scholarly journals Analisis Meta Regresi untuk Menjelaskan Heterogenitas Hasil Penelitian pada Kejadian Demam Berdarah Dengue

Author(s):  
S. Shindy ◽  
Muhammad Kasim Aidid ◽  
Muhammad Nusrang

Abstract. Meta regression analysis is an analysis that can summarize the results of research with the same topic so that a conclusion is obtained in the form of effect size and can explain the heterogeneity of the results of several studies. In this study using data from the previous Dengue Hemorrhagic Fever incident study which linked the factors of habit of draining habits of water shelters (TPA). Based on the results of the analysis, there was heterogeneity between studies. For the landfill drainage factor, the estimated parameter combined effect size random effect model is 3.60 and the proportion of heterogeneity is 54.08%. The results of the meta-regression for habitual factors of landfill drainage factors, the influence of TPA drainage habits can explain heterogeneity between effect sizes.Keywords: Effect size, Heterogeneity, Meta Regression Analysis, Dengue Hemorrhagic Fever.

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 234
Author(s):  
Patrizio E. Tressoldi ◽  
Lance Storm

This meta-analysis is an investigation into anomalous perception (i.e., conscious identification of information without any conventional sensorial means). The technique used for eliciting an effect is the ganzfeld condition (a form of sensory homogenization that eliminates distracting peripheral noise). The database consists of studies published between January 1974 and December 2020 inclusive. The overall effect size estimated both with a frequentist and a Bayesian random-effect model, were in close agreement yielding an effect size of .088 (.04-.13). This result passed four publication bias tests and seems not contaminated by questionable research practices. Trend analysis carried out with a cumulative meta-analysis and a meta-regression model with Year of publication as covariate, did not indicate sign of decline of this effect size. The moderators analyses show that selected participants outcomes were almost three-times those obtained by non-selected participants and that tasks that simulate telepathic communication show a two-fold effect size with respect to tasks requiring the participants to guess a target. The Stage 1 Registered Report can be accessed here: https://doi.org/10.12688/f1000research.24868.3


2016 ◽  
Vol 21 (1) ◽  
pp. 3-13 ◽  
Author(s):  
Carlos Renato Moreira Maia ◽  
Samuele Cortese ◽  
Arthur Caye ◽  
Thomas Kuhn Deakin ◽  
Guilherme Vanoni Polanczyk ◽  
...  

Objective: To evaluate the long-term effects of methylphenidate imediate-release (MPH-IR), and to confirm the efficacy established in previous meta-analyses of short-term studies. Method: Published and unpublished studies in which participants were treated with MPH-IR for 12 weeks or more were searched. Pooled effect sizes from these studies were computed with the DerSimonian and Laird random-effect model. Meta-regression analysis was conducted to estimate covariates associated with treatment effects. Results: Seven studies were included. Pooled parents ratings for inattention and hyperactivity/impulsivity resulted in standardized mean difference (SMD) = 0.96 (95% confidence interval [CI] = [0.60, 1.32]) and SMD = 1.12 (95% CI = [0.85, 1.39]), respectively; pooled teachers ratings showed SMD = 0.98 (95% CI = [0.09, 1.86]) for inattention and SMD = 1.25 (95% CI = [0.7, 1.81]) for hyperactivity/impulsivity. No evidence of association of any covariates with treatment effect was detected in the meta-regression. Conclusion: MPH-IR is efficacious for childhood ADHD for periods longer than 12 weeks.


Author(s):  
Leonidas Palaiodimos ◽  
Natalia Chamorro-Pareja ◽  
Dimitrios Karamanis ◽  
Weijia Li ◽  
Phaedon D. Zavras ◽  
...  

AbstractBackgroundInfectious diseases are more frequent and can be associated with worse outcomes in patients with diabetes. Our aim was to systematically review and synthesize with a meta-analysis the available observational studies reporting the effect of diabetes in mortality among hospitalized patients with COVID-19.MethodsMedline, Embase, Google Scholar, and medRxiv databases were reviewed. A random-effect model meta-analysis was used and I-square was utilized to assess the heterogeneity. In-hospital mortality was defined as the endpoint. Sensitivity, subgroup, and meta-regression analyses were performed.Results18,506 patients were included in this meta-analysis (3,713 diabetics and 14,793 non-diabetics). Patients with diabetes were associated with a higher risk of death compared to patients without diabetes (OR: 1.65; 95% CI: 1.35-1.96; I2 77.4%). The heterogeneity was high. A study level meta-regression analysis was performed for all the important covariates and no significant interactions were found between the covariates and the outcome of mortality.ConclusionThis meta-analysis shows that that the likelihood of death is 65% higher in diabetic hospitalized patients with COVID-19 compared to non-diabetics. Further studies are needed to assess whether this association is independent or not, as well as to investigate to role of glucose control prior or during the disease.


2018 ◽  
Vol 7 (12) ◽  
pp. 556 ◽  
Author(s):  
Karolina Skonieczna-Żydecka ◽  
Mariusz Kaczmarczyk ◽  
Igor Łoniewski ◽  
Luis Lara ◽  
Anastasios Koulaouzidis ◽  
...  

Intestinal microbiota play an important role in the pathogenesis of surgical site infections (SSIs) and other surgery-related complications (SRCs). Probiotics and synbiotics were found to lower the risk of surgical infections and other surgery-related adverse events. We systematically reviewed the approach based on the administration of probiotics and synbiotics to diminish SSIs/SRCs rates in patients undergoing various surgical treatments and to determine the mechanisms responsible for their effectiveness. A systematic literature search in PubMed/MEDLINE/Cochrane Central Register of Controlled Trials from the inception of databases to June 2018 for trials in patients undergoing surgery supplemented with pre/pro/synbiotics and randomized to the intervention versus placebo/no treatment and reporting on primarily: (i) putative mechanisms of probiotic/symbiotic action, and secondarily (ii) SSIs and SRCs outcomes. Random-effect model meta-analysis and meta-regression analysis of outcomes was done. Thirty-five trials comprising 3028 adult patients were included; interventions were probiotics (n = 16) and synbiotics (n = 19 trials). We found that C-reactive protein (CRP) and Interleukin-6 (IL-6) were significantly decreased (SMD: −0.40, 95% CI [−0.79, −0.02], p = 0.041; SMD: −0.41, 95% CI [−0.70, −0.02], p = 0.006, respectively) while concentration of acetic, butyric, and propionic acids were elevated in patients supplemented with probiotics (SMD: 1.78, 95% CI [0.80, 2.76], p = 0.0004; SMD: 0.67, 95% CI [0.37, −0.97], p = 0.00001; SMD: 0.46, 95% CI [0.18, 0.73], p = 0.001, respectively). Meta-analysis confirmed that pro- and synbiotics supplementation was associated with significant reduction in the incidence of SRCs including abdominal distention, diarrhea, pneumonia, sepsis, surgery site infection (including superficial incisional), and urinary tract infection, as well as the duration of antibiotic therapy, duration of postoperative pyrexia, time of fluid introduction, solid diet, and duration of hospital stay (p < 0.05). Probiotics and synbiotics administration counteract SSIs/SRCs via modulating gut-immune response and production of short chain fatty acids.


Author(s):  
Vanamail Perumal

Objective of the study was to provide a more precise estimate of maternal mortality (MM), maternal mortality ratio (MMR) and to identify significant factors contributing for heterogeneity between the states in India. “Metaprop” procedure in STATA software, which are specific to binomial data was applied on state wise MM data published by sample registration system (SRS) during 2014-16. An overall MM estimate and potential sources of heterogeneity could be identified using meta-regression. Corrected estimates of MMR by states were compared. SRS published the MM data by 17 Major states. Overall reported MM was 8.8 per 100, 000 women. Estimate obtained by random effect model was 8.3 (95% CI: 5.9-11.1) per 100,000 women. Heterogeneity between states was very high (I2-statistics =91.9%), and egger regression revealed no reporting bias (p=0.672). Meta-regression analysis indicated that the percent women attending full antenatal care (ANC) visits found to be highly significant (p<0.001) for MM with inverse relationship implying that the states with a higher percentage of women with full ANC visits are likely to have lesser MM. While the estimate of MMR by SRS was 130 per 100,000 live births, corrected MMR was 123 (95% CI: 87-164) accounting for 26% reduction from previous estimate 167 obtained in 2013. This paper provided a precious estimate of both MM and MMR adjusted for sampling weight. Further, the importance of either full ANC visits or four ANC visits could be demonstrated for reduction in MMR on achieving the Millennium development goal (MDG) in the country. 


F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 826
Author(s):  
Patrizio E. Tressoldi ◽  
Lance Storm

This meta-analysis is an investigation into anomalous perception (i.e., conscious identification of information without any conventional sensorial means). The technique used for eliciting an effect is the ganzfeld condition (a form of sensory homogenization that eliminates distracting peripheral noise). The database consists of peer-reviewed studies published between January 1974 and June 2020 inclusive. The overall effect size will be estimated using a frequentist and a Bayesian random-effect model. Moderators analyses will be used to examine the influence of level of experience of participants, the type of task and the peer-review level. Publication bias will be estimated by using four different tests. Trend analysis will be conducted with a cumulative meta-analysis and a meta-regression model with Year of publication as covariate.


F1000Research ◽  
2021 ◽  
Vol 9 ◽  
pp. 826 ◽  
Author(s):  
Patrizio E. Tressoldi ◽  
Lance Storm

This meta-analysis is an investigation into anomalous perception (i.e., conscious identification of information without any conventional sensorial means). The technique used for eliciting an effect is the ganzfeld condition (a form of sensory homogenization that eliminates distracting peripheral noise). The database consists of peer-reviewed studies published between January 1974 and June 2020 inclusive. The overall effect size will be estimated using a frequentist and a Bayesian random-effect model. Moderators analyses will be used to examine the influence of level of experience of participants, the type of task and the peer-review level. Publication bias will be estimated by using four different tests. Trend analysis will be conducted with a cumulative meta-analysis and a meta-regression model with Year of publication as covariate.


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