Role of long non-coding RNAs in cholangiocarcinoma: A systematic review and meta-analysis.

BACKGROUND: Cholangiocarcinoma (CCA), as a rare malignancy of the biliary tree, has a poor prognosis most of the time. CCA is highly epigenetically regulated and several long non-coding RNAs (lncRNA) have been investigated to have a diagnostic and prognostic role in CCA. The current study aimed to assess the studies finding relevant lncRNAs in CCA systematically. METHODS: International databases, including PubMed, Cochrane Library, and Embase, were comprehensively searched in order to identify studies investigating any lncRNA in CCA. After screening by title/abstract and full-text, necessary data were extracted. Random-effect meta-analysis was performed for pooling the areas under the curve (AUCs), specificity, and sensitivity of lncRNAs for the diagnosis of CCA. RESULTS: A total of 33 studies were chosen to be included in the final analysis, comprised of 2677 patients. Meta-analysis of AUCs for evaluation of CCA resulted in pooled AUC of 0.79 (95% CI: 0.75-0.82; I2 = 69.11, p < .01). Additionally, overall sensitivity of 0.80 (95% CI 0.75-0.84) and specificity of 0.77 (95% CI: 0.68-0.84) were observed. Measurement of lncRANs in the assessment of CCA also improved overall survival significantly (effect size 1.61, 95% CI: 1.39-1.82). A similar result was found for progression-free survival (effect size 1.57, 95% CI: 1.20-1.93). CONCLUSION: Based on our findings, lncRNAs showed promising results as biomarkers in the diagnosis of CCA since they had acceptable sensitivity and specificity, in addition to the fact that improved survival in this poor prognosis cancer. Further studies might be needed to address this issue and find the best clinically useful lncRNA.

Current Applications of Artificial Intelligence for Pediatric Dentistry: A Systematic Review and Meta-Analysis.

Purpose: To systematically evaluate artificial intelligence applications for diagnostic and treatment planning possibilities in pediatric dentistry. Methods: PubMed®, EMBASE®, Scopus, Web of Science™, IEEE, medRxiv, arXiv, and Google Scholar were searched using specific search queries. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) checklist was used to assess the risk of bias assessment of the included studies. Results: Based on the initial screening, 33 eligible studies were included (among 3,542). Eleven studies appeared to have low bias risk across all QUADAS-2 domains. Most applications focused on early childhood caries diagnosis and prediction, tooth identification, oral health evaluation, and supernumerary tooth identification. Six studies evaluated AI tools for mesiodens or supernumerary tooth identification on radigraphs, four for primary tooth identification and/or numbering, seven studies to detect caries on radiographs, and 12 to predict early childhood caries. For these four tasks, the reported accuracy of AI varied from 60 percent to 99 percent, sensitivity was from 20 percent to 100 percent, specificity was from 49 percent to 100 percent, F1-score was from 60 percent to 97 percent, and the area-under-the-curve varied from 87 percent to 100 percent. Conclusions: The overall body of evidence regarding artificial intelligence applications in pediatric dentistry does not allow for firm conclusions. For a wide range of applications, AI shows promising accuracy. Future studies should focus on a comparison of AI against the standard of care and employ a set of standardized outcomes and metrics to allow comparison across studies.

Deep learning for tooth identification and numbering on dental radiography: a systematic review and meta-analysis.

OBJECTIVES: Improved tools based on deep learning can be used to accurately number and identify teeth. This study aims to review the use of deep learning in tooth numbering and identification. METHODS: An electronic search was performed through October 2023 on PubMed, Scopus, Cochrane, Google Scholar, IEEE, arXiv, and medRxiv. Studies that used deep learning models with segmentation, object detection, or classification tasks for teeth identification and numbering of human dental radiographs were included. For risk of bias assessment, included studies were critically analysed using quality assessment of diagnostic accuracy studies (QUADAS-2). To generate plots for meta-analysis, MetaDiSc and STATA 17 (StataCorp LP, College Station, TX, USA) were used. Pooled outcome diagnostic odds ratios (DORs) were determined through calculation. RESULTS: The initial search yielded 1618 studies, of which 29 were eligible based on the inclusion criteria. Five studies were found to have low bias across all domains of the QUADAS-2 tool. Deep learning has been reported to have an accuracy range of 81.8%-99% in tooth identification and numbering and a precision range of 84.5%-99.94%. Furthermore, sensitivity was reported as 82.7%-98% and F1-scores ranged from 87% to 98%. Sensitivity was 75.5%-98% and specificity was 79.9%-99%. Only 6 studies found the deep learning model to be less than 90% accurate. The average DOR of the pooled data set was 1612, the sensitivity was 89%, the specificity was 99%, and the area under the curve was 96%. CONCLUSION: Deep learning models successfully can detect, identify, and number teeth on dental radiographs. Deep learning-powered tooth numbering systems can enhance complex automated processes, such as accurately reporting which teeth have caries, thus aiding clinicians in making informed decisions during clinical practice.

Risk of flare or relapse in patients with immune-mediated diseases following SARS-CoV-2 vaccination: a systematic review and meta-analysis.

BACKGROUND: Patients with autoimmune and immune-mediated diseases (AI-IMD) are at greater risk of COVID-19 infection; therefore, they should be prioritized in vaccination programs. However, there are concerns regarding the safety of COVID-19 vaccines in terms of disease relapse, flare, or exacerbation. In this study, we aimed to provide a more precise and reliable vision using systematic review and meta-analysis. METHODS: PubMed-MEDLINE, Embase, and Web of Science were searched for original articles reporting the relapse/flare in adult patients with AI-IMD between June 1, 2020 and September 25, 2022. Subgroup analysis and sensitivity analysis were conducted to investigate the sources of heterogeneity. Statistical analysis was performed using R software. RESULTS: A total of 134 observations of various AI-IMDs across 74 studies assessed the rate of relapse, flare, or exacerbation in AI-IMD patients. Accordingly, the crude overall prevalence of relapse, flare, or exacerbation was 6.28% (95% CI [4.78%; 7.95%], I2 = 97.6%), changing from 6.28% (I2 = 97.6%) to 6.24% (I2 = 65.1%) after removing the outliers. AI-IMD patients administering mRNA, vector-based, and inactive vaccines showed 8.13% ([5.6%; 11.03%], I2 = 98.1%), 0.32% ([0.0%; 4.03%], I2 = 93.5%), and 3.07% ([1.09%; 5.9%], I2 = 96.2%) relapse, flare, or exacerbation, respectively (p-value = 0.0086). In terms of disease category, nephrologic (26.66%) and hematologic (14.12%) disorders had the highest and dermatologic (4.81%) and neurologic (2.62%) disorders exhibited to have the lowest crude prevalence of relapse, flare, or exacerbation (p-value < 0.0001). CONCLUSION: The risk of flare/relapse/exacerbation in AI-IMD patients is found to be minimal, especially with vector-based vaccines. Vaccination against COVID-19 is recommended in this population.

Burden of type 2 diabetes mellitus and its risk factors in North Africa and the Middle East, 1990-2019: findings from the Global Burden of Disease study 2019.

BACKGROUND: The prevalence of Type 2 Diabetes Mellitus (T2DM) in the North Africa and Middle East region is alarmingly high, prompting us to investigate the burden and factors contributing to it through the GBD study. Additionally, there is a lack of knowledge about the epidemiological status of T2DM in this region, so our aim is to provide a comprehensive overview of the burden of T2DM and its associated risk factors. METHODS: Using data from the 2019 Global Burden of Disease Study, we calculated the attributable burden of T2DM for each of the 21 countries in the region for the years 1990 and 2019. This included prevalence, mortality, disability-adjusted life years (DALYs), and risk factors. RESULTS: Between 1990 and 2019, there was a significant increase in the age-standardized incidence (79.6%; 95% Uncertainty Interval: 75.0 to 84.5) and prevalence (85.5%; [80.8 to 90.3]) rates of T2DM per 100,000 populations. The age-standardized mortality rate (1.7%; [-10.4 to 14.9]), DALYs (31.2%; [18.3 to 42.2]), and years lived with disability (YLDs) (82.6%; [77.2 to 88.1]) also increased during this period. Modifiable risk factors, such as high body mass index (56.4%; [42.8 to 69.8]), low physical activity (15.5%; [9.0 to 22.8]), and ambient particulate matter pollution (20.9%; [15.2 to 26.2]), were the main contributors to the number of deaths. CONCLUSION: The burden of T2DM, in terms of mortality, DALYs, and YLDs, continues to rise in the region. The incidence rate of T2DM has increased in many areas. The burden of T2DM attributed to modifiable risk factors continues to grow in most countries. Targeting these modifiable risk factors could effectively reduce the growth and disease burden of T2DM in the region.

Burden of Ischemic Heart Disease and Its Attributable Risk Factors in North Africa and the Middle East, 1990 to 2019: Results From the GBD Study 2019.

BACKGROUND: The North Africa and Middle East (NAME) region has one of the highest burdens of ischemic heart disease (IHD) worldwide. This study reports the contemporary epidemiology of IHD in NAME. METHODS AND RESULTS: We estimated the incidence, prevalence, deaths, years of life lost, years lived with disability, disability-adjusted life years (DALYs), and premature mortality of IHD, and its attributable risk factors in NAME from 1990 to 2019 using the results of the GBD (Global Burden of Disease study 2019). In 2019, 0.8 million lives and 18.0 million DALYs were lost due to IHD in NAME. From 1990 to 2019, the age-standardized DALY rate of IHD significantly decreased by 33.3%, mostly due to the reduction of years of life lost rather than years lived with disability. In 2019, the proportion of premature death attributable to IHD was higher in NAME compared with global measures: 26.8% versus 16.9% for women and 18.4% versus 14.8% for men, respectively. The age-standardized DALY rate of IHD attributed to metabolic risks, behavioral risks, and environmental/occupational risks significantly decreased by 28.7%, 37.8%, and 36.4%, respectively. Dietary risk factors, high systolic blood pressure, and high low-density lipoprotein cholesterol were the top 3 risks contributing to the IHD burden in most countries of NAME in 2019. CONCLUSIONS: In 2019, IHD was the leading cause of death and lost DALYs in NAME, where premature death due to IHD was greater than the global average. Despite the great reduction in the age-standardized DALYs of IHD in NAME from 1990 to 2019, this region still had the second-highest burden of IHD in 2019 globally.

Deep learning for diagnosis of head and neck cancers through radiographic data: a systematic review and meta-analysis.

PURPOSE: This study aims to review deep learning applications for detecting head and neck cancer (HNC) using magnetic resonance imaging (MRI) and radiographic data. METHODS: Through January 2023, a PubMed, Scopus, Embase, Google Scholar, IEEE, and arXiv search were carried out. The inclusion criteria were implementing head and neck medical images (computed tomography (CT), positron emission tomography (PET), MRI, Planar scans, and panoramic X-ray) of human subjects with segmentation, object detection, and classification deep learning models for head and neck cancers. The risk of bias was rated with the quality assessment of diagnostic accuracy studies (QUADAS-2) tool. For the meta-analysis diagnostic odds ratio (DOR) was calculated. Deeks' funnel plot was used to assess publication bias. MIDAS and Metandi packages were used to analyze diagnostic test accuracy in STATA. RESULTS: From 1967 studies, 32 were found eligible after the search and screening procedures. According to the QUADAS-2 tool, 7 included studies had a low risk of bias for all domains. According to the results of all included studies, the accuracy varied from 82.6 to 100%. Additionally, specificity ranged from 66.6 to 90.1%, sensitivity from 74 to 99.68%. Fourteen studies that provided sufficient data were included for meta-analysis. The pooled sensitivity was 90% (95% CI 0.820.94), and the pooled specificity was 92% (CI 95% 0.87-0.96). The DORs were 103 (27-251). Publication bias was not detected based on the p-value of 0.75 in the meta-analysis. CONCLUSION: With a head and neck screening deep learning model, detectable screening processes can be enhanced with high specificity and sensitivity.

Cerebellar Microstructural Abnormalities in Obsessive-Compulsive Disorder (OCD): a Systematic Review of Diffusion Tensor Imaging Studies.

Previous neuroimaging studies have suggested that obsessive-compulsive disorder (OCD) is associated with altered resting-state functional connectivity of the cerebellum. In this study, we aimed to describe the most significant and reproducible microstructural abnormalities and cerebellar changes associated with obsessive-compulsive disorder (OCD) using diffusion tensor imaging (DTI) investigations. PubMed and EMBASE were searched for relevant studies using the PRISMA 2020 protocol. A total of 17 publications were chosen for data synthesis after screening titles and abstracts, full-text examination, and executing the inclusion criteria. The patterns of cerebellar white matter (WM) integrity loss, determined by fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) metrics, varied across studies and symptoms. Changes in fractional anisotropy (FA) values were described in six publications, which were decreased in four and increased in two studies. An increase in diffusivity parameters of the cerebellum (i.e., MD, RD, and AD) in OCD patients was reported in four studies. Alterations of the cerebellar connectivity with other brain areas were also detected in three studies. Heterogenous results were found in studies that investigated cerebellar microstructural abnormalities in correlation with symptom dimension or severity. OCD's complex phenomenology may be characterized by changes in cerebellar WM connectivity across wide networks, as shown by DTI studies on OCD patients in both children and adults. Classification features in machine learning and clinical tools for diagnosing OCD and determining the prognosis of the disorder might both benefit from using cerebellar DTI data.

Brain-derived neurotrophic factor in fibromyalgia: A systematic review and meta-analysis of its role as a potential biomarker.

BACKGROUND: Fibromyalgia (FM) is a form of chronic pain disorder accompanied by several tender points, fatigue, sleeping and mood disturbances, cognitive dysfunction, and memory problems. Brain-derived neurotrophic factor (BDNF) is also a mediator of neurotrophin for many activity-dependent processes in the brain. Despite numerous research studies investigating BDNF in FM, contradictory results have been reported. Thus, we investigated the overall effect shown by studies to find the association between peripheral BDNF concentrations and its gene polymorphisms with FM. METHODS: A systematic search in online international databases, including PubMed, Cochrane Library, Embase, the Web of Science, and Scopus was performed. Relevant studies assessing BDNF levels or gene polymorphism in patients with FM and comparing them with controls were included. Case reports, reviews, and non-English studies were excluded. We conducted the random-effect meta-analysis to estimate the pooled standardized mean difference (SMD) or odds ratio (OR) and 95% confidence interval (CI). RESULTS: Twenty studies were found to be included composed of 1,206 FM patients and 1,027 controls. The meta-analysis of 15 studies indicated that the circulating BDNF levels were significantly higher in FM (SMD 0.72, 95% CI 0.12 to 1.31; p-value = 0.02). However, no difference between the rate of Val/Met carrier status at the rs6265 site was found (p-value = 0.43). Using meta-regression, the sample size and age variables accounted for 4.69% and 6.90% of the observed heterogeneity of BDNF level analysis, respectively. CONCLUSION: Our meta-analysis demonstrated that FM is correlated with increased peripheral BDNF levels. This biomarker's diagnostic and prognostic value should be further investigated in future studies.

The national trend of the burden of Chronic Kidney Disease (CKD) in Iran from 1990 to 2019.

Purpose: Chronic Kidney Disease (CKD) has become the 8th leading cause of death in Iran in 2017, 5 steps up from 1990. This is important as hypertension, diabetes, and chronic glomerulonephritis along with exposure to toxins or heavy metals are the main risk factors for the disease. Despite its heavy burden, there are limited studies on the incidence and prevalence of the disease in the Iranian adult population. The present article studies the burden of CKD at the national level in 2019, and its trend over the past three decades. Methods: In 2019, the Global Burden of Disease (GBD) study provided an annual estimation of the burden of 369 diseases and injuries in 204 countries from 1990 until 2019. The data estimating CKD and related mortality in Iran were collected from the disease registry, survey, and scientific literature. All-ages and age-standardised indices of incidence, prevalence, deaths, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) were extracted for both sexes. Results: Since 1990, the age-standardized incidence (34.7% (95% uncertainty interval 30.8 - 38.8)) and prevalence (19.6% (17.7 - 21.8)) of CKD have risen, while a 21.5% (-28.8 - -15.4) and 18.0% (-35.4 - -10.8) decrease were noted in age-standardized DALYs and deaths rates, respectively. The lowest prevalence was reported in the eastern and western provinces. Conclusion: Current study provides comprehensive knowledge about the CKD burden, suggesting the Iranian healthcare system has been more effective in averting deaths rather than managing morbidities. Multi-sectoral action plans are needed to strengthen preventive and early detection programs in high-risk areas. Supplementary Information: The online version contains supplementary material available at 10.1007/s40200-023-01298-y.

The levels and trends of metabolic risk factors in the elderly population at the national and sub-national scale in Iran from 1990 to 2016.

Purpose: Describing the trends of metabolic risk factors (MRFs) in the elderly population. Methods: We used modeled data from previous comprehensive systematic reviews for MRFs among adults aged ≥ 60 years. Two stages of age-specific Spatio-temporal modeling and Gaussian process regression were used to estimate the mean of MRFs. We used crosswalk modeling to estimate the prevalence of elevated and raised Total cholesterol (TC), overweight/obesity and obesity, hypertension, and diabetes. Estimates were analyzed based on combinations of sex, age, year, and province from 1990 to 2016. Results: Comparing prevalence estimates from 2016 with those of 1990, in the elderly population, the age-standardized prevalence of overweight/obesity, obesity, diabetes, and hypertension increased, conversely, the prevalence of hypercholesteremia decreased. The prevalence of hypertension increased about 141.5% and 129.9% in men and women respectively. The age-standardized prevalence of diabetes increased about 109.5% in females, and 116.0% in males. Prevalence of elevated TC at the national level decreased to 67.4% (64.1-70.4) in women and to 51.1% (47.5-54.8) in men. These findings were almost shown across provinces. In general, the northern and western provinces had the highest prevalence of overweight/obesity in women in 2016. Conclusion: The rising prevalence of most MRFs, as well as the greater prevalence and mean of all MRFs in women, necessitate effective public health policies to reduce the burden of non-communicable diseases and run preventive programs. Supplementary Information: The online version contains supplementary material available at 10.1007/s40200-023-01297-z.

A systematic review and meta-analysis of the global epidemiology of pediatric traumatic spinal cord injuries.

Despite being relatively rare, pediatric traumatic spinal cord injury (TSCI) is a debilitating event with high morbidity and long-term damage and dependency. This study aims to provide insight on the epidemiological characteristics of pediatric TSCI worldwide. The studies were included if they provided data for the pediatric population with the diagnosis of TSCI. Information sources included PubMed, Embase, Web of Science, and Scopus. All databases were searched from 1990 to April 2023. The quality of included studies was evaluated by Joanna Briggs Institute Critical Appraisal Tools. The results of the meta-analysis were presented as forest plots. PROSPERO Registration code: CRD42020189757. We identified 87 studies from 18 developed and 11 developing countries. Of the 87 studies evaluated, 52 studies were considered medium quality, 27 studies were considered high quality, and 8 studies were considered low quality. In developed countries, the proportion of TSCIs occurring in patients aged 0-15 years was 3% (95% CI: 2.2%; 3.9%), while in developing countries, it was 4.5% (95% CI: 2.8%; 6.4%). In developed countries, the pooled incidence of pediatric TSCI was 4.3/millions of children aged 0-15/year (95% CI: 3.1; 6.0/millions children aged 0-15/year) and boys comprised 67% (95% CI: 63%; 70%) of cases. The most prevalent level of injury was cervical (50% [95% CI: 41%; 58%]). The frequency of SCI Without Obvious Radiological Abnormality (SCIWORA) was 35% (95% CI: 18%; 54%) among children 0-17 years. The most common etiology in developed countries was transport injuries (50% [95% CI: 42%; 57%]), while in developing countries falls were the leading cause (31% [95% CI: 20%; 42%]). The most important limitation of our study was the heterogeneity of studies in reporting age subgroups that hindered us from age-specific analyses.   Conclusion: Our study provided accurate estimates for the epidemiology of pediatric TSCI. We observed a higher proportion of pediatric TSCI cases in developing countries compared to developed countries. Furthermore, we identified distinct epidemiological characteristics of pediatric TSCI when compared to adult cases and variations between developing and developed countries. Recognizing these unique features allows for the implementation of cost-effective preventive strategies aimed at reducing the incidence and burden of TSCI in children. What is Known: • Pediatric Traumatic Spinal Cord Injury (TSCI) can have profound physical and social consequences for affected children, their families, and society as a whole. • Epidemiological insights are vital for they provide the data and understanding needed to the identification of vulnerable populations, aiding in the development of targeted prevention strategies and effective resource allocation. What is New: • The estimated incidence of pediatric TSCI in developed countries is 4.3 cases per million children aged 0-15. The proportion of pediatric TSCI cases in relation to all-age TSCI cases is 3% in developed countries and 4.5% in developing countries. • The etiology of TSCI in pediatric cases differs between developing and developed countries. In developed countries, transport injuries are the most prevalent cause of pediatric TSCI, while falls are the least common cause. Conversely, in developing countries, falls are the leading cause of pediatric TSCI.

Diagnostic performance of MRI radiomics for classification of Alzheimer's disease, mild cognitive impairment, and normal subjects: a systematic review and meta-analysis.

BACKGROUND: Alzheimer's disease (AD) is a debilitating neurodegenerative disease. Early diagnosis of AD and its precursor, mild cognitive impairment (MCI), is crucial for timely intervention and management. Radiomics involves extracting quantitative features from medical images and analyzing them using advanced computational algorithms. These characteristics have the potential to serve as biomarkers for disease classification, treatment response prediction, and patient stratification. Of note, Magnetic resonance imaging (MRI) radiomics showed a promising result for diagnosing and classifying AD, and MCI from normal subjects. Thus, we aimed to systematically evaluate the diagnostic performance of the MRI radiomics for this task. METHODS AND MATERIALS: A comprehensive search of the current literature was conducted using relevant keywords in PubMed/MEDLINE, Embase, Scopus, and Web of Science databases from inception to August 5, 2023. Original studies discussing the diagnostic performance of MRI radiomics for the classification of AD, MCI, and normal subjects were included. Method quality was evaluated with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) and the Radiomics Quality Score (RQS) tools. RESULTS: We identified 13 studies that met the inclusion criteria, involving a total of 5448 participants. The overall quality of the included studies was moderate to high. The pooled sensitivity and specificity of MRI radiomics for differentiating AD from normal subjects were 0.92 (95% CI [0.85; 0.96]) and 0.91 (95% CI [0.85; 0.95]), respectively. The pooled sensitivity and specificity of MRI radiomics for differentiating MCI from normal subjects were 0.74 (95% CI [0.60; 0.85]) and 0.79 (95% CI [0.70; 0.86]), respectively. Also, the pooled sensitivity and specificity of MRI radiomics for differentiating AD from MCI were 0.73 (95% CI [0.64; 0.80]) and 0.79 (95% CI [0.64; 0.90]), respectively. CONCLUSION: MRI radiomics has promising diagnostic performance in differentiating AD, MCI, and normal subjects. It can potentially serve as a non-invasive and reliable tool for early diagnosis and classification of AD and MCI.

Radiomics: The New Promise for Differentiating Progression, Recurrence, Pseudoprogression, and Radionecrosis in Glioma and Glioblastoma Multiforme.

Glioma and glioblastoma multiform (GBM) remain among the most debilitating and life-threatening brain tumors. Despite advances in diagnosing approaches, patient follow-up after treatment (surgery and chemoradiation) is still challenging for differentiation between tumor progression/recurrence, pseudoprogression, and radionecrosis. Radiomics emerges as a promising tool in initial diagnosis, grading, and survival prediction in patients with glioma and can help differentiate these post-treatment scenarios. Preliminary published studies are promising about the role of radiomics in post-treatment glioma/GBM. However, this field faces significant challenges, including a lack of evidence-based solid data, scattering publication, heterogeneity of studies, and small sample sizes. The present review explores radiomics's capabilities in following patients with glioma/GBM status post-treatment and to differentiate tumor progression, recurrence, pseudoprogression, and radionecrosis.

A Global, Regional, and National Burden and Quality of Care Index for Schizophrenia: Global Burden of Disease Systematic Analysis 1990-2019.

BACKGROUND AND HYPOTHESIS: Schizophrenia is a mental disorder usually presented in adulthood that affects roughly 0.3 percent of the population. The disease contributes to more than 13 million years lived with disability the global burden of disease. The current study aimed to provide new insights into the quality of care in Schizophrenia via the implementation of the newly introduced quality of care index (QCI) into the existing data. STUDY DESIGN: The data from the global burden of disease database was used for schizophrenia. Two secondary indices were calculated from the available indices and used in a principal component analysis to develop a proxy of QCI for each country. The QCI was then compared between different sociodemographic index (SDI) and ages. To assess the disparity in QCI between the sexes, the gender disparity ratio (GDR) was also calculated and analyzed in different ages and SDIs. STUDY RESULTS: The global QCI proxy score has improved between 1990 and 2019 by roughly 13.5%. Concerning the gender disparity, along with a rise in overall GDR the number of countries having a GDR score of around one has decreased which indicates an increase in gender disparity regarding quality of care of schizophrenia. Bhutan and Singapore had 2 of the highest QCIs in 2019 while also showing GDR scores close to one. CONCLUSIONS: While the overall conditions in the quality of care have improved, significant disparities and differences still exist between different countries, genders, and ages in the quality of care regarding schizophrenia.

A Global, Regional, and National Survey on Burden and Quality of Care Index of Multiple Sclerosis: Global Burden of Disease Systematic Analysis 1990-2019.

BACKGROUND: Multiple sclerosis (MS) is a common neurologic autoimmune disorder. We have used a newly introduced measure, Quality of Care Index (QCI), which is associated with the efficacy of care given to patients suffering from MS. OBJECTIVES: The aims of the study were to report and compare the quality of care given to MS patients in different regions and country. METHODS: Primary measures were retrieved from Global Burden of Disease (GBD) from 1990 to 2019. Secondary measures (mortality-to-incidence ratio, DALY-to-prevalence ratio, prevalence-to-incidence ratio, and YLL-to-YLD ratio) were combined using principal component analysis, to form an essential component (QCI) (0-100 index with higher values representing better condition). RESULTS: In 2019, there were 59,345 (95% UI: 51,818-66,943) new MS incident cases globally. Global QCI of 88.4 was calculated for 2019. At national level, Qatar had the highest quality of care (100) followed by Kuwait (98.5) and Greenland (98.1). The lowest QCI was observed in Kiribati (13.5), Nauru (31.5), and Seychelles (36.3), respectively. Most countries have reached gender equity during the 30 years. Also, QCI was lowest in ages from 55 to 80 in global scale. CONCLUSION: MS QCI is better among those countries of higher socioeconomic status, possibly due to better healthcare access and early detection in these regions. Countries could benefit from adopting the introduced QCI to evaluate the quality of care given to MS patients at national and global level.

Trend in global burden attributable to low bone mineral density in different WHO regions: 2000 and beyond, results from the Global Burden of Disease (GBD) study 2019.

Background: We aimed to document the current state of exposure to low bone mineral density (BMD) and trends in attributable burdens between 2000 and 2019 globally and in different World Health Organization (WHO) regions using the Global Burden of Disease (GBD) study 2019. Methods: We reviewed the sex-region-specific summary exposure value (SEV) of low BMD and the all-ages numbers and age-standardized rates of disability-adjusted life years (DALYs), years lived with disability (YLDs), years of life lost (YLLs), and deaths attributed to low BMD. We compared different WHO regions (Africa, the Eastern Mediterranean Region, Europe, Region of the Americas, Southeast Asia, and Western Pacific), age categories, and sexes according to the estimates of the GBD 2019 report. Results: The global age-standardized SEV of low BMD is estimated to be 20.7% in women and 11.3% in men in 2019. Among the WHO regions, Africa had the highest age-standardized SEV of low BMD in women (28.8% (95% uncertainty interval 22.0-36.3)) and men (16.8% (11.5-23.8)). The lowest SEV was observed in Europe in both women (14.7% (9.9-21.0)) and men (8.0% (4.3-13.4)). An improving trend in the global rate of DALY, death, and YLL was observed during 2000-2019 (-5.7%, -4.7%, and -11.9% change, respectively); however, the absolute numbers increased with the highest increase observed in global YLD (70.9%) and death numbers (67.6%). Southeast Asia Region had the highest age-standardized rates of DALY (303.4 (249.2-357.2)), death (10.6 (8.5-12.3)), YLD (133.5 (96.9-177.3)), and YLL (170.0 (139-197.7)). Conclusions: Overall, the highest-burden attributed to low BMD was observed in the Southeast Asia Region. Knowledge of the SEV of low BMD and the attributed burden can increase the awareness of healthcare decision-makers to adopt appropriate strategies for early screening, and also strategies to prevent falls and fragility fractures and their consequent morbidity and mortality.

Endocan as a marker of endothelial dysfunction in hypertension: a systematic review and meta-analysis.

Hypertension is one of the foremost risk factors for cardiovascular disease and a significant cause of death worldwide. Importantly, endothelial dysfunction (ED) is one of the primary manifestations that may precede the development of hypertension. Endocan is a novel endothelial dysfunction and inflammation biomarker secreted from endothelial cells. Whether endocan may serve as a biomarker of hypertension is currently debated. This systematic review and meta-analysis aimed at linking endocan to ED in hypertensive patients. International databases, including PubMed, Scopus, Embase, and Web of Science, were systematically searched for studies investigating Endocan serum or plasma levels in hypertensive patients and healthy controls. Random effect meta-analysis was performed to calculate the standardized mean difference (SMD) and 95% confidence interval (CI). A total of 20 studies assessing the association between endocan levels and hypertension were included in which 3130 individuals with a mean age of 50.48 ± 8.45 years were assessed. Hypertensive patients presented with higher circulating endocan levels (SMD 0.91, 95% CI 0.44-1.38, p-value < 0.01) compared with healthy controls. Interestingly, our data demonstrated that removing three studies assessing endocan levels in hypertensive patients with different comorbidities or special populations resulted in the same statistically higher endocan levels (SMD 1.16, 95% CI 0.66-1.65, p-value < 0.01). Overall, this systematic review and meta-analysis indicated that in hypertensive patients circulating endocan levels are significantly elevated. Thus, suggesting endocan as an easy-to-use biomarker to detect ED in hypertension. Despite this, more research is warranted to address this potential ability specifically.

Radiological Findings as Predictors of COVID-19 Lung Sequelae: A Systematic Review and Meta-analysis.

RATIONALE AND OBJECTIVES: This systematic review and meta-analysis aimed to investigate the radiological predictors of post-coronavirus disease 19 (COVID-19) pulmonary fibrosis and incomplete absorption of pulmonary lesions. MATERIALS AND METHODS: We systematically searched PubMed, EMBASE, and Web of Science for studies reporting the predictive value of radiological findings in patients with post-COVID-19 lung residuals published through November 11, 2022. The pooled odds ratios with a 95% confidence interval (CI) were assessed. The random-effects model was used due to the heterogeneity of the true effect sizes. RESULTS: We included 11 studies. There were 1777 COVID-19-positive patients, and 1014 (57%) were male. All studies used chest computed tomography (CT) as a radiologic tool. Moreover, chest X-ray (CXR) and lung ultrasound were used in two studies, along with a CT scan. CT severity score (CTSS), Radiographic Assessment of Lung Edema score (RALE), interstitial score, lung ultrasound score (LUS), patchy opacities, abnormal CXR, pleural traction, and subpleural abnormalities were found to be predictors of post-COVID-19 sequels. CTSS and consolidations were the most common predictors among included studies. Pooled analysis revealed that pulmonary residuals in patients with initial consolidation are about four times more likely than in patients without this finding (odds ratio: 3.830; 95% CI: 1.811-8.102, I2: 4.640). CONCLUSION: Radiological findings can predict the long-term pulmonary sequelae of COVID-19 patients. CTSS is an important predictor of lung fibrosis and COVID-19 mortality. Lung fibrosis can be diagnosed and tracked using the LUS. Changes in RALE score during hospitalization can be used as an independent predictor of mortality.

The burden of metabolic risk factors in North Africa and the Middle East, 1990-2019: findings from the Global Burden of Disease Study.

Background: The objective of this study is to investigate the trends of exposure and burden attributable to the four main metabolic risk factors, including high systolic blood pressure (SBP), high fasting plasma glucose (FPG), high body-mass index (BMI), and high low-density lipoproteins cholesterol (LDL) in North Africa and the Middle East from 1990 to 2019. Methods: The data were retrieved from Global Burden of Disease Study 2019. Summary exposure value (SEV) was used for risk factor exposure. Burden attributable to each risk factor was incorporated in the population attributable fraction to estimate the total attributable deaths and disability-adjusted life-years (DALYs). Findings: While age-standardized death rate (ASDR) attributable to high-LDL and high-SBP decreased by 26.5% (18.6-35.2) and 23.4% (15.9-31.5) over 1990-2019, respectively, high-BMI with 5.1% (-9.0-25.9) and high-FPG with 21.4% (7.0-37.4) change, grew in ASDR. Moreover, age-standardized DALY rate attributed to high-LDL and high-SBP declined by 30.2% (20.9-39.0) and 25.2% (16.8-33.9), respectively. The attributable age-standardized DALY rate of high-BMI with 8.3% (-6.5-28.8) and high-FPG with 27.0% (14.3-40.8) increase, had a growing trend. Age-standardized SEVs of high-FPG, high-BMI, high-SBP, and high-LDL increased by 92.4% (82.8-103.3), 76.0% (58.9-99.3), 10.4% (3.8-18.0), and 5.5% (4.3-7.1), respectively. Interpretation: The burden attributed to high-SBP and high-LDL decreased during the 1990-2019 period in the region, while the attributable burden of high-FPG and high-BMI increased. Alarmingly, exposure to all four risk factors increased in the past three decades. There has been significant heterogeneity among the countries in the region regarding the trends of exposure and attributable burden. Urgent action is required at the individual, community, and national levels in terms of introducing effective strategies for prevention and treatment that account for local and socioeconomic factors. Funding: Bill & Melinda Gates Foundation.