Z Shateri Amiri , Ss Hoseini, L Jarahi,
Volume 16, Issue 2 (Vol 16, No.2 2020)
Abstract
Background and Objectives: Clinical trials are used extensively in the compilation of systematic review studies and clinical guidelines. Critical appraisal of articles is a part of systematic review writing and also effective in citation. This study aimed to evaluate quality of randomized clinical trial articles of Mashhad University of Medical Sciences with consideration report of randomized, blindness, and allocation concealment methods in them.
Methods: In this study, all randomized clinical trials with Mashhad University of Medical Sciences affiliation indexed in PubMed by 2018 were evaluated.
Results: Of 257 eligible articles, dentistry (n=44 , 17.1%) , obstetrics and gynecology (n=28 , 10.9%) and internal medicine (n=23 , 8.9%) had the highest relative frequency of published randomized clinical trial articles. Eithy-three articles (32.3%) reported the randomization method and most of them (86.9%) used simple randomization. Blinding was done in 138 papers (53.7%) with double blinding being the most common (70.2%). Only three articles (1.2%) reported allocation concealment.
Conclusion: The report of "random allocation and randomization" in articles was far less than acceptable. It may seem that there may be different biases in the methodology. Upholding the principles of scientific writing and avoiding errors and biases increase the validity of the scientific articles and citation, which is one of the criteria of the scientific ranking of top universities.
Mohammad Khajedaluee, Maliheh Dadgar Moghaddam, Amir-Reza Khajedaluee, Hiva Sharebiani, Hamidreza Bahrami Taghanaki, Maryam Ziadi Lotfabadi, Zeinab Shateri Amiri,
Volume 18, Issue 4 (Vol.18, No.4, Winter 2023)
Abstract
Background and Objectives: Cardiovascular diseases are the leading cause of adult mortality in many developing countries. This study aims to compare the estimation of the ten-year relative risk of cardiovascular events using the Framingham criteria with a native model.
Methods: This population-based cross-sectional study was conducted in 2014, focusing on the adult population (≥16 years) of Mashhad. Stratified random cluster sampling was employed to gather participants' information based on Framingham's criteria. Data mining, utilizing the decision tree algorithm design, was evaluated using Rapidminer v5.3 software and the cross-validation method.
Results: Out of 2978 individuals, 1930 (64.9%) were women and 1041 (35.1%) were men, with a mean age of 43.5±14.7. Applying the Framingham criteria, the ten-year risk levels of cardiovascular disease were estimated as follows: 77.8% at a low-risk level, 13.4% at a medium-risk level, and 8.8% at a high-risk level.
Regarding data mining, model number (1) achieved an accuracy of 79.56%, indicating that the predicted risk levels using the Framingham algorithm matched the observed values at 95.24% for the low-risk level, 90.8% for the medium-risk level, and 33.13% for the high-risk level. As for model number (2), an accuracy of 82.78% was obtained, with the matching values being 98.20% for the low-risk level, 0.42% for the medium-risk level, and 53.01% for the high-risk level.
Conclusion: The Framingham criteria demonstrate limited effectiveness in predicting medium and high-risk levels in the Mashhad population. According to the local model, smoking and high blood pressure in adulthood are the most significant factors in predicting the risk of cardiovascular diseases in young individuals.
Maliheh Dadgar Moghadam, Majid Khadem Rezaian, Zainab Shateri Amiri,
Volume 18, Issue 4 (Vol.18, No.4, Winter 2023)
Abstract
Background and Objectives: The novel and rapidly spreading nature of COVID-19 surpasses the capacity and capabilities of the healthcare system, necessitating comprehensive management. This study aims to explore the role and relationship of social determinants of health with the ultimate outcome of patients.
Methods: In this cross-sectional study, the information of COVID-19 patients within the coverage area of Mashhad University of Medical Sciences was examined from three sources (outpatient or inpatient) between March 2018 and March 2019, utilizing the census method. The logistic regression model was employed to assess the predictability of social determinants of health.
Results: Out of 182,602 patients, 100,407 (55%) were men, and 82,195 (45%) were women. Logistic regression analysis revealed that the odds of mortality due to corona infection increased by 1.075 (1.073-1.077) times for each year of age. Additionally, the odds were 2.37 (2.06-2.73) times higher in men compared to women and displayed an inverse relationship with educational level (PV<0.001). Job status did not demonstrate a significant effect. The presence of diabetes (OR=1.28, 95% CI: 1.19-1.38), underlying diseases (OR=1.16, 95% CI: 1.09-1.22), and immune system weakness (OR=7.94, 95% CI: 6.44-9.80) were associated with an increased likelihood of death. Conversely, pregnancy (OR=0.90, 95% CI: 0.57-1.42) and high blood pressure (OR=0.95, 95% CI: 0.89-1.02) exhibited no significant association.
Conclusion: Considering the relationship between social determinants of health and COVID-19 mortality, it is recommended that policymakers involve sectors outside the healthcare system in addressing health matters.
