scholarly journals Acute effects of fine particulate matter constituents on mortality: A systematic review and meta-regression analysis

2017 ◽  
Vol 109 ◽  
pp. 89-100 ◽  
Author(s):  
Souzana Achilleos ◽  
Marianthi-Anna Kioumourtzoglou ◽  
Chih-Da Wu ◽  
Joel D. Schwartz ◽  
Petros Koutrakis ◽  
...  
Keyword(s):  
Systematic Review ◽  
Regression Analysis ◽  
Particulate Matter ◽  
Fine Particulate Matter ◽  
Acute Effects ◽  
Fine Particulate ◽  
Meta Regression ◽  
Meta Regression Analysis

scholarly journals Temporal trends in sperm count: a systematic review and meta-regression analysis

2017 ◽  
Vol 23 (6) ◽  
pp. 646-659 ◽  
Author(s):  
Hagai Levine ◽  
Niels Jørgensen ◽  
Anderson Martino-Andrade ◽  
Jaime Mendiola ◽  
Dan Weksler-Derri ◽  
...  
Keyword(s):  
Systematic Review ◽  
Regression Analysis ◽  
Sperm Count ◽  
Temporal Trends ◽  
Meta Regression ◽  
Meta Regression Analysis

Short-term and long-term exposures to fine particulate matter constituents and health: A systematic review and meta-analysis

2019 ◽  
Vol 247 ◽  
pp. 874-882 ◽  
Author(s):  
Yang Yang ◽  
Zengliang Ruan ◽  
Xiaojie Wang ◽  
Yin Yang ◽  
Tonya G. Mason ◽  
...  
Keyword(s):  
Systematic Review ◽  
Particulate Matter ◽  
Meta Analysis ◽  
Fine Particulate Matter ◽  
Short Term ◽  
Fine Particulate

scholarly journals Long-term manifestations and modifiers of prevalence estimates of the post-COVID-19 syndrome: A systematic review and meta-analysis.

2021 ◽  
Author(s):  
Daniel De-la-Rosa-Martínez ◽  
Marco Antonio Delaye-Martínez ◽  
Omar Yaxmehen Bello-Chavolla ◽  
Alejandro Sicilia-Andrade ◽  
Isaac David Juárez-Cruz ◽  
...  
Keyword(s):  
Systematic Review ◽  
Regression Analysis ◽  
Meta Analysis ◽  
Population Characteristics ◽  
Published Data ◽  
System Disease ◽  
Prevalence Estimates ◽  
Meta Regression ◽  
Meta Regression Analysis

Background: Post-acute COVID-19 syndrome (PACS) is a multi-system disease comprising persistent symptomatology after the acute phase of infection. Long-term PACS effects significantly impact patient outcomes, but their incidence remains uncharacterized due to high heterogeneity between studies. Therefore, we aimed to summarize published data on PACS, characterizing the clinical presentation, prevalence, and modifiers of prevalence estimates. Method: In this systematic review and meta-analysis, we research MEDLINE for original studies published from January 1st, 2020, to January 31st, 2021, that reported proportions of PACS manifestations. Studies were eligible for inclusion if they included patients aged ≥18 years with confirmed COVID-19 by RT-PCR or antigen testing and a minimum follow-up of 21 days. The prevalence of individual manifestations across studies was pooled using random-effects meta-analysis. For evaluating determinants of heterogeneity, meta-regression analysis was performed. This study was registered in PROSPERO (CRD42019125025). Results: After screening 1,235 studies, we included 29 reports for analysis. Twenty-seven meta-analyses were performed, and 61 long-term manifestations were described. The pooled prevalence of PACS was 56% (95%CI 45-66%), with the most common manifestations being diminished health status, fatigue, asthenia, dyspnea, myalgias, hyposmia and dysgeusia. Most of the included studies presented high heterogeneity. After conducting the meta-regression analysis, we identified that age, gender, number of comorbidities, and reported symptoms significantly modify the prevalence estimation of PACS long-term manifestations. Conclusion: PACS is inconsistently reported between studies, and population characteristics influence the prevalence estimates due to high heterogeneity. A systematized approach for the study of PACS is needed to characterize its impact adequately.

Systematic review and meta-regression analysis of technical efficiency in dairy farms

2016 ◽  
Vol 65 (3) ◽  
pp. 279-301 ◽  
Author(s):  
Taciana Mareth ◽  
Antonio Marcio Tavares Thomé ◽  
Fernando Luiz Cyrino Oliveira ◽  
Luiz Felipe Scavarda
Keyword(s):  
Systematic Review ◽  
Regression Analysis ◽  
Technical Efficiency ◽  
Geographical Location ◽  
Dairy Farms ◽  
Two Dimensions ◽  
Farm Size ◽  
Content Type ◽  
Meta Regression ◽  
Meta Regression Analysis

Purpose – The purpose of this paper is to complement and extend previous literature reviews on Technical Efficiency (TE) in dairy farms, analysing the effects of different methodologies and study-specific characteristics on Mean TE (MTE). Design/methodology/approach – The researchers independently conducted a systematic review of more than 400 abstracts and 85 full-text papers. Original keywords were applied to seven key electronic databases. Results from a meta-regression analysis of 85 published papers totalling 443 TE distributions in dairy farms worldwide are discussed. Findings – The variation in the MTE indexes reported in the literature can be explained by the methodology of estimations (method of estimation, functional form of frontier models, model dimensionality), the farms geographical location and farm size. Additionally, the results suggest that, given the state of technology prevailing in each country at the time that the studies on TE were conducted, dairy farmers in the sample could increase milk output by 20.9 per cent (level of inefficiency), on average, if they produce on their frontiers. Originality/value – This study makes two important contributions: first, it updates and compares previous works on frontier estimation of TE in dairy farms; and second, it adds two dimensions of dairy farms, size (herd and land area) and economic development, to the known differentials of TE measurement.

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