto) are the most common causes of calf diarrhoea during the first 30 days of animal age. Three weighted-stratified random-effects meta-analyses were performed to calculate the worldwide prevalence of mixed infections of the causative agents (i.e., BRV-BCoV, BRV-ETEC, BRV-Crypto) and their potential influencing factors. The meta-analysis covered 41 studies (94 sub-studies) in 21 countries that determined the presence or absence of mixed infections in global calf populations. The highest worldwide estimated pooled prevalence was identified for BRV-Crypto (6.69%), followed by BRV-BCoV (2.84%), and BRV-ETEC (1.64%). The chance of detecting BCoV in calves with diarrhoea was 1.83 higher in the presence of BRV compared to calves without BRV, whereby an inhibition effect (odds ratio: 0.77) was determined between BRV and Crypto infections. The diagnostic methods were identified as a significant influencing factor in the detection of all considered mixed infections, while the other analysed factors differed in relation to their effect on prevalence. In contrast to BRV-BCoV, the prevalence of BRV-ETEC and BRV-Crypto mixed infections followed the course of individual ETEC and Crypto prevalence related to the age class of the sampled animals.

scholarly journals Cryptosporidium spp. Infections in Combination with Other Enteric Pathogens in the Global Calf Population

Animals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1786
Author(s):  
Beate Conrady ◽  
Michael Brunauer ◽  
Franz-Ferdinand Roch
Keyword(s):  
Meta Analysis ◽  
Random Effect ◽  
Inhibitory Effect ◽  
Enterotoxigenic Escherichia Coli ◽  
Bovine Rotavirus ◽  
Cryptosporidium Spp ◽  
The United Kingdom ◽  
Concurrent Infections ◽  
Neonatal Calves ◽  
Meta Analyses

The most common worldwide diarrhoea-causing agents in neonatal calves are Cryptosporidium spp. (Crypto), bovine rotavirus (BRV), bovine coronavirus (BCoV), and enterotoxigenic Escherichia coli F5 (K99) (ETEC). Crypto is a zoonotic pathogen of diarrhoea in humans, particularly for children and immunocompromised adults. Four weighted-stratified random-effect meta-analyses including meta-regression analyses were performed to calculate the worldwide mean prevalence of Crypto and associated concurrent infections with BRV, BCoV and ETEC, as well as their potential influencing factors. The meta-analysis incorporated 28 studies (56 substudies) in 17 countries that determined the presence or absence of concurrent infections with Crypto in the global calf population. Approximately half of all considered studies presented here were conducted in Europe independently of the type of infections with Crypto. Within Europe, the highest estimated mean Crypto-BRV prevalence was identified in Ireland (16.7%), the highest estimated mean Crypto-BCoV prevalence was detected in the United Kingdom (4.3%), and the highest estimated mean Crypto-ETEC prevalence across the literature was determined in Turkey (4.7%). The chance of detecting BRV, BCoV, and ETEC in calves with diarrhoea was 0.8 (confidence interval (CI): 0.6–1.0), 0.7 (CI: 0.5–1.0) and 0.6 (CI: 0.4–0.9) lower in the presence of Crypto compared to calves without Crypto. This may indicate an inhibitory effect between BRV, BCoV, ETEC, and Crypto in calves. The variance in the published prevalence across the literature can mainly be explained by the “diagnostic” factor (R2 min–max: 0.0–40.3%), followed by the “health status of the sampled animals” (R2 min–max: 1.4–27.3%) and “geographical region” (R2 min–max: 5.9–23.6%).

scholarly journals Standardisation of lymphatic filariasis microfilaraemia prevalence estimates based on different diagnostic methods: a systematic review and meta-analysis

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Natalie V. S. Vinkeles Melchers ◽  
Luc E. Coffeng ◽  
Sake J. de Vlas ◽  
Wilma A. Stolk
Keyword(s):  
Systematic Review ◽  
Lymphatic Filariasis ◽  
Membrane Filtration ◽  
Meta Analysis ◽  
Diagnostic Technique ◽  
Diagnostic Techniques ◽  
Diagnostic Methods ◽  
Prevalence Estimates ◽  
Study Population ◽  
Meta Analyses

Abstract Background Lymphatic filariasis (LF) infection is generally diagnosed through parasitological identification of microfilariae (mf) in the blood. Although historically the most commonly used technique for counting mf is the thick blood smear based on 20 µl blood (TBS20), various other techniques and blood volumes have been applied. It is therefore a challenge to compare mf prevalence estimates from different LF-survey data. Our objective was to standardise microfilaraemia (mf) prevalence estimates to TBS20 as the reference diagnostic technique. Methods We first performed a systematic review to identify studies reporting on comparative mf prevalence data as measured by more than one diagnostic test, including TBS20, on the same study population. Associations between mf prevalences based on different diagnostic techniques were quantified in terms of odds ratios (OR, with TBS20 blood as reference), using a meta-regression model. Results We identified 606 articles matching our search strategy and included 14 in our analyses. The OR of the mf prevalences as measured by the more sensitive counting chamber technique (≥ 50 µl blood) was 2.90 (95% confidence interval (CI): 1.60–5.28). For membrane filtration (1 ml blood) the OR was 2.39 (95% CI: 1.62–3.53), Knott’s technique it was 1.54 (95% CI: 0.72–3.29), and for TBS in ≥ 40 µl blood it was 1.37 (95% CI: 0.81–2.30). Conclusions We provided transformation factors to standardise mf prevalence estimates as detected by different diagnostic techniques to mf prevalence estimates as measured by TBS20. This will facilitate the use and comparison of more datasets in meta-analyses and geographic mapping initiatives across countries and over time.

scholarly journals The global prevalence and trend of human intestinal carriage of ESBL-producing Escherichia coli in the community

2020 ◽  
Vol 76 (1) ◽  
pp. 22-29 ◽  
Author(s):  
Yihienew M Bezabih ◽  
Wilber Sabiiti ◽  
Endalkachew Alamneh ◽  
Alamneh Bezabih ◽  
Gregory M Peterson ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Meta Analysis ◽  
Fold Increase ◽  
Upward Trend ◽  
Carriage Rate ◽  
E Coli ◽  
The Past ◽  
Pooled Prevalence ◽  
Meta Analyses ◽  
Public Health Strategies

Abstract Objectives Intestinal colonization by ESBL Escherichia coli and its association with community-acquired MDR infections is of great concern. This review determined the worldwide prevalence of human faecal ESBL E. coli carriage and its trend in the community over the past two decades. Methods A systematic literature search was conducted using PubMed, EMBASE and Google Scholar to retrieve articles published between 1 January 2000 and 13 February 2020 that contained data on the prevalence of faecal carriage of ESBL E. coli among healthy individuals. A cumulative (for the whole period) meta-analysis was used to estimate the global and regional pooled prevalence rates. Articles were grouped into study periods of 3 years, and subgroup meta-analyses were undertaken to examine the global pooled prevalence over time. Results Sixty-two articles covering 29 872 healthy persons were included in this meta-analysis. The cumulative (2003–18) global pooled prevalence of ESBL E. coli intestinal carriage in the community was 16.5% (95% CI 14.3%–18.7%; P  <  0.001). The pooled prevalence showed an upward trend, increasing from 2.6% (95% CI 1.6%–4.0%) in 2003–05 to 21.1% (95% CI 15.8%–27.0%) in 2015–18. Over the whole period, the highest carriage rate was observed in South-East Asia (27%; 95% CI 2.9%–51.3%), while the lowest occurred in Europe (6.0%; 95% CI 4.6%–7.5%). Conclusions Globally, an 8-fold increase in the intestinal carriage rate of ESBL E. coli in the community has occurred over the past two decades. Prevention of its spread may require new therapeutic and public health strategies.

A Meta-Analysis of Interviews and Cognitive Ability

2013 ◽  
Vol 12 (4) ◽  
pp. 157-169 ◽  
Author(s):  
Philip L. Roth ◽  
Allen I. Huffcutt
Keyword(s):  
Cognitive Ability ◽  
Meta Analysis ◽  
Incremental Validity ◽  
Employment Interviews ◽  
Moderator Analysis ◽  
The Future ◽  
Research Questions ◽  
Meta Analyses ◽  
The Relationship

The topic of what interviews measure has received a great deal of attention over the years. One line of research has investigated the relationship between interviews and the construct of cognitive ability. A previous meta-analysis reported an overall corrected correlation of .40 ( Huffcutt, Roth, & McDaniel, 1996 ). A more recent meta-analysis reported a noticeably lower corrected correlation of .27 ( Berry, Sackett, & Landers, 2007 ). After reviewing both meta-analyses, it appears that the two studies posed different research questions. Further, there were a number of coding judgments in Berry et al. that merit review, and there was no moderator analysis for educational versus employment interviews. As a result, we reanalyzed the work by Berry et al. and found a corrected correlation of .42 for employment interviews (.15 higher than Berry et al., a 56% increase). Further, educational interviews were associated with a corrected correlation of .21, supporting their influence as a moderator. We suggest a better estimate of the correlation between employment interviews and cognitive ability is .42, and this takes us “back to the future” in that the better overall estimate of the employment interviews – cognitive ability relationship is roughly .40. This difference has implications for what is being measured by interviews and their incremental validity.

Power-Enhanced Funnel Plots for Meta-Analysis

2020 ◽  
Vol 228 (1) ◽  
pp. 43-49 ◽  
Author(s):  
Michael Kossmeier ◽  
Ulrich S. Tran ◽  
Martin Voracek
Keyword(s):  
Statistical Power ◽  
Meta Analysis ◽  
Relevant Information ◽  
Selective Reporting ◽  
Graphical Display ◽  
Funnel Plot ◽  
Evidential Value ◽  
Graphical Displays ◽  
Funnel Plots ◽  
Meta Analyses

Abstract. Currently, dedicated graphical displays to depict study-level statistical power in the context of meta-analysis are unavailable. Here, we introduce the sunset (power-enhanced) funnel plot to visualize this relevant information for assessing the credibility, or evidential value, of a set of studies. The sunset funnel plot highlights the statistical power of primary studies to detect an underlying true effect of interest in the well-known funnel display with color-coded power regions and a second power axis. This graphical display allows meta-analysts to incorporate power considerations into classic funnel plot assessments of small-study effects. Nominally significant, but low-powered, studies might be seen as less credible and as more likely being affected by selective reporting. We exemplify the application of the sunset funnel plot with two published meta-analyses from medicine and psychology. Software to create this variation of the funnel plot is provided via a tailored R function. In conclusion, the sunset (power-enhanced) funnel plot is a novel and useful graphical display to critically examine and to present study-level power in the context of meta-analysis.

Which Data to Meta-Analyze, and How?

2019 ◽  
Vol 227 (1) ◽  
pp. 64-82 ◽  
Author(s):  
Martin Voracek ◽  
Michael Kossmeier ◽  
Ulrich S. Tran
Keyword(s):  
Empirical Research ◽  
Meta Analysis ◽  
Curve Analysis ◽  
Research Progress ◽  
Primary Data ◽  
Statistical Procedures ◽  
Graphical Displays ◽  
Primary Data Analysis ◽  
Meta Analyses ◽  
Data Analytic

Abstract. Which data to analyze, and how, are fundamental questions of all empirical research. As there are always numerous flexibilities in data-analytic decisions (a “garden of forking paths”), this poses perennial problems to all empirical research. Specification-curve analysis and multiverse analysis have recently been proposed as solutions to these issues. Building on the structural analogies between primary data analysis and meta-analysis, we transform and adapt these approaches to the meta-analytic level, in tandem with combinatorial meta-analysis. We explain the rationale of this idea, suggest descriptive and inferential statistical procedures, as well as graphical displays, provide code for meta-analytic practitioners to generate and use these, and present a fully worked real example from digit ratio (2D:4D) research, totaling 1,592 meta-analytic specifications. Specification-curve and multiverse meta-analysis holds promise to resolve conflicting meta-analyses, contested evidence, controversial empirical literatures, and polarized research, and to mitigate the associated detrimental effects of these phenomena on research progress.

The Orchard Plot: Cultivating a Forest Plot for Use in Ecology, Evolution and Beyond

2019 ◽  
Author(s):  
Shinichi Nakagawa ◽  
Malgorzata Lagisz ◽  
Rose E O'Dea ◽  
Joanna Rutkowska ◽  
Yefeng Yang ◽  
...  
Keyword(s):  
Meta Analysis ◽  
R Package ◽  
Effect Sizes ◽  
Forest Plot ◽  
Point Estimates ◽  
Aggregate Effect ◽  
The Individual ◽  
Meta Analyses ◽  
Heterogeneous Effect ◽  
Intuitive Interpretation

‘Classic’ forest plots show the effect sizes from individual studies and the aggregate effect from a meta-analysis. However, in ecology and evolution meta-analyses routinely contain over 100 effect sizes, making the classic forest plot of limited use. We surveyed 102 meta-analyses in ecology and evolution, finding that only 11% use the classic forest plot. Instead, most used a ‘forest-like plot’, showing point estimates (with 95% confidence intervals; CIs) from a series of subgroups or categories in a meta-regression. We propose a modification of the forest-like plot, which we name the ‘orchard plot’. Orchard plots, in addition to showing overall mean effects and CIs from meta-analyses/regressions, also includes 95% prediction intervals (PIs), and the individual effect sizes scaled by their precision. The PI allows the user and reader to see the range in which an effect size from a future study may be expected to fall. The PI, therefore, provides an intuitive interpretation of any heterogeneity in the data. Supplementing the PI, the inclusion of underlying effect sizes also allows the user to see any influential or outlying effect sizes. We showcase the orchard plot with example datasets from ecology and evolution, using the R package, orchard, including several functions for visualizing meta-analytic data using forest-plot derivatives. We consider the orchard plot as a variant on the classic forest plot, cultivated to the needs of meta-analysts in ecology and evolution. Hopefully, the orchard plot will prove fruitful for visualizing large collections of heterogeneous effect sizes regardless of the field of study.

Laser Influence on Dental Sensitivity Compared to Other Light Sources Used During In-office Dental Bleaching: Systematic Review and Meta-analysis

2020 ◽  
Vol 45 (6) ◽  
pp. 589-597
Author(s):  
BGS Casado ◽  
EP Pellizzer ◽  
JR Souto Maior ◽  
CAA Lemos ◽  
BCE Vasconcelos ◽  
...  
Keyword(s):  
Randomized Clinical Trials ◽  
Color Change ◽  
Meta Analysis ◽  
Present Review ◽  
Cochrane Library ◽  
Light Sources ◽  
Eligibility Criteria ◽  
Tooth Color ◽  
Significant Difference ◽  
Meta Analyses

Clinical Relevance The use of laser light during bleaching will not reduce the incidence or severity of sensitivity and will not increase the degree of color change compared with nonlaser light sources. SUMMARY Objective: To evaluate whether the use of laser during in-office bleaching promotes a reduction in dental sensitivity after bleaching compared with other light sources. Methods: The present review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) and is registered with PROSPERO (CDR42018096591). Searches were conducted in the PubMed/Medline, Web of Science, and Cochrane Library databases for relevant articles published up to August 2018. Only randomized clinical trials among adults that compared the use of laser during in-office whitening and other light sources were considered eligible. Results: After analysis of the texts retrieved during the database search, six articles met the eligibility criteria and were selected for the present review. For the outcome dental sensitivity, no significant difference was found favoring any type of light either for intensity (mean difference [MD]: −1.60; confidence interval [CI]: −3.42 to 0.22; p=0.09) or incidence (MD: 1.00; CI: 0.755 to 1.33; p=1.00). Regarding change in tooth color, no significant differences were found between the use of the laser and other light sources (MD: −2.22; CI: −6.36 to 1.93; p=0.29). Conclusions: Within the limitations of the present study, laser exerts no influence on tooth sensitivity compared with other light sources when used during in-office bleaching. The included studies demonstrated that laser use during in-office bleaching may have no influence on tooth color change.

Identification of and Correction for Publication Bias: Comment

2019 ◽  
Author(s):  
Amanda Kvarven ◽  
Eirik Strømland ◽  
Magnus Johannesson
Keyword(s):  
Publication Bias ◽  
False Positive ◽  
Large Scale ◽  
Meta Analysis ◽  
False Positive Rate ◽  
Effect Sizes ◽  
Replication Studies ◽  
Moderate Reduction ◽  
Positive Rate ◽  
Meta Analyses

Andrews & Kasy (2019) propose an approach for adjusting effect sizes in meta-analysis for publication bias. We use the Andrews-Kasy estimator to adjust the result of 15 meta-analyses and compare the adjusted results to 15 large-scale multiple labs replication studies estimating the same effects. The pre-registered replications provide precisely estimated effect sizes, which do not suffer from publication bias. The Andrews-Kasy approach leads to a moderate reduction of the inflated effect sizes in the meta-analyses. However, the approach still overestimates effect sizes by a factor of about two or more and has an estimated false positive rate of between 57% and 100%.

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