2023 CiteScore: 0.8
pISSN: 2383-4196
eISSN: 2383-420X
Editor-in-Chief:
Hojjat Zeraati, PhD.
Current Issue
Vol 11 No 1 (2025): .
Articles
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Background: Continuous glucose monitoring (CGM) has become an essential tool in diabetes management as it provides real-time information on blood glucose levels. Present study summarizes current evidence on the clinical outcomes, glycemic control, and patient-reported outcomes of CGM compared to non-CGM strategies among the included studies with diabetes.
Methods: The systematic review was performed following the PRISMA guidelines. PubMed, Google Scholar, JAMA Network, and SpringerLink, etc. were searched for relevant research published after 2010. Included research assessed the use of CGM with non-CGM treatments, such as traditional therapy or self-monitoring of blood glucose (SMBG) for diabetics. The study's design, participant characteristics, intervention specifics, glycemic outcomes (i.e. HbA1c and duration in range), and quality of life were all included in the extracted data.
Results: Twelve studies (1916 subjects) based on randomized controlled trials and satisfied the inclusion criteria. Findings show that using a CGM is linked to notable improvements in glycemic control, as evidenced by falls in HbA1c readings when compared to non-CGM approaches. The studies had adequate heterogeneity: I² = 32%, Chi² = 16.08, and Tau² = 0.00. An impact was found in the overall effect using a random effects model, with weighted mean difference (WMD) = 0.43; CI: 0.34-0.52 (p< 0.001). To evaluate the cause of heterogeneity and publication bias, meta-regression and Egger's regression were used.
Conclusion: This study highlights the potential of CGM devices to enhance diabetes management by improving glycemic control and patient outcomes. Despite several obstacles, CGM shows promise as a substitute for conventional diabetes treatment approaches. Future studies should address these issues and assess the long-term advantages of using a CGM in more detail. This study is registered in PROSPERO (Registration ID: CRD42024518635).
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Purpose: Brain tumors are among the fatal cancers and cause the death of many people annually. Early diagnosis of a brain tumor can help save the patient’s life.
Method: We have collected a dataset consisting of 314 brain MRI images in all planes taken by giving a contrast medium with the dimension of 800*512, which offers the highest resolution. First, skull stripping has been implemented to separate the brain from other parts in the images. Next, we have annotated the tumors in the images under the supervision of experienced radiologists to create ground truth. To determine the most effective model versions for all three loss functions, hyperparameter tuning was performed. Following the comparison, the study further evaluates the effectiveness of two loss functions, Binary Cross-Entropy (BCE) and Focal loss, specifically in handling tumor regions within the dataset.
Result: The two proposed loss functions were evaluated using 5-fold cross-validation, and the average precision, recall, and f1 were 76.16%, 71.9%, and 74.52 for BCE loss and 82.92%, 79.32%, and 81% for the Focal loss on the test data, respectively. Moreover, the accuracy for BCE loss was 99.03% and 99.44% for the Focal loss.
Conclusion: We recommend using BCE loss cautiously in classification tasks without data imbalance and emphasize the adoption of Focal loss for more accurate and reliable results in brain tumor segmentation.
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Background
Estimating prevalence in cause-effect relationships where the mediator variables are assumed to be latent is not usually easy. However, the use of proper indicators and statistical model can make the measurement and use of such constructs easy.
Methods
Structural Equation Modeling makes it possible to analyze simultaneously both the relationship between the latent variable and the links between the latent variable and their indicators. The 2018 Kenya AIDS Indicator Survey data was used to validate the model developed. The maximum likelihood was used to estimate the model parameters. The findings of the study were, there is a relationship between education attainment and knowledge /awareness of HIV/AIDS.
Results
The results further shows that education levels are not associated with HIV prevalence after controlling for a number of socio-demographic characteristics and behavioral factors.
Conclusion
These findings can inform policy makers in formulation of appropriate HIV/AIDS management (policies) and intervention strategies aimed at reducing HIV/AIDS prevalence that has remained a challenge in many developing countries.
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Background: More than 85% of premature deaths from major non-communicable diseases (NCDs) occur in low- and middle-income countries.
Objectives: This study aimed to investigate trends of premature deaths (30-70 years) due to the non-communicable diseases in Iran, from 2012 to 2020.
Methods: Data on causes of death from 2012 to 2020 was extracted from the death registration system of the Ministry of Health and Medical Education.
To calculate completeness of death registration system, we used the new method presented by Adair and Lopez, which is based on the fixed effects model for predicting completeness of data from death registration system.
Results: Non-communicable diseases from 2012 to 2020 accounted for percentages of all deaths: 70.47, 69.13, 72.19, 70.55, 68.98, 69.44, 69.17, 67.94 and 54.15 percent of all deaths, respectively.
Premature deaths due to these diseases during the years of this study ranged from 50% to 71% of premature deaths.
The probability of premature deaths due to these diseases in these years was as follows: 17.35, 16.65, 16.61, 15.60, 14.95, 15.15, 15.25, 16.63 and 15.81 percent, respectively.
Conclusions: With the knowledge that the most common cause of premature death in women is non-communicable disease and the most common cause in the general population is cardiovascular disease, evidence-based planning and policy-making should be done to achieve further reductions in premature mortality, with an approach to be adopted in a unified way by focusing on modifiable risk factors in different sectors and disciplines in Iran.
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Introduction: Variable selection has become an increasingly important topic in biomedical research, as evidenced by its modern applications in high-throughput genomic data analysis. Specifically, interest in analyzing high-throughput data to link gene expression profiles to the timing of an event such as death has grown, with the goal of evaluating the influence of biomedical variables on survival outcomes. One common special case in survival data is competing risks data where identifying a small subset of gene expression profiles related to cumulative incidence function (CIF) is crucial.
Methods: Several methods for directly modeling CIF are proposed, involving modeling the subdistribution hazard function of the interested cause or event using the proportional hazards approach. We proposed a regularized method for variable selection in the additive subdistribution hazards model by combining the nonconcave penalized likelihood approach and the pseudoscore method. We also conducted Monte Carlo simulations to evaluate the performance of our proposed method. In addition, a publicly available dataset was used to illustrate the proposed model.
Results: Results from simulation studies were presented together with an application to genomic data when the endpoint is progression-free survival and the objective is to identify genes related to CIF of bladder cancer in the presence of competing events. Five genes in common (CDC20, PLEK, FCN2, IGF1R and DCTD) were identified by the proposed penalized additive subdistribution hazards model with different penalties.
Conclusions: Monte Carlo simulation studies results suggested that the results of all penalties were comparable in terms of sensitivity and specificity, whereas those based on Adaptive Elastic Net (AENET) and Adaptive Least Absolute Shrinkage and Selection Operator (ALASSO) penalties tended to perform better in terms of estimation accuracy.
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Background: The current article primarily aims to ascertain the impact of any risk arising from the technology of satellite media in this era, whatsoever, specially those connected to the internet (including Cyborgs, Metaverse and AI), on the individual health (mental, attitudes and behaviors that even may cause physical impacts such as violence, etc.), families, the social health and as a whole, humans and human dignity. Consequently, some actions should be taken to deal with these risks to identify, analyze and treat them with the aim of taking the identified risks under control.
Objective: In order to prevent any kind of direct and/or indirect negative impacts of satellite media on the individual health, families, the social health and as a whole humans and human dignity, the objective of this article was to display a new way of assessing the related risks and developing a comparative analysis model. The process of developing a comparative analysis and study, by identifying, analyzing and treating risks to assist managing all of them and then reaching to a result for Iran.
Methods: Basically, the research done was a comparative study; therefore, in nature, it called for a qualitative research. So, a descriptive research along with case studies as well as an analytical study were applied too. Distributing questionnaires to get to the final result led to an exploratory research and consequently applying the Mann-Whitney U Test using the SPSS statistics concluded to a quantitative research. The final result can be applied by the related authorities to protect the individual health, families and the social health in any society, and as a whole humans and human dignity. Therefore this research can be considered as an applied research too.
Findings: By comparing five countries which were randomly selected from almost each continent along with Iran, focused on Tehran as a metropolitan counting different ethnic groups, risks of satellite media which have impacts on any society understudy and which are in common among all those countries, were identified by risk management approach. Then the comparative and analytical studies and appraisals as well as statistical processes revealed that Iran’s current media approach and its performance towards the whole society are quite different from the other five countries that Iran was compared to.
Conclusions: A new technical way to approach risks of satellite media to control them for preventing any kind of satellite media risks that impacts on the individual health, families, the social health, and as a whole humans and human dignity, plus a new result for Iran obtained. As an applied research the new result showed that an immediate action is required to regulate media standards for the whole society to protect the individual health, families, the social health and as a whole humans and human dignity and also to modify the current situation of Iran’s media approach towards them.
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Background: Sleep pattern is a vital part of healthy lifestyle, with deviations from the recommended 7-9 hours associated to negative outcomes. Limited studies have investigated the connection between sleep patterns and mental health in underserved urban communities. This study explores the association between sleep health metrics, such as sleep duration and mental health among the population residing in Southern Tehran.
Methods: This population-based cross-sectional study has utilized data from 1,311 participants of the "Study Protocol and Lessons from Iran for the Integrated and Repeated Public Health Surveillance System (IRPHS) " telephone survey participants to evaluate amount of sleep duration (<7h and ≥9h) and sleep quality, as well as their associations with anxiety, depression, suicidal ideation, and related sociodemographic factors.
Result: The mean (standard deviation) age of participants was 40.4 ± 13.4 years, and 60.4% of the sample was female. Among our participants 15.0% had insufficient sleep (<7h) and 18.5% had long sleep duration (≥9h). Sex, socioeconomic status, and tobacco use were associated with sleep duration (p < 0.05). Moderate and high anxiety, moderate depression, and high suicidal ideation were associated with long sleep (p < 0.05).
Conclusion: In southern Tehran population, prevalence of both insufficient and long sleep duration is high. Poor sleep quality and oversleeping can happen due to underlying depression and anxiety, and targeting improvement of mental health can increase sleep hygiene. The findings provide insights for prevention strategies tailored to the study.
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Bachground :While the main advantage of the confidence interval is that it enables more precise evaluations when the risk for the outcome of interest is related to the cluster size, the predicted confidence interval width demonstrates the degree of variability in the future data instead.
Methods : We present a novel algorithm to create an intra‐cluster robust neighborhood confidence interval and width for each cluster to rank the widths from the narrowest to the widest width to determine each cluster's predicted variability and evaluate the corresponding observed values. An example was developed that assesses the finite‐sample behavior of this new method.
Results : Robust neighborhood intra-cluster predicted CI width was obtained for interpreting results of binary unequal sizes data. Narrow confidence intervals CI bounds suggest the results are not subjected to a high degree of random variations. Conclusions: Intra-cluster predicted robust neighborhood CI and its corresponding width is a useful instrument in binary outcome unequal cluster sizes data as a method of analysis.
