scholarly journals Diurnal preference and depressive symptomatology: a meta-analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ray Norbury
Keyword(s):  
Visual Inspection ◽  
Depressive Symptomatology ◽  
Meta Analysis ◽  
Large Body ◽  
Physical And Mental Health ◽  
Major Depressive ◽  
Small Effect Size ◽  
Diurnal Preference ◽  
Funnel Plots ◽  
Substantial Heterogeneity

AbstractEveningness, a preference for later sleep and rise times, has been associated with a number of negative outcomes in terms of both physical and mental health. A large body of evidence links eveningness to Major Depressive Disorder (MDD). However, to date, evidence quantifying this association is limited. The current meta-analysis included 43 effect sizes from a total 27,996 participants. Using a random-effects model it was demonstrated that eveningness is associated with a small effect size (Fisher’s Z = − 2.4, 95% CI [− 0.27. − 0.21], p < 0.001). Substantial heterogeneity between studies was observed, with meta-regression analyses demonstrating a significant effect of mean age on the association between diurnal preference and depression. There was also evidence of potential publication bias as assessed by visual inspection of funnel plots and Egger’s test. The association between diurnal preference and depression is small in magnitude and heterogenous. A better understanding of the mechanistic underpinnings linking diurnal preference to depression and suitably powered prospective studies that allow causal inference are required.

scholarly journals Global Incidence of Necrotizing Enterocolitis: a Systematic Review and Meta-Analysis

2020 ◽  
Author(s):  
Amer Alsaied ◽  
Nazmul Islam ◽  
Lukman Thalib
Keyword(s):  
Systematic Review ◽  
Cohort Studies ◽  
Publication Bias ◽  
Necrotizing Enterocolitis ◽  
Meta Analysis ◽  
Sensitivity Analyses ◽  
Cochrane Library ◽  
Vlbw Infants ◽  
Funnel Plots ◽  
Substantial Heterogeneity

Abstract Background: Necrotizing Enterocolitis (NEC) is a major cause of morbidity and mortality in the Neonatal Intensive Care Unit (NICU), yet the global incidence of NEC has not been systematically evaluated. We conducted a systematic review and meta-analysis of cohort studies reporting the incidence of NEC in infants with Very Low Birth Weight (VLBW).Methods: The databases searched included PubMed, MEDLINE, the Cochrane Library, EMBASE and grey literature. Eligible studies were cohort or population-based studies of newborns including registry data reporting incidence of NEC. Data were extracted from the selected papers included incidence of NEC cases and size of population at risk, author and publication details, follow up period covered by the study, location and setting of the study and whether it was VLBW infants or preterm infants. Additionally, risk of bias assessment of the included studies were carried out using a validated tool. Bias adjusted Quality Effect Model (QEM) were used to pool the estimates. In the presence of substantial heterogeneity, Random Effect Models (REM) were used as an additionally sensitivity analyses. The heterogeneity between studies were evaluated using the Cochrane Q statistics and Higgin’s I2 value. Subgroup analysis and meta-regression were used to explore the sources of heterogeneity. Funnel plots as appropriate for ratio measures were used to assess publication bias. Results: A systematic and comprehensive search of databases identified 27 cohort studies reporting the incidence of NEC. The pooled estimate of the global incidence of NEC was 6.0% (95% CI: 4.0%-9.0%). There were substantial heterogeneity (I2 = 100%) between studies. Funnel plots showed no evidence of publication bias.Conclusion: Seven out of 100 of all VLBW infants in NICU are likely to develop NEC. However, there were considerable heterogeneity between studies. High quality studies assessing incidence of NEC along with associated risk factors are warranted.

Visual Inference for the Funnel Plot in Meta-Analysis

2019 ◽  
Vol 227 (1) ◽  
pp. 83-89 ◽  
Author(s):  
Michael Kossmeier ◽  
Ulrich S. Tran ◽  
Martin Voracek
Keyword(s):  
Visual Inspection ◽  
Type I Error ◽  
Statistical Tests ◽  
Meta Analysis ◽  
Real Data ◽  
Type I ◽  
Funnel Plot ◽  
Funnel Plots ◽  
Meta Analyses ◽  
Open Nature

Abstract. The funnel plot is widely used in meta-analyses to assess potential publication bias. However, experimental evidence suggests that informal, mere visual, inspection of funnel plots is frequently prone to incorrect conclusions, and formal statistical tests (Egger regression and others) entirely focus on funnel plot asymmetry. We suggest using the visual inference framework with funnel plots routinely, including for didactic purposes. In this framework, the type I error is controlled by design, while the explorative, holistic, and open nature of visual graph inspection is preserved. Specifically, the funnel plot of the actually observed data is presented simultaneously, in a lineup, with null funnel plots showing data simulated under the null hypothesis. Only when the real data funnel plot is identifiable from all the funnel plots presented, funnel plot-based conclusions might be warranted. Software to implement visual funnel plot inference is provided via a tailored R function.

scholarly journals Coinfections with Bacteria, Fungi, and Respiratory Viruses in Patients with SARS-CoV-2: A Systematic Review and Meta-Analysis

Pathogens ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 809
Author(s):  
Saad Alhumaid ◽  
Abbas Al Mutair ◽  
Zainab Al Alawi ◽  
Abeer M. Alshawi ◽  
Salamah A. Alomran ◽  
...  
Keyword(s):  
Systematic Review ◽  
Cohort Studies ◽  
Visual Inspection ◽  
Fungal Infections ◽  
Meta Analysis ◽  
Case Series ◽  
Respiratory Viruses ◽  
Effect Sizes ◽  
P Values ◽  
Funnel Plots

Background: Coinfection with bacteria, fungi, and respiratory viruses in SARS-CoV-2 is of particular importance due to the possibility of increased morbidity and mortality. In this meta-analysis, we calculated the prevalence of such coinfections. Methods: Electronic databases were searched from 1 December 2019 to 31 March 2021. Effect sizes of prevalence were pooled with 95% confidence intervals (CIs). To minimize heterogeneity, we performed sub-group analyses. Results: Of the 6189 papers that were identified, 72 articles were included in the systematic review (40 case series and 32 cohort studies) and 68 articles (38 case series and 30 cohort studies) were included in the meta-analysis. Of the 31,953 SARS-CoV-2 patients included in the meta-analysis, the overall pooled proportion who had a laboratory-confirmed bacterial infection was 15.9% (95% CI 13.6–18.2, n = 1940, 49 studies, I2 = 99%, p < 0.00001), while 3.7% (95% CI 2.6–4.8, n = 177, 16 studies, I2 = 93%, p < 0.00001) had fungal infections and 6.6% (95% CI 5.5–7.6, n = 737, 44 studies, I2 = 96%, p < 0.00001) had other respiratory viruses. SARS-CoV-2 patients in the ICU had higher co-infections compared to ICU and non-ICU patients as follows: bacterial (22.2%, 95% CI 16.1–28.4, I2 = 88% versus 14.8%, 95% CI 12.4–17.3, I2 = 99%), and fungal (9.6%, 95% CI 6.8–12.4, I2 = 74% versus 2.7%, 95% CI 0.0–3.8, I2 = 95%); however, there was an identical other respiratory viral co-infection proportion between all SARS-CoV-2 patients [(ICU and non-ICU) and the ICU only] (6.6%, 95% CI 0.0–11.3, I2 = 58% versus 6.6%, 95% CI 5.5–7.7, I2 = 96%). Funnel plots for possible publication bias for the pooled effect sizes of the prevalence of coinfections was asymmetrical on visual inspection, and Egger’s tests confirmed asymmetry (p values < 0.05). Conclusion: Bacterial co-infection is relatively high in hospitalized patients with SARS-CoV-2, with little evidence of S. aureus playing a major role. Knowledge of the prevalence and type of co-infections in SARS-CoV-2 patients may have diagnostic and management implications.

Alcohol misuse in bipolar disorder. A systematic review and meta-analysis of comorbidity rates

2014 ◽  
Vol 29 (3) ◽  
pp. 117-124 ◽  
Author(s):  
A. Di Florio ◽  
N. Craddock ◽  
M. van den Bree
Keyword(s):  
Bipolar Disorder ◽  
Alcohol Misuse ◽  
Meta Analysis ◽  
Geographical Location ◽  
Significant Heterogeneity ◽  
Gender Ratio ◽  
Control Groups ◽  
Funnel Plots ◽  
And Gender ◽  
Substantial Heterogeneity

AbstractAims:To assess the comorbidity rates of alcohol use disorders (AUDs) in bipolar disorder (BD) and to explore possible sources of heterogeneity.Methods:Studies were identified through database searches. Meta-analytic techniques were employed to aggregate data on lifetime comorbidity and to explore possible sources of heterogeneity. Funnel plots were used to detect publication bias.Results:In clinical studies, AUDs affected more than one in three subjects with BD. Significant heterogeneity was found, which was largely explained by the geographical location of study populations and gender ratio of participants. AUDs affected more than one in five women and two in five men.Conclusion:AUDs are highly prevalent in BD. Our study revealed a substantial heterogeneity across studies. Further research including control groups is needed. Patients with BD should be assessed for current and previous AUDs.

Abstract P014: Impact of Antihypertensive Class on Central Systolic Blood Pressure and Augmentation Index: A Meta-Analysis

Circulation ◽  
2015 ◽  
Vol 131 (suppl_1) ◽  
Author(s):  
Tracey J McGaughey ◽  
Emily A Fletcher ◽  
Sachin A Shah
Keyword(s):  
Blood Pressure ◽  
Systolic Blood Pressure ◽  
Publication Bias ◽  
Visual Inspection ◽  
Augmentation Index ◽  
Meta Analysis ◽  
Cochrane Library ◽  
Central Systolic Blood Pressure ◽  
Funnel Plots ◽  
The Impact

Introduction: New evidence suggests central systolic blood pressure (cSBP) is a superior predictor of adverse cardiovascular outcomes as compared to peripheral systolic blood pressure (pSBP). Additionally, augmentation index (AI) provides a surrogate assessment of vascular stiffness. We performed a meta-analysis to assess the impact of antihypertensive drug classes on cSBP and AI. METHODS: Search terms related to blood pressure and AI were used to identify relevant articles in PubMed, Cochrane Library and CINAHL limited to randomized trials in humans and publications in English. Appropriate data on cSBP, pSBP and AI were extracted along with other study characteristics. Weighted mean differences (WMD) between the pSBP and cSBP with 95% confidence intervals (CI) were calculated using the DerSimonian-Laird random-effects methodology. For AI, the WMD from baseline was determined. Further, the data was sorted by antihypertensive class (angiotensin converting enzyme inhibitors (ACE-Is), angiotensin II receptor blockers (ARBs), beta-blockers (BBs), calcium channel blockers (CCBs) and diuretics) to determine their impact on cSBP and AI. Subgroup analyses were performed to assess robustness of results by limiting to the fixed-effects model, a primary diagnosis of hypertension, and excluding studies with JADAD scores < 3. Publication bias was assessed using the Egger’s statistic and visual inspection of funnel plots. Statistical heterogeneity was assessed using the I2 statistic. RESULTS: Fifty-one and 58 studies incorporating 4381 and 3716 unique subjects were included for cSBP and AI respectively. Overall, antihypertensives reduced pSBP more than cSBP (2.52mmHg, 95%CI 1.35 to 3.69; I2 =21.9%). ACE-Is, ARBs, CCBs and diuretics reduced cSBP and pSBP in a similar manner (-2.40mmHg, 95%CI -4.89 to 0.08; 1.12mmHg, 95%CI -2.25 to 4.49; 1.01mmHg, 95%CI -2.17 to 4.19; 0.65mmHg, 95%CI -2.47 to 3.77 respectively). BBs posed a significantly greater reduction in pSBP as compared to cSBP (5.19mmHg, 95%CI 3.21 to 7.18). The change in AI from baseline was (-3.09, 95%CI -3.90 to -2.28; I2 =84.5%). A significant reduction in AI was seen with ACE-Is, ARBs, CCB and diuretics (-5.61, 95%CI -6.95 to -4.27; -5.28, 95%CI -8.61 to -1.95; -5.36, 95%CI -6.95 to -3.77; -3.24, 95%CI -5.45 to -1.03 respectively). BBs reduced AI non-significantly (-0.32, 95% CI -1.48 to 0.84). While the Egger’s statistic showed a lack of publication bias (p>0.125), it cannot be ruled out based on visual inspection of funnel plots. CONCLUSIONS: BBs are not as beneficial in reducing cSBP as opposed to ACE-Is, ARBs, CCBs and diuretics. In contrast, ACE-Is, ARBs, CCBs and diuretics significantly reduce AI, which is not evident with BB therapy. The views expressed in this material are those of the author(s), and do not reflect the official policy or position of the U.S. Government, the Department of Defense, or the Department of the Air Force.

scholarly journals Efficacy of bio- and neurofeedback for depression: a meta-analysis

2021 ◽  
pp. 1-16
Author(s):  
J. Fernández-Alvarez ◽  
M. Grassi ◽  
D. Colombo ◽  
C. Botella ◽  
P. Cipresso ◽  
...  
Keyword(s):  
Effect Size ◽  
Treatment Efficacy ◽  
Depressive Symptomatology ◽  
Meta Analysis ◽  
Group Analysis ◽  
Research Quality ◽  
Major Depressive ◽  
Publication Number ◽  
Treatment Of Depression

Abstract Background For many years, biofeedback and neurofeedback have been implemented in the treatment of depression. However, the effectiveness of these techniques on depressive symptomatology is still controversial. Hence, we conducted a meta-analysis of studies extracted from PubMed, Scopus, Web of Science and Embase. Methods Two different strings were considered for each of the two objectives of the study: A first group comprising studies patients with major depressive disorder (MDD) and a second group including studies targeting depressive symptomatology reduction in other mental or medical conditions. Results In the first group of studies including patients with MDD, the within-group analyses yielded an effect size of Hedges' g = 0.717, while the between-group analysis an effect size of Hedges' g = 1.050. Moderator analyses indicate that treatment efficacy is only significant when accounting for experimental design, in favor of randomized controlled trials (RCTs) in comparison to non RCTs, whereas the type of neurofeedback, trial design, year of publication, number of sessions, age, sex and quality of study did not influence treatment efficacy. In the second group of studies, a small but significant effect between groups was found (Hedges' g = 0.303) in favor of bio- and neurofeedback against control groups. Moderator analyses revealed that treatment efficacy was not moderated by any of the sociodemographic and clinical variables. Conclusions Heart rate variability (HRV) biofeedback and neurofeedback are associated with a reduction in self-reported depression. Despite the fact that the field has still a large room for improvement in terms of research quality, the results presented in this study suggests that both modalities may become relevant complementary strategies for the treatment of MDD and depressive symptomatology in the coming years.

scholarly journals The Efficacy of Bio- and Neurofeedback for Depression: A Meta-analysis

2020 ◽  
Author(s):  
Javier Fernández-Álvarez ◽  
Massimiliano Grassi ◽  
Desirée Colombo ◽  
Desiree Colombo ◽  
Cristina Botella ◽  
...  
Keyword(s):  
Effect Size ◽  
Treatment Efficacy ◽  
Depressive Symptomatology ◽  
Meta Analysis ◽  
Group Analysis ◽  
Research Quality ◽  
Major Depressive ◽  
Publication Number ◽  
Treatment Of Depression

For many years, biofeedback and neurofeedback have been implemented in the treatment of depression. However, the effectiveness of these techniques on depressive symptomatology is still controversial. Hence, we conducted a meta-analysis of studies extracted from PubMed, Scopus, Web of Science and Embase.Two different strings were considered for each of the two objectives of the study: A first group comprising studies with Major Depressive Disorder (MDD) patients and a second group including studies targeting depressive symptomatology reduction in other mental or medical conditions.In the first group of studies including MDD patients, the within-group analyses yielded an effect size of Hedges’ g = 0.717, while the between-group analysis an effect size of Hedges’ g = 1.050. Moderator analyses indicate that treatment efficacy is only significant when accounting for experimental design, in favor of RCTs in comparison to non RCTs, whereas type of neurofeedback, trial design, year of publication, number of sessions, age, gender and quality of study did not influence treatment efficacy. In the second group of studies, a small but significant effect between groups was found (Hedges’ g = 0.303) in favor of bio- and neurofeedback against control groups. Moderator analyses revealed that treatment efficacy was not moderated by any of the sociodemographic and clinical variables.HRV Biofeedback and Neurofeedback are associated with a reduction in self-reported depression. Despite the fact that the field has still a large room for improvement in terms of research quality, the results presented in this study suggests that both modalities may become relevant complementary strategies for the treatment of MDD and depressive symptomatology in the coming years.

scholarly journals Global Incidence of Necrotizing Enterocolitis: a Systematic Review and Incidence Meta-Analysis

2020 ◽  
Author(s):  
Amer Alsaied ◽  
Nazmul Islam ◽  
Lukman Thalib
Keyword(s):  
Systematic Review ◽  
Cohort Studies ◽  
Publication Bias ◽  
Necrotizing Enterocolitis ◽  
Meta Analysis ◽  
Cochrane Library ◽  
Effect Model ◽  
Funnel Plots ◽  
Meta Regression ◽  
Substantial Heterogeneity

Abstract Background: Necrotizing Enterocolitis (NEC) is a major source of morbidity and mortality in the Neonatal Intensive Care Unit (NICU), yet the global incidence is not systematically evaluated. We conducted a systematic review and Meta-Analysis of cohort studies reporting the incidence of NEC in infants with Very Low Birth Weight (VLBW).Methods: The databases searched included PubMed, MEDLINE, the Cochrane Library, EMBASE and grey literature. Eligible studies were cohort or population-based studies of newborns including registry data reporting incidence of NEC. Data were extracted from the selected papers and variables extracted included author and publication details, time period covered by the study, location and setting of the study and whether it was VLBW infants or preterm infants, incidence or number on NEC cases and size of population at risk were extracted from the selected papers. Additionally, risk of bias assessment of the included studies were carried out using a validated tool. Bias adjusted Quality Effect Model (QEM) were used to pool the estimates. Due to substantial heterogeneity, Random Effect Model (REM) estimates were also evaluated. The heterogeneity between studies were evaluated using the Cochrane Q statistics and Higgin’s I2 value. Subgroup analysis and meta-regression were used to explore the sources of heterogeneity. Funnel plots as appropriate for ratio measures were used to assess publication bias.Results: A systematic and comprehensive search of databases identified 27 cohort studies reporting the incidence of NEC. The pooled estimate of the global incidence of NEC was 6.0% (95% CI: 4.0%-9.0%). There were substantial heterogeneity (I2 = 100%) between studies. Funnel plots showed no evidence of publication bias.Conclusion: The incidence of NEC vary considerably, although meta-regression failed provide evidence for any substantial regional variation. High quality studies along with detailed risk factors of NEC is warranted, to predict and NEC.

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.

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