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ELife Aug 2023Polycystic ovary syndrome (PCOS) is the most common hormone disorder affecting about one in seven reproductive-aged women worldwide and approximately 6 million women in... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Polycystic ovary syndrome (PCOS) is the most common hormone disorder affecting about one in seven reproductive-aged women worldwide and approximately 6 million women in the United States (U.S.). PCOS can be a significant burden to those affected and is associated with an increased prevalence of mental health (MH) disorders such as depression, anxiety, eating disorders, and postpartum depression. We undertook this study to determine the excess economic burden associated with MH disorders in women with PCOS in order to allow for a more accurate prioritization of the disorder as a public health priority.
METHODS
Following PRISMA reporting guidelines for systematic review, we searched PubMed, Web of Science, EBSCO, Medline, Scopus, and PsycINFO through July 16, 2021, for studies on MH disorders in PCOS. Excluded were studies not in humans, without controls, without original data, or not peer reviewed. As anxiety, depression, eating disorders, and postpartum depression were by far the most common MH disorders assessed by the studies, we performed our meta-analysis on these disorders. Meta-analyses were performed using the DerSimonian-Laird random effects model to compute pooled estimates of prevalence ratios (PRs) for the associations between PCOS and these MH disorders and then calculated the excess direct costs related to these disorders in U.S. dollars (USD) for women suffering from PCOS in the U.S. alone. The quality of selected studies was assessed using the Newcastle-Ottawa Scale.
RESULTS
We screened 78 articles by title/abstract, assessed 43 articles in full text, and included 25 articles. Pooled PRs were 1.42 (95% confidence interval [CI]: 1.32-1.52) for anxiety, 1.65 (95% CI: 1.44-1.89) for depression, 1.48 (95% CI: PR: 1.06-2.05) for eating disorders, and 1.20 (95% CI: 0.96-1.50) for postpartum depression, for PCOS relative to controls. In the U.S., the additional direct healthcare costs associated with anxiety, depression, and eating disorders in PCOS were estimated to be $1.939 billion/yr, $1.678 billion/yr, and $0.644 billion/yr in 2021 USD, respectively. Postpartum depression was excluded from the cost analyses due to the non-significant meta-analysis result. Taken together, the additional direct healthcare costs associated with anxiety, depression, and eating disorders in PCOS were estimated to be $4.261 billion/yr in 2021 USD.
CONCLUSIONS
Overall, the direct healthcare annual costs for the most common MH disorders in PCOS, namely anxiety, depression, and eating disorders, exceeds $4 billion in 2021 USD for the U.S. population alone. Taken together with our prior work, these data suggest that the healthcare-related economic burden of PCOS exceeds $15 billion yearly, considering the costs of PCOS diagnosis, and costs related to PCOS-associated MH, reproductive, vascular, and metabolic disorders. As PCOS has much the same prevalence across the world, the excess economic burden attributable to PCOS globally is enormous, mandating that the scientific and policy community increase its focus on this important disorder.
FUNDING
The study was supported, in part, by PCOS Challenge: The National Polycystic Ovary Syndrome Association and by the Foundation for Research and Education Excellence.
Topics: Humans; Female; United States; Adult; Polycystic Ovary Syndrome; Depression, Postpartum; Financial Stress; Mental Health; Anxiety
PubMed: 37534878
DOI: 10.7554/eLife.85338 -
Sports Medicine (Auckland, N.Z.) Nov 2023The primary aim of our systematic review and meta-analysis was to investigate the effect of resistance training on academic outcomes in school-aged youth.
BACKGROUND
The primary aim of our systematic review and meta-analysis was to investigate the effect of resistance training on academic outcomes in school-aged youth.
METHODS
We conducted a systematic search of six electronic databases (CINAHL Complete, PsycINFO, SCOPUS, Ovid MEDLINE, SPORTDiscus and EMBASE) with no date restrictions. Studies were eligible if they: (a) included school-aged youth (5-18 years), and (b) examined the effect of resistance training on academic outcomes (i.e., cognitive function, academic achievement, and/or on-task behaviour in the classroom). Risk of bias was assessed using the appropriate Cochrane Risk of Bias Tools, funnel plots and Egger's regression asymmetry tests. A structural equation modelling approach was used to conduct the meta-analysis.
RESULTS
Fifty-three studies were included in our systematic review. Participation in resistance training (ten studies with 53 effect sizes) had a small positive effect on the overall cognitive, academic and on-task behaviours in school-aged youth (standardized mean difference (SMD) 0.19, 95% confidence interval (CI) 0.05-0.32). Resistance training was more effective (SMD 0.26, 95% CI 0.10-0.42) than concurrent training, i.e., the combination of resistance training and aerobic training (SMD 0.11, 95% CI - 0.05-0.28). An additional 43 studies (including 211 effect sizes) examined the association between muscular fitness and cognition or academic achievement, also yielding a positive relationship (SMD 0.13, 95% CI 0.10-0.16).
CONCLUSION
This review provides preliminary evidence that resistance training may improve cognitive function, academic performance, and on-task behaviours in school-aged youth.
PROSPERO REGISTRATION
CRD42020175695.
PubMed: 37466900
DOI: 10.1007/s40279-023-01881-6 -
PLoS Neglected Tropical Diseases Jul 2023Repeated distribution of preventative chemotherapy (PC) by mass drug administration forms the mainstay of transmission control for five of the 20 recognised neglected...
Repeated distribution of preventative chemotherapy (PC) by mass drug administration forms the mainstay of transmission control for five of the 20 recognised neglected tropical diseases (NTDs); soil-transmitted helminths, schistosomiasis, lymphatic filariasis, onchocerciasis and trachoma. The efficiency of such programmes is reliant upon participants swallowing the offered treatment consistently at each round. This is measured by compliance, defined as the proportion of eligible participants swallowing treatment. Individually linked longitudinal compliance data is important for assessing the potential impact of MDA-based control programmes, yet this accurate monitoring is rarely implemented in those for NTDs. Longitudinal compliance data reported by control programmes globally for the five (PC)-NTDs since 2016 is examined, focusing on key associations of compliance with age and gender. PubMed and Web of Science was searched in January 2022 for articles written in English and Spanish, and the subsequent extraction adhered to PRISMA guidelines. Study title screening was aided by Rayyan, a machine learning software package. Studies were considered for inclusion if primary compliance data was recorded for more than one time point, in a population larger than 100 participants. All data analysis was conducted in R. A total of 89 studies were identified containing compliance data, 57 were longitudinal studies, of which 25 reported individually linked data reported by varying methods. The association of increasing age with the degree of systematic treatment was commonly reported. The review is limited by the paucity of data published on this topic. The varying and overlapping terminologies used to describe coverage (receiving treatment) and compliance (swallowing treatment) is reviewed. Consequently, it is recommended that WHO considers clearly defining the terms for coverage, compliance, and longitudinal compliance which are currently contradictory across their NTD treatment guidelines. This review is registered with PROSPERO (number: CRD42022301991).
Topics: Animals; Humans; Mass Drug Administration; Schistosomiasis; Helminths; Onchocerciasis; Tropical Medicine; Neglected Diseases
PubMed: 37459369
DOI: 10.1371/journal.pntd.0010853 -
Annals of Behavioral Medicine : a... Sep 2023To end the HIV epidemic, we need to better understand how to address HIV-related stigmas in healthcare settings, specifically the common theoretical bases across...
A Systematic Review of Intervention Studies That Address HIV-Related Stigmas Among US Healthcare Workers and Health Systems: Applying a Theory-Based Ontology to Link Intervention Types, Techniques, and Mechanisms of Action to Potential Effectiveness.
BACKGROUND
To end the HIV epidemic, we need to better understand how to address HIV-related stigmas in healthcare settings, specifically the common theoretical bases across interventions so that we can generalize about their potential effectiveness.
PURPOSE
We describe theory-based components of stigma interventions by identifying their functions/types, techniques, and purported mechanisms of change.
METHODS
This systematic review examined studies published by April 2021. We applied a transtheoretical ontology developed by the Human Behaviour Change Project, consisting of 9 intervention types (ITs), 93 behavior change techniques (BCTs), and 26 mechanisms of action (MOAs). We coded the frequency and calculated the potential effectiveness of each IT, BCT, and MOA. We evaluated study quality with a 10-item adapted tool.
RESULTS
Among the nine highest quality studies, indicated by the use of an experimental design, the highest potentially effective IT was "Persuasion" (i.e. using communication to induce emotions and/or stimulate action; 66.7%, 4/6 studies). The highest potentially effective BCTs were "Behavioral practice/rehearsal" (i.e. to increase habit and skill) and "Salience of consequences" (i.e. to make consequences of behavior more memorable; each 100%, 3/3 studies). The highest potentially effective MOAs were "Knowledge" (i.e. awareness) and "Beliefs about capabilities" (i.e. self-efficacy; each 67%, 2/3 studies).
CONCLUSIONS
By applying a behavior change ontology across studies, we synthesized theory-based findings on stigma interventions. Interventions typically combined more than one IT, BCT, and MOA. Practitioners and researchers can use our findings to better understand and select theory-based components of interventions, including areas for further evaluation, to expedite ending the HIV epidemic.
Topics: Humans; Behavior Therapy; Learning; Communication; Health Personnel; HIV Infections
PubMed: 37318287
DOI: 10.1093/abm/kaad022 -
International Journal of Medical... Sep 2023Natural Language Processing (NLP) applications have developed over the past years in various fields including its application to clinical free text for named entity... (Review)
Review
BACKGROUND
Natural Language Processing (NLP) applications have developed over the past years in various fields including its application to clinical free text for named entity recognition and relation extraction. However, there has been rapid developments the last few years that there's currently no overview of it. Moreover, it is unclear how these models and tools have been translated into clinical practice. We aim to synthesize and review these developments.
METHODS
We reviewed literature from 2010 to date, searching PubMed, Scopus, the Association of Computational Linguistics (ACL), and Association of Computer Machinery (ACM) libraries for studies of NLP systems performing general-purpose (i.e., not disease- or treatment-specific) information extraction and relation extraction tasks in unstructured clinical text (e.g., discharge summaries).
RESULTS
We included in the review 94 studies with 30 studies published in the last three years. Machine learning methods were used in 68 studies, rule-based in 5 studies, and both in 22 studies. 63 studies focused on Named Entity Recognition, 13 on Relation Extraction and 18 performed both. The most frequently extracted entities were "problem", "test" and "treatment". 72 studies used public datasets and 22 studies used proprietary datasets alone. Only 14 studies defined clearly a clinical or information task to be addressed by the system and just three studies reported its use outside the experimental setting. Only 7 studies shared a pre-trained model and only 8 an available software tool.
DISCUSSION
Machine learning-based methods have dominated the NLP field on information extraction tasks. More recently, Transformer-based language models are taking the lead and showing the strongest performance. However, these developments are mostly based on a few datasets and generic annotations, with very few real-world use cases. This may raise questions about the generalizability of findings, translation into practice and highlights the need for robust clinical evaluation.
Topics: Humans; Natural Language Processing; Machine Learning; Language; Information Storage and Retrieval; PubMed
PubMed: 37295138
DOI: 10.1016/j.ijmedinf.2023.105122 -
JAMA Psychiatry Aug 2023Social anxiety disorder (SAD) can be adequately treated with cognitive behavioral therapy (CBT). However, there is a large gap in knowledge on factors associated with... (Meta-Analysis)
Meta-Analysis
Baseline Severity as a Moderator of the Waiting List-Controlled Association of Cognitive Behavioral Therapy With Symptom Change in Social Anxiety Disorder: A Systematic Review and Individual Patient Data Meta-analysis.
IMPORTANCE
Social anxiety disorder (SAD) can be adequately treated with cognitive behavioral therapy (CBT). However, there is a large gap in knowledge on factors associated with prognosis, and it is unclear whether symptom severity predicts response to CBT for SAD.
OBJECTIVE
To examine baseline SAD symptom severity as a moderator of the association between CBT and symptom change in patients with SAD.
DATA SOURCES
For this systematic review and individual patient data meta-analysis (IPDMA), PubMed, PsycInfo, Embase, and the Cochrane Library were searched from January 1, 1990, to January 13, 2023. Primary search topics were social anxiety disorder, cognitive behavior therapy, and randomized controlled trial.
STUDY SELECTION
Inclusion criteria were randomized clinical trials comparing CBT with being on a waiting list and using the Liebowitz Social Anxiety Scale (LSAS) in adults with a primary clinical diagnosis of SAD.
DATA EXTRACTION AND SYNTHESIS
Authors of included studies were approached to provide individual-level data. Data were extracted by pairs of authors following the Preferred Reporting Items for Systematic Reviews and Meta-analyses reporting guideline, and risk of bias was assessed using the Cochrane tool. An IPDMA was conducted using a 2-stage approach for the association of CBT with change in LSAS scores from baseline to posttreatment and for the interaction effect of baseline LSAS score by condition using random-effects models.
MAIN OUTCOMES AND MEASURES
The main outcome was the baseline to posttreatment change in symptom severity measured by the LSAS.
RESULTS
A total of 12 studies including 1246 patients with SAD (mean [SD] age, 35.3 [10.9] years; 738 [59.2%] female) were included in the meta-analysis. A waiting list-controlled association between CBT and pretreatment to posttreatment LSAS change was found (b = -20.3; 95% CI, -24.9 to -15.6; P < .001; Cohen d = -0.95; 95% CI, -1.16 to -0.73). Baseline LSAS scores moderated the differences between CBT and waiting list with respect to pretreatment to posttreatment symptom reductions (b = -0.22; 95% CI, -0.39 to -0.06; P = .009), indicating that individuals with severe symptoms had larger waiting list-controlled symptom reductions after CBT (Cohen d = -1.13 [95% CI, -1.39 to -0.88] for patients with very severe SAD; Cohen d = -0.54 [95% CI, -0.80 to -0.29] for patients with mild SAD).
CONCLUSIONS AND RELEVANCE
In this systematic review and IPDMA, higher baseline SAD symptom severity was associated with greater (absolute but not relative) symptom reductions after CBT in patients with SAD. The findings contribute to personalized care by suggesting that clinicians can confidently offer CBT to individuals with severe SAD symptoms.
Topics: Adult; Humans; Female; Male; Phobia, Social; Waiting Lists; Cognitive Behavioral Therapy; Randomized Controlled Trials as Topic
PubMed: 37256597
DOI: 10.1001/jamapsychiatry.2023.1291 -
Journal of Medical Screening Sep 2023To systematically review the accuracy of artificial intelligence (AI)-based systems for grading of fundus images in diabetic retinopathy (DR) screening. (Review)
Review
OBJECTIVES
To systematically review the accuracy of artificial intelligence (AI)-based systems for grading of fundus images in diabetic retinopathy (DR) screening.
METHODS
We searched MEDLINE, EMBASE, the Cochrane Library and the ClinicalTrials.gov from 1st January 2000 to 27th August 2021. Accuracy studies published in English were included if they met the pre-specified inclusion criteria. Selection of studies for inclusion, data extraction and quality assessment were conducted by one author with a second reviewer independently screening and checking 20% of titles. Results were analysed narratively.
RESULTS
Forty-three studies evaluating 15 deep learning (DL) and 4 machine learning (ML) systems were included. Nine systems were evaluated in a single study each. Most studies were judged to be at high or unclear risk of bias in at least one QUADAS-2 domain. Sensitivity for referable DR and higher grades was ≥85% while specificity varied and was <80% for all ML systems and in 6/31 studies evaluating DL systems. Studies reported high accuracy for detection of ungradable images, but the latter were analysed and reported inconsistently. Seven studies reported that AI was more sensitive but less specific than human graders.
CONCLUSIONS
AI-based systems are more sensitive than human graders and could be safe to use in clinical practice but have variable specificity. However, for many systems evidence is limited, at high risk of bias and may not generalise across settings. Therefore, pre-implementation assessment in the target clinical pathway is essential to obtain reliable and applicable accuracy estimates.
Topics: Humans; Artificial Intelligence; Diabetic Retinopathy; Early Detection of Cancer; Mass Screening; Diabetes Mellitus
PubMed: 36617971
DOI: 10.1177/09691413221144382 -
Neuropsychology Review Dec 2023Although attention and early associative learning in preverbal children is predominantly driven by rapid eye-movements in response to moving visual stimuli and... (Meta-Analysis)
Meta-Analysis Review
Although attention and early associative learning in preverbal children is predominantly driven by rapid eye-movements in response to moving visual stimuli and sounds/words (e.g., associating the word "bottle" with the object), the literature examining the role of visual attention and memory in ongoing vocabulary development across childhood is limited. Thus, this systematic review and meta-analysis examined the association between visual memory and vocabulary development, including moderators such as age and task selection, in neurotypical children aged 2-to-12 years, from the brain-based perspective of cognitive neuroscience. Visual memory tasks were classified according to the visual characteristics of the stimuli and the neural networks known to preferentially process such information, including consideration of the distinction between the ventral visual stream (processing more static visuo-perceptual details, such as form or colour) and the more dynamic dorsal visual stream (processing spatial temporal action-driven information). Final classifications included spatio-temporal span tasks, visuo-perceptual or spatial concurrent array tasks, and executive judgment tasks. Visuo-perceptual concurrent array tasks, reliant on ventral stream processing, were moderately associated with vocabulary, while tasks measuring spatio-temporal spans, associated with dorsal stream processing, and executive judgment tasks (central executive), showed only weak correlations with vocabulary. These findings have important implications for health professionals and researchers interested in language, as they advocate for the development of more targeted language learning interventions that include specific and relevant aspects of visual processing and memory, such as ventral stream visuo-perceptual details (i.e., shape or colour).
Topics: Child; Humans; Vocabulary; Memory; Visual Perception; Brain; Language
PubMed: 36136174
DOI: 10.1007/s11065-022-09561-4