Application of latent class modelling in students� life skills: The case of Iran university of medical sciences

Background: Many people facing life difficulties are unable to sort out these problems. Objectives: A study was designed to determine students� life skills at the Iran University of Medical Sciences (IUMS). Methods: This cross-sectional study was conducted at IUMS in 2016-17 with a sample of 342 students. A questionnaire was used with multi-choice questions from poor to high skills. Latent class models were applied for data analysis using Mplus. Bayesian information criterion (BIC) and Bootstrap likelihood ratio tests were used to determine the number of classes. Results: A two-class model had the best fit since the BIC had the lowest amount. Almost 76 and 24 of the cases entered the high and moderate skill classes of the model, respectively. The level of education (LOE) was the only significant variable (P = 0.004) for classifying the students. Conclusions: The model could predict the probability of high life skilled students. Also, LOE had a high impact on the probability of high life skills. © 2020, Author(s)

Identifying developmental trajectories of worldwide road traffic accident death rates using a latent growth mixture modeling approach

Road Traffic Accidents (RTA) are a major worldwide public health problem. The aim of this study was to use the growth mixture model for clustering countries on the basis of the mortality rate patterns of RTAs from 2007 to 2013. We obtained the data on RTA death rates from World Health Organization reports and Human Development Index (HDI) of United Nations Development Programme reports for the years 2007, 2010 and 2013. Simple Latent Growth Models (LGM) in 181 countries were applied to estimate overall RTA mortality rate growth trajectories and the latent growth mixture modeling utilized to cluster them. According to non-linear LGM, the overall mortality rate of RTAs showed a decrease from 2007 to 2010 followed by an increase from 2010 to 2013. The HDI covariate had a significant negative and positive effect on intercept and slope of the LGM, respectively. The extracted mixture model appeared to have seven classes with different trends in RTA mortality rates. The worldwide countries were clustered into seven classes. Further studies on each of the seven classes are suggested to provide recommendations for reducing the mortality rate of the RTAs. Additionally, increasing HDI in some countries could have a significant effect on reducing the RTA death rates. © 2019 Salehi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Parametric and semi parametric survival analysis of patients with lung cancer

Introduction: The lung cancer is the third cause of death and also one of the five common cancers in Iran. In this study, the efficiency of semi-parametric Cox models and Weibull parametric models in order to evaluate the effective factors of survival time of patients with lung cancer were investigated. Materials and Methods: This study was a prospective-cohort study in which the total number of 228 patients with lung cancer followed up from 1991-2007 and necessary information such as age at the time of diagnosis, gender, place of residence, education, residence status smoking, family history of cancer, province were collected from Babol cancer registry center. Then, these added to cox and weibull models as demographic factors. Akaike information criterion (AIC) was used to compare the efficiency of competing models. Results: In this study, 75 of cases were men and only 8 of patients survived until the end of the study. The 1, 3, and 5- year survival rates were 13, 8 and 8 respectively. Among the factors studied in the weibull model, the effect of smoking on survival time was significant (p0.05). However, AIC suggested higher efficiency for parametric Weibull model. Conclusion: In spite of the importance of the cox model is as a more common method by researchers, this study showed that the weibull model is more efficient in survival data analysis. According to the results of this study smoking prevention is necessary to increase the longevity of patients with lung cancer. © 2017, Semnan University of Medical Sciences. All rights reserved

Parametric and semi parametric survival analysis of patients with lung cancer

Introduction: The lung cancer is the third cause of death and also one of the five common cancers in Iran. In this study, the efficiency of semi-parametric Cox models and Weibull parametric models in order to evaluate the effective factors of survival time of patients with lung cancer were investigated. Materials and Methods: This study was a prospective-cohort study in which the total number of 228 patients with lung cancer followed up from 1991-2007 and necessary information such as age at the time of diagnosis, gender, place of residence, education, residence status smoking, family history of cancer, province were collected from Babol cancer registry center. Then, these added to cox and weibull models as demographic factors. Akaike information criterion (AIC) was used to compare the efficiency of competing models. Results: In this study, 75 of cases were men and only 8 of patients survived until the end of the study. The 1, 3, and 5- year survival rates were 13, 8 and 8 respectively. Among the factors studied in the weibull model, the effect of smoking on survival time was significant (p0.05). However, AIC suggested higher efficiency for parametric Weibull model. Conclusion: In spite of the importance of the cox model is as a more common method by researchers, this study showed that the weibull model is more efficient in survival data analysis. According to the results of this study smoking prevention is necessary to increase the longevity of patients with lung cancer. © 2017, Semnan University of Medical Sciences. All rights reserved

Effect of spirulina and chlorella alone and combined on the healing process of diabetic wounds: an experimental model of diabetic rats

Background: Using chemical agents to cure diabetes mellitus and its complications may be accompanied by complications. New natural agents, such as spirulina and chlorella, could be used as alternative choices in this case. Methods: 65 male Wistar rats were allocated to 5 groups: A (healthy control), B (diabetic rats with a normal diet), C (diabetic rats supplemented with 50 g/kg/day spirulina), D (diabetic rats supplemented with 50 g/kg/day chlorella) and E (diabetic rats supplemented with 25 g/kg/day chlorella and 25 g/kg/day spirulina). After 21 days, wounds were inflicted on the back of rats. Assessment of blood sugar (BS), high-sensitivity C-reactive protein (hs-CRP), vascular endothelial growth factor (VEGF), granulation tissue formation, vascularization, epithelialization, and percentage of wound healing were determined along with macroscopic examinations. Results: The microscopic changes at days 3, 7, 14, and 21 showed significant evidence of improved angiogenesis, epithelial proliferation, and granulation tissue formation in the spirulina and chlorella treated rats compared with the controls (p�0.05). Both spirulina and chlorella treatments of diabetic rats resulted in a significant reduction in BS and weight (p�0.05), but VEGF and hs-CRP levels did not significantly change (p > 0.05). Percentage of wound healing was 100 on day 21 in all groups, except the control group B (97.8 ± 1.15). Conclusions: The results of this study showed that supplementation with spirulina and chlorella alone and combined could improve wound healing indices in diabetic rats and could therefore be recommended for the management of diabetic ulcer. © 2021, Springer Nature Switzerland AG