scholarly journals Neural effects of antidepressant medication and psychological treatments: a quantitative synthesis across three meta-analyses

2021 ◽  
pp. 1-5
Author(s):  
Camilla L. Nord ◽  
Lisa Feldman Barrett ◽  
Kristen A. Lindquist ◽  
Yina Ma ◽  
Lindsey Marwood ◽  
...  

Background Influential theories predict that antidepressant medication and psychological therapies evoke distinct neural changes. Aims To test the convergence and divergence of antidepressant- and psychotherapy-evoked neural changes, and their overlap with the brain's affect network. Method We employed a quantitative synthesis of three meta-analyses (n = 4206). First, we assessed the common and distinct neural changes evoked by antidepressant medication and psychotherapy, by contrasting two comparable meta-analyses reporting the neural effects of these treatments. Both meta-analyses included patients with affective disorders, including major depressive disorder, generalised anxiety disorder and panic disorder. The majority were assessed using negative-valence tasks during neuroimaging. Next, we assessed whether the neural changes evoked by antidepressants and psychotherapy overlapped with the brain's affect network, using data from a third meta-analysis of affect-based neural activation. Results Neural changes from psychotherapy and antidepressant medication did not significantly converge on any region. Antidepressants evoked neural changes in the amygdala, whereas psychotherapy evoked anatomically distinct changes in the medial prefrontal cortex. Both psychotherapy- and antidepressant-related changes separately converged on regions of the affect network. Conclusions This supports the notion of treatment-specific brain effects of antidepressants and psychotherapy. Both treatments induce changes in the affect network, but our results suggest that their effects on affect processing occur via distinct proximal neurocognitive mechanisms of action.

Author(s):  
Holly J. Baker ◽  
Peter J. Lawrence ◽  
Jessica Karalus ◽  
Cathy Creswell ◽  
Polly Waite

AbstractAnxiety disorders are common in adolescence but outcomes for adolescents are unclear and we do not know what factors moderate treatment outcome for this age group. We conducted meta-analyses to establish the effectiveness of psychological therapies for adolescent anxiety disorders in (i) reducing anxiety disorder symptoms, and (ii) remission from the primary anxiety disorder, compared with controls, and examine potential moderators of treatment effects. The protocol was registered with PROSPERO (CRD42018091744). Electronic databases (Web of Science, MEDLINE, Psycinfo, EMBASE) were searched from January 1990 to December 2019. 2511 articles were reviewed, those meeting strict criteria were included. Random effects meta-analyses were conducted. Analyses of symptom severity outcomes comprised sixteen studies (CBT k = 15, non-CBT k = 1; n = 766 adolescents), and analyses of diagnostic remission outcomes comprised nine (CBT k = 9; n = 563 adolescents). Post-treatment, those receiving treatment were significantly more likely to experience reduced symptom severity (SMD = 0.454, 95% CI 0.22–0.69) and remission from the primary anxiety disorder than controls (RR = 7.94, 95% CI 3.19–12.7) (36% treatment vs. 9% controls in remission). None of the moderators analysed were statistically significant. Psychological therapies targeting anxiety disorders in adolescents are more effective than controls. However, with only just over a third in remission post-treatment, there is a clear need to develop more effective treatments for adolescents, evaluated through high-quality randomised controlled trials incorporating active controls and follow-up data.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xi Ouyang ◽  
Zhiqiang Liu ◽  
Chenglin Gui

Purpose Underpinned by the ability–motivation–opportunity framework, this paper aims to establish a framework of employee creativity antecedents in the hospitality and tourism industries and meta-analytically examine the magnitude of effect sizes as well as the moderating effects of cultural factors. Design/methodology/approach A meta-analysis using data from 82 independent studies was conducted to explore the hypothesized relationships and verify how they were contingent on uncertainty avoidance and long-term orientation. Findings The results supported the majority of hypotheses about the relationships between antecedents and creativity. Furthermore, they showed that the effects of intrinsic motivation, positive affect and climate for innovation on creativity in the hospitality and tourism industries were significantly larger than those reported in previous meta-analyses. It also showed that uncertainty avoidance and long-term orientation could buffer or strengthen some associations. Practical implications This study generates some essential managerial suggestions for organizations in need of innovation. Managers can learn from the results so as to effectively promote the ability, motivation and opportunity for creativity and merge cultural elements with innovation strategy when they operate globally. Originality/value This study provides a theory-based explanation for how employee creativity can be activated. To the best of the authors’ knowledge, this study is a first attempt to meta-analytically test the underlying determinants of employee creativity in the hospitality and tourism industries. Additionally, the search for boundary conditions of the proposed relationships is likely to reconcile existing conflicts and inspire future studies.


Author(s):  
Colin Baigent ◽  
Richard Peto ◽  
Richard Gray ◽  
Natalie Staplin ◽  
Sarah Parish ◽  
...  

Clinical trials generally need to be able to detect or to refute realistically moderate (but still worthwhile) differences between treatments in long-term disease outcome. Large-scale randomized evidence should be able to detect such effects, but medium-sized trials or medium-sized meta-analyses can, and often do, yield false-negative or exaggeratedly positive results. Hundreds of thousands of premature deaths each year could be avoided by seeking appropriately large-scale randomized evidence about various widely practicable treatments for the common causes of death, and by disseminating this evidence appropriately. This chapter takes a look at the use of large-scale randomized evidence—produced from trials and meta-analysis of trials—and how this data should be handled in order to produce accurate result.


2021 ◽  
Vol 33 (1) ◽  
pp. 9-24
Author(s):  
Swambhavi Awasthi ◽  
Sunil Sharma ◽  
Saurav Attri ◽  
Sakshi Malik Attri ◽  
Rajesh Sharawat ◽  
...  

COVID-19 made a huge impact on the world due to its rapid transmission and no treatments being available for it. The virus affected more people and spread to various countries than what was predicted when COVID-19 initially began spreading. There have been numerous pandemics and epidemics in the 21st century yet COVID-19 has affected more people and spread widely. The primary objective of the study was to explore history, spread and associated parameters of existing viruses especially COVID-19. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was followed for a systematic search to identify eligible published articles. Clinical data, regarding COVID-19 patients, was obtained from previously published articles. The main cause of COVID-19 spreading rapidly was noted to be due to a high percentage of asymptomatic patients, transmission being air-borne, and the lack of knowledge and preventative measures being implemented when the virus began spreading. The common co-morbidity that found in patients was Diabetes Mellitus, Hypertension, and Coronary Heart Disease. The common symptoms, found through the Meta-analysis, that the patients faced included cough (55.4%), fever (68.4%), fatigue (20.3%), and shortness of breath (18.1%). The proportion of asymptotic positive cases was measured 58.3% (95%CI: 24.7% – 87.9%) while mortality proportion was found to be 6.7% (fixed-effect model) and 13.4% (random-effect model). The Meta-analysis indicated that a higher percentage of males were affected by COVID-19 than females and more patients are found to be asymptomatic. Moreover, the mortality rate of patients that have had COVID-19 was found to be low. 


2021 ◽  
Vol 108 (Supplement_4) ◽  
Author(s):  
P Probst ◽  
U Klaiber ◽  
S Seide ◽  
M Kawai ◽  
I Matsumoto ◽  
...  

Abstract Objective Some studies have indicated that resecting the pylorus during partial pancreatoduodenectomy (PD) may lead to reduced delayed gastric emptying (DGE). Randomized controlled trials (RCTs) showed conflicting results regarding superiority of pylorus-resecting PD (prPD) compared to the pylorus-preserving procedure (ppPD). The aim of this individual patient data meta-analysis was to investigate risk factors on an individual patient level which may explain the observed differences between the existing RCTs. Methods RCTs comparing ppPD and prPD were searched systematically in MEDLINE, Web of Science and CENTRAL. Individual patient data (IPD) from existing RCTs were included. The primary endpoint was DGE according to the International Study Group of Pancreatic Surgery (ISGPS) adjusted for age, sex and body-mass-index (BMI). The meta-regression model was applied to the IPD of the RCTs. Mixed effects models were applied to perform meta-analyses. Results IPD from 418 patients (three RCTs) were used for quantitative synthesis. There was no significant statistical difference between ppPD and prPD regarding DGE adjusted for age, sex and BMI (OR 0.72; 95%-CI: 0.41 to 1.22) and DGE grade (RR 1.01; 95%-CI: 0.64 to 1.57). Regarding other relevant perioperative and postoperative outcome parameters, there were also no significant differences among the two techniques. Conclusion This IPD meta-analysis comparing preservation and resection of the pylorus during PD confirmed that the resection of the pylorus is not superior to the pylorus-preserving procedure regarding DGE. The pylorus should therefore be preserved whenever possible. Further RCT are futile, because their results are unlikely to change the pooled estimate for DGE.


2021 ◽  
pp. 152660282110586
Author(s):  
Yu Li ◽  
Wenhao Cui ◽  
Jukun Wang ◽  
Chao Zhang ◽  
Tao Luo

Objective: The objective of the present study was to compare the effectiveness of high-pressure balloon (HPB) versus conventional balloon (CB) angioplasty in treating arteriovenous fistula (AVF) stenosis. Materials and Methods: A meta-analysis was conducted using data acquired from PubMed, EMBASE, the Cochrane Library, SinoMed, CNKI, WanFang, and VIP databases from the time the databases were established to December 2020. All analyses included in the studies comprised the subgroups of HPB and CB. The patency rates of AVF were compared between 2 groups at 3, 6, and 12 months after operation. Results: Seven studies comprising 364 patients were included in the meta-analyses. The pooled results revealed that restenosis rate of AVFs treated with HPB was significantly lower than that of AVFs treated with CB at 3 months (odds ratio [OR] = 0.32, 95% confidence interval [CI] = 0.16 to 0.61, p<0.001) and 6 months after operation (OR= 0.29, 95% CI = 0.11 to 0.79, p = 0.01). In addition, the technical success rate of HPB groups was higher (OR = 0.13, 95% CI = 0.05 to 0.36, p<0.001). However, no significant difference was observed between HPB and CB groups at 12 months after operation (OR = 0.68, 95% CI = 0.30 to 1.52, p = 0.35). No significant publication bias was observed in the analyses. Conclusion: High-pressure balloon is a potential option for the treatment of AVF stenosis, with a lower 3- and 6-month restenosis rate than CB. However, 12-month patency rate of HPB was not superior to CB. Therefore, further studies should be conducted to investigate the mechanisms of restenosis after angioplasty.


2021 ◽  
pp. 232102222110543
Author(s):  
Lauren Zimmermann ◽  
Subarna Bhattacharya ◽  
Soumik Purkayastha ◽  
Ritoban Kundu ◽  
Ritwik Bhaduri ◽  
...  

Introduction: Fervourous investigation and dialogue surrounding the true number of SARS-CoV-2-related deaths and implied infection fatality rates in India have been ongoing throughout the pandemic, and especially pronounced during the nation’s devastating second wave. We aim to synthesize the existing literature on the true SARS-CoV-2 excess deaths and infection fatality rates (IFR) in India through a systematic search followed by viable meta-analysis. We then provide updated epidemiological model-based estimates of the wave 1, wave 2 and combined IFRs using an extension of the Susceptible-Exposed-Infected-Removed (SEIR) model, using data from 1 April 2020 to 30 June 2021. Methods: Following PRISMA guidelines, the databases PubMed, Embase, Global Index Medicus, as well as BioRxiv, MedRxiv and SSRN for preprints (accessed through iSearch), were searched on 3 July 2021 (with results verified through 15 August 2021). Altogether, using a two-step approach, 4,765 initial citations were screened, resulting in 37 citations included in the narrative review and 19 studies with 41datapoints included in the quantitative synthesis. Using a random effects model with DerSimonian-Laird estimation, we meta-analysed IFR1, which is defined as the ratio of the total number of observed reported deaths divided by the total number of estimated infections, and IFR2 (which accounts for death underreporting in the numerator of IFR1). For the latter, we provided lower and upper bounds based on the available range of estimates of death undercounting, often arising from an excess death calculation. The primary focus is to estimate pooled nationwide estimates of IFRs with the secondary goal of estimating pooled regional and state-specific estimates for SARS-CoV-2-related IFRs in India. We also tried to stratify our empirical results across the first and second waves. In tandem, we presented updated SEIR model estimates of IFRs for waves 1, 2, and combined across the waves with observed case and death count data from 1 April 2020 to 30 June 2021. Results: For India, countrywide, the underreporting factors (URF) for cases (sourced from serosurveys) range from 14.3 to 29.1 in the four nationwide serosurveys; URFs for deaths (sourced from excess deaths reports) range from 4.4 to 11.9 with cumulative excess deaths ranging from 1.79 to 4.9 million (as of June 2021). Nationwide pooled IFR1 and IFR2 estimates for India are 0.097% (95% confidence interval [CI]: 0.067–0.140) and 0.365% (95% CI: 0.264–0.504) to 0.485% (95% CI: 0.344–0.685), respectively, again noting that IFR2 changes as excess deaths estimates vary. Among the included studies in this meta-analysis, IFR1 generally appears to decrease over time from the earliest study end date to the latest study end date (from 4 June 2020 to 6 July 2021, IFR1 changed from 0.199 to 0.055%), whereas a similar trend is not as readily evident for IFR2 due to the wide variation in excess death estimates (from 4 June 2020 to 6 July 2021, IFR2 ranged from (0.290–1.316) to (0.241–0.651)%). Nationwide SEIR model-based combined estimates for IFR1 and IFR2 are 0.101% (95% CI: 0.097–0.116) and 0.367% (95% CI: 0.358–0.383), respectively, which largely reconcile with the empirical findings and concur with the lower end of the excess death estimates. An advantage of such epidemiological models is the ability to produce daily estimates with updated data, with the disadvantage being that these estimates are subject to numerous assumptions, arduousness of validation and not directly using the available excess death data. Whether one uses empirical data or model-based estimation, it is evident that IFR2 is at least 3.6 times more than IFR1. Conclusion: When incorporating case and death underreporting, the meta-analysed cumulative infection fatality rate in India varied from 0.36 to 0.48%, with a case underreporting factor ranging from 25 to 30 and a death underreporting factor ranging from 4 to 12. This implies, by 30 June 2021, India may have seen nearly 900 million infections and 1.7–4.9 million deaths when the reported numbers stood at 30.4 million cases and 412 thousand deaths (Coronavirus in India) with an observed case fatality rate (CFR) of 1.35%. We reiterate the need for timely and disaggregated infection and fatality data to examine the burden of the virus by age and other demographics. Large degrees of nationwide and state-specific death undercounting reinforce the call to improve death reporting within India. JEL Classifications: I15, I18


2016 ◽  
Vol 2016 ◽  
pp. 1-5 ◽  
Author(s):  
George A. Kelley ◽  
Kristi S. Kelley

Purpose. While individual participant data (IPD) meta-analyses are considered the gold standard for meta-analysis, the feasibility of obtaining IPD may be problematic.Methods. Using data from a previous meta-analysis of 29 studies on exercise in adults with arthritis and other rheumatic diseases, the percentage of studies in which useable IPD was provided was calculated.Results. Eight of 29 authors (28%, 95% CI = 11% to 44%) provided IPD. Using logistic regression, neither year of publication (odds ratio = 1.05, 95% CI = 0.90 to 1.27,p=0.58) nor country (odds ratio = 1.36, 95% CI = 0.20 to 10.9,p=1.00) was significantly associated with the obtainment of IPD.Conclusions. The retrieval of IPD for exercise meta-analyses may not be worth the time and effort. However, further research is needed before any final recommendations can be made.


Author(s):  
Alan J. Silman ◽  
Gary J. Macfarlane ◽  
Tatiana Macfarlane

The previous chapter has discussed how to gather and evaluate existing evidence from epidemiological studies. Here further consideration is given to summarizing the identified evidence in such a way that it can be used for decision-making, including approaches to control for chance and potential bias. Meta-analysis refers to the statistical analysis of results from individual studies for integrating the findings. There are other terms related to meta-analysis such as quantitative review, combined analysis, pooled analysis, or quantitative synthesis. Some of them use different methods, for example, meta-analysis of published data considers each study as a unit of analysis while individual patient data analysis includes the original data from each study on a participant level. This chapter describes how to numerically summarize data through performing a meta-analysis using data from a systematic review of epidemiological studies. It also considers possible bias, reporting guidelines, and statistical software available for meta-analysis.


2020 ◽  
Vol 77 (9) ◽  
pp. 1574-1591 ◽  
Author(s):  
Kyleisha J. Foote ◽  
Pascale M. Biron ◽  
James W.A. Grant

Owing to declines in salmonid populations, in-stream restoration structures have been used for over 80 years to increase abundance of fish. However, the relative effectiveness of these structures remains unclear for some species or regions, partly due to contrasting conclusions from two previous meta-analyses. To update and reconcile these previous analyses, we conducted a meta-analysis using data available from 1969 to 2019 to estimate the effect of in-stream structures on salmonid abundance (number and density) and biomass. Data from 100 stream restoration projects showed a significant increase in salmonid abundance (effect size 0.636) and biomass (0.621), consistent with previous reviews and studies, and a stronger effect was found in adults than in juvenile fish. Despite a shift towards using more natural structures (wood and boulders) since the 1990s, structures have not become more effective. However, most projects monitor for less than 5 years, which may be insufficient time in some systems for channel morphology to adjust and population changes to be apparent. Process-based techniques, which give more space for the river, allow more long-term, self-sustaining restoration.


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