Long-Term Efficacy of Methylphenidate Immediate-Release for the Treatment of Childhood ADHD

2016 ◽  
Vol 21 (1) ◽  
pp. 3-13 ◽  
Author(s):  
Carlos Renato Moreira Maia ◽  
Samuele Cortese ◽  
Arthur Caye ◽  
Thomas Kuhn Deakin ◽  
Guilherme Vanoni Polanczyk ◽  
...  
Keyword(s):  
Random Effect ◽  
Random Effect Model ◽  
Immediate Release ◽  
Long Term Effects ◽  
Childhood Adhd ◽  
Meta Regression ◽  
Meta Regression Analysis ◽  
Inattention And Hyperactivity ◽  
Meta Analyses

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 Method: Published and unpublished studies in which participants were treated with MPH-IR for 12 weeks or more were searched.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.

scholarly journals Diabetes is associated with increased risk for in-hospital mortality in patients with COVID-19: a systematic review and meta-analysis comprising 18,506 patients

2020 ◽  
Author(s):  
Leonidas Palaiodimos ◽  
Natalia Chamorro-Pareja ◽  
Dimitrios Karamanis ◽  
Weijia Li ◽  
Phaedon D. Zavras ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Hospitalized Patients ◽  
Risk Of Death ◽  
Increased Risk ◽  
Patients With Diabetes ◽  
Meta Regression ◽  
Meta Regression Analysis

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.

scholarly journals A Systematic Review, Meta-Analysis, and Meta-Regression Evaluating the Efficacy and Mechanisms of Action of Probiotics and Synbiotics in the Prevention of Surgical Site Infections and Surgery-Related Complications

2018 ◽  
Vol 7 (12) ◽  
pp. 556 ◽  
Author(s):  
Karolina Skonieczna-Żydecka ◽  
Mariusz Kaczmarczyk ◽  
Igor Łoniewski ◽  
Luis Lara ◽  
Anastasios Koulaouzidis ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Surgical Site Infections ◽  
Short Chain Fatty Acids ◽  
Cochrane Central Register ◽  
Reactive Protein ◽  
Central Register ◽  
Meta Regression ◽  
Meta Regression Analysis

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.

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

2021 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
S. Shindy ◽  
Muhammad Kasim Aidid ◽  
Muhammad Nusrang
Keyword(s):  
Regression Analysis ◽  
Dengue Hemorrhagic Fever ◽  
Effect Size ◽  
Random Effect ◽  
Random Effect Model ◽  
Hemorrhagic Fever ◽  
Meta Regression ◽  
Meta Regression Analysis ◽  
Using Data ◽  
Size Heterogeneity

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.

scholarly journals Meta-analysis on maternal deaths and assessing significant factors for heterogeneity between states of India during 2016

2021 ◽  
Vol 10 (8) ◽  
pp. 3192
Author(s):  
Vanamail Perumal
Keyword(s):  
Maternal Mortality ◽  
Meta Analysis ◽  
Random Effect ◽  
Maternal Mortality Ratio ◽  
Random Effect Model ◽  
Registration System ◽  
Mortality Ratio ◽  
Meta Regression ◽  
Meta Regression Analysis ◽  
Significant Factors

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. 

scholarly journals More than 50 long-term effects of COVID-19: a systematic review and meta-analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sandra Lopez-Leon ◽  
Talia Wegman-Ostrosky ◽  
Carol Perelman ◽  
Rosalinda Sepulveda ◽  
Paulina A. Rebolledo ◽  
...  
Keyword(s):  
Systematic Review ◽  
Meta Analysis ◽  
Management Strategies ◽  
Original Data ◽  
Long Term Effects ◽  
Pooled Prevalence ◽  
Attention Disorder ◽  
Initial Recovery ◽  
Meta Analyses

AbstractCOVID-19 can involve persistence, sequelae, and other medical complications that last weeks to months after initial recovery. This systematic review and meta-analysis aims to identify studies assessing the long-term effects of COVID-19. LitCOVID and Embase were searched to identify articles with original data published before the 1st of January 2021, with a minimum of 100 patients. For effects reported in two or more studies, meta-analyses using a random-effects model were performed using the MetaXL software to estimate the pooled prevalence with 95% CI. PRISMA guidelines were followed. A total of 18,251 publications were identified, of which 15 met the inclusion criteria. The prevalence of 55 long-term effects was estimated, 21 meta-analyses were performed, and 47,910 patients were included (age 17–87 years). The included studies defined long-COVID as ranging from 14 to 110 days post-viral infection. It was estimated that 80% of the infected patients with SARS-CoV-2 developed one or more long-term symptoms. The five most common symptoms were fatigue (58%), headache (44%), attention disorder (27%), hair loss (25%), and dyspnea (24%). Multi-disciplinary teams are crucial to developing preventive measures, rehabilitation techniques, and clinical management strategies with whole-patient perspectives designed to address long COVID-19 care.

Mindfulness- and Acceptance-Based Interventions for Stroke Survivors: A Systematic Review and Meta-Analysis

2021 ◽  
pp. 003435522110432
Author(s):  
Areum Han
Keyword(s):  
Systematic Review ◽  
Depressive Symptoms ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Mental Fatigue ◽  
Stroke Survivors ◽  
Positive Effects ◽  
Meta Analyses

Objective: Mindfulness- and acceptance-based intervention (MABI) is an emerging evidenced-based practice, but no systematic review incorporating meta-analyses for MABIs in stroke survivors has been conducted. The objective of this systematic review was to measure the effectiveness of MABIs on outcomes in people with stroke. Method: Three electronic databases, including PubMed, CINAHL, and PsycINFO, were searched to identify relevant studies published in peer-reviewed journals. The methodological quality of the included studies was assessed. Data were extracted and combined in a meta-analysis with a random-effect model to compute the size of the intervention effect. Results: A total of 11 studies met the eligibility criteria. Meta-analyses found a small-to-moderate effect of MABIs on depressive symptoms (standardized mean difference [SMD] = 0.39, 95% confidence interval [CI] = [0.12, 0.66]) and a large effect on mental fatigue (SMD = 1.22, 95% CI = [0.57, 1.87]). No statistically significant effect of MABIs on anxiety, quality of life, and mindfulness was found, but there was a trend in favor of MABIs overall. Conclusions: This meta-analysis found positive effects of MABIs on depressive symptoms and mental fatigue in stroke survivors, but future high-quality studies are needed to guarantee treatment effects of MABIs on varied outcomes in stroke survivors.

Long-Term Effects of Bariatric Surgery on Type II Diabetes, Hypertension and Hyperlipidemia: A Meta-Analysis and Meta-Regression Study with 5-Year Follow-Up

2014 ◽  
Vol 25 (3) ◽  
pp. 397-405 ◽  
Author(s):  
Cristian Ricci ◽  
Maddalena Gaeta ◽  
Emanuele Rausa ◽  
Emanuele Asti ◽  
Francesco Bandera ◽  
...  
Keyword(s):  
Bariatric Surgery ◽  
Type Ii Diabetes ◽  
Meta Analysis ◽  
Type Ii ◽  
Long Term Effects ◽  
Meta Regression

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.

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