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Multinomial response models, for modeling and determining important factors in different contraceptive methods in women
Khalkhali H, Haji Nejad E, Mohammad K,
Volume 59, Issue 1 (4-2001)
Abstract
Difference aspects of multinomial statistical modelings and its classifications has been studied so far. In these type of problems Y is the qualitative random variable with T possible states which are considered as classifications. The goal is prediction of Y based on a random Vector X ? IR^m. Many methods for analyzing these problems were considered. One of the modern and general method of classification is Classification and Regression Trees (CART). Another method is recursive partitioning techniques which has a strange relationship with nonparametric regression. Classical discriminant analysis is a standard method for analyzing these type of data. Flexible discriminant analysis method which is a combination of nonparametric regression and discriminant analysis and classification using spline that includes least square regression and additive cubic splines. Neural network is an advanced statistical method for analyzing these types of data. In this paper properties of multinomial logistics regression were investigated and this method was used for modeling effective factors in selecting contraceptive methods in Ghom province for married women age 15-49. The response variable has a tetranomial distibution. The levels of this variable are: nothing, pills, traditional and a collection of other contraceptive methods. A collection of significant independent variables were: place, age of women, education, history of pregnancy and family size. Menstruation age and age at marriage were not statistically significant.
The survey of the affecting factors on unwanted children in the women visiting health-centers in Tehran, 1998
Rahnavard Z, Heidarnia A, Babaei Gh, Mahmoodi M, Khalkhali H,
Volume 59, Issue 5 (9-2001)
Abstract
Population growth has been one of the main anxieties of different countries planners so far. Background and purpose growth of population has always had various impacts on society in economical, social, health and even political fields and its cure is controlling population growth. In order to study the efficient factors upon unwanted children, 1527 married women in Tehran have been randomly selected and data from questionnaire was selected. In this study, effective factors such as couple's education level, couple's occupation, number of children, age of marriage, age of last pregnancy, having stillbirth, breast feeding period in last born and effect of sex of infant in family planning upon unwanted children have been studied. Results show that some factors like husband's age, number of children, age of first marriage, age of last pregnancy, husband occupation, having stillbirth, breast feeding period and effect of infant's sex in family planning increase the chance of unwanted children and some criteria like women age, woman's education, fist pregnancy age, woman occupation, decrease the chance of unwanted children. According to logistic regression model, women age is one of the most important effective factors and one year increment in woman's age increase the chance of unwanted child 0.89 more times. Other factors is the number of children that in return for increasing one child to family, the chance of un wanting become 116.8 more times. It seems families don't have enough knowledge about family planning measures and their usage. Breast feeding period in wives who have fed their last children for more than six months, is another important factor which increases the chance of unwanted child to 1.02 more times than woman who have fed their last children for less than six months.
Radiologists’ intra-rater agreement and category distinguishability in diagnosis of ovarian mass by ultrasonography
A Akbarzadeh Bagheban, G Babaei, A Kazemnejad, S Faghihzadeh, F Baradaran Anaraki, Z Elahipanah,
Volume 64, Issue 3 (5-2006)
Abstract

Background: Intra-rater agreement in observing and decision making in diagnosis of any disease is of great importance.This investigation is to observe and read ultrasound pictures of ovarian cysts and distinguish its category for any radiologist. Distinguishability is one of the related entities in this matter and radiologists&apos ability in correct diagnosis is of great concern. In this study, we evaluated radiologist’s distinguishability of ordered categories of ovarian cyst diseases (benign, borderline and malignant) in ultrasonography. To do this, we measured intra-rater agreement of radiologists by Weighted Kappa coefficient, and then by the help of “square scores association model” and “agreement plus square scores association model” we evaluated their distinguishability in diagnosis of the severity of the ovarian cyst’s diseases.

Methods: In this analytical cross-sectional study, two radiologists and three radiology residents assessed ultrasounds of 40 patients separately and independently in two periods (with the interval of one week). Patients selected from those who were referred to Mirza Koochak Khan Hospital in January 2005. Ultrasounds were performed by an expert radiologist and by a single apparatus.

Result: Data from radiologists was evaluated by “square scores association model” due to their superior results of distinguishability. Mean of Weighted Kappa coefficient was 0.81 and intra-rater agreement was 0.99 for our radiologists, but due to weaker results of our residents, we used “agreement plus square scores association model” for analyzing and mean of Weighted Kappa coefficient was 0.65 and intra-rater agreement was 0.97 for them.

Conclusion: Although radiologists had a better function than their residents, all of them showed appropriate distinguishability and intra-rater agreement in diagnosis and categorizing of the ovarian cyst’s disease. To distinguish benign category from borderline was more difficult than to distinguish malignant category from borderline and radiologists showed better results in this than their residents did.


Effects of zinc and
Mahmoudian S.a , Poya A,
Volume 65, Issue 6 (9-2007)
Abstract

Background: The common cold is the most prevalent sickness and an important cause of absence from job. Furthermore, it often disturbs travel, including the practice of hajj, causing the use of many inappropriate drugs by these travelers. The health belief model is a psychological model that attempts to explain and predict health behaviors. The purpose of this study was to determine the effects of zinc and health belief model based educational intervention on the behavior of hajj travelers with regard to viral upper respiratory tract infections (URTI).

Methods: This double-blinded randomized controlled trial was performed among hajj travelers in 2005. Preventive measures were randomly allocated to four groups: 1- education + zinc sulfate. 2- education + placebo. 3- zinc sulfate only 4- placebo only. Data regarding incidence and duration of URTIs, background disorders, vaccination and health behaviors for cold were gathered by questionnaire by physicians and finally analyzed by SPSS 11.5 software using chi-square, t-test and independent samples t-test.

Results: A total of 646 travelers were studied. The incidence of common cold in groups receiving zinc were significantly less than that for those receiving the placebo. (P=0.05). However, incidence was statistically the same for those who received education versus those who did not. Use of handkerchief was the most prevalent behavior and use of mask was the least prevalent behavior. Mean duration of symptoms was less in those receiving zinc and education (3.7 days) comparing to those who received placebo and education (5.6 days). 

Conclusions: This study showed that zinc consumption can decrease the incidence and duration of the common cold. Health belief model based education could promote some preventive behaviors although most people do not take advantage of them. We recommend the use of zinc by those attending hajj.


Effects of applying continuous care model on blood tests in hemodialysis patients
Rahimi A, Ahmadi F, Gholyaf M,
Volume 66, Issue 1 (3-2008)
Abstract

Background: The kidney is a complex and vital organ, regulating the electrolyte and fluid status of the human body. In clients with a chronic disease, such as end-stage renal disease, functioning status and hematologic indexes are different than among the general population. Electrolyte and hematologic changes may induce many illnesses for such patients. The purpose of this study is to determine the effects of applying the continuous hemodialysis (HD) the blood test results of HD patients.

Methods: This quasi-experimental, before-after study included 38 HD patients from Hamedan, Iran in 2005. Subjects were selected using simple randomized sampling and were assigned to one group for the purpose of this research and investigated over a period of six months. Data collection tools included demographic questionnaire and control check lists. The first phase of the research involved orientation of the control group, which was limited to completion of the questionnaires and control check lists. Immediately after, the same patients became the case group, upon which continuous HD was applied and hemoglobin, hematocrit, blood urea nitrogen (BUN), potassium, sodium, and albumin tests were performed. Statistical analysis of the data employed SPSS (version 13), descriptive statistics, paired t-test and the Friedman test.

Results: In this group, 47.2% of the subjects were male and 52.8% female. Data analysis shows that, using repeated measurement ANOVA test, a significant relationship between application of the continuous HD and improvement in hemoglobin, hematocrit, BUN, potassium, sodium, and albumin levels (p<0.05).

 conclusion: Application of continuous HD causes a significant improvement in the blood test results of HD patients. We recommend that continuous HD be used, whenever appropriate, to resolve the common causes of complications in HD clients, including abnormal levels of electrolytes, especially potassium and phosphorus, as well as BUN and creatinine.


Survival analysis of gastric cancer patients using Cox model: a five year study
Biglarian A, Hajizadeh E, Kazemnejad A, Zali M,
Volume 67, Issue 5 (8-2009)
Abstract

Normal 0 false false false EN-US X-NONE AR-SA MicrosoftInternetExplorer4 Background: Gastric cancer is the second most common cancer and known as the second cause of death due to cancers worldwide. Adenocarcinoma is the most fatal cancer in Iran and a patient with this kind of cancer, has a lower lifetime than others. In this research, the survival of patients with gastric carcinoma who were registered at Taleghani Hospital, were studied.
Methods:  291 patients with Gastric carcinoma who had received care, chemotherapy or chemoradiotherapy, at Taleghani Hospital in Tehran from 2002 to 2007 were studied as a historical cohort. Their survival rates and its relationship with 12 risk factors were assessed.
Results:  Of the 291 patients with Gastric carcinoma, 70.1 percent were men and others (29.9%) were women. The mean age of men was 62.26 years and of women was 59.32 years at the time of diagnosis. Most of patients (93.91%) were advanced stage and metastasis. The Cox proportional hazards model showed that age at diagnosis, tumor stage and histology type with survival time had significant relationships (p=0.039, p=0.042 and p=0.032 respectively).
Conclusion: The five-year survival rate and median lifetime of gastric cancer patients who underwent chemotherapy or chemoradiotherapy are very low and seems that one of the important reasons for this situation is delayed diagnosis. The scheme of public education about the early warning signs of the disease and diagnosis and administration of periodic examinations is unavoidable.


Studying angiogenesis in autochthonous xenograft models of glioblastoma multiforme by MVD-CD34 technique in Iranian patients
Amanpour S, Muhammadnejad S, Muhammadnejad A, Mazaheri Z, Kazem-Haghighi M, Oghabian M, Khoshnevisan A,
Volume 69, Issue 3 (6-2011)
Abstract
Background: Despite advances in cancer diagnosis and treatment, survival rate of patients suffering from glioblastoma multiform (GBM) has not been significantly improved. Therefore, novel therapeutic adjuncts to routine therapies have been suggested over time. Inhibition of angiogenesis by antiangiogenic drugs is one of the new approaches to inhibit the growth of malignant cells. Microvessel density (MVD) assay is a technique performed by counting immunohistochemically-stained blood vessels. Nowadays, athymic nude mice are widely used for the establishment of xenograft tumor models in cancer research. The aim of this study was to evaluate the MVD of autochthonous xenograft models of GBM isolated from Iranian patients for use in pharmaceutical research on antiangiogenic drugs.Methods: Fresh tumor samples of GBM were obtained from three patients in Cancer Institute of Tehran University of Medical Sciences in Fall of 2010 and Winter of 2011. After preliminary processing, minced tumor samples were implanted heterotopically on flanks of athymic nude mice. Two months later, the animals were sacrificed and the xenograft tumor samples were sent to the pathology laboratory. After establishing the proof of the xenograft tumor type, MVD-CD34, an endothelial cell marker, was assessed by counting hot spot areas in 22 samples.Results: The mean number of microvessels in these xenograft tumor models was 30±2.1. Conclusion: These autochthonous xenograft models of GBM can be used in preclinical settings for research on antiangiogenic drugs regarding a pharmacogenomics-based treatment regimen for the Iranian population. Moreover, such models can be used in future studies for determining the sensitivity or resistance to antiangiogenic drugs in individualized cancer therapy.
The effects of temperature and birth weight on the transition rate of hypothermia in hospitalized neonates using Markov models
Akbarzadeh Baghban A, Jambarsang S, Pezeshk H, Nayeri F,
Volume 70, Issue 5 (8-2012)
Abstract
Background: Hypothermia is an important determinant of survival in newborns, especially among low-birth-weight ones. Prolonged hypothermia leads to edema, generalized hemorrhage, jaundice and ultimately death. This study was undertaken to examine the factors affecting transition from hypothermic state in neonates.
Methods:  The study consisted of 439 neonates hospitalized in NICU of Valiasr in Tehran, Iran in 2005. The neonates' rectal temperature was measured immediately after birth and every 30 minutes afterwards, until neonates passed hypothermia stages. In order to estimate the rate of transition from neonatal hypothermic state, we used multi-state Markov models with two covariates, birth weight and environmental temperature. We also used R package to fit the model.
Results:  Estimated transition rates from severe hypothermia and mild hypothermia were 0.1192 and 0.0549 per minute, respectively. Weight had a significant effect on transition from hypothermia to normal condition (95% CI: 0.1364-0.4165, P<0.001). Environmental temperature significantly affected the transition from hypothermia to normal stage (95% CI: 0.0439-0.4963, P<0.001).
Conclusion:  The results of this study showed that neonates with normal weight and neonates in an environmental temperature greater than 28 °C had a higher transition rate from hypothermia stages. Since birth weight at the time of delivery is not under the control of medical staff, keeping the environmental temperature in an optimum level could help neonates to pass through the hypothermiastages faster.


Wound healing in animal models: review article
Fariba Jaffary , Mohammad Ali Nilforoushzadeh , Hanieh Sharifian , Zahra Mollabashi ,
Volume 75, Issue 7 (10-2017)
Abstract
Wound healing and reduction of its recovery time is one of the most important issues in medicine. Wound is defined as disruption of anatomy and function of normal skin. This injury could be the result of physical elements such as  surgical incision, hit or pressure cut of the skin and gunshot wound. Chemical or caustic burn is another category of wound causes that can be induced by acid or base contact irritation. Healing is a process of cellular and extracellular matrix interactions that occur in the damaged tissue. Wound healing consists of several stages including hemostasis, inflammatory phase, proliferative phase and new tissue formation which reconstructs by new collagen formation. Wounds are divided into acute and chronic types based on their healing time. Acute wounds have sudden onset and in normal individuals usually have healing process of less than 4 weeks without any residual side effects. In contrast, chronic wounds have gradual onset. Their inflammatory phase is prolonged and the healing process is stopped due to some background factors like diabetes, ischemia or local pressure. If the healing process lasts more than 4 weeks it will be classified as chronic wound. Despite major advances in the treatment of wounds, still finding effective modalities for healing wounds in the shortest possible time with the fewest side effects is a current challenge. In this review different phases of wound healing and clinical types of wound such as venous leg ulcer, diabetic foot ulcer and pressure ulcer are discussed. Also acute wound models (i.e burn wounds or incisional wound) and chronic wound models (such as venous leg ulcers, diabetic foot ulcer, pressure ulcers or bedsore) in laboratory animals are presented. This summary can be considered as a preliminary step to facilitate designing of more targeted and applied research in this area.

A model for improving medical records by creating electronic health records: review article
Hamidreza Salmani Mojaveri , Mahboubeh Kordmostfapour , Kokab Mansour Kiaiy , Fatemeh Amouzad Khalili , Negin Qavi Kutenai ,
Volume 75, Issue 8 (11-2017)
Abstract
Today, the use of information and communication technology (ICT) is an important and key factor in the progress of all organizations, including health-centered and health systems. Given the importance of the subject matter above, these organizations have created a particular transformation and change in order to upgrade their systems in use, one of which is the creation of Electronic Health Records (EHR). This evolving system, by increasing productivity, both by increasing staffing efficiency and by increasing the effectiveness of the treatment process, simplifies the diagnosis path to treatment and prevents the submission of written and bulky reports. Given the ethical principles of protecting the privacy of patients and the confidentiality of their information, how to archive electronic medical records in a secure database is very important. This is one of the most important issues of ethics and hospital managers should provide mechanisms to keep all patient data properly stored and maintained. In this paper, we have tried to provide a model for the Electronic Health Record Hospital, which many of them could use to optimize their medical records systems. The purpose of this model is to accelerate and apply the process of creating electronic records in the health system, especially government hospitals with a large number of patients. By using this model, internal and external interaction of organization is facilitated, and agile responsiveness can be provided at a given time. In addition to the above, with the implementation and operationalization of the model, the possibility of reducing the volume of criticisms and complaints from hospitals will also be realized and the use of drugs will be based on the actual needs of the community and based on individual data. Implementation of this model also has barriers to addressing some of them in this article, but in order to overcome these barriers, more administrative effort and wider governmental support are needed. These efforts in the context of culture-building use of information technology, both among hospital personnel and among patients and healthcare users, are more important.
 

Comparison of ordinary logistic regression and robust logistic regression models in modeling of pre-diabetes risk factors
Fateme Azizi Mayvan , Mehdi Jabbari Nooghabi , Ali Taghipour , Mohammad Taghi Shakeri , Mahsa Mokarram ,
Volume 76, Issue 7 (10-2018)
Abstract
Background: Regarding the increased risk of developing type 2 diabetes in pre-diabetic people, identifying pre-diabetes and determining of its risk factors seems so necessary. In this study, it is aimed to compare ordinary logistic regression and robust logistic regression models in modeling pre-diabetes risk factors.
Methods: This is a cross-sectional study and conducted on 6460 people, over 30 years old, who have participated in the screening of diabetes plan in Mashhad city that it was done by Mashhad University of Medical Sciences from October to December 2010. According to the fasting blood sugar criteria, 5414 individuals were identified as healthy and 1046 individuals were identified as pre-diabetic. Age, gender, body mass index, systolic blood pressure, diastolic blood pressure and waist-to-hip ratio were measured for every participant. The data was entered into the Microsoft Excel 2013 (Microsoft Corp., Redmond, WA, USA) and then analysis of the data was done in R Project for Statistical Computing, Version R 3.1.2 (www.r-project.org). Ordinary logistic regression model was fitted on the data. The outliers were identified. Then Mallow, WBY and BY robust logistic regression models were fitted on the data. And then, the robust models were compared with each other and with ordinary logistic regression model according to goodness of fit and prediction ability using Pearson's chi-square and area under the receiver operating characteristic (ROC) curve respectively.
Results: Among the variables that were included in the ordinary logistic regression model and three robust logistic models, age, body mass index and systolic blood pressure were statistically significant (P< 0.01) but waist-to-hip ratio was not statistically significant (P> 0.1). There were 552 outliers with misclassification error in the ordinary logistic regression model. Pearson's chi-square value and area under the ROC curve value in the Mallow model were almost the same as for ordinary logistic regression model. But it was relatively higher in BY and WBY models.
Conclusion: Based on results of this study age, overweight and hypertension are risk factors of prediabetes. Also, WBY and BY models were better than ordinary logistic regression model, according to goodness of fit criteria and prediction ability.

Preparation, characterization and evaluation the effects of microemulsion containing sesame oil on fibrinogen and factor VII level in animal model
Mahmoud Ebrahimi , Mohammad Karimi , Faranak Dehghani , Amir Biriaei , Nafiseh Farhadian, Shiva Golmohammadzadeh ,
Volume 77, Issue 3 (6-2019)
Abstract
Background: Sesame oil can be used to treat cardiovascular diseases, such as atherosclerosis, by reducing the levels of fibrinogen and factor VII. The aim of this study is to prepare a microemulsion containing sesame oil as a drug nanocarrier for improving the aqueous solubility and therapeutic effects of this vegetable oil on the reduction of the fibrinogen and factor VII levels in animal model.
Methods: This experimental study was performed for microemulsion preparation and animal test at Ferdowsi University of Mashhad and Cardiovascular Research Center of Mashhad University of Medical Sciences, Mashhad, Iran, respectively, from April 2015 to January 2017. To prepare the microemulsion samples, Tween 80 and span 80 were selected as surfactant couple and surfactant ratios of 8:1, 9:1 and 10:1 were determined for construction of pseudo-ternary phase diagrams. The Zealand white rabbits were categorized in three groups: receiver of base diet group, high cholesterol diet and high cholesterol diet plus microemulsion.
Results: The average particle size of the samples was in the range of 16.64±0.1 to 21.16±0.2 nm with a uniform particle size distribution. Zeta potential was in the range of -10.7 to 18.4 mV, refraction index was approximately 1.39. Electrical conductivity coefficient was in the range of 297 to 311 μz and pH of all the samples were approximately 6.42 for all samples. All of the microemulsion samples were physically stable and the prepared sample with 9:1 surfactant ratio was selected to investigate the animal test due to the higher oil percentage in comparison with the other samples that be stable over 6 months. Significant decrease in the levels of fibrinogen and factor VII in the third group of rabbits was observed compared to the other groups.
Conclusion: The results of this study showed the effective performance of nanostructured drug delivery systems in the form of microemulsion to improve the aqueous solubility and therapeutic effects of hydrophobic compounds such as vegetable oils.

The effect of oral Aphanizomenon flos-aquae extract on excisional wound healing
Maria Zahiri , Khalil Pourkhalili , Sadegh Darvishi , Hossein Heydari , Zahra Akbari,
Volume 77, Issue 10 (1-2020)
Abstract
Background: Aphanizomenon flos-aquae (AFA) is a type of blue-green algae and contains a source of biological compounds. These microalgae have many beneficial health effects. Recently, fucoidan, known sulfated polysaccharide component of AFA algae, has been claimed to stimulate stem-cell mobilization in animal models. Stem cells play an essential role in tissue repair process. In this study, we use excisional full thickness wound model to investigate the effectiveness of trademark AFA extract on skin wound repair process.
Methods: In this experimental study, 21 adult male Wistar rats (weighing 200-250 g) were used and under general anesthesia (intraperitoneally with a ketamine/xylazine solution), two round excisional wounds were created under sterile conditions by a 6 mm punch on the dorsum (paravertebral area) of all rats. Animals were randomly assigned into 3 groups. In groups 1 and 2 (SE-200, SE-400), StemEnhance© (StemTech Health Sciences Inc. British Columbia, Canada) were given respectively 200 or 400 mg/kg by oral gavage once daily and in group 3 (Sham), distilled water (DW) was given to all subjects. Post-wounding gavage of StemEnhance or DW started from 1st day and continued to 7th day. The wound surface area was monitored daily by digital camera and assessed by Image Tool™ software, version 3.5 (UTHSCSA, San Antonio, TX, USA). At 9th day post-wounding animals were sacrificed and repaired tissues were harvested by and assessed by a 8 mm punch. Repaired skin areas were processed for hematoxylin and eosin (H&E). Histopathological parameters of healing including inflammatory cell infiltration, angiogenesis, and fibroblast count were assessed by pathologist. Our study was conducted in the Physiology Department of Medical School, Bushehr University of Medical Sciences, Iran, from October 2016 to March 2016.
Results: Macroscopic imaging of wound area revealed that there was statistically significant difference in wound area reduction between SE-200 group and sham group on day 6 post wounding (P=0.032). Moreover, histological findings showed that the number of neutrophils, macrophages, fibroblasts, and microvessel density decreased in both StemEnhace-treated groups. There were no significant differences between two treatment groups.
Conclusion: According to the obtained results it seems that the extract of Aphanizomenon flos-aquae algae positively affects wound healing process by ameliorating inflammatory response in early healing phases.

An integrated health policy making and analysis model: letter to the editor
Ali Mohammad Mosadeghrad,
Volume 77, Issue 12 (3-2020)
Abstract
Full Text in Persian.
The effect of massage and shaking on infants with colic in a clinical trial concerning the misspecification
Ali Sheidaei, Alireza Abadi, Fatemeh Nahidi, Farzaneh Amini, Farid Zayeri, Nafiseh Gazrani,
Volume 79, Issue 1 (4-2021)
Abstract
Background: Statistical models are used to investigate the relationship between variables in statistical studies. Considering the variety of statistical models, finding the most suitable model is a complex work. This study aimed to compare different models in the treatment of infants' colic and the misspecification of specificity.
Methods: This randomized clinical trial was conducted on 100 infants with colic in the pediatric clinic of Amir Kabir Hospital in Arak, the intervention and control groups were randomly divided into two groups. The collection and analysis of the data was performed in 2016. After teaching massage to mothers of the intervention group, they were asked to perform massage on infants three times a day during the week. In the control group, mothers can relieve the symptoms of colic by shaking the infant. Parents recorded the number and severity of crying daily in the checklist. Finally, by using different models, R software, SAS, and goodness of fit, the best model was introduced.
Results: In the massage group, the mean crying intensity of infants with colic decreased from 5.01 units on the first day to 2.47 units on the seventh day. On the other hand, the difference in mean sleep time changed from 1.81 hours in favor of the shaking group on the first day to 1.26 hours in favor of the massage group on the seventh day. Also, the severity of crying in the infants of the massage group was significantly higher than the impulse group. Regarding the grace of marginal models, the first-order self-return correlation structure was the best grace and for some variables, the model had random effects with a gamma distribution for the random component.
Conclusion: Massage can reduce infants' colic. Statistically, in the case of a nonlinear model, the variance of estimates is more than estimated to be influenced by the misspecification of the correlation structure.

Prediction of mortality in patients admitted to intensive care units, A comparison of three data mining techniques: a brief report.
Zahra Mohammadi Taghiabad , Maryam Ahmadi, Alireza Atashi,
Volume 79, Issue 7 (10-2021)
Abstract
Background: Early outcome prediction of hospitalized patients is critical because the intensivists are constantly striving to improve patients' survival by taking effective medical decisions about ill patients in Intensive Care Units (ICUs). Despite rapid progress in medical treatments and intensive care technology, the analysis of outcomes, including mortality prediction, has been a challenge in ICUs. Hence, this study aims to predict the mortality of patients admitted to ICUs using data mining techniques.
Methods: In this study, among the cases of patients who were admitted to ICUs of the Rasoul Akram and Firoozgar hospitals of Tehran City, Iran, from December 2017 to March 2018, the first 24 hours of the ICUs admission data of 874 cases were gathered. A new model based on the standard methodology CRISP was developed. In the modeling section, two well-known data mining techniques called artificial neural network (ANN), K nearest neighbor (KNN) and decision tree (DT) were used. WEKA 3.9.2 open-source software was implemented for data analysis. Finally, according to the accuracy, sensitivity, specificity criteria and AUC-ROC Curve, the superior model was introduced.
Results: Based on the WEKA results, 19 variables had the most impact on the mortality prediction of patients admitted to ICUs including Glasgow Coma Scale (GCS), mechanical ventilation, surgical service at ICUs admission, gender, temperature, serum creatinine, diabetes, Blood urea nitrogen (BUN), age, addiction, International Normalized Ratio (INR), PH, Partial Thromboplastin Time (PTT), albumin, hemoglobin, glucose, pulse rate, hematocrit (HCT), PO2.  Based on the created models, some rules have been extracted which can be used as a pattern to predict the probability of mortality. Although the AUC of the three models was acceptable (KNN 81.5%, ANN 77.5% and DT 74.3%), but the accuracy of decision tree J48 (74.2%) was higher.
Conclusion: The study indicated that in the KNN model, the rules derived from it can be effective in mortality prediction in patients admitted to ICUs.

Evaluation of changes in blood sugar levels in a 14-years cohort study of pre-diabetic patients and its relation with diabetes
Parisa Zakeri, Masoud Amini, Ashraf Aminorroaya, Fahimeh Haghighatdoost, Awat Feizi,
Volume 79, Issue 9 (12-2021)
Abstract
Background: Examining the course of changes in predictive indicators of future diabetes, such as blood sugar in high-risk individuals including pre-diabetic patients, can provide valuable information about the incidence of diabetes in these individuals. This study aimed to classify people at risk (pre-diabetes) based on the course of changes in their blood sugar and blood lipid and to investigate the incidence of diabetes in these classes on a sample of patients who were referred to the Endocrine and Metabolism Research Center of Isfahan.
Methods: This cohort study was performed based on the information of the Isfahan Diabetes Prevention Plan (IDPs). This project was implemented from April 2004 to March 2018 in the clinics of the Endocrine and Metabolism Research Center of Isfahan. The subjects in this study include 1228 pre-diabetic patients who participated in this project. Demographic and clinical variables of patients including blood sugar and lipid-blood variables were obtained using a questionnaire and laboratory measurements. Also in this study, the number of clinical variables was recorded 3 times. Data analysis was performed using the latent class growth trees model in R software version v4. (R v4.1.0)
Results: The mean (standard deviation) age of participants was 44 (6.86) years. Subjects were classified into two classes of low-risk impaired blood sugar (n=1165) and high-risk impaired blood sugar (n=63) based on the trend of changes in blood sugar levels. Blood sugar levels were reported in the first class (104.28) and the second class (132.41).
Conclusion: In the present study, it was concluded that there is a significant relationship between the incidence of diabetes and the different classes formed based on the course of changes in blood sugar of at-risk individuals. Therefore, by classifying people at risk, the incidence of this disease can be predicted and thus prevented. Also,measures such as managing the blood sugar and lifestyle variables of pre-diabetic patients through nutrition counseling classes and regular periodic tests can be used to reduce the incidence of diabetes in the future is used in people with pre-diabetes who are at high risk for the disease.
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Evaluation of risk factors of recurrence of hodgkin's lymphoma using random survival forest and comparison with cox regression model
Zeinab Asakereh, Elham Maraghi, Bijan Keikhaei, Amal Saki Malehi ,
Volume 80, Issue 7 (10-2022)
Abstract
Background: In many studies, Cox regression was used to assess the important factors that affect the survival of cancer patients based on demographic and clinical variables. The aim of this study was to determine the factors affecting the survival of patients with Hodgkin's lymphoma using the random survival forest (RSF) method and compare it with the Cox model.
Methods: In this retrospective cohort study, all patients with Hodgkin's lymphoma who were referred to the Oncology and Hematology Center of Ahvaz Shafa Hospital from March 2000 to February 2010 were included. The survival time was calculated from diagnosis to the first recurrence event date (based on month). To assess the process of the disease, demographic characteristics and disease-related variables (including disease stage, chemotherapy, site of lymph involvement, etc.) were extracted from the records of 387 patients with Hodgkin's lymphoma. To investigate the prognostic factors that affect the recurrence of disease the Cox model and RSF were implemented. Moreover, their performance based on the C-index, IBS, and predictor error rate of the two models were compared Data analysis was implemented by using R4.0.3 software (survival and RandomForestSRC packages).
Results: The results of the Cox model showed that LDH (P=0.001) and classical lymphoma classification (P<0.001) were associated with an increased risk of relapse in patients. However, the results of the RSF model showed that the important variables affecting the recurrence of disease were the stage of disease, chemotherapy, classical lymphoma classification, and hemoglobin, respectively. Also, the RSF model showed a higher (c-index=84.9) than the Cox model (c-index=57.6). Furthermore, the RSF model revealed a lower error rate predictor (0.09) and IBS index (0.175) than the Cox model. So, RSF has performed better than the Cox model in determining prognostic factors based on the suitability indicators of the model.
Conclusion: The RSF has high accuracy than the Cox model when there is a high number of predictors and there is collinearity. It can also identify the important variables that affect the patient's survival.

Presenting a model for assessing general medical students: a brief report
Neda Negahban Jouzan , Hossein Karimi Moonaghi , Hoorak Poorzand, Mohammad Khajedaluee,
Volume 81, Issue 1 (4-2023)
Abstract
Background: By examining the comprehensive system for evaluating the academic progress of general medical students, often the objectives of the cognitive domain and the form of cumulative evaluation were used, and the tests were not used much for feedback to the students. The aim of the study is to develop a model that fits the levels of Miller's evaluation pyramid in formative-cumulative forms.
Methods: The search was started in Iranian and international databases, magazines, curriculum of prestigious universities in the world. To find out about the latest events in the field of assessment, AMEE international virtual conferences in August 2021 and the summary booklet of medical education articles of Shahid Motahari 1400 (the 22nd national conference of medical education) were reviewed. Data analysis was done by Beredy's adaptive model. The search and analysis lasted for 11 months. Finally, a model was developed according to Miller's evaluation pyramid. Its validation was done in the focus group meeting in two ways, in person at Mashhad Medical School and virtual.
Results: According to the extracted data, the approach of assessment is towards formative assessment format and improvement of traditional methods along with modern methods, which was clearly observed in the study of the curriculum of Harvard-Stanford University in America and Oxford University in England. Integrating the results with Miller's evaluation levels, and the formative and cumulative evaluation format, led to the formulation of a model with the most favorable opinions of experts. In addition, the majority of opinions and suggestions of experts were related to the change in the way of executive policies of universities and providing a context for the emergence of new idea.
Conclusion: A model including measurement methods according to the levels of Miller's evaluation pyramid was developed in formative-cumulative. It is suggested that the model be reviewed by the relevant experts and notified by taking into account the implementation conditions for the correct evaluation process.

Enhancing bioterrorism defense, leveraging animal models for viral drug and vaccine development: a review article
Hadi Lotfi, Morteza Izadi, Ehsan Lutfi , Hadi Esmaeili Gouvarchin Ghaleh,
Volume 81, Issue 7 (10-2023)
Abstract
Deliberate or threatening use of viruses, bacteria, toxins, or poisonous substances prepared from living organisms to cause death or disease in humans, animals, and plants is called bioterrorism. These agents can be spread by spraying them in the air, causing infection in animals, transferring this infection to humans, or contaminating water and food sources. Defense measures, such as emergency responses to this type of terrorism, are unfamiliar and unknown. The general state of helplessness caused by the lack of complete preparation and the lack of anti-pollution strategies complicates the issue. The ability and widespread interest of civilian personnel to participate in the development of chemical and biological weapons is directly related to easy access to academic excellence around the world. Another factor is the tempting misuse of freely available electronic data and knowledge about the production of antibiotics, vaccines, and conventional weapons with their various complex details. The use of animals in laboratory research to better understand the mechanisms of disease and treatment and to overcome the limitations of clinical trials has a long history. For many viruses, laboratory diagnostic methods and reagents must be continuously modified to account for genetic variations and variants. Unlike bacterial diseases, many of which can be treated with antimicrobial drugs, there are fewer medical countermeasures to combat viral infections. Many of these pathogens are lethal or cause debilitating diseases in humans, making it ethically inappropriate to test the effectiveness of these countermeasures on human volunteers. Researchers must have a correct understanding of various animal models so that they can make the correct choice, gain a better understanding of the clinical symptoms of viral diseases, and provide possible options for treatment and vaccine development. It should be noted that decision-making when faced with a biological attack should be done away from too much fear, and this requires researchers to have prior knowledge of facing these threats. Despite all these checks and measures taken in advance, the international preparedness against these attacks is weak, which can be attributed to the lack of global plans to deal with the epidemic.

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