Iranian Journal of

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Background & objectives: In the management of crush syndrome, the way of treating compartment syndrome is controversial. The aim of this study was to evaluate the outcomes of compartment syndrome treatment after Bam earthquake.
Methods: Clinical and laboratory findings of all fasciotomized patients in Bam earthquake were analyzed. Then nonfasciotomized patients with same characteristics were selected and the outcomes of two groups were compared.
Results: Fasciotomy for 107 injured out of 2962 hospitalized patients, was performed (46% female). Mean age of fasciotomized patients was 27.4±9.7 years (min=10, max=65 year). There were not significant differences in the final outcome of two groups with the same clinical, biochemical and demographic characteristics.
Conclusions: Fasciotomy for 107 injured out of 2962 hospitalized patients, was performed (46% female). Mean age of fasciotomized patients was 27.4±9.7 years (min=10, max=65 year). There were not significant differences in the final outcome of two groups with the same clinical, biochemical and demographic characteristics.

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Dear Editor We read with interest the recent original article by Esmailnasab and his colleagues (1) discussing the issue of influencing factors on type 2 diabetes in Sanandajd. The authors are to be congratulated for conducting such an important topic both for healthcare providers and researchers. We have noticed that in that interesting paper the occupational status was classified unclearly into four categories as "housekeeper", "employee", "farmer and free job" and "unemployed" that the journals reviewers have been overlooked this easily. Since one of the main characteristic of occupation is making money, some groups such as "student" and "housekeeper" are excluded from this category. There are several international classifications for occupational status that can be used for national studies in Iran. These categorizations also called "social class" that considered to occupational exposure, amount of income and some other components. One of these classifications is presented by the International Labor Organization (ILO). A number of countries have localized this classification and many countries have used it without changes (2). The latest revised classification (ISCO) has been revealed 11 occupational groups (major group) provides the following (3): 1- Legislators, senior officials and managers, 2- Professionals, 3- Technicians and associate professionals, 4- Clerks, 5- Service workers and shop and market sales workers, 6- Skilled agricultural and fishery workers, 7- Craft and related trade workers, 8- Plant and machine operators and assemblers, 9- Elementary occupations, 11- Armed forces. It seems that with modification of such classifications, we could obtain a national standard categorization for occupation and then would be able to better understanding the role of occupation in development of disease and health problems.

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Background and Objectives: Diabetes is a major health issue worldwide. This study evaluates whether a community-based participatory program may improve diabetes care in adult in west area of Yasouj.
Methods: A community based participatory research was designed. A local leading group was established consisted of academic researchers, local leaders, health providers and public representatives. All the 30-65 years old residents of designated area (2569 persons) were screened for detecting diabetes anthropometric measurements and biochemical tests were measured. Educational interventions about improving the diet and physical activities were performed for high risk individuals through a 3-months period.
Results: Out of 2569 individuals, 1336 were at high risk. Approximately 228 persons (17%) identified having diabetes. After the intervention, the mean FBS, HbA1C, TG and cholesterol of participant significantly decreased (p<0.05), decreasing in systolic and diastolic blood pressure and body mass index were seen however this was not statistically significant. The mean physical activity and exercise increased and consumption of frying foods, saturated oil decreased significantly.
Conclusion: Community-Based Participatory cares could be a feasible model for control of diabetes and its risk factors.

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Background & Objectives: Prevalence of cytomegalovirus (CMV) infection varies is highly prevalent in different societies. CMV infection in susceptible patients is associated with serious morbidity and a high mortality and is a matter of concern for blood bank professionals and blood transfusion recipients, especially in cases of transfusions to neonates and immunocompromised patients. Thus, the present study aimed to determine the prevalence rate of anti-CMV antibodies among the blood donors of Mashhad Blood Transfusion Center.
 Methods: This seroepidemiology study carried out on 1008 samples from blood donors in Mashhad Blood Transfusion Center and the prevalence rate of anti-CMV antibodies (IgM, IgG) was estimated by ELISA method in the samples
Results: Out Of 1008 serum samples from donors, 1000 persons (99.2%) had anti-CMV IgG and 16 donors (1.6%) had anti-CMV IgM in their sera. Eight (8) persons had no anti-CMV IgG and IgM in their sera.
Conclusion: The high rate of prevalence of CMV in this study region indicating blood component screening strategies for blood transfusions require particular attention among healthcare professionals as part of the actions for prevention and reduction of primary infections caused by CMV.

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Background and Objectives: Disorders of height and weight growth are the most important health disorders affecting children younger than two in developing societies. Failure to treat these disorders can lead to the increased mortality and mental, emotional or physical disability. The objective of this study was to investigate the growth trends of children and the factors affecting it.

Methods: This retrospective cohort study was conducted on 2030 children younger than two in Khorramabad, Iran who were selected using stratified and cluster sampling. Based on household records, the weight growth trend was recorded as a four-level variable (decline, stagnation, slowness and desirable) and the the height growth trend was recorded as a three-level variable (stagnation, slowness and desirable); finally, the data were modeled using a longitudinal marginal model and the SAS software version 9.2.

Results: The incidence of at least one decline in the weight growth curve and one stagnation in the height growth curve was 14.2% and 10.4%, respectively. The child’s age and the maternal educational level had a significant effect on the growth trends. However, the sex, parity and the exclusive breastfeeding during the first six months had no significant relationship with the growth trends.

Conclusion: Given the results and the relatively high prevalence of growth disorders among children, it seems that increasing the awareness of low literate women about feeding of the children is the most important approach to manage growth disorders. Additionally, health-care professionals should mostly focus on monitoring the growth of children older than 12 months.

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Background and Objectives: Missing data is a big challenge in the research. According to the type of the study and of the variables, different ways have been proposed to work with these data. This study compared five popular imputation approaches in addressing missing data in the questionnaires.

Methods: In this study, 500 questionnaires were used for self-medication in diabetic patients. Missing in the observations was artificially generated by random selection of questions and then deleting them. Five imputation ways included: 1) the mean of the questions, 2) the mean of the person, 3) the mode of the person, 4) linear regression, and 5) EM algorithm. For each method, the mean and standard deviation were compared with imputation. The Spearman correlation coefficient, the percentage of incorrectly classified and kappa statistic were also calculated.

Results: A kappa higher than 0.81 represented almost perfect agreement at 10% missingness. The EM algorithm showed the highest level of agreement with the results of actual data with a Kappa of 0.886. With increasing missingness to 30%, the EM algorithm and the mean of  the person showed a rather similar agreement with a Kappa of 0.697 and 0.687, respectively.

Conclusion: In this study, the EM algorithm was the most accurate method for handling missing data in all models. The mean of the person method is easy for handling missing data, especially for most non statisticians.

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Background and Objectives: Taking into account the roles and positions of WHO Collaborating Centers (WHOCCs) in the furtherance of national goals and the great impact of their interaction as well as cooperative relations between these centres, this study was conducted to assess the current status of WHOCCs, identify opportunities and threats, and provide practical solutions to solve WHOCCs problems.

Methods: This cross-sectional study was conducted using an open-ended questionnaire in 2014. The questionnaire revolved around the WHOCCs' status in terms of goal achievement, manpower problems, financial resources, communications, as well as suggestions to solve problems in these domains. These findings were approved in the second convention of the heads of WHOCCs in Kerman in 2014 and the questionnaires of the second phase were distributed and completed by participants. Data were analyzed using the content analysis method.

Results: The majority of the centres assessed their performance regarding the national goals (11.59) in comparison with international goals (14.20), and self-regulated goal setting (14.7o) in an unfavorable condition. Financial problems and lack of recruitment were the most important problems for WHOCCs. The support of the Ministry of Health, WHO, supporting universities, and establishing research networks at national and international levels to foster communication, contracts to share experiences and resources, considering the authors' rights as well as introducing the competencies of centres at national and international levels, were some of the suggestions proposed.

Conclusion: It seems that more support of the WHO, Ministry of Health, and supporting universities is needed to increase financial resources and recruit staff.

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Background and Objectives: Social determinants of health affect a wide range of health consequences. The aim of this study was to analyze the effects of social determinants of health factors on survival in patients with malignant brain tumors.

Methods: This cross-sectional retrospective study was done in Imam Khomeini and Shariati Hospitals in 2014. Based on inclusion criteria, the data of 148 patients were collected. The collected data included demographic information (including age, sex, education level, employment status, marital status, health insurance status, number of household members), information about the tumor and disease (stage / grade), The first and the last time of follow-up, type of selected treatment, and the duration of survival after treatment. We used SPSS 15 to analyze data.

Results: Our results showed a significant relationship between survival and variables such as the size of the household, education, employment status, and age. Patients with grade 3 tumors had a lower relative risk of dying while employed patients, patients in the age range 18-30 years, and male patients had a higher relative risk of dying (lower survival).

Conclusion: Lack of reliable databases and appropriate integration and communication between different organizations recording to patient data, and also probable sensitivity in obtaining personal information has led to the lack of systematic information about the impact of social determinants of health. it is recommended that a system of recording integrated information for different disease should be established in the country for designing informed policies based on the evidence.

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Background and Objectives: Food is one of the major needs of the humans that is defined in the context of food security. The objective of this study was to find the relationship between food insecurity and stunting combined with obesity and overweight in children aged 7-11 years old in Zabol.

Methods: This study had two phases. In the first phase (cross-sectional), 3443 students aged 7-11 years old were selected with stratified – cluster sampling. In the second phase, all of the children with stunting and obesity or overweight based on the CDC growth chart comprised the case group and 112 students with normal height and weight based on the CDC growth chart comprised the control group. The case and control groups were matched in terms of age, sex, and school. The food security USDA questionnaire that consists of 18 items was completed through interview with mothers to evaluate the family food security.

Results: The prevalence of stunting, obesity, and overweight was 17.95%, 4.56%, and 10.98% respectively and the prevalence of stunting combined with obesity and overweight was 1.71% in the first phase of the study. There was a significant relationship between food insecurity and stunting combined with obesity and overweight. Food insecurity had a significant relationship with low economic status, living in rented homes, labor job and unemployment of the household head, and low education level of the household head in the case group.

Conclusion: Because of the significant relationship between food insecurity and stunting combined with obesity and overweight, it is necessary to design interventional programs to prevent or reduce food insecurity.

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Background and Objectives: Using the anthropometric indicators of children is one of the ways of monitoring their growth. Because of the racial divisions and levels of health and welfare, comparing these indicators with the global reference is not reasonable; therefore, designing a local reference seems necessary. This study aimed to evaluate the growth indices for boys and girls aged 5 to 18 years old living in Isfahan and to compare the indices with standard values.
Methods: In this cross-sectional study, 53,839 subjects were included. Percentiles of body mass index, height, and weight were calculated using the LMS method in the LMS Light software. After normalization of the growth indices, their mean and standard deviation were calculated for each age group and anthropometric indices curves were plotted versus the 5th, 50th and 95th percentiles of the NCHS reference.
Results: In all age categories, the mean SDS scores of BMI in boys and girls was -0.004 ± 0.029 and 0.014 ± 0.062, respectively, indicating no difference with reference values. However, the 95th percentile of the body mass index for the reference population was consistent with the 90th percentile for the population studied. Also, weight in boys below 13 years of age was higher than the reference line while in girls, weight was always higher than the reference value.
Conclusion: Due to differences in the pattern of growth and also lower anthropometric values, particularly among boys, it seems that a national growth curve can be a better guide for future decisions.

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Background and Objectives: Tuberculosis is a chronic bacterial disease and a major cause of morbidity and mortality. It is caused by a Mycobacterium tuberculosis. Awareness of the incidence and number of new cases of the disease is valuable information for revising the implemented programs and development indicators. time series and regression are commonly used models for prediction but these methods require some assumptions. The purpose of this study was to predict new TB cases using the hidden Markov model which does not require many assumption.
 
Methods: The data used in this study was the monthly number of new TB cases during 2006-2016 identified and recorded in Hamedan Province. Rorecasting the number of new TB cases was done using hidden Markov models using the hidden Markov package in the R software.
Results: According to the AIC and BIC criterion, two states had the best fit to the data, i.e. the data of this study were a mixture of two Poisson distributions with average number of event 5.96 and 10.2 respectively. The results also predicted the number of new cases over the next 24 months based on the hidden Markov model would be between 8 and 9 new cases in each month.
Conclusion: The hidden Markov model is the best model for prediction using the Markov chain. This model, in addition to detection of an appropriate model for the available data, can determine the transition probability matrix, which can help physicians predict the future state of the disease and take preventive measures befor reaching advanced stages.

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Background and Objectives: Researchers and health specialists are increasingly using self-reports to obtain information on chronic illnesses. This study was conducted to assess the validity of self-reports of diabetes based on a recent field survey in Mashhad.
 
Methods: In this cross-sectional study, we used the results of 2015 census in Mashhad, a population based survey of people over the age of 30 (n =307103), to determine the proportion of self-reported diabetes. The patient records of Sina Electronic Health Record system (SinaEHR®) coded as E11 and E12 approved by doctors were used as a reference. The sensitivity, specificity, positive predictive value, and negative predictive value were calculated with 95% confidence intervals.
 
Results: The sensitivity, specificity, PLR, NLR, PPV, and NPV of self-reported diabetes was 24.59% (95% CI: 23.97-25.21), 98.04% (95% CI: 97.99-98.09), 12.56% (95% CI: 12.11-13.02), 0.77% (95% CI: 0.76-0.78), 44.77% (95% CI: 43.89-45.67), and 95.27% (95% CI: 95.23-95.31), respectively. The sensitivity of self-reported diabetes was higher in men, Iranian individuals, single subjects, people aged 60 and over, individuals with a BMI of 18.5-25, and those with university education.
 
Conclusion: Although the sensitivity of self-reported diabetes was poor in this study, its specificity and positive and negative predictive values were good. Furthermore, the sensitivity of self-reported diabetes was higher in men, Iranian individuals, single subjects, people aged 60 and over, individuals with a BMI of 18.5-25, and those with university education. It seems that caution should be exercised in using self-reported data in epidemiological studies.

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Background and Objectives: Pulmonary embolism is a potentially fatal and prevalent event that has led to a gradual increase in the number of hospitalizations in recent years. For this reason, it is one of the most challenging diseases for physicians. The main purpose of this paper was to report a research project to compare different data mining algorithms to select the most accurate model for predicting pulmonary embolism in hospitalized patients. This model would provide the knowledge needed by the medical staff fir better decision making.
 
Methods: In this research, we designed a prediction model using different methods of machine learning that would best predict the probability of pulmonary embolism in patients at risk. Among data mining algorithms, Bayesian network, decisions tree (J48), logistic regression (LR), and sequential minimal optimization (SMO) were used. The data used in the study included risk factors and past history of patients admitted to the Lung Department of Shariati Hospital, Tehran, Iran.
 
Results: The results showed that the accuracy and specificity of all prediction models were satisfactory. The Bayesian model had the highest sensitivity in predicting pulmonary embolism.
 
Conclusion: Although the results showed a little difference in the performance of prediction models, the Bayesian model is a more appropriate tool to predict the occurrence of pulmonary embolism in hospitalized patients in this type of data. It can be considered a supportive approach along medical decisions to improve disease prediction.

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Background and Objectives: In survival analysis, using the Cox model to determine the effective factors requires the assumptions whose failure of leads to biased results. The aim of this paper was to determine the factors affecting the survival of metastatic gastric cancer patients using the non-parametric method of Randomized Survival Forest (RSF) model and to compare its result with the Cox model.
 
Methods: In this retrospective cohort study, 201 patients with metastatic gastric cancer were evaluated in Hamadan Province. Patient survival was calculated from diagnosis to death or end of study. Demographic characteristics (such as gender and age) and clinical variables (including stage, tumor size, etc.) were extracted from the patient records. Factors affecting survival were determined using the Cox model and RSF. Data analysis was performed using the R3.4.3 software and RandomForestSRC and survival packages.
 
Results: The mean (SD) age of patients was 61.5 (12.9) years old. The Cox model showed that chemotherapy (p=0.033) was effective in survival, and the results of fitting the RSF model showed that the most important variables affecting survival were type of surgery, location of metastasis, chemotherapy, age, tumor grade, surgery, number of involved lymph nodes, sex and radiotherapy. Based on the model appropriateness, the RSF model with log-rank split rule had a better performance compared to the Cox model.
 
Conclusion: If the number of variables is high and there is a relationship between the variables, the RSF method identifies the important and effective variables on survival with high accuracy without requiring restrictive assumptions compared to the Cox model.

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Background and Objectives: On 12 November 2017, an earthquake with a magnitude of 7.3 on the Richter scale occurred in Kermanshah Province. Explaining the challenges and needs of the victims in such circumstances can be an important source of information for future planning and better management of such conditions. Thus, the purpose of this study was to explain the challenges and needs of the earthquake victims.
 
Methods: This study was a qualitative study. Twenty-nine semi-structured interviews were conducted with managers, policymakers, and health and emergency relief providers in earthquake areas, and 10 focused group discussions were held with earthquake victims from December to February 2016. The data were analyzed using conventional content analysis.
 
Results: The needs and challenges in Kermanshah earthquake were classified into three periods after the earthquake: 1. Challenges and needs in the first few days with three sub-categories including management, rescue services, and urgent care, 2- Challenges and needs in the first few weeks  after the earthquake with three sub-categories including housing and emergency assistance, public health services, and access to health care; and 3. Needs and challenges in several months after the earthquake with four sub-categories including economic, social, infrastructural and health service needs.
 
Conclusion: Lack of unity of command was the main challenge in this earthquake. Another point was the health needs of victim earthquakes over time. Therefore, dispatching of aid forces to the affected areas during natural disasters should be based on planning and needs.

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Background and Objectives: The COVID-19 pandemic has led to major health and socioeconomic problems worldwide. This study was conducted to determine the clinical features and health behaviors related to COVID-19 in patients presenting to selected COVID-19 centers of North Khorasan University of Medical Sciences.
 
Methods: This cross-sectional study was carried out using stratified random sampling in 350 patients presenting to selected COVID-19 centers of North Khorasan University of Medical Sciences in August and September 2020. Demographic and clinical features and the data related to COVID-19 disease were collected using a researcher-made checklist and analyzed with the SPSS 24 software using chi-square test and logistic regression.
 
Results: Of 350 patients, 200 (57.1%) were male and the rest were female. The PCR test was positive in 72% of the patients. The highest percentage of infection was seen in self-employed subjects and driver, people in the age group 30-50 years, and male subjects. The highest observance of masking, hand washing, and social distancing was related to healthcare staff and the lowest was seen in self-employed people, drivers, and military staff. A history of attending a gas station increased the chance of a positive test by 2.3 times (95% CI: 1.13-4.79).
 
Conclusion: According to the results, age, gender, occupation and history of presence in crowded places are important determinants of infection and adherence to protocols.

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Background and Objectives: The incidence of rectal cancer is increasing in developing societies, especially in younger age groups. The aim of this study was to evaluate the factors affecting the survival of patients with rectal cancer in the presence of competing risks.
 
Methods: In this retrospective cohort study, the data of 121 patients with rectal cancer during 2001-2017 were studied. Death related to cancer progression was considered as the interest outcome and other causes of death were considered as competing risks. Cause-specific and sub-distribution hazard models were used to investigate the factors affecting patient survival in the presence of competing risk.
 
Results: The mean (SD) age of the patients was 53.4 (13.9) years and 68 patients (56.2%) were male. The results of log-rank test showed that sex, age, metastasis, type of first treatment, rate of penetration into intestinal wall, tumor location, number of lymphomas involved and tumor size had significant effects on the patient survival (P<0.05). Based on cause-specific and sub-distribution hazard models, tumor stage, lymph node metastasis, and tumor grade had significant effects on death hazard due to the cancer progression (P<0.05).
 
Conclusion: Due to the need to consider competing risks, the results of both competing risk methods showed that tumor grade, lymph node metastasis and stage increased the instantaneous hazard and hazard of cancer death. Therefore, to determine the specific risk factors for each cause of death in the survival analysis, competing risk methods should be used if there is more than one cause of death.

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Background and Objectives: low utility of health care services is one of the main determinants of not achieving desired health indicators in urban areas. This study aimed to investigate the barriers and facilitators of receiving health services from health centers in Kerman city, Iran.
 
Methods: This study was a qualitative study with a content analysis approach conducted in 2020. After selecting health centers with the experience of desirable or low utility services, purposive sampling continued until information saturation. A total of 78 staff members, recipients, and non-recipients of services citizens were interviewed semi-structured and face-to-face at health centers. All interviews were recorded and coded manually and then reviewed and analyzed using directional content analysis.
 
Results: The essential services for children and mothers, free services, and service providers' behavior were mentioned as facilitators of referral. Distance and physical factors, knowledge of different types of services, preference of private centers, time access, view of people on regular visits to centers, addresses and telephone numbers registered in the system, responsiveness to health needs, fear of disease disclosure, lack of human resources in the centers, and service providers' behavior, were among the barriers of visiting the centers.
 
Conclusion: According to the results of this study, an accurate understanding of the under-coverage people's views and perceptions can help national and local planners and policymakers design the necessary strategies to increase the use of health services in urban health centers.

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