Diagnostic test accuracy of machine learning algorithms for the detection intracranial hemorrhage: a systematic review and meta-analysis study.

BACKGROUND: This systematic review and meta-analysis were conducted to objectively evaluate the evidence of machine learning (ML) in the patient diagnosis of Intracranial Hemorrhage (ICH) on computed tomography (CT) scans. METHODS: Until May 2023, systematic searches were conducted in ISI Web of Science, PubMed, Scopus, Cochrane Library, IEEE Xplore Digital Library, CINAHL, Science Direct, PROSPERO, and EMBASE for studies that evaluated the diagnostic precision of ML model-assisted ICH detection. Patients with and without ICH as the target condition who were receiving CT-Scan were eligible for the research, which used ML algorithms based on radiologists' reports as the gold reference standard. For meta-analysis, pooled sensitivities, specificities, and a summary receiver operating characteristics curve (SROC) were used. RESULTS: At last, after screening the title, abstract, and full paper, twenty-six retrospective and three prospective, and two retrospective/prospective studies were included. The overall (Diagnostic Test Accuracy) DTA of retrospective studies with a pooled sensitivity was 0.917 (95% CI 0.88-0.943, I2 = 99%). The pooled specificity was 0.945 (95% CI 0.918-0.964, I2 = 100%). The pooled diagnostic odds ratio (DOR) was 219.47 (95% CI 104.78-459.66, I2 = 100%). These results were significant for the specificity of the different network architecture models (p-value = 0.0289). However, the results for sensitivity (p-value = 0.6417) and DOR (p-value = 0.2187) were not significant. The ResNet algorithm has higher pooled specificity than other algorithms with 0.935 (95% CI 0.854-0.973, I2 = 93%). CONCLUSION: This meta-analysis on DTA of ML algorithms for detecting ICH by assessing non-contrast CT-Scans shows the ML has an acceptable performance in diagnosing ICH. Using ResNet in ICH detection remains promising prediction was improved via training in an Architecture Learning Network (ALN).

Machine learning algorithms for diagnosis of hip bone osteoporosis: a systematic review and meta-analysis study.

BACKGROUND: Osteoporosis is a significant health problem in the skeletal system, associated with bone tissue changes and its strength. Machine Learning (ML), on the other hand, has been accompanied by improvements in recent years and has been in the spotlight. This study is designed to investigate the Diagnostic Test Accuracy (DTA) of ML to detect osteoporosis through the hip dual-energy X-ray absorptiometry (DXA) images. METHODS: The ISI Web of Science, PubMed, Scopus, Cochrane Library, IEEE Xplore Digital Library, CINAHL, Science Direct, PROSPERO, and EMBASE were systematically searched until June 2023 for studies that tested the diagnostic precision of ML model-assisted for predicting an osteoporosis diagnosis. RESULTS: The pooled sensitivity of univariate analysis of seven studies was 0.844 (95% CI 0.791 to 0.885, I2 = 94% for 7 studies). The pooled specificity of univariate analysis was 0.781 (95% CI 0.732 to 0.824, I2 = 98% for 7 studies). The pooled diagnostic odds ratio (DOR) was 18.91 (95% CI 14.22 to 25.14, I2 = 93% for 7 studies). The pooled mean positive likelihood ratio (LR+) and the negative likelihood ratio (LR-) were 3.7 and 0.22, respectively. Also, the summary receiver operating characteristics (sROC) of the bivariate model has an AUC of 0.878. CONCLUSION: Osteoporosis can be diagnosed by ML with acceptable accuracy, and hip fracture prediction was improved via training in an Architecture Learning Network (ALN).

Functional Magnetic Resonance Spectroscopy of Lactate in Alzheimer Disease: A Comprehensive Review of Alzheimer Disease Pathology and the Role of Lactate.

ABSTRACT: Functional 1H magnetic resonance spectroscopy (fMRS) is a derivative of dynamic MRS imaging. This modality links physiologic metabolic responses with available activity and measures absolute or relative concentrations of various metabolites. According to clinical evidence, the mitochondrial glycolysis pathway is disrupted in many nervous system disorders, especially Alzheimer disease, resulting in the activation of anaerobic glycolysis and an increased rate of lactate production. Our study evaluates fMRS with J-editing as a cutting-edge technique to detect lactate in Alzheimer disease. In this modality, functional activation is highlighted by signal subtractions of lipids and macromolecules, which yields a much higher signal-to-noise ratio and enables better detection of trace levels of lactate compared with other modalities. However, until now, clinical evidence is not conclusive regarding the widespread use of this diagnostic method. The complex machinery of cellular and noncellular modulators in lactate metabolism has obscured the potential roles fMRS imaging can have in dementia diagnosis. Recent developments in MRI imaging such as the advent of 7 Tesla machines and new image reconstruction methods, coupled with a renewed interest in the molecular and cellular basis of Alzheimer disease, have reinvigorated the drive to establish new clinical options for the early detection of Alzheimer disease. Based on the latter, lactate has the potential to be investigated as a novel diagnostic and prognostic marker for Alzheimer disease.

Exposure to Low Levels of Radiofrequency Electromagnetic Fields Emitted from Cell-phones as a Promising Treatment of Alzheimer's Disease: A Scoping Review Study.

Background: Alzheimer's disease (AD) is one of the most significant public health concerns and tremendous economic challenges. Studies conducted over the past decades show that exposure to radiofrequency electromagnetic fields (RF-EMFs) may relieve AD symptoms. Objective: To determine if exposure to RF-EMFs emitted by cellphones affect the risk of AD. Material and Methods: In this review, all relevant published articles reporting an association of cell phone use with AD were studied. We systematically searched international datasets to identify relevant studies. Finally, 33 studies were included in the review. Our review discusses the effects of RF-EMFs on the amyloid ß (Aß), oxidative stress, apoptosis, reactive oxygen species (ROS), neuronal death, and astrocyte responses. Moreover, the role of exposure parameters, including the type of exposure, its duration, and specific absorption rate (SAR), are discussed. Results: Progressive factors of AD such as Aß, myelin basic protein (MBP), nicotinamide adenine dinucleotide phosphate (NADPH) oxidase, and neurofilament light polypeptide (NFL) were decreased. While tau protein showed no change, factors affecting brain activity such as glial fibrillary acidic protein (GFAP), mitogen-activated protein kinases (MAPKs), cerebral blood flow (CBF), brain temperature, and neuronal activity were increased. Conclusion: Exposure to low levels of RF-EMFs can reduce the risk of AD by increasing MAPK and GFAP and decreasing MBP. Considering the role of apoptosis in AD and the effect of RF-EMF on the progression of the process, this review indicates the positive effect of these exposures.

The diagnostic accuracy of Artificial Intelligence-Assisted CT imaging in COVID-19 disease: A systematic review and meta-analysis.

Artificial intelligence (AI) systems have become critical in support of decision-making. This systematic review summarizes all the data currently available on the AI-assisted CT-Scan prediction accuracy for COVID-19. The ISI Web of Science, Cochrane Library, PubMed, Scopus, CINAHL, Science Direct, PROSPERO, and EMBASE were systematically searched. We used the revised Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool to assess all included studies' quality and potential bias. A hierarchical receiver-operating characteristic summary (HSROC) curve and a summary receiver operating characteristic (SROC) curve have been implemented. The area under the curve (AUC) was computed to determine the diagnostic accuracy. Finally, 36 studies (a total of 39,246 image data) were selected for inclusion into the final meta-analysis. The pooled sensitivity for AI was 0.90 (95% CI, 0.90-0.91), specificity was 0.91 (95% CI, 0.90-0.92) and the AUC was 0.96 (95% CI, 0.91-0.98). For deep learning (DL) method, the pooled sensitivity was 0.90 (95% CI, 0.90-0.91), specificity was 0.88 (95% CI, 0.87-0.88) and the AUC was 0.96 (95% CI, 0.93-0.97). In case of machine learning (ML), the pooled sensitivity was 0.90 (95% CI, 0.90-0.91), specificity was 0.95 (95% CI, 0.94-0.95) and the AUC was 0.97 (95% CI, 0.96-0.99). AI in COVID-19 patients is useful in identifying symptoms of lung involvement. More prospective real-time trials are required to confirm AI's role for high and quick COVID-19 diagnosis due to the possible selection bias and retrospective existence of currently available studies.

Statin for Migraine Headache: Is It Worthwhile?

Migraine is a severe primary headache disorder that affects about 12% of the population, and it often occurs along with nausea, vomiting, and extreme sensitivity to light and sound. For patients with migraine, beta-blockers, antidepressants, anticonvulsants, are given as the first line of preventive treatment; alternatives include calcium channel blockers. Not only statins prevent the synthesis of cholesterol biosynthesis but also they have a pleiotropic effect such as antiinflammatory effects, antioxidant property, antiproliferative and immunomodulatory effects, the stability of plaque, normalization of sympathetic outflow, and inhibit of platelet aggregation. Here, we should focus on the evidence that works on the effect of the statins on migraine headaches, especially in patients who do not respond to first-line prevention treatments. The hypothesis may show that statins could be effective in the treatment of patients with migraine. Taken together, some epidemiologic, clinical, and experimental evidence suggest that statin may be a novel and promising candidate. For future treatment or prophylaxis of migraine, we hope that the use of this drug as cholesterol and triglycerides(blood lipids) leads to rebate drugs, as well as to reduce migraine headaches episodes agent to enhance the role of this drug in cure or prevent migraine attacks or recurrence, and finally to improve the patient's quality of life.

Environmental concern regarding the effect of humidity and temperature on 2019-nCoV survival: fact or fiction.

The new coronavirus, called 2019-nCoV, is a new type of virus that was first identified in Wuhan, China, in December 2019. Environmental conditions necessary for survival and spread of 2019-nCoV are somewhat transparent but unlike animal coronaviruses. We are poorly aware of their survival in environment and precise factors of their transmission. Countries located in east and west of globe did not have a significant impact on prevalence of disease among communities, and on the other hand, north and south have provided a model for relative prediction of disease outbreaks. The 2019-nCoV can survive for up to 9 days at 25 °C, and if this temperature rises to 30 °C, its lifespan will be shorter. The 2019-nCoV is sensitive to humidity, and lifespan of viruses in 50% humidity is longer than that of 30%. Also, temperature and humidity are important factors influencing the COVID-19 mortality rate and may facilitate 2019-nCoV transmission. Thus, considering the available and recent evidence, it seems that low temperatures, as well as dry and unventilated air, may affect stability and transmissibility of 2019-nCoV.

Global View of HIV Prevalence in Prisons: A Systematic Review and Meta-Analysis.

BACKGROUND: We aimed to estimate the global prevalence of HIV, as well as cross-countries comparison in people who are in prison. METHODS: We systematically assessed published studies reporting HIV prevalence among prisoners in the world. We searched international datasets banks, including PubMed, SCOPUS, Cumulative Index to Nursing and ISI web of science along with local databases and included original articles reporting data on the prevalence of HIV from 1980 to 2017. RESULTS: We included 72 studies that reported HIV prevalence for 2,275,930 adult male and female prisoners. The pooled estimate of HIV prevalence was 3.4% (95% CI 3.2%-3.6%); however, the prevalence of HIV across individual studies varied considerably (ranging from 0 in Bosnia and Herzegovina to More than 20% in Iran, Zambia, Spain) and statistical heterogeneity was substantial (I2=0.99, Q=121; P<0.0001). The prevalence of HIV among prisoners in the continents Asia, Africa, North America and Europe was estimated as 3.0% (95% CI 3.3%-4.3 %), 6% (95% CI -0.0%-2.0%), 4% (95% CI 3.0%-4.0%), 5.0% (95% CI 0.0%-11%), respectively. CONCLUSION: Protecting prisoners' health protects general public health. Successful HIV preventive measures in prisons include provision of HIV education and information; clean needles and syringes; drug treatment; and condoms. Governments have a moral and ethical obligation to prevent the spread of HIV/AIDS in prisons and to provide compassionate care, treatment and support for those infected.

The possible global hazard of cell phone radiation on thyroid cells and hormones: a systematic review of evidences.

The aim of this review was to investigate the effects of possible harmful waves from either cell phone use or being within the range of the cell phone from 450 to 3800 MHz on the thyroid cells and hormones. Eight electronic datasets were systematically searched using MeSH terms, including "cell phone," "mobile phone," "GSM," "radio frequency," "smartphone," "triiodothyronine," "thyroxin," "thyroid-stimulating hormone," "T3," "T4," "TSH," and "morphological" and all possible combinations, to identify relevant studies published up to Dec 2018. We also manually searched the reference lists of potentially selected studies to identify further relevant publications. About 161 relevant studies were initially found. After screening titles and abstracts, 139 studies were excluded, and finally 22 studies (comprising 7182 cases) were included in the qualitative synthesis. Of the 22 included studies, 11 studies reported changes in T3 and T4 levels (six reported a decrease in T3 levels and one reported increase in it); moreover, five found decreased T4 levels and two studies an increased level. In other 10 studies, TSH alteration was reported. Of these, two studies reported a decrease in TSH level and one reported an increase in the hormone levels, while in the remaining studies non-significant changes were reported. Finally, seven studies examined histological changes in the thyroid gland follicles and showed that the volume of these cells was reduced. Based on the evidence discussed above, the reduction in diameter of thyroid follicles is potentially linked with cell phone radiation. Exposure may negatively influence the iodine uptake in the thyroid gland or increases temperature effect on the thyroid gland. However, further research are needed in order to show that the level of TSH and thyroid hormone suppression by microwave.

Sports Injuries: Diagnosis, Prevention, Stem Cell Therapy, and Medical Sport Strategy.

Sports injuries diagnosis, prevention, and treatment are the most important issues of sports medicine. Fortunately, sports injuries are often treated effectively, and people with damage recover and return to the sport in a satisfactory condition. Meanwhile, many sports injuries and complications can be prevented. In general, sports injuries include acute or chronic injuries. Given increasing in popularity, sports medicine doctors use stem cells to treat a wide variety of sports injuries, including damage to tendons, ligaments, muscles, and cartilage. Stem cell therapy to an injured area could be done through direct surgical application, stem-cell-bearing sutures, and injection. Stem cell therapy holds potential for repair and functional plasticity following sports injuries compared to traditional methods; however, the mechanism of stem cell therapy for sports injuries remains largely unknown. Medical imaging technologies provide the hope to ample the knowledge concerning basic stem cell biology in real time when transplanted into sport-induced damaged organs. Using stem cell treatment might restore continuity and regeneration and promote growth back the organ targets. Besides, using a noninvasive medical imaging method would have the long-time monitoring advantage to the stem cells transplanting individual. The multimodality imaging technique allows for studying acute pathological events following sports injuries; therefore, the use of imaging techniques in medicine permits the straight examination of dynamic regenerative events of specific stem cells following a sports injury in people.

Which came first, the risk of migraine or the risk of asthma? A systematic review.

OBJECTIVES: We conducted this review to systematically assess the association and risk of the migraine in the patient with asthma and vice versa. METHODS: We systematically searched publishes articles indexed in PubMed, Scopus, Cochrane library, PsycINFO, CINAHL, ISI Web of Science, Science Direct from inception, and Embase databases until June 2017. The quality assessment of the involved studies was done using the Newcastle-Ottawa Scale (NOS). RESULTS: Eight studies with 389,573 participants were reviewed and selected for data extraction. Among the selected studies, 5 were reported the association between migraine with asthma risk, and the rest three studies reported the risk of asthma in patient with migraine compared to non-moraine individuals. Odds ratio (OR) of migraine for patient with asthma as compared with non-asthmatic individuals was 1.62 (95% CI 1.43-1.82). Data pooling using a random-effect model showed that migraine was associated with a significant increased risk of asthma (relative risk (RR): 1.56; 95% CI: 1.51-1.60; p < .00001). Besides, sub-group and sensitivity analyses supported the positive association between asthma and migraine, and risk of asthma in migraine patients. CONCLUSION: Now it is unknown if control of the asthma will impact the severity of migraines or vice versa, but it is necessary to perform more research to further explain the mechanisms through which asthma increases the frequency of migraine or vice versa. If two conditions linked, once an individual undergo better control of asthma symptoms, might the excruciating migraine ease, too.

A Systematic Review and Meta-Analysis of the Prevalence of Methamphetamine Abuse in Iranian High School Students.

Background and Aim: Abuse of drugs such as methamphetamine is one of the most important problems in high-school children and adolescents according to the World Health Organization (WHO), which has mentioned it as a concerning event in the world. Therefore, the purpose of this study was to estimate the prevalence of methamphetamine abuse in Iranian students using the meta-analysis method on studies conducted in Iran. Materials and Methods: To select the studies, a systematic search was performed on leading databases, including ISI web of science, PubMed, Scopus, Embase, PsycINFO and PROSPERO with no language limits from their inception to 31 Jan 2018. Furthermore, local databases, including SID, Magiran, and IRANDOC were searched systematically using both Persian and English languages from their inception to 31 Jan 2018. Results: We found a total of 828 potentially relevant studies, of which 30 met our criteria, and 7 articles (7452 students, 3063 females and 4389 males) were included. The pooled prevalence of methamphetamine use in Iranian students was 0.016% (95% CI: 0.06-0.041, P=0.00). The heterogeneity was low (I2 =44.41, d.f = 6), which shows that about 94.41 of the total observed variance was true variance between the studies. Conclusion: Although the prevalence of methamphetamine in high-school students is lower than in other drugs, a growing pattern in Iranian high-school students in recent years is a serious warning to authorities and families. Increasing families and students' knowledge about the harmful effects of this drug can be an effective approach to reducing its prevalence in young people, especially high-school students.

Stem cell therapy for patients with diabetes: a systematic review and meta-analysis of metabolomics-based risks and benefits.

BACKGROUND: There is a general agreement that to ensure promising results of stem cell therapy in patients with diabetes, one must first understand its risks and benefits; thus, if the risk is sufficiently low along with many benefits, it can lead to developing a novel therapeutic approach based on sound science. METHODS: A systematic review and meta-analysis was performed using all available clinical trials to determine the benefits and risks associated with stem cell therapy in patients with diabetes (both T1DM and T2DM). An extensive search was conducted across several databases using all MeSH words regarding stem cell therapy and diabetes. RESULTS: In T2DM, a large body of research has shown that stem cell therapy has improved the insulin daily requirement and glycosylated hemoglobin (HbA1C) levels, and also has a positive effect on these variables, but has a negative impact on c-peptide. Hence, in T1DM, stem cell therapy improves c-peptide and HbA1C levels and has a positive effect on these variables, but has a negative impact on insulin daily requirement. CONCLUSIONS: A total of 639 cells have the ability to self-renew and differentiate into a variety of cells, including blood, heart, nervous and cartilage cells. Paradoxically, it has been stated that these cells also have the potential to form cancer cells. These possible risks warrant caution by both medical specialists and patients while proceeding with the treatment; thus, it is critically crucial to conduct further research on stem cell therapy but with first considering their risk and benefits.

Use of a problem-based learning teaching model for undergraduate medical and nursing education: a systematic review and meta-analysis.

OBJECTIVES: The aim of this systematic review and meta-analysis was to evaluate the problem-based learning (PBL) method as an alternative to conventional educational methods in Iranian undergraduate medical courses. MATERIALS AND METHODS: We systematically searched international datasets banks, including PubMed, Scopus, and Embase, and internal resources of banks, including MagirIran, IranMedex, IranDoc, and Scientific Information Database (SID), using appropriate search terms, such as "PBL", "problem-based learning", "based on problems", "active learning", and" learner centered", to identify PBL studies, and these were combined with other key terms such as "medical", "undergraduate", "Iranian", "Islamic Republic of Iran", "I.R. of Iran", and "Iran". The search included the period from 1980 to 2016 with no language limits. RESULTS: Overall, a total of 1,057 relevant studies were initially found, of which 21 studies were included in the systematic review and meta-analysis. Of the 21 studies, 12 (57.14%) had a high methodological quality. Considering the pooled effect size data, there was a significant difference in the scores (standardized mean difference [SMD]=0.80, 95% CI [0.52, 1.08], P<0.000) in favor of PBL, compared with the lecture-based method. Subgroup analysis revealed that using PBL alone is more favorable compared to using a mixed model with other learning methods such as lecture-based learning (LBL). CONCLUSION: The results of this systematic review showed that using PBL may have a positive effect on the academic achievement of undergraduate medical courses. The results suggest that teachers and medical education decision makers give more attention on using this method for effective and proper training.