Peer Review Research Articles

Community-Based Participatory Obesity Prevention Interventions in Rural Communities: A Scoping Review

Child obesity is a worldwide public health concern. In America, children from rural areas have greater odds of obesity in comparison to those from urban areas. Community-engaged research is important for all communities, particularly under-represented communities. This paper reports the results of a scoping review investigating community-engaged research in obesity prevention programs tested with school-aged children in rural America. A literature search of Medline Ovid was conducted to identify interventions reporting the results of obesity prevention interventions that promoted a healthy diet or physical activity (PA) behaviors to school-age children in rural communities of the United States (US). After title and abstract review, potentially relevant citations were further examined by assessing the full text. Each stage of review was conducted by two independent reviewers. Twelve studies met the inclusionary criteria and are included in this review. Most of the studies focused on elementary school participants (n = 7) and improving both diet and PA (n = 9). Out of the twelve studies, only five included the target audience in intervention development or implementation. The most popular type of community engagement was community participation (n = 4). This review revealed that community-engaged research is under-utilized in obesity prevention interventions tested with school-aged children in rural US communities.

Laboratory-confirmed respiratory viral infection triggers for acute myocardial infarction and stroke: Systematic review protocol.

Cardiovascular disease contributes substantially to global mortality and morbidity. Respiratory tract infections, particularly influenza, may trigger an increase in the short-term risk of acute myocardial infarction (AMI) and stroke. Recent studies have also linked this risk to other respiratory viruses, including respiratory syncytial virus (RSV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the pathogen-specific relative contributions, the strength of their associations, and overall public health significance are poorly understood. Assuming causal links, understanding, quantifying, and comparing the effects of different pathogens as triggering factors for acute cardiovascular events is critical to guide future research and prevention. Our aim is to conduct a systematic review to examine the relative effects of laboratory-confirmed respiratory virus infections as triggers for acute myocardial infarction and stroke. We will conduct a comprehensive search of Ovid MEDLINE, PubMed, Ovid Embase, Cochrane Library Central Register of Controlled Trials, and Web of Science, from inception to the end of March 2024. Studies capturing respiratory viral infection(s) using laboratory-confirmatory methods, incidence of AMI or stroke (ischaemic or haemorrhagic), and those involving human participants in any country, will be assessed for eligibility. We will include the following analytical epidemiological study types: randomised controlled trials, cohort and case-control studies, self-controlled case series, and case-crossover designs. We will not impose restrictions on the date, language, study population, geographical region, or sample size, to minimise the risk of introducing biases. Search results will be screened for eligibility by two independent reviewers, and discrepancies resolved by consensus and/or arbitration by a third reviewer. We will assess the risk of bias among the included studies by adopting the Cochrane Collaboration tools for randomised and non-randomised studies. The overall quality of studies will be assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach. We will examine sources of heterogeneity, and if studies are sufficiently homogeneous, a meta-analysis will be conducted to calculate the pooled effect sizes. Reporting will adhere to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. International Prospective Register of Systematic Reviews (PROSPERO) registration number: CRD42024494997.

Clinical, Cultural, Computational, and Regulatory Considerations to Deploy AI in Radiology: Perspectives of RSNA and MICCAI Experts.

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. The Radiological Society of North of America (RSNA) and the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society have led a series of joint panels and seminars focused on the present impact and future directions of artificial intelligence (AI) in radiology. These conversations have collected viewpoints from multidisciplinary experts in radiology, medical imaging, and machine learning on the current clinical penetration of AI technology in radiology, and how it is impacted by trust, reproducibility, explainability, and accountability. The collective points-both practical and philosophical-define the cultural changes for radiologists and AI scientists working together and describe the challenges ahead for AI technologies to meet broad approval. This article presents the perspectives of experts from MICCAI and RSNA on the clinical, cultural, computational, and regulatory considerations-coupled with recommended reading materials-essential to adopt AI technology successfully in radiology and more generally in clinical practice. The report emphasizes the importance of collaboration to improve clinical deployment and highlights the need to integrate clinical and medical imaging data and introduces strategies to ensure smooth and incentivized integration. ©RSNA, 2024.

Artificial Intelligence Outcome Prediction in Neonates with Encephalopathy (AI-OPiNE).

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Purpose To develop a deep learning algorithm to predict 2-year neurodevelopmental outcomes in neonates with hypoxic-ischemic encephalopathy (HIE) using MRI and basic clinical data. Materials and Methods In this study, MRI data of term neonates with encephalopathy in the High Dose Erythropoietin for Asphyxia (HEAL) trial (ClinicalTrials.gov: NCT02811263), who were enrolled from 17 institutions between January 25th, 2017 and October ninth, 2019, were retrospectively analyzed. The harmonized MRI protocol included T1-weighted, T2-weighted, and diffusion tensor imaging. Deep learning classifiers were trained to predict the primary outcome of the HEAL trial (death or any neurodevelopmental impairment [NDI] at 2 years) using multisequence MRI and basic clinical variables, including sex and gestational age at birth. Model performance was evaluated on a test sets comprising 10% of cases from 15 institutions (in-distribution test set, n = 41) and 100% of cases from 2 institutions (out-of-distribution test set, n = 41). Model performance in predicting additional secondary outcomes, including death alone, was also assessed. Results For the 414 neonates (mean gestational age, 39 weeks ± 1.4, 232 males, 182 females), in the study cohort, 198 (48%) died or had any NDI at 2 years. The deep learning model achieved an area under the receiver operating characteristic curve (AUC) of 0.74 (95% CI: 0.60-0.86) and 63% accuracy on the in-distribution test set and an AUC of 0.77 (95% CI: 0.63-0.90) and 78% accuracy on the out-of-distribution test set. Performance was similar or better for predicting secondary outcomes. Conclusion Deep learning analysis of neonatal brain MRI yielded high performance for predicting 2-year neurodevelopmental outcomes. ©RSNA, 2024.

Artificial Intelligence Outcome Prediction in Neonates with Encephalopathy (AI-OPiNE).

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Purpose To develop a deep learning algorithm to predict 2-year neurodevelopmental outcomes in neonates with hypoxic-ischemic encephalopathy (HIE) using MRI and basic clinical data. Materials and Methods In this study, MRI data of term neonates with encephalopathy in the High Dose Erythropoietin for Asphyxia (HEAL) trial (ClinicalTrials.gov: NCT02811263), who were enrolled from 17 institutions between January 25th, 2017 and October ninth, 2019, were retrospectively analyzed. The harmonized MRI protocol included T1-weighted, T2-weighted, and diffusion tensor imaging. Deep learning classifiers were trained to predict the primary outcome of the HEAL trial (death or any neurodevelopmental impairment [NDI] at 2 years) using multisequence MRI and basic clinical variables, including sex and gestational age at birth. Model performance was evaluated on a test sets comprising 10% of cases from 15 institutions (in-distribution test set, n = 41) and 100% of cases from 2 institutions (out-of-distribution test set, n = 41). Model performance in predicting additional secondary outcomes, including death alone, was also assessed. Results For the 414 neonates (mean gestational age, 39 weeks ± 1.4, 232 males, 182 females), in the study cohort, 198 (48%) died or had any NDI at 2 years. The deep learning model achieved an area under the receiver operating characteristic curve (AUC) of 0.74 (95% CI: 0.60-0.86) and 63% accuracy on the in-distribution test set and an AUC of 0.77 (95% CI: 0.63-0.90) and 78% accuracy on the out-of-distribution test set. Performance was similar or better for predicting secondary outcomes. Conclusion Deep learning analysis of neonatal brain MRI yielded high performance for predicting 2-year neurodevelopmental outcomes. ©RSNA, 2024.

Stepwise Transfer Learning for Expert-Level Pediatric Brain Tumor MRI Segmentation in a Limited Data Scenario.

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Purpose To develop, externally test, and evaluate clinical acceptability of a deep learning (DL) pediatric brain tumor segmentation model using stepwise transfer learning. Materials and Methods In this retrospective study, the authors leveraged two T2-weighted MRI datasets (May 2001-December 2015) from a national brain tumor consortium (n = 184; median age, 7 years (range: 1-23 years); 94 male) and a pediatric cancer center (n = 100; median age, 8 years (range: 1-19 years); 47 male) to develop and evaluate DL neural networks for pediatric low-grade glioma segmentation using a novel stepwise transfer learning approach to maximize performance in a limited data scenario. The best model was externally-tested on an independent test set and subjected to randomized, blinded evaluation by three clinicians, wherein they assessed clinical acceptability of expert- and artificial intelligence (AI)-generated segmentations via 10-point Likert scales and Turing tests. Results The best AI model used in-domain, stepwise transfer learning (median DSC: 0.88 [IQR 0.72-0.91] versus 0.812 [0.56-0.89] for baseline model; P = .049). On external testing, AI model yielded excellent accuracy using reference standards from three clinical experts (Expert-1: 0.83 [0.75-0.90]; Expert-2: 0.81 [0.70-0.89]; Expert-3: 0.81 [0.68-0.88]; mean accuracy: 0.82)). On clinical benchmarking (n = 100 scans), experts rated AI-based segmentations higher on average compared with other experts (median Likert score: median 9 [IQR 7-9]) versus 7 [IQR 7-9]) and rated more AI segmentations as clinically acceptable (80.2% versus 65.4%). Experts correctly predicted the origin of AI segmentations in an average of 26.0% of cases. Conclusion Stepwise transfer learning enabled expert-level, automated pediatric brain tumor auto-segmentation and volumetric measurement with a high level of clinical acceptability. ©RSNA, 2024.

Analysis of core quality criteria and requirements for high-level waste disposal R&D based on the US NQA-1 and Korea KEPIC-QAP

This study presents the key quality criteria and requirements as well as an implementation plan for R&D related to the disposal of high-level waste. From the results of the analysis based on NQA-1 and KEPIC-QAP, it was found that test control, software control, design control and independent review of the report were derived as QA key criteria. In addition, the R&D organization should gradually expand the quality assurance criteria to increase R&D efficiency for licensing the construction of the spent nuclear fuel repository. In order to improve research quality, it is necessary to customize the quality requirements for the organization. That is, from the 18 quality criteria of NQA-1, such factors as the quality requirements of organization and quality assurance program, design and software control, document control, purchasing management, test control, quality assurance records, and audit can be selected as R&D quality assurance criteria. In other words, high-level waste disposal R&D should be performed considering not only nuclear quality standards but also research resources. However, as of yet, legal R&D quality assurance requirements in Korea are not specific and only general standards are presented.

Gender-Specific Medicine in the European Society of Cardiology Guidelines from 2018 to 2023: Where Are We Going?

Background/Objectives: Evidence-based medicine (EBM) shapes most clinical guidelines. Although the advent of EBM marked a significant advancement, failure to include sex differences in the study design and analysis of most trials leads to an under-representation of gender-specific medicine (GM) in EBM-directed guidelines. In this review, we evaluated how the topic of GM was developed in the guidelines produced by the European Society of Cardiology (ESC) from 2018 to 2023. Methods: Two independent reviewers evaluated 24 ESC guidelines. Significant mentions of GM were counted and divided between epidemiology, diagnosis, and therapeutics. The qualitative and semi-quantitative analysis of information relating to GM was performed. Data on the number of citations of papers with a title concerning GM and the prevalence and role of women in guidelines’ authorship were also analyzed. Results: Less than 50% of guidelines had a section dedicated to GM. Only nine guidelines were led by a woman, and 144/567 authors were female. In the most recent guidelines and in those with at least 30% of female authors, there was an increased mention of GM. On average, guidelines had four significant mentions of GM regarding epidemiology, two regarding diagnosis, and one regarding therapy. Articles with titles concerning GM made up, on average, 1.5% of the total number of citations. Conclusions: Although sex differences play a significant role in most clinical scenarios, ESC guidelines still do not sufficiently account for this. The problem does not seem to solely lie in the guidelines, but in the lack of attention to GM in research needed for their preparation.

Frameworks describing the transition to open labour employment for persons with mild and moderate intellectual disability: a scoping review protocol

IntroductionPersons with mild and moderate intellectual disability (MMID) have the right to participate in all aspects of society and be afforded equal opportunities to realise their full potential. However, it...

Effect of composite textured rough surfaces on the lubrication performance of cylindrical roller bearings

Purpose The purpose of this paper is to study the impact of different types of textures on the friction lubrication performance of cylindrical roller bearings. Design/methodology/approach In the present study, the composite texture hydrodynamic lubrication model that takes into account the effects of surface roughness is established, and the Reynolds equation for the oil film is numerically solved using the finite difference method. The study investigates the oil film carrying capacity and maximum pressure of bearings under two different arrangements of four composite textures and conducts a comparative analysis of the oil film characteristics under various texture parameters and surface roughness levels. Findings When the roughness of the inner texture surface and the contact surface are equal, the bearing capacity of the composite texture is intermediate between the two textures. The impact trend of surface roughness on fluid dynamic pressure effects varies with the type of composite texture; the internal roughness of the texture affects the micro-hydrodynamic pressure action. Composite textures with different depths exhibit improved bearing capacities; elliptical cylindrical parallel and elliptical hemispherical parallel textures perform better when their area densities are similar, while other types of composite textures show enhanced bearing performance as the ratio of their area densities increases. Originality/value This paper contributes to the theoretical investigations and analyses on designing the textured rolling bearings with high lubrication performance. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2024-0050

Effect of composite textured rough surfaces on the lubrication performance of cylindrical roller bearings

Purpose The purpose of this paper is to study the impact of different types of textures on the friction lubrication performance of cylindrical roller bearings. Design/methodology/approach In the present study, the composite texture hydrodynamic lubrication model that takes into account the effects of surface roughness is established, and the Reynolds equation for the oil film is numerically solved using the finite difference method. The study investigates the oil film carrying capacity and maximum pressure of bearings under two different arrangements of four composite textures and conducts a comparative analysis of the oil film characteristics under various texture parameters and surface roughness levels. Findings When the roughness of the inner texture surface and the contact surface are equal, the bearing capacity of the composite texture is intermediate between the two textures. The impact trend of surface roughness on fluid dynamic pressure effects varies with the type of composite texture; the internal roughness of the texture affects the micro-hydrodynamic pressure action. Composite textures with different depths exhibit improved bearing capacities; elliptical cylindrical parallel and elliptical hemispherical parallel textures perform better when their area densities are similar, while other types of composite textures show enhanced bearing performance as the ratio of their area densities increases. Originality/value This paper contributes to the theoretical investigations and analyses on designing the textured rolling bearings with high lubrication performance. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2024-0050

Interactive voice response (IVR) for tobacco cessation: a systematic review

ObjectiveTo summarise the uses, outcomes and implementation of interactive voice response (IVR) as a tobacco cessation intervention.Data sourcesA systematic review was conducted. Searches were performed on 3 May 2023. The...

Trastuzumab deruxtecan versus trastuzumab emtansine in Asian patients with HER2-positive metastatic breast cancer.

The global phase 3 DESTINY-Breast03 study (ClinicalTrials.gov; NCT03529110) showed statistically significant and clinically meaningful improvements in progression-free survival (PFS) and overall survival (OS) with trastuzumab deruxtecan (T-DXd) over trastuzumab emtansine (T-DM1) in patients with human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer (mBC) previously treated with trastuzumab and a taxane. Here, we report a subgroup analysis of Asian patients enrolled in DESTINY-Breast03. In total, 309 patients (149 in the T-DXd arm and 160 in the T-DM1 arm) from Asian countries and regions were randomized. At data cutoff (July 25, 2022), the median duration of follow-up in the Asian subpopulation was 29.0 months with T-DXd and 26.0 months with T-DM1. The PFS (determined by blinded independent central review) hazard ratio was 0.30 (95% confidence interval 0.22-0.41) favoring T-DXd over T-DM1 (median PFS 25.1 vs. 5.4 months). Median OS was not reached in the T-DXd arm and was 37.7 months in the T-DM1 arm. The median treatment duration was 15.4 months with T-DXd and 5.5 months with T-DM1. The incidence of grade ≥3 drug-related treatment-emergent adverse events was similar between both treatment arms (49.0% vs. 46.5%) and was consistent with the overall DESTINY-Breast03 population. Adjudicated drug-related interstitial lung disease or pneumonitis occurred in 12.9% of patients treated with T-DXd and 2.5% treated with T-DM1, with a higher incidence in Japanese patients; none of these were grade ≥4 events. These efficacy and safety data reinforce the favorable benefit-risk profile of T-DXd in HER2-positive mBC, including in the Asian subgroup.

Telemedicine in Improving Glycemic Control Among Children and Adolescents With Type 1 Diabetes Mellitus: Systematic Review and Meta-Analysis.

Type 1 diabetes mellitus (T1DM) is the most common chronic autoimmune disease among children and adolescents. Telemedicine has been widely used in the field of chronic disease management and can benefit patients with T1DM. However, existing studies lack high-level evidence related to the effectiveness of telemedicine for glycemic control in children and adolescents with T1DM. This study aims to systematically review the evidence on the effectiveness of telemedicine interventions compared with usual care on glycemic control among children and adolescents with T1DM. In this systematic review and meta-analysis, we searched PubMed, Cochrane Library, Embase, Web of Science (all databases), and CINAHL Complete from database inception to May 2023. We included randomized controlled trials (RCTs) that evaluated the effectiveness of a telemedicine intervention on glycemic control in children and adolescents with T1DM. In total, 2 independent reviewers performed the study selection and data extraction. Study quality was assessed using the Cochrane Risk of Bias 2 tool. Our primary outcome was glycated hemoglobin (HbA1c) levels. Secondary outcomes were quality of life, self-monitoring of blood glucose, the incidence of hypoglycemia, and cost-effectiveness. A random-effects model was used for this meta-analysis. Overall, 20 RCTs (1704 participants from 12 countries) were included in the meta-analysis. Only 5% (1/20) of the studies were at high risk of bias. Compared to usual care, telemedicine was found to reduce HbA1c levels by 0.22 (95% CI -0.33 to -0.10; P<.001; I2=35%). There was an improvement in self-monitoring of blood glucose (mean difference [MD] 0.54, 95% CI -0.72 to 1.80; P=.40; I2=67.8%) and the incidence of hypoglycemia (MD -0.15, 95% CI -0.57 to 0.27; P=.49; I2=70.7%), although this was not statistically significant. Moreover, telemedicine had no convincing effect on the Diabetes Quality of Life for Youth score (impact of diabetes: P=.59; worries about diabetes: P=.71; satisfaction with diabetes: P=.68), but there was a statistically significant improvement in non-youth-specific quality of life (MD -0.24, 95% CI -0.45 to -0.02; P=.04; I2=0%). Subgroup analyses revealed that the effect of telemedicine on HbA1c levels appeared to be greater in studies involving children (MD -0.41, 95% CI -0.62 to -0.20; P<.001), studies that lasted <6 months (MD -0.32, 95% CI -0.48 to -0.17; P<.001), studies where providers used smartphone apps to communicate with patients (MD -0.37, 95% CI -0.53 to -0.21; P<.001), and studies with medication dose adjustment (MD -0.25, 95% CI -0.37 to -0.12; P<.001). Telemedicine can reduce HbA1c levels and improve quality of life in children and adolescents with T1DM. Telemedicine should be regarded as a useful supplement to usual care to control HbA1c levels and a potentially cost-effective mode. Meanwhile, researchers should develop higher-quality RCTs using large samples that focus on hard clinical outcomes, cost-effectiveness, and quality of life.

A Scoping Review of Stigma Related to Prostate Cancer in Black Men.

Prostate cancer (CaP) disproportionately affects 1-in-4 Black men and is a stigmatised disease within their communities. Yet, Black men are underrepresented in CaP research concerning stigma, which necessitates a scoping review to map available evidence on this topic to inform future research. To map published literature on stigma related to CaP in Black men to understand their experiences and/or perceptions and identify directions for future research. A scoping review was conducted using the five-step framework by Arksey and O'Malley. Studies published in English addressing stigma related to CaP from the perspectives of Black men and/or their families were included. We searched six databases including Medline, Embase, PsycInfo, CINAHL, Web of Science Core Collection and Google Scholar, from inception to April 2023. Citation searches were also conducted. Two independent reviewers conducted screening and data extraction. Data was synthesised using descriptive content analysis. Thirty-four eligible studies conducted in the USA, UK, Trinidad and Tobago, South Africa, Cameroon and Canada from 1995 to 2023 were included. A total of 1867 Black men with/without a CaP diagnosis and 145 adult partners were included. Review findings showed a complex intersection of self-stigma, public stigma and structural stigma impacted Black men's perceptions of their masculinity. While men's experiences/perceptions of stigma varied depending on their illness status, there were commonalities in their masculinity concerns (underpinned by stigma), which influenced their attitude towards digital rectal examination, post-treatment side effects and social interactions on CaP. These have implications for public health messaging on CaP within Black communities, as well as patient-provider interactions with the men. This novel review highlights the need to pay attention to how CaP is presented to Black men and their communities using avenues and languages that are culturally acceptable and empower them to negotiate self-stigma, public stigma and structural stigma related to CaP. Directions for further research were also identified.

Is three-dimensional ultrasonography a valuable diagnostic tool for patients with ovarian cancer? Systematic review and meta-analysis

IntroductionThis paper was to assess the diagnostic performance and clinical value of three-dimensional ultrasonography (3DUS), three-dimensional ultrasonography power Doppler (3DPD), and 3DUS combined with 3DPD in ovarian cancer (OC).MethodsThe study was registered with PROSPERO (CRD 42023405765). PubMed and Web of Science were searched from inception to 25 January 2022, and reference lists of potentially eligible studies were also manually searched. Patient and study characteristics were extracted by two independent reviewers. Any discrepancies were addressed through discussion. The sensitivity, specificity, positive and negative likelihood ratio (PLR and NLR, respectively), and the area under the receiver operating characteristic curve (AUC) were pooled separately.ResultsWe retrieved 2,566 studies, of which 18 were finally enrolled, with 2,548 cases. The pooled sensitivity, specificity, PLR, NLR, and AUC for 3DUS were 0.89 (95% CI: 0.85–0.93), 0.93 (95% CI: 0.88–0.96), 13.1 (95% CI: 7.3–23.4), 0.11 (95% CI: 0.08–0.16), and 0.90 (95% CI: 0.87–0.93), respectively. The pooled sensitivity, specificity, PLR, NLR, and AUC for 3DPD were 0.90 (95% CI: 0.80–0.95), 0.85 (95% CI: 0.71–0.92), 5.8 (95% CI: 3.0–11.2), 0.12 (95% CI: 0.06–0.24), and 0.94 (95% CI: 0.91–0.96), respectively. The pooled sensitivity, specificity, PLR, NLR, and AUC for 3DUS combined with 3DPD were 0.99 (95% CI: 0.73–1.00), 0.95 (95% CI: 0.85–0.99), 21.9 (95% CI: 6.1–78.9), 0.01 (95% CI: 0.00–0.37), and 0.99 (95% CI: 0.98–1.00), respectively.Conclusions3DUS, 3DPD, and 3DUS combined with 3DPD are promising diagnostic tools for OC, alongside elevated sensitivity and specificity. However, the combination of 3DUS and 3DPD techniques has higher diagnostic efficiency.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD 42023405765.

Longitudinal changes in executive function in autism spectrum disorder: A systematic review and meta-analyses.

Individuals with an autism spectrum disorder (ASD) diagnosis show impairment in executive function (EF). However, findings are mixed regarding differences in the age effect on EF between autistic individuals and persons with typical development (TD). Questions remain regarding whether the age-related trajectories of EF in ASD are the same as or different from those in TD. To bridge this knowledge gap, we conducted a systematic review and meta-analyses of longitudinal studies that compared age-related changes in EF between ASD and TD groups (preregistration: osf.io/j5764). A literature search was conducted using PubMed, PsycINFO, and Web of Science on January 29, 2024. After screening by two independent reviewers, 14 longitudinal studies were included. Random-effects meta-analyses of studies involving a maximum total of 518 autistic and 3558 TD children and adolescents (mean baseline ages: 5.7-12.0 years) showed that ASD had significantly poorer EF than TD at both baseline and follow-up. However, there was no significant group difference in the age-related change in EF across domains, including working memory, inhibition, shifting, and planning. Robust Bayesian meta-analyses also provided substantial evidence in favor of the null hypothesis that ASD and TD groups showed similar changes over time for most EF processes. Limitations of the literature included the limited number of longitudinal studies and a narrow range of developmental stages and EF constructs analyzed across studies. Altogether, these findings suggest that autistic children and adolescents generally can improve in EF over time similarly to their neurotypical peers. This has important implications for parents and educators, encouraging appropriate EF training and intervention for autistic children and adolescents at an early stage.

Diabetes mellitus in sub-saharan Africa during the COVID-19 pandemic: A scoping review.

The COVID-19 pandemic impacted the healthcare and outcomes of individuals with various chronic diseases. However, there is a paucity of data on the impact of the COVID-19 pandemic on diabetes mellitus (DM) in low-resource settings. To address this, we conducted a scoping review to explore the literature published on diabetes-related COVID-19 outcomes and care during the COVID-19 pandemic in countries of sub-Saharan Africa. We applied our search strategy to PubMed, Web of Science, CINAHL, African Index Medicus, Google Scholar, Cochrane Library, Scopus, Science Direct, ERIC and Embase to obtain relevant articles published from January 2020 to March 2023. Two independent reviewers were involved in screening the retrieved articles. Data from eligible articles were extracted from quantitative, qualitative and mixed-methods studies. Quantitative evidence was summarised using descriptive statistics, while a thematic framework was used to identify and categorise themes from qualitative evidence. We found 42 of the retrieved 360 articles eligible, mainly from South Africa, Ethiopia and Ghana (73.4%). The incidence of DM among COVID-19 cases was 13.7/1,000 person-days observation. COVID-19 was associated with increased odds of death (OR 1.30-9.0, 95% CI), hospitalisation (OR 3.30-3.73: 95% CI), and severity (OR: 1.30-4.05, 95% CI) in persons with DM. Challenges in caring for DM during the pandemic were inadequate patient self-management, difficulties in healthcare access, and inadequate healthcare resources. The COVID-19 pandemic was characterised by a high incidence of DM in persons infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and high COVID-19-associated mortality, severity, and hospitalisation among people persons with DM. The pandemic also created difficulties in DM self-management and worsened the quality of DM care services. Policymakers should devise preventive and management strategies for DM during emerging and re-emerging infectious disease epidemics and outbreaks, given that such occurrences are increasingly frequent in the region.

Is three-dimensional ultrasonography a valuable diagnostic tool for patients with ovarian cancer? Systematic review and meta-analysis

IntroductionThis paper was to assess the diagnostic performance and clinical value of three-dimensional ultrasonography (3DUS), three-dimensional ultrasonography power Doppler (3DPD), and 3DUS combined with 3DPD in ovarian cancer (OC).MethodsThe study was registered with PROSPERO (CRD 42023405765). PubMed and Web of Science were searched from inception to 25 January 2022, and reference lists of potentially eligible studies were also manually searched. Patient and study characteristics were extracted by two independent reviewers. Any discrepancies were addressed through discussion. The sensitivity, specificity, positive and negative likelihood ratio (PLR and NLR, respectively), and the area under the receiver operating characteristic curve (AUC) were pooled separately.ResultsWe retrieved 2,566 studies, of which 18 were finally enrolled, with 2,548 cases. The pooled sensitivity, specificity, PLR, NLR, and AUC for 3DUS were 0.89 (95% CI: 0.85–0.93), 0.93 (95% CI: 0.88–0.96), 13.1 (95% CI: 7.3–23.4), 0.11 (95% CI: 0.08–0.16), and 0.90 (95% CI: 0.87–0.93), respectively. The pooled sensitivity, specificity, PLR, NLR, and AUC for 3DPD were 0.90 (95% CI: 0.80–0.95), 0.85 (95% CI: 0.71–0.92), 5.8 (95% CI: 3.0–11.2), 0.12 (95% CI: 0.06–0.24), and 0.94 (95% CI: 0.91–0.96), respectively. The pooled sensitivity, specificity, PLR, NLR, and AUC for 3DUS combined with 3DPD were 0.99 (95% CI: 0.73–1.00), 0.95 (95% CI: 0.85–0.99), 21.9 (95% CI: 6.1–78.9), 0.01 (95% CI: 0.00–0.37), and 0.99 (95% CI: 0.98–1.00), respectively.Conclusions3DUS, 3DPD, and 3DUS combined with 3DPD are promising diagnostic tools for OC, alongside elevated sensitivity and specificity. However, the combination of 3DUS and 3DPD techniques has higher diagnostic efficiency.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD 42023405765.

Psychosocial interventions before conception and the impact on perinatal depression, anxiety and stress: A scoping review (WHO ICTRP).

Abstract Background: While the preconception period is widely acknowledged as a critical phase for enhancing maternal health, there lacks a comprehensive overview of preconceptional psychosocial or midwife-supported psychological interventions aimed at tackling perinatal mental health issues. Objective: This scoping review aimed to identify existing psychosocial and midwife-supported psychological interventions performed during the preconception period, for the prevention of depressive symptoms, anxiety and stress during pregnancy or after childbirth. Methods: After an informative, exploratory search, seven electronic databases were searched on the 31st of January 2023. In addition, clinical trials registries were searched, and forward/backward citation searching of included articles was performed, and the authors of conference abstracts were contacted. Two independent end blinded reviewers screened a total of 7254 articles by title/abstract using pre-discussed inclusion and exclusion criteria, and 132 by full text using a predetermined data extraction table. Finally 3 studies and 5 study protocols were included. Results: Two studies showed a statistically non-significant reduction in prenatal levels of anxiety in women who received preconception counseling by a health care provider not directly trained as a psychotherapist. One study showed a statistically non-significant marginal reduction in stress and a small increase in depressive symptoms during pregnancy in women who received preconceptional education, whether or not in combination with a social-cognitive theory based lifestyle intervention. Five study protocols were found requiring further follow-up in the near future. Conclusion: Longitudinal randomized controlled trials, starting during the preconception period, are needed to facilitate the process of developing tailored prevention strategies.