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Hepatology (Baltimore, Md.) Apr 2023NAFLD is a leading cause of liver-related morbidity and mortality. We assessed the global and regional prevalence, incidence, and mortality of NAFLD using an in-depth... (Meta-Analysis)
Meta-Analysis
BACKGROUND AND AIMS
NAFLD is a leading cause of liver-related morbidity and mortality. We assessed the global and regional prevalence, incidence, and mortality of NAFLD using an in-depth meta-analytic approach.
APPROACH AND RESULTS
PubMed and Ovid MEDLINE were searched for NAFLD population-based studies from 1990 to 2019 survey year (last published 2022) per Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Meta-analysis was conducted using random-effects models. Bias risk assessment was per Joanna Briggs Institute. Of 2585 studies reviewed, 92 studies (N=9,361,716) met eligibility criteria. Across the study period (1990-2019), meta-analytic pooling of NAFLD prevalence estimates and ultrasound-defined NAFLD yielded an overall global prevalence of 30.05% (95% CI: 27.88%-32.32%) and 30.69% (28.4-33.09), respectively. Global NAFLD prevalence increased by +50.4% from 25.26% (21.59-29.33) in 1990-2006 to 38.00% (33.71-42.49) in 2016-2019 ( p <0.001); ultrasound-defined NAFLD prevalence increased by +38.7% from 25.16% (19.46-31.87) in 1990-2006 to 34.59% (29.05-40.57) ( p =0.029). The highest NAFLD prevalence was in Latin America 44.37% (30.66%-59.00%), then Middle East and North Africa (MENA) (36.53%, 28.63%-45.22%), South Asia (33.83%, 22.91%-46.79%), South-East Asia (33.07%, 18.99%-51.03%), North America (31.20%, 25.86%-37.08%), East Asia (29.71%, 25.96%-33.76%), Asia Pacific 28.02% (24.69%-31.60%), Western Europe 25.10% (20.55%-30.28%). Among the NAFLD cohort diagnosed without a liver biopsy, pooled mortality rate per 1000 PY was 12.60 (6.68-23.67) for all-cause mortality; 4.20 (1.34-7.05) for cardiac-specific mortality; 2.83 (0.78-4.88) for extrahepatic cancer-specific mortality; and 0.92 (0.00-2.21) for liver-specific mortality.
CONCLUSIONS
NAFLD global prevalence is 30% and increasing which requires urgent and comprehensive strategies to raise awareness and address all aspects of NAFLD on local, regional, and global levels.
Topics: Humans; Non-alcoholic Fatty Liver Disease; North America; Risk Assessment; Prevalence
PubMed: 36626630
DOI: 10.1097/HEP.0000000000000004 -
BioMed Research International 2021The objective of this systematic review was to investigate the quality and outcome of studies into artificial intelligence techniques, analysis, and effect in dentistry.
OBJECTIVE
The objective of this systematic review was to investigate the quality and outcome of studies into artificial intelligence techniques, analysis, and effect in dentistry.
MATERIALS AND METHODS
Using the MeSH keywords: artificial intelligence (AI), dentistry, AI in dentistry, neural networks and dentistry, machine learning, AI dental imaging, and AI treatment recommendations and dentistry. Two investigators performed an electronic search in 5 databases: PubMed/MEDLINE (National Library of Medicine), Scopus (Elsevier), ScienceDirect databases (Elsevier), Web of Science (Clarivate Analytics), and the Cochrane Collaboration (Wiley). The English language articles reporting on AI in different dental specialties were screened for eligibility. Thirty-two full-text articles were selected and systematically analyzed according to a predefined inclusion criterion. These articles were analyzed as per a specific research question, and the relevant data based on article general characteristics, study and control groups, assessment methods, outcomes, and quality assessment were extracted.
RESULTS
The initial search identified 175 articles related to AI in dentistry based on the title and abstracts. The full text of 38 articles was assessed for eligibility to exclude studies not fulfilling the inclusion criteria. Six articles not related to AI in dentistry were excluded. Thirty-two articles were included in the systematic review. It was revealed that AI provides accurate patient management, dental diagnosis, prediction, and decision making. Artificial intelligence appeared as a reliable modality to enhance future implications in the various fields of dentistry, i.e., diagnostic dentistry, patient management, head and neck cancer, restorative dentistry, prosthetic dental sciences, orthodontics, radiology, and periodontics.
CONCLUSION
The included studies describe that AI is a reliable tool to make dental care smooth, better, time-saving, and economical for practitioners. AI benefits them in fulfilling patient demand and expectations. The dentists can use AI to ensure quality treatment, better oral health care outcome, and achieve precision. AI can help to predict failures in clinical scenarios and depict reliable solutions. However, AI is increasing the scope of state-of-the-art models in dentistry but is still under development. Further studies are required to assess the clinical performance of AI techniques in dentistry.
Topics: Artificial Intelligence; Dentistry; Diagnostic Imaging; Forecasting; Humans; Machine Learning; Neural Networks, Computer; Radiography, Dental
PubMed: 34258283
DOI: 10.1155/2021/9751564 -
Psychiatry Research Dec 2021We aimed to do a systematic review and meta-analysis of studies describing suicidal ideation, suicide attempts and suicide and associated risk factors during COVID-19... (Meta-Analysis)
Meta-Analysis Review
We aimed to do a systematic review and meta-analysis of studies describing suicidal ideation, suicide attempts and suicide and associated risk factors during COVID-19 pandemic. We searched following electronic databases using relevant search terms: Medline, Embase, PsycInfo and CINAHL and systematically reviewed the evidence following PRISMA guidelines. The meta-analysis of prevalence of suicidal ideation was done using random effect model. The search returned 972 records, we examined 106 in full text and included 38 studies describing 120,076 participants. Nineteen studies described suicide or attempted self-harm, mostly in case reports. Out of 19 studies describing suicidal ideations, 12 provided appropriate data for meta-analysis. The pooled prevalence of suicidal ideation in these studies was 12.1% (CI 9.3-15.2). Main risk factors for suicidal ideations were: low social support, high physical and mental exhaustion and poorer self-reported physical health in frontline medical workers, sleep disturbances, quarantine and exhaustion, loneliness, and mental health difficulties. We provide first meta-analytic estimate of suicidal ideation based on large sample from different countries and populations. The rate of suicidal ideations during COVID pandemic is higher than that reported in studies on general population prior to pandemic and may result in higher suicide rates in future.
Topics: COVID-19; Humans; Pandemics; SARS-CoV-2; Suicidal Ideation; Suicide, Attempted
PubMed: 34670162
DOI: 10.1016/j.psychres.2021.114228 -
Journal of Functional Morphology and... Feb 2021Ashwagandha () is considered a potent adaptogen and anti-stress agent that could have some potential to improve physical performance. This preferred reporting items for... (Review)
Review
Ashwagandha () is considered a potent adaptogen and anti-stress agent that could have some potential to improve physical performance. This preferred reporting items for systematic reviews and meta-analyses (PRISMA)-based comprehensive systematic review and Bayesian meta-analysis aimed to evaluate clinical trials up to 2020 from PubMed, ScienceDirect, and Google Scholar databases regarding the effect of Ashwagandha supplementation on physical performance in healthy individuals. Besides implementing estimation statistics analysis, we developed Bayesian hierarchical models for a pre-specified subgroup meta-analysis on strength/power, cardiorespiratory fitness and fatigue/recovery variables. A total of 13 studies met the requirements of this systematic review, although only 12 were included in the quantitative analysis. A low-to-moderate overall risk of bias of the trials included in this study was detected. All Bayesian hierarchical models converged to a target distribution (Ȓ = 1) for both meta-analytic effect size (μ) and between-study standard deviation (τ). The meta-analytic approaches of the included studies revealed that Ashwagandha supplementation was more efficacious than placebo for improving variables related to physical performance in healthy men and female. In fact, the Bayesian models showed that future interventions might be at least in some way beneficial on the analyzed outcomes considering the 95% credible intervals for the meta-analytic effect size. Several practical applications and future directions are discussed, although more comparable studies are needed in exercise training, and athletic populations are needed to derive a more stable estimate of the true underlying effect.
PubMed: 33670194
DOI: 10.3390/jfmk6010020 -
JAMA Neurology Sep 2022To date, no systematic review has taken a meta-analytic approach to estimating the prevalence and incidence of tinnitus in the general population. (Meta-Analysis)
Meta-Analysis
IMPORTANCE
To date, no systematic review has taken a meta-analytic approach to estimating the prevalence and incidence of tinnitus in the general population.
OBJECTIVE
To provide frequency estimates of tinnitus worldwide.
DATA SOURCES
An umbrella review followed by a traditional systematic review was performed by searching PubMed-MEDLINE and Embase from inception through November 19, 2021.
STUDY SELECTION
Research data from the general population were selected, and studies based on patients or on subgroups of the population with selected lifestyle habits were excluded. No restrictions were applied according to date, age, sex, and country.
DATA EXTRACTION AND SYNTHESIS
Relevant extracted information included type of study, time and location, end point, population characteristics, and tinnitus definition. The study followed the Meta-analysis of Observational Studies in Epidemiology (MOOSE) reporting guideline.
MAIN OUTCOMES AND MEASURES
Pooled prevalence estimates of any tinnitus, severe tinnitus, chronic tinnitus, and diagnosed tinnitus as well as incidence of tinnitus were obtained using random-effects meta-analytic models; heterogeneity between studies was controlled using the χ2 test, and inconsistency was measured using the I2 statistic.
RESULTS
Among 767 publications, 113 eligible articles published between 1972 and 2021 were identified, and prevalence estimates from 83 articles and incidence estimates from 12 articles were extracted. The pooled prevalence of any tinnitus among adults was 14.4% (95% CI, 12.6%-16.5%) and ranged from 4.1% (95% CI, 3.7%-4.4%) to 37.2% (95% CI, 34.6%-39.9%). Prevalence estimates did not significantly differ by sex (14.1% [95% CI, 11.6%-17.0%] among male individuals; 13.1% [95% CI, 10.5%-16.2%] among female individuals), but increased prevalence was associated with age (9.7% [95% CI, 7.4%-12.5%] among adults aged 18-44 years; 13.7% [95% CI, 11.0%-17.0%] among those aged 45-64 years; and 23.6% [95% CI, 19.4%-28.5%] among those aged ≥65 years; P < .001 among age groups). The pooled prevalence of severe tinnitus was 2.3% (95% CI, 1.7%-3.1%), ranging from 0.5% (95% CI, 0.3%-0.7%) to 12.6% (95% CI, 11.1%-14.1%). The pooled prevalence of chronic tinnitus was 9.8% (95% CI, 4.7%-19.3%) and the pooled prevalence of diagnosed tinnitus was 3.4% (95% CI, 2.1%-5.5%). The pooled incidence rate of any tinnitus was 1164 per 100 000 person-years (95% CI, 479-2828 per 100 000 person-years).
CONCLUSIONS AND RELEVANCE
Despite the substantial heterogeneity among studies, this comprehensive systematic review on the prevalence and incidence of tinnitus suggests that tinnitus affects more than 740 million adults globally and is perceived as a major problem by more than 120 million people, mostly aged 65 years or older. Health policy makers should consider the global burden of tinnitus, and greater effort should be devoted to boost research on tinnitus.
Topics: Female; Humans; Incidence; Male; Prevalence; Tinnitus
PubMed: 35939312
DOI: 10.1001/jamaneurol.2022.2189 -
Environmental Pollution (Barking, Essex... Jan 2022We provide a comprehensive and updated systematic review and meta-analysis of the association between air pollution exposure and depression, searching PubMed, Embase,... (Meta-Analysis)
Meta-Analysis Review
We provide a comprehensive and updated systematic review and meta-analysis of the association between air pollution exposure and depression, searching PubMed, Embase, and Web of Sciences for relevant articles published up to May 2021, and eventually including 39 studies. Meta-analyses were performed separately according to pollutant type [particulate matter with diameter ≤10 μm (PM) and ≤2.5 μm (PM), nitrogen dioxide (NO), sulfur dioxide (SO), ozone (O), and carbon monoxide (CO)] and exposure duration [short- (<30 days) and long-term (≥30 days)]. Test for homogeneity based on Cochran's Q and I statistics were calculated and the restricted maximum likelihood (REML) random effect model was applied. We assessed overall quality of pooled estimates, influence of single studies on the meta-analytic estimates, sources of between-study heterogeneity, and publication bias. We observed an increased risk of depression associated with long-term exposure to PM (relative risk: 1.074, 95% confidence interval: 1.021-1.129) and NO (1.037, 1.011-1.064), and with short-term exposure to PM (1.009, 1.006-1.012), PM (1.009, 1.007-1.011), NO (1.022, 1.012-1.033), SO (1.024, 1.010-1.037), O (1.011, 0.997-1.026), and CO (1.062, 1.020-1.105). The publication bias affecting half of the investigated associations and the high heterogeneity characterizing most of the meta-analytic estimates partly prevent to draw very firm conclusions. On the other hand, the coherence of all the estimates after excluding single studies in the sensitivity analysis supports the soundness of our results. This especially applies to the association between PM and depression, strengthened by the absence of heterogeneity and of relevant publication bias in both long- and short-term exposure studies. Should further investigations be designed, they should involve large sample sizes, well-defined diagnostic criteria for depression, and thorough control of potential confounding factors. Finally, studies dedicated to the comprehension of the mechanisms underlying the association between air pollution and depression remain necessary.
Topics: Air Pollutants; Air Pollution; Depression; Environmental Exposure; Humans; Nitrogen Dioxide; Ozone; Particulate Matter
PubMed: 34600062
DOI: 10.1016/j.envpol.2021.118245 -
Journal of Medical Internet Research Oct 2020The high demand for health care services and the growing capability of artificial intelligence have led to the development of conversational agents designed to support a...
BACKGROUND
The high demand for health care services and the growing capability of artificial intelligence have led to the development of conversational agents designed to support a variety of health-related activities, including behavior change, treatment support, health monitoring, training, triage, and screening support. Automation of these tasks could free clinicians to focus on more complex work and increase the accessibility to health care services for the public. An overarching assessment of the acceptability, usability, and effectiveness of these agents in health care is needed to collate the evidence so that future development can target areas for improvement and potential for sustainable adoption.
OBJECTIVE
This systematic review aims to assess the effectiveness and usability of conversational agents in health care and identify the elements that users like and dislike to inform future research and development of these agents.
METHODS
PubMed, Medline (Ovid), EMBASE (Excerpta Medica dataBASE), CINAHL (Cumulative Index to Nursing and Allied Health Literature), Web of Science, and the Association for Computing Machinery Digital Library were systematically searched for articles published since 2008 that evaluated unconstrained natural language processing conversational agents used in health care. EndNote (version X9, Clarivate Analytics) reference management software was used for initial screening, and full-text screening was conducted by 1 reviewer. Data were extracted, and the risk of bias was assessed by one reviewer and validated by another.
RESULTS
A total of 31 studies were selected and included a variety of conversational agents, including 14 chatbots (2 of which were voice chatbots), 6 embodied conversational agents (3 of which were interactive voice response calls, virtual patients, and speech recognition screening systems), 1 contextual question-answering agent, and 1 voice recognition triage system. Overall, the evidence reported was mostly positive or mixed. Usability and satisfaction performed well (27/30 and 26/31), and positive or mixed effectiveness was found in three-quarters of the studies (23/30). However, there were several limitations of the agents highlighted in specific qualitative feedback.
CONCLUSIONS
The studies generally reported positive or mixed evidence for the effectiveness, usability, and satisfactoriness of the conversational agents investigated, but qualitative user perceptions were more mixed. The quality of many of the studies was limited, and improved study design and reporting are necessary to more accurately evaluate the usefulness of the agents in health care and identify key areas for improvement. Further research should also analyze the cost-effectiveness, privacy, and security of the agents.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)
RR2-10.2196/16934.
Topics: Artificial Intelligence; Communication; Delivery of Health Care; Female; Humans; Male
PubMed: 33090118
DOI: 10.2196/20346 -
Molecular Neurodegeneration Mar 2022Alzheimer's disease (AD) is the most common form of dementia, characterized by progressive cognitive impairment and neurodegeneration. Extensive clinical and genomic... (Review)
Review
Alzheimer's disease (AD) is the most common form of dementia, characterized by progressive cognitive impairment and neurodegeneration. Extensive clinical and genomic studies have revealed biomarkers, risk factors, pathways, and targets of AD in the past decade. However, the exact molecular basis of AD development and progression remains elusive. The emerging single-cell sequencing technology can potentially provide cell-level insights into the disease. Here we systematically review the state-of-the-art bioinformatics approaches to analyze single-cell sequencing data and their applications to AD in 14 major directions, including 1) quality control and normalization, 2) dimension reduction and feature extraction, 3) cell clustering analysis, 4) cell type inference and annotation, 5) differential expression, 6) trajectory inference, 7) copy number variation analysis, 8) integration of single-cell multi-omics, 9) epigenomic analysis, 10) gene network inference, 11) prioritization of cell subpopulations, 12) integrative analysis of human and mouse sc-RNA-seq data, 13) spatial transcriptomics, and 14) comparison of single cell AD mouse model studies and single cell human AD studies. We also address challenges in using human postmortem and mouse tissues and outline future developments in single cell sequencing data analysis. Importantly, we have implemented our recommended workflow for each major analytic direction and applied them to a large single nucleus RNA-sequencing (snRNA-seq) dataset in AD. Key analytic results are reported while the scripts and the data are shared with the research community through GitHub. In summary, this comprehensive review provides insights into various approaches to analyze single cell sequencing data and offers specific guidelines for study design and a variety of analytic directions. The review and the accompanied software tools will serve as a valuable resource for studying cellular and molecular mechanisms of AD, other diseases, or biological systems at the single cell level.
Topics: Alzheimer Disease; Animals; Computational Biology; DNA Copy Number Variations; Data Analysis; Mice; Single-Cell Analysis
PubMed: 35236372
DOI: 10.1186/s13024-022-00517-z -
Pharmacopsychiatry May 2022Partial response to pharmacotherapy is common in major depressive disorder (MDD) and many patients require alternative pharmacotherapy or augmentation, including... (Meta-Analysis)
Meta-Analysis
OBJECTIVES
Partial response to pharmacotherapy is common in major depressive disorder (MDD) and many patients require alternative pharmacotherapy or augmentation, including adjunctive L-methylfolate. Given that L-methylfolate augmentation is rarely included in major clinical practice guidelines, we sought to systematically review evidence for L-methylfolate augmentation in adults with MDD and to examine its efficacy meta-analytically.
METHODS
We systematically searched PubMed for articles up to December 31, 2020, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) recommendations. Included studies were published in peer-reviewed, English-language journals and examined L-methylfolate adjunctive therapy in depressive disorders or its effect on antidepressant response. A fixed- and random-effects meta-analysis and risk of bias assessment using the Cochrane Risk of Bias Tool were conducted.
RESULTS
Qualitative assessment of nine articles (N=6,707 patients) suggests that adjunctive L-methylfolate improved antidepressant response. In the meta-analysis of categorical Hamilton Rating Scale for Depression-17 response, (three studies, 483) adjunctive L-methylfolate was associated with a small effect versus antidepressant monotherapy (relative risk: 1.25, 95% confidence interval [CI]=1.08 to 1.46, 0.004). A meta-analysis of four studies (507) using a continuous measure of depressive symptoms showed a similar effect of adjunctive L-methylfolate (standardized mean difference=- 0.38, 95% CI=- 0.59 to-0.17, 0.0003).
CONCLUSION
Adjunctive L-methylfolate may have modest efficacy in antidepressant-treated adults with MDD.
Topics: Adult; Antidepressive Agents; Depressive Disorder, Major; Humans; Tetrahydrofolates
PubMed: 34794190
DOI: 10.1055/a-1681-2047 -
Brain Sciences Sep 2019Video gaming, the experience of playing electronic games, has shown several benefits for human health. Recently, numerous video gaming studies showed beneficial effects... (Review)
Review
Video gaming, the experience of playing electronic games, has shown several benefits for human health. Recently, numerous video gaming studies showed beneficial effects on cognition and the brain. A systematic review of video gaming has been published. However, the previous systematic review has several differences to this systematic review. This systematic review evaluates the beneficial effects of video gaming on neuroplasticity specifically on intervention studies. Literature research was conducted from randomized controlled trials in PubMed and Google Scholar published after 2000. A systematic review was written instead of a meta-analytic review because of variations among participants, video games, and outcomes. Nine scientific articles were eligible for the review. Overall, the eligible articles showed fair quality according to Delphi Criteria. Video gaming affects the brain structure and function depending on how the game is played. The game genres examined were 3D adventure, first-person shooting (FPS), puzzle, rhythm dance, and strategy. The total training durations were 16-90 h. Results of this systematic review demonstrated that video gaming can be beneficial to the brain. However, the beneficial effects vary among video game types.
PubMed: 31557907
DOI: 10.3390/brainsci9100251