Introducing novel key genes and transcription factors associated with rectal cancer response to chemoradiation through co-expression network analysis.

Preoperative radiochemotherapy is a promising therapeutic method for locally advanced rectal cancer patients. However, the response of colorectal cancer (CRC) patients to preoperative radiotherapy varies widely. In this study, we aimed to identify novel biomarkers that could predict the response of colorectal tumors to treatment using a systems biology approach. We applied the Weighted Gene Co-Expression Network Analysis to construct co-expression networks and evaluated the correlation of these networks with radiation using the module-trait relationship. We then identified hub genes and related transcription factors in the selected co-expression module. Our analysis of seven constructed modules revealed that one module, which contained 113 nodes and 6066 edges, had the strongest correlation with radiation effects on CRC (correlation = 0.85; p-value = 6e-7). By analyzing the selected module with the CytoHubba plugin, we identified four hub genes, including ZEB2, JAM2, NDN, and PPAP2A. We also identified seven important transcription factors, including KLF4, SUZ12, TCF4, NANOG, POU5F1, SOX2, and SMARCA4, which may play essential roles in regulating the four hub genes. In summary, our findings suggest that ZEB2, JAM2, NDN, and PPAP2A, along with the seven transcription factors related to these hub genes, may be associated with the response of colorectal tumors to chemoradiotherapy.

Machine Learning-based Classifiers for the Prediction of Low Birth Weight / 대한의료정보학회지

Objectives@#Low birth weight (LBW) is a global concern associated with fetal and neonatal mortality as well as adverse consequences such as intellectual disability, impaired cognitive development, and chronic diseases in adulthood. Numerous factors contribute to LBW and vary based on the region. The main objectives of this study were to compare four machine learning classifiers in the prediction of LBW and to determine the most important factors related to this phenomenon in Hamadan, Iran. @*Methods@#We carried out a retrospective cross-sectional study on a dataset collected from Fatemieh Hospital in 2017 that included 741 mother-newborn pairs and 13 potential factors. Decision tree, random forest, artificial neural network, support vector machine, and logistic regression (LR) methods were used to predict LBW, with five evaluation criteria utilized to compare performance. @*Results@#Our findings revealed a 7% prevalence of LBW. The average accuracy of all models was 87% or higher. The LR method provided a sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and accuracy of 74%, 89%, 7.04%, 29%, and 88%, respectively. Using LR, gestational age, number of abortions, gravida, consanguinity, maternal age at delivery, and neonatal sex were determined to be the six most important variables associated with LBW. @*Conclusions@#Our findings underscore the importance of facilitating timely diagnosis of causes of abortion, providing genetic counseling to consanguineous couples, and strengthening care before and during pregnancy (particularly for young mothers) to reduce LBW.

The factors in older adults' health literacy in the field of physical activity: a qualitative study.

BACKGROUND: Older adults are one of the most vulnerable groups to the undesirable effects of low health literacy. Inadequate health literacy in older adults is associated with decreased physical activity, deviation from the path of health, and suffering from various diseases. Considering the role and importance of health literacy in promoting physical activity and improving health in older adults and the hypothesis that there are certain factors associated with health literacy in the field of physical activity, this study is aimed at understanding the factors related to older adults' health literacy about physical activity. METHODS: This study is a qualitative study on older adults 60 to 75 years old in retirement centers in Kermanshah, Iran, in 2020. Totally, 25 participants were recruited through purposeful sampling with maximum variation until data saturation. The data were collected through in-depth semi-structured interviews and analyzed using directed qualitative content analysis. RESULTS: By analyzing the manuscripts obtained from the interviews, 59 initial codes were extracted, which were reduced to 32 main codes after careful assessment. The main codes were grouped into 13 subcategories under 5 categories. Subcategories are the detected factors that are related to health literacy and categories are the five aspects of health literacy including access, reading skill, comprehension, evaluation and decision-making, and application of information. Health literacy was the main theme that encompassed the categories. CONCLUSION: This study provided a comprehensive understanding of beliefs, opinions and factors related to older adults' health literacy about physical activity. According to these findings, physical problems and diseases are not obstacles to making decisions and applying physical activity information in older adults who have a high understanding and proper evaluation of physical activity recommendations. Support, advertising, and organizational facilities are related to all dimensions of older adults' health literacy about physical activity, while socio-economic factors are related to the dimensions of access, comprehension, decision-making, and application of information. The factors related to older adults' health literacy about physical activity that were identified in this study, can be used by organizations that are responsible for policy-making, decision-making, and implementing physical activity promotion programs to improve the health in older adults.

Physical Activity Health Literacy in Iranian Older Adults: Development and Psychometric Testing.

Inadequate health literacy decreases physical activity. This study aimed to develop and examine psychometrics of physical activity health literacy in Iranian older adults. This methodological work was conducted in two phases. Phase 1 consisted of extensive studies review and qualitative study to extract and design the items. The psychometrics were measured in Phase 2 included content, faceconstruct validities, reliability, and stability. The collected data were analyzed in SPSS (version 25.0) and AMOS (version 24.0). The results of the exploratory factor analysis showed four factors- information evaluation, reading skill, perception, and decision making-and used information that explained 70.08% of the variance. The model's fitness was supported by confirmatory factor analysis. Internal consistency based on Cronbach's alpha was .89 with composite reliability >0.85. Stability was confirmed through the test-retest method and intraclass correlation coefficient (.89-1). Psychometrics of physical activity health literacy in Iranian older adults supported validity and reliability of the tool.

Determining correlates of the average number of cigarette smoking among college students using count regression models.

College students, as a large part of young adults, are a vulnerable group to several risky behaviors including smoking and drug abuse. This study aimed to utilize and to compare count regression models to identify correlates of cigarette smoking among college students. This was a cross-sectional study conducted on students of Hamadan University of Medical Sciences. The Poisson, negative binomial, generalized Poisson, exponentiated-exponential geometric regression models and their zero-inflated counterparts were fitted and compared using the Vuong test (α = 0.05). A number of 1258 students participated in this study. The majority of students were female (60.8%) and their average age was 23 years. Most of the students were non-smokers (84.6%). Negative binomial regression was selected as the most appropriate model for analyzing the data (comparable fit and simpler interpretation). The significant correlates of the number of cigarettes smoked per day included gender (male: incident-rate-ratio (IRR = 9.21), birth order (Forth: IRR = 1.99), experiencing a break-up (IRR = 2.11), extramarital sex (heterosexual (IRR = 2.59), homosexual (IRR = 3.13) vs. none), and drug abuse (IRR = 5.99). Our findings revealed that several high-risk behaviors were associated with the intensity of smoking, suggesting that these behaviors should be considered in smoking cessation intervention programs for college students.

Position of the hyoid bone and its correlation with airway dimensions in different classes of skeletal malocclusion using cone-beam computed tomography

Purpose@#This study investigated the position of the hyoid bone and its relationship with airway dimensions in different skeletal malocclusion classes using cone-beam computed tomography (CBCT). @*Materials and Methods@#CBCT scans of 180 participants were categorized based on the A point-nasion-B point angle into class I, class Ⅱ, and class Ⅲ malocclusions. Eight linear and 2 angular hyoid parameters (H-C3, H-EB, H-PNS, H-Me, H-X, H-Y, H-[C3-Me], C3-Me, H-S-Ba, and H-N-S) were measured. A 3-dimensional airway model was designed to measure the minimum cross-sectional area, volume, and total and upper airway length. The mean cross-sectional area, morphology, and location of the airway were also evaluated. Data were analyzed using analysis of variance and the Pearson correlation test, with p values <0.05 indicating statistical significance. @*Results@#The mean airway volume differed significantly among the malocclusion classes (p<0.05). The smallest and largest volumes were noted in class Ⅱ (2107.8±844.7 mm3) and class Ⅲ (2826.6±2505.3 mm3), respectively. The means of most hyoid parameters (C3-Me, C3-H, H-Eb, H-Me, H-S-Ba, H-N-S, and H-PNS) differed significantly among the malocclusion classes. In all classes, H-Eb was correlated with the minimum cross-sectional area and airway morphology, and H-PNS was correlated with total airway length. A significant correlation was also noted between H-Y and total airway length in class Ⅱ and Ⅲ malocclusions and between H-Y and upper airway length in class I malocclusions. @*Conclusion@#The position of the hyoid bone was associated with airway dimensions and should be considered during orthognathic surgery due to the risk of airway obstruction.

Prediction of Serum Creatinine in Hemodialysis Patients Using a Kernel Approach for Longitudinal Data / 대한의료정보학회지

ObjectivesLongitudinal data are prevalent in clinical research; due to their correlated nature, special analysis must be used for this type of data. Creatinine is an important marker in predicting end-stage renal disease, and it is recorded longitudinally. This study compared the prediction performance of linear regression (LR), linear mixed-effects model (LMM), least-squares support vector regression (LS-SVR), and mixed-effects least-squares support vector regression (MLS-SVR) methods to predict serum creatinine as a longitudinal outcome.MethodsWe used a longitudinal dataset of hemodialysis patients in Hamadan city between 2013 and 2016. To evaluate the performance of the methods in serum creatinine prediction, the data was divided into two sets of training and testing samples. Then LR, LMM, LS-SVR, and MLS-SVR were fitted. The prediction performance was assessed and compared in terms of mean squared error (MSE), mean absolute error (MAE), mean absolute prediction error (MAPE), and determination coefficient (R2). Variable importance was calculated using the best model to select the most important predictors.ResultsThe MLS-SVR outperformed the other methods in terms of the least prediction error; MSE = 1.280, MAE = 0.833, and MAPE = 0.129 for the training set and MSE = 3.275, MAE = 1.319, and MAPE = 0.159 for the testing set. Also, the MLS-SVR had the highest R2, 0.805 and 0.654 for both the training and testing samples, respectively. Blood urea nitrogen was the most important factor in the prediction of creatinine.ConclusionsThe MLS-SVR achieved the best serum creatinine prediction performance in comparison to LR, LMM, and LS-SVR.

Factors associated with in-hospital death in patients with nosocomial infections: a registry-based study using community data in western Iran / 한국역학회지

Objectives@#Determining the predictors of in-hospital death related to nosocomial infections is an essential part of efforts made in the overall health system to improve the delivery of health care to patients. Therefore, this study investigated the predictors of in-hospital death related to nosocomial infections. @*Methods@#This registry-based, longitudinal study analyzed data on 8,895 hospital-acquired infections (HAIs) in Hamadan Province, Iran from March 2017 to December 2019. The medical records of all patients who had been admitted to the hospitals were extracted from the Iranian Nosocomial Infections Surveillance Software. The effects of the type and site of infection, as well as age group, on in-hospital death were estimated using univariate and multivariable Cox regression models. @*Results@#In total, 4,232 (47.8%) patients with HAIs were males, and their mean age was 48.25±26.22 years. In both sexes, most nosocomial infections involved Gram-negative bacteria and the most common site of infection was the urinary tract. Older patients had a higher risk of in-hospital death (adjusted hazard ratio [aHR], 2.26; 95% confidence interval [CI], 1.38 to 3.69 for males; aHR, 2.44; 95% CI, 1.29 to 4.62 for females). In both sexes, compared with urinary tract infections, an increased risk of in-hospital death was found for ventilator-associated events (VAEs) (by 95% for males and 93% for females) and bloodstream infections (BSIs) (by 67% for males and 82% for females). @*Conclusion@#We found that VAEs, BSIs, and fungal infections were independently and strongly associated with increased mortality.

Risk factors for low back pain among elementary school students in western Iran using penalized logistic regression / 한국역학회지

OBJECTIVES@#This study investigated the prevalence of low back pain (LBP) and its risk factors among elementary-school students. @*METHODS@#In this cross-sectional study, 693 elementary students from Hamadan city, western Iran, were selected by multistage stratified cluster sampling. Data were collected through interviews using questionnaires. Posture and psychosocial elements were assessed using the observational Rapid Upper Limb Assessment (RULA) checklist and the standard Strengths and Difficulties Questionnaire, respectively. Penalized logistic regression with the group smoothly-clipped absolute deviation regularization method was used for variable selection and data analysis (α=0.05). The chi-square test was also used. @*RESULTS@#In total, 26.6% of the students (7-12 years old) reported LBP in the last month. Older age (odds ratio [OR], 3.08; 95% confidence interval [CI], 1.80 to 5.26), watching TV for more than 3 hours a day (OR, 2.62; 95% CI, 1.46 to 4.68), very short seat backrests (OR, 3.08; 95% CI, 1.61 to 5.90), excessively curved seat backrests (OR, 4.36; 95% CI, 2.08 to 9.13), very short desks (OR, 3.44; 95% CI, 1.61 to 7.35), a family history of LBP (OR, 2.49; 95% CI, 1.58 to 3.91), carrying a school bag on one shoulder (OR, 1.91; 95% CI, 1.03 to 3.54), and RULA scores of 3 (OR, 2.26; 95% CI, 1.13 to 4.50) or 4 (OR, 2.85; 95% CI, 1.37 to 5.91) were associated with LBP. @*CONCLUSIONS@#A high prevalence of LBP was found among elementary-school students. This study underscores the importance of recognizing vulnerable children and teenagers and developing interventional health promotion programs to prevent LBP based on an appropriate consideration of its contributory factors.

Factors associated with in-hospital death in patients with nosocomial infections: a registry-based study using community data in western Iran / 한국역학회지

Objectives@#Determining the predictors of in-hospital death related to nosocomial infections is an essential part of efforts made in the overall health system to improve the delivery of health care to patients. Therefore, this study investigated the predictors of in-hospital death related to nosocomial infections. @*Methods@#This registry-based, longitudinal study analyzed data on 8,895 hospital-acquired infections (HAIs) in Hamadan Province, Iran from March 2017 to December 2019. The medical records of all patients who had been admitted to the hospitals were extracted from the Iranian Nosocomial Infections Surveillance Software. The effects of the type and site of infection, as well as age group, on in-hospital death were estimated using univariate and multivariable Cox regression models. @*Results@#In total, 4,232 (47.8%) patients with HAIs were males, and their mean age was 48.25±26.22 years. In both sexes, most nosocomial infections involved Gram-negative bacteria and the most common site of infection was the urinary tract. Older patients had a higher risk of in-hospital death (adjusted hazard ratio [aHR], 2.26; 95% confidence interval [CI], 1.38 to 3.69 for males; aHR, 2.44; 95% CI, 1.29 to 4.62 for females). In both sexes, compared with urinary tract infections, an increased risk of in-hospital death was found for ventilator-associated events (VAEs) (by 95% for males and 93% for females) and bloodstream infections (BSIs) (by 67% for males and 82% for females). @*Conclusion@#We found that VAEs, BSIs, and fungal infections were independently and strongly associated with increased mortality.

Risk factors for low back pain among elementary school students in western Iran using penalized logistic regression / 한국역학회지

OBJECTIVES@#This study investigated the prevalence of low back pain (LBP) and its risk factors among elementary-school students. @*METHODS@#In this cross-sectional study, 693 elementary students from Hamadan city, western Iran, were selected by multistage stratified cluster sampling. Data were collected through interviews using questionnaires. Posture and psychosocial elements were assessed using the observational Rapid Upper Limb Assessment (RULA) checklist and the standard Strengths and Difficulties Questionnaire, respectively. Penalized logistic regression with the group smoothly-clipped absolute deviation regularization method was used for variable selection and data analysis (α=0.05). The chi-square test was also used. @*RESULTS@#In total, 26.6% of the students (7-12 years old) reported LBP in the last month. Older age (odds ratio [OR], 3.08; 95% confidence interval [CI], 1.80 to 5.26), watching TV for more than 3 hours a day (OR, 2.62; 95% CI, 1.46 to 4.68), very short seat backrests (OR, 3.08; 95% CI, 1.61 to 5.90), excessively curved seat backrests (OR, 4.36; 95% CI, 2.08 to 9.13), very short desks (OR, 3.44; 95% CI, 1.61 to 7.35), a family history of LBP (OR, 2.49; 95% CI, 1.58 to 3.91), carrying a school bag on one shoulder (OR, 1.91; 95% CI, 1.03 to 3.54), and RULA scores of 3 (OR, 2.26; 95% CI, 1.13 to 4.50) or 4 (OR, 2.85; 95% CI, 1.37 to 5.91) were associated with LBP. @*CONCLUSIONS@#A high prevalence of LBP was found among elementary-school students. This study underscores the importance of recognizing vulnerable children and teenagers and developing interventional health promotion programs to prevent LBP based on an appropriate consideration of its contributory factors.

Prediction of Kidney Graft Rejection Using Artificial Neural Network / 대한의료정보학회지

OBJECTIVES: Kidney transplantation is the best renal replacement therapy for patients with end-stage renal disease. Several studies have attempted to identify predisposing factors of graft rejection; however, the results have been inconsistent. We aimed to identify prognostic factors associated with kidney transplant rejection using the artificial neural network (ANN) approach and to compare the results with those obtained by logistic regression (LR). METHODS: The study used information regarding 378 patients who had undergone kidney transplantation from a retrospective study conducted in Hamadan, Western Iran, from 1994 to 2011. ANN was used to identify potential important risk factors for chronic nonreversible graft rejection. RESULTS: Recipients' age, creatinine level, cold ischemic time, and hemoglobin level at discharge were identified as the most important prognostic factors by ANN. The ANN model showed higher total accuracy (0.75 vs. 0.55 for LR), and the area under the ROC curve (0.88 vs. 0.75 for LR) was better than that obtained with LR. CONCLUSIONS: The results of this study indicate that the ANN model outperformed LR in the prediction of kidney transplantation failure. Therefore, this approach is a promising classifier for predicting graft failure to improve patients' survival and quality of life, and it should be further investigated for the prediction of other clinical outcomes.