Background Osteoporosis is one of the most common bone system diseases that is associated with an increased risk of bone fractures and causes many complications for patients. With age, the prevalence of this disease increases so that it has become a serious problem among the elders. In this study, the prevalence of osteoporosis among elders around the world is examined to gain an understanding of its prevalence pattern. Methods In this systematic review and meta-analysis, articles that have focused on prevalence of osteoporosis in the world’s elders were searched with these key words, such as Prevalence, Osteoporosis, Elders, Older adult in the Science Direct, Embase, Scopus, PubMed, Web of Science (WoS) databases and Google Scholar search engine, and extracted without time limit until March 2020 and transferred to information management software (EndNote). Then, duplicate studies were eliminated and the remaining studies were evaluated in terms of screening, competence and qualitative evaluation based on inclusion and exclusion criteria. Data analysis was performed with Comprehensive Meta-Analysis software (Version 2) and Begg and Mazumdar test was used to check the publication bias and I2 test was used to check the heterogeneity. Results In a review of 40 studies (31 studies related to Asia, 5 studies related to Europe and 4 studies related to America) with a total sample size of 79,127 people, the prevalence of osteoporosis in the elders of the world; 21.7% (95% confidence interval: 18.8–25%) and the overall prevalence of osteoporosis in older men and women in the world, 35.3% (95% confidence interval: 27.9–43.4%), 12.5% (95% confidence interval: 9.3–16.7%) was reported. Also, the highest prevalence of osteoporosis in the elders was reported in Asia with; 24.3% (95% confidence interval: 20.9–28.1%). Conclusion The results of the present study showed that the prevalence of osteoporosis in the elders and especially elders' women is very high. Osteoporosis was once thought to be an inseparable part of elders’ lives. Nowadays, Osteoporosis can be prevented due to significant scientific advances in its causes, diagnosis, and treatment. Regarding the growing number of elderly people in the world, it is necessary for health policy-makers to think of measures to prevent and treat osteoporosis among the elders.

Background A variety of mutations in the largest human gene, dystrophin, cause a spectrum from mild to severe dystrophin-associated muscular dystrophies. Duchenne (DMD) and Becker (BMD) muscular dystrophies are located at the severe end of the spectrum that primarily affects skeletal muscle. Progressive muscle weakness in these purely genetic disorders encourages families with a positive history for genetic counseling to prevent a recurrence, which requires an accurate prevalence of the disorder. Here, we provide a systematic review and meta-analysis to determine the prevalence of DMD and BMD worldwide. Method The current systematic review and meta-analysis was carried out using Cochrane seven-step procedure. After determining the research question and inclusion and exclusion criteria, the MagIran, SID, ScienceDirect, WoS, ProQuest, Medline (PubMed), Embase, Cochrane, Scopus, and Google Scholar databases were searched to find relevant studies using defined keywords and all possible keyword combinations using the AND and OR, with no time limit until 2021. The heterogeneity of studies was calculated using the I2 test, and the publication bias was investigated using the Begg and Mazumdar rank correlation test. Statistical analysis of data was performed using Comprehensive Meta-Analysis software (version 2). Results A total of 25 articles involving 901,598,055 people were included. The global prevalence of muscular dystrophy was estimated at 3.6 per 100,000 people (95 CI 2.8–4.5 per 100,000 people), the largest prevalence in the Americans at 5.1 per 100,000 people (95 CI 3.4–7.8 per 100,000 people). According to the subgroup analysis, the prevalence of DMD and BMD was estimated at 4.8 per 100,000 people (95 CI 3.6–6.3 per 100,000 people) and 1.6 per 100,000 people (95 CI 1.1–2.4 per 100,000 people), respectively. Conclusion Knowing the precise prevalence of a genetic disorder helps to more accurately predict the likelihood of preventing its occurrence in families. The global prevalence of DMD and BMD was very high, indicating the urgent need for more attention to prenatal screening and genetic counseling for families with a positive history.

COVID-19 affects several human genes, each with its own p-value. The combination of drugs associated with these genes with small p-values may lead to an estimation of the combined p-value between COVID-19 and some drug combinations, thereby increasing the effectiveness of these combinations in defeating the disease. Based on human genes, we introduced a new machine learning method that offers an effective drug combination with low combined p-values between them and COVID-19. This study follows an improved approach to systematic reviews, called the Systematic Review and Artificial Intelligence Network Meta-Analysis (RAIN), registered within PROSPERO (CRD42021256797), in which, the PRISMA criterion is still considered. Drugs used in the treatment of COVID-19 were searched in the databases of ScienceDirect, Web of Science (WoS), ProQuest, Embase, Medline (PubMed), and Scopus. In addition, using artificial intelligence and the measurement of the p-value between human genes affected by COVID-19 and drugs that have been suggested by clinical experts, and reported within the identified research papers, suitable drug combinations are proposed for the treatment of COVID-19. During the systematic review process, 39 studies were selected. Our analysis shows that most of the reported drugs, such as azithromycin and hydroxyl-chloroquine on their own, do not have much of an effect on the recovery of COVID-19 patients. Based on the result of the new artificial intelligence, on the other hand, at a significance level of less than 0.05, the combination of the two drugs therapeutic corticosteroid + camostat with a significance level of 0.02, remdesivir + azithromycin with a significance level of 0.03, and interleukin 1 receptor antagonist protein + camostat with a significance level 0.02 are considered far more effective for the treatment of COVID-19 and are therefore recommended. Additionally, at a significance level of less than 0.01, the combination of interleukin 1 receptor antagonist protein + camostat + azithromycin + tocilizumab + oseltamivir with a significance level of 0.006, and the combination of interleukin 1 receptor antagonist protein + camostat + chloroquine + favipiravir + tocilizumab7 with corticosteroid + camostat + oseltamivir + remdesivir + tocilizumab at a significant level of 0.009 are effective in the treatment of patients with COVID-19 and are also recommended. The results of this study provide sets of effective drug combinations for the treatment of patients with COVID-19. In addition, the new artificial intelligence used in the RAIN method could provide a forward-looking approach to clinical trial studies, which could also be used effectively in the treatment of diseases such as cancer.

No abstract

Background Artificial Intelligence (AI) as a suite of technologies can complement systematic review and meta-analysis studies and answer questions that cannot be typically answered using the traditional review protocols and reporting methods. The purpose of this protocol is to introduce a new protocol to complete systematic review and meta-analysis studies. Methods In this work, systematic review, meta-analysis, and meta-analysis network based on selected AI technique, and for p values less than 0.05 are followed, with a view to responding to questions and challenges that the global population are facing in light of the COVID-19 pandemic. Discussion Finally, it is expected that conducting reviews by following the proposed protocol can provide suitable answers to some of the research questions raised due to COVID-19.