Zero-Inflated Count Regression Models in Solving Challenges Posed by Outlier-Prone Data; an Application to Length of Hospital Stay.

Introduction: Ignoring outliers in data may lead to misleading results. Length of stay (LOS) is often considered a count variable with a high frequency of outliers. This study exemplifies the potential of robust methodologies in enhancing the accuracy and reliability of analyses conducted on skewed and outlier-prone count data of LOS. Methods: The application of Zero-Inflated Poisson (ZIP) and robust Zero-Inflated Poisson (RZIP) models in solving challenges posed by outlier LOS data were evaluated. The ZIP model incorporates two components, tackling excess zeros with a zero-inflation component and modeling positive counts with a Poisson component. The RZIP model introduces the Robust Expectation-Solution (RES) algorithm to enhance parameter estimation and address the impact of outliers on the model's performance. Results: Data from 254 intensive care unit patients were analyzed (62.2% male). Patients aged 65 or older accounted for 58.3% of the sample. Notably, 38.6% of patients exhibited zero LOS. The overall mean LOS was 5.89 (± 9.81) days, and 9.45% of cases displayed outliers. Our analysis using the RZIP model revealed significant predictors of LOS, including age, underlying comorbidities (p<0.001), and insurance status (p=0.013). Model comparison demonstrated the RZIP model's superiority over ZIP, as evidenced by lower Akaike information criteria (AIC) and Bayesians information criteria (BIC) values. Conclusions: The application of the RZIP model allowed us to uncover meaningful insights into the factors influencing LOS, paving the way for more informed decision-making in hospital management.

Longitudinal machine learning model for predicting systolic blood pressure in patients with heart failure.

Objective: Systolic blood pressure (SBP) strongly indicates the prognosis of heart failure (HF) patients, as it is closely linked to the risk of death and readmission. Hence, maintaining control over blood pressure is a vital factor in the management of these patients. In order to determine significant variables associated with changes in SBP over time and assess the effectiveness of classical and machine learning models in predicting SBP, this study aimed to conduct a comparative analysis between the two. Methods: This retrospective cohort study involved the analysis of data from 483 patients with HF who were admitted to Farshchian Heart Center located in Hamadan in the west of Iran, and hospitalized at least two times between October 2015 and July 2019. To predict SBP, we utilized a linear mixed-effects model (LMM) and mixed-effects least-square support vector regression (MLS-SVR). The effectiveness of both models was evaluated based on the mean absolute error and root mean squared error. Results: The LMM analysis revealed that changes in SBP over time were significantly associated with sex, body mass index (BMI), sodium, time, and history of hypertension (P-value < 0.05). Furthermore, according to the MLS-SVR analysis, the four most important variables in predicting SBP were identified as history of hypertension, sodium, BMI, and triglyceride. In both the training and testing datasets, MLS-SVR outperformed LMM in terms of performance. Conclusions: Based on our results, it appears that MLS-SVR has the potential to serve as a viable alternative to classical longitudinal models for predicting SBP in patients with HF.

Balance-energy of resting state network in obsessive-compulsive disorder.

Stability of the brain functional network is directly linked to organization of synchronous and anti-synchronous activities. Nevertheless, impact of arrangement of positive and negative links called links topology requires to be well understood. In this study, we investigated how topology of the functional links reduce balance-energy of the brain network in obsessive-compulsive disorder (OCD) and push the network to a more stable state as compared to healthy controls. Therefore, functional associations between the regions were measured using the phase synchrony between the EEG activities. Subsequently, balance-energy of the brain functional network was estimated based on the quality of triadic interactions. Occurrence rates of four different types of triadic interactions including weak and strong balanced, and unbalanced interactions were compared. In addition, impact of the links topology was also investigated by looking at the tendency of positive and negative links to making hubs. Our results showed although the number of positive and negative links were not statistically different between OCD and healthy controls, but positive links in OCDs' brain networks have more tendency to make hub. Moreover, lower number of unbalanced triads and higher number of strongly balanced triad reduced the balance-energy in OCDs' brain networks that conceptually has less requirement to change. We hope these findings could shed a light on better understanding of brain functional network in OCD.

Pattern of weight gain in pregnant women in slum areas of Hamadan using multilevel ordinal regression.

BACKGROUND: Adequate gestational weight gain (GWG) is an important factor for maternal and fetal health. This is especially important in low-income and slum areas due to limited access to health services and malnutrition. Thus, the purpose of this study is to evaluate the pattern of GWG changes in the slum areas of Hamadan in Iran. METHODS: In this longitudinal study, the study sample consisted of 509 pregnant women who referred to nine health care clinics in the slum areas of Hamadan. Women's weight gain based on the recommended GWG by U.S. Institute of Medicine (IOM) was divided into three categories: Inadequate weight gain, Adequate weight gain, and Excessive weight gain. In order to evaluate the trend of GWG, a multi-level ordinal model was used. RESULTS: According to pre-pregnancy BMI, a little more than half people (56.6%) were overweight or obese. 85.4% women in the first trimester and 49.1% in the second trimester did not have adequate GWG, but in the third trimester (38.9%) had adequate GWG. Based on multivariate analysis, pre- pregnancy BMI has a significant effect on the odds of inadequate GWG (P-value = 0.021); with one unit increase in pre-pregnancy BMI, the odds of inadequate GWG grows by 1.07 times compared to adequate and excessive GWG. CONCLUSIONS: In general, women did not have adequate weight gain in the first and second trimesters.Thus, designing appropriate interventions to achieve optimal GWG seems to be necessary in slums.

Zero-augmented beta-prime model for multilevel semi-continuous data: a Bayesian inference.

Semi-continuous data characterized by an excessive proportion of zeros and right-skewed continuous positive values appear frequently in medical research. One example would be the pharmaceutical expenditure (PE) data for which a substantial proportion of subjects investigated may report zero. Two-part mixed-effects models have been developed to analyse clustered measures of semi-continuous data from multilevel studies. In this study, we propose a new flexible two-part mixed-effects model with skew distributions for nested semi-continuous cost data under the framework of a Bayesian approach. The proposed model specification consists of two mixed-effects models linked by the correlated random effects: Part I) a model on the occurrence of positive values using a generalized logistic mixed model; and Part II) a model on the magnitude of positive values using a linear mixed model where the model errors follow skew distributions including beta-prime (BP). The proposed method is illustrated with pharmaceutical expenditure data from a multilevel observational study and the analytic results are reported by comparing potential models under different skew distributions. Simulation studies are conducted to assess the performance of the proposed model. The DIC3, LPML, WAIC, and LOO as the Bayesian model selection criteria and measures of divergence used to compare the models.

Modeling of smoking intensity by age at smoking onset among Iranian adult male using generalized additive model.

Because the age at which a person first starts smoking has such a strong correlation with future smoking behaviours, it's crucial to examine its relationship with smoking intensity. However, it is still challenging to accurately prove this relationship due to limitations in the methodology of the performed studies. Therefore the main purpose of this study is to evaluate the potential risk factors affecting the intensity of smoking, especially the age of smoking onset among Iranian adult male smokers over 18 years of age using a generalized additive model (GAM). In GAM a latent variable with logistic distribution and identity link function was considered. Data from 913 Iranian male current smokers over the age of 18 was evaluated from a national cross-sectional survey of non-communicable disease (NCD) risk factors in 2016. Individuals were classified into: light, moderate, and heavy smokers. A GAM was used to assess the relationship. The results showed that 246 (26.9%) subjects were light smokers, 190 (20.8%) subjects were moderate smokers and 477 (52.2%) subjects were heavy smokers. According to the GAM results, the relationship was nonlinear and smokers who started smoking at a younger age were more likely to become heavy smokers. The factors of unemployment (OR = 1.364, 95% CI 0.725-2.563), retirement (OR = 1.217, 95% CI 0.667-2.223), and exposure to secondhand smoke at home (OR = 1.364, 95% CI 1.055-1.763) increased the risk of heavy smoking. but, smokers with high-income (OR = 0.742, 95% CI 0.552-0.998) had a low tendency to heavy smoking. GAM identified the nonlinear relationship between the age of onset of smoking and smoking intensity. Tobacco control programs should be focused on young and adolescent groups and poorer socio-economic communities.

Health and economic impacts of ambient air particulate matter (PM2.5) in Karaj city from 2012 to 2019 using BenMAP-CE.

The present study aims to estimate the effects of PM2.5 on the health and economy of Karaj city from 2012 to 2019. In this study, mortality attributed to long-term exposure to PM2.5 and its spatial distribution in Karaj over the 2012-2019 period were estimated using the Global Exposure Mortality Model (GEMM) concentration-response function and BenMAP software. PM2.5 hourly concentration data of air quality monitoring stations were used to estimate PM2.5 for the whole city of Karaj. The economic effects of this pollutant were also assessed using the value of statistical life (VSL) method. The results showed that the annual average PM2.5 concentration during the studied time increased and was higher than the air quality guideline levels recommended by the World Health Organization. Also, the annual number of deaths attributed to PM2.5 in adults (older than 25 years) was estimated to be about 1200. The highest to lowest proportions of PM2.5-related deaths were non-accidental mortality, ischemic heart attack, stroke, acute respiratory tract infection, chronic obstructive pulmonary disease (COPD), and lung cancer, in the order of their appearance. The results showed that the economic loss attributed to this pollutant was estimated at 380 to 504 million USD per year. Due to the effects of PM2.5 on health and the economy in this city, we suggest conducting special planning to control and reduce the concentration of ambient air particulate matter by improving the public transportation system and updating industrial processes.

Prevalence of renal scaring caused by urinary tract infections in children: a systematic review and meta-analysis.

PURPOSE. SOURCES OF INFORMATION: Urinary tract infection (UTI) is the second most common infection in children, the most important complication of which is renal scarring. The aim of present study was to evaluate the prevalence of renal scarring after UTI in children through systematic review and meta-analysis. METHODS: The international databases of Science Direct, PubMed, Scopus, and Web of Science and the Google Scholar search engine were searched using standard keywords. The sources found were from 2010 to 2020 and the search stage was updated until 2021.02.16. Data were analyzed using STATA-14 software and the significance level was considered at P<0.05. RESULTS: In 29 studies with a sample size of 9,986 children, the prevalence of renal scarring in children was estimated at 35% (95% CI: 29-41). Also, the prevalence of renal scarring was in girls 61% (95% CI: 40-81) and in boys 34% (95% CI: 11-57). The prevalence of unilateral renal scarring in children was 56% (95% CI: 48-65) and bilateral renal scarring was 31% (95% CI: 14-48). In addition, the prevalence of scar was 54% in children with reflux and 12% in children without vesicoureteral reflux. CONCLUSIONS: More than one third of people under the age of 18 after UTI have renal scarring. The prevalence of this complication in girls is about 2 times higher than that in boys and in people with reflux, it is about 4 times higher than people who do not have urinary reflux. Also, about half of people under the age of 18 suffer from unilateral renal scarring and about one third of them suffer from bilateral renal scarring.

Comparative study of laminin332-γ2 chain expression in oral lichen planus and squamous cell carcinoma by immunohistochemistry.

BACKGROUND: Classification of oral lichen planus (OLP) as a condition with malignant potential is still controversial. One of the major properties of malignancy is invasion. Ln332-γ2 chain plays a critical role in invasive activity of cancer cells. This study aims to compare Ln332-γ2 chain expression in OLP, oral epithelial dysplasia (OED) and oral squamous cell carcinoma (OSCC). METHODS: Ln332-γ2 expression was evaluated in 16 epithelial hyperplasia with no dysplasia (group A), 16 OLP (group B), 18 OED (group C) and 18 OSCC (group D) by immunohistochemistry. RESULTS: Except in A group, Ln332-γ2 expression was detected in other groups. There was a significant difference in Ln332-γ2 expression among B, C and D groups as well as between B and D, C and D groups (P<0.001). However, there was no significant difference between B and C groups (P=0.999). CONCLUSIONS: According to the findings of this study, the likelihood of similarity of OLP with premalignant dysplastic lesion can be suggested. This is not corroborating OLP definitive transformation to an OSCC. But it might be advisable that OLPs with >10% Ln332- γ2 expression may have a higher risk of cellular invasion occurrence and malignant transformation.

Identifying factors associated with the hospital readmission rate among patients with major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is a common recurrent mental disorder and one of the leading causes of disability in the world. The recurrence of MDD is associated with increased psychological and social burden, limitations for the patient, family, and society; therefore, action to reduce and prevent the recurrence of this disorder or hospital readmissions for depression among the patients is essential. METHODS: The data of this retrospective cohort study were extracted from records of 1005 patients with MDD hospitalized in Farshchian hospital in Hamadan city, Iran (2011-2018). The hospital readmissions rate due to depression episodes was modeled using generalized Poisson regression (GPR). Demographic and clinical characteristics of the patients were considered as explanatory variables. SAS v9.4 was used (P < 0.05). RESULTS: A majority of the patients were male (66.37%). The mean (standard deviation) of age at onset of MDD and the average number of hospital readmissions were 32.39 (13.03) years and 0.53 (1.84), respectively (most patients (74.3%) did not experience hospital readmissions). According to the results of the GPR, the lower age at the onset of the disease (IRR = 1.02;P = 0.008), illiteracy (IRR = 2.06;P = 0.003), living in urban areas (IRR = 1.56;P = 0.015), history of psychiatric illnesses in the family (IRR = 1.75;P = 0.004), history of emotional problems (IRR = 1.42;P = 0.028) and having medical disorders (IRR = 1.44;P = 0.035) were positively associated with the number of hospitalizations. CONCLUSION: According to our findings, urbanization, early onset of the disease, illiteracy, family history of mental illness, emotional problems, and medical disorders are among major risk factors associated with an increased number of hospital readmissions of MDD.

Predicting Hospital Readmission in Heart Failure Patients in Iran: A Comparison of Various Machine Learning Methods.

OBJECTIVES: Heart failure (HF) is a common disease with a high hospital readmission rate. This study considered class imbalance and missing data, which are two common issues in medical data. The current study's main goal was to compare the performance of six machine learning (ML) methods for predicting hospital readmission in HF patients. METHODS: In this retrospective cohort study, information of 1,856 HF patients was analyzed. These patients were hospitalized in Farshchian Heart Center in Hamadan Province in Western Iran, from October 2015 to July 2019. The support vector machine (SVM), least-square SVM (LS-SVM), bagging, random forest (RF), AdaBoost, and naïve Bayes (NB) methods were used to predict hospital readmission. These methods' performance was evaluated using sensitivity, specificity, positive predictive value, negative predictive value, and accuracy. Two imputation methods were also used to deal with missing data. RESULTS: Of the 1,856 HF patients, 29.9% had at least one hospital readmission. Among the ML methods, LS-SVM performed the worst, with accuracy in the range of 0.57-0.60, while RF performed the best, with the highest accuracy (range, 0.90-0.91). Other ML methods showed relatively good performance, with accuracy exceeding 0.84 in the test datasets. Furthermore, the performance of the SVM and LS-SVM methods in terms of accuracy was higher with the multiple imputation method than with the median imputation method. CONCLUSIONS: This study showed that RF performed better, in terms of accuracy, than other methods for predicting hospital readmission in HF patients.

Investigating the effect of behavioral and demographic characteristics of Iranian women on the number of children ever born.

Background: The number of children ever born (CEB) to a woman, as an index of her fertility behavior, are interesting for the governments and demographer policymakers. In recent years, a notable reduction of fertility and population aging in Iran has caused concern among politicians, and it has led to starting new changes in demographic policies. Therefore, to adopting new demographic and health policies programs, identification of factors that affecting CEB is essential. Methods: To evaluate determinant factors on CEB, information of 20093 married Iranian women aged between 15 and 54 years has been analyzed from the Iranian National Institute of Health Research survey. Based on the structure of data and the possible influential unobserved population heterogeneity on CEB in each city and province, a multilevel count regression model was applied. The analysis was performed using the 'R' software (version 3.5) with a significant level of 0.05. Results: Findings show that the mean and median number of CEB was 2.82 and 2.00 for all women, respectively. Meanwhile, these values were 4.56 and 4.00 for the women who reached menopause. There was a significant unobserved heterogeneity affecting CEB in each province (σp=0.018). Also, the results of the multilevel model show that living in an urban area (RR=0.90), higher age at first marriage (RR=0.96), higher education (RR=0.84, RR=0.81), and exposure to mass media (RR=0.87) decrease the risk ratio of the number of CEB (p <0.001). Conclusion: It seems that the tendency of women to academic education and their access to mass media has a significant effect on reducing childbearing. Therefore, in future planning, attention to these two factors can be useful and helpful to move to increase fertility.

Assessing the Factors Affecting Cesarean Section Selection in Iranian Women Using Multilevel Count Models with Excess Zeros.

BACKGROUND: Iran has ranked second in the frequency of cesarean delivery (CD) and this rate in 2014 has increased by 56 percent. The CD has multiple complications for the woman and newborn, and due to the women's readmission after surgery impose additional costs to the countries. Although CD has many complications and is not recommended by obstetrician and midwives; some factors affect the choice of this method of delivery. METHODS: We used data from the Iranian Institute for Health Sciences Research (IIHSR) in 2015. We studied the effects of factors such as socioeconomic and demographic factors and supplemental insurance status in the choice of CD. We used multilevel Zero-Inflated models for the modeling of data. RESULTS: The employed women resident in urban areas with the high-income and age greater than 34-yr old and supplemental insurance more likely chose CD. On the other hand, women with high education level, women who use at least one media (e.g. Radio, television, etc.) and women that use contraceptive methods have chosen the less CD. CONCLUSION: Our findings highlighted the importance of supplemental insurance and socio-economic status in choosing a CD by women. However, in some cases especially in the rich class of society, the high cost of this type of delivery does not affect the choice decrease of it, and governments should adopt rigorous policies in using this method.

Polyethylene eye-cover versus artificial teardrops in the prevention of ocular surface diseases in comatose patients: A prospective multicenter randomized triple-blinded three-arm clinical trial.

BACKGROUND: Polyethylene covers are claimed to be useful in preventing ocular surface diseases (OSD); however, evidence of their clinical efficacy is limited. This clinical trial aimed to compare the use of polyethylene eye covers and artificial teardrops versus normal saline on the incidence and severity of OSD in comatose patients. METHODS: Of 90 eligible patients randomly assigned to three treatment groups, 79 patients completed the study, In group A, patients (n = 25) received artificial teardrops for left and normal saline for right eyes, in group B (n = 29) polyethylene covers for left and normal saline for right eyes, and in group C (n = 25) polyethylene covers for left and artificial teardrops for right eyes. As the patients were comatose, their blinding did not applicable, and a blinded observer evaluated the patients' eyes based on the Corneal Fluorescein Staining Pattern. The blinded analyzer analyzed collected data by SPSS-16 software at a 95% confidential level. RESULTS: The OSDs were observed in 65 (41.14%) out of 158 eyes examined. The artificial teardrop was more effective than the normal saline in group A, polyethylene eye cover was more useful than the normal saline in group B, and polyethylene eye cover was more effective than the artificial teardrop in group C in reducing the incidence of OSD (p< 0.01). Polyethylene eye covers had the most impact on reducing the severity of the OSD compared to the other interventions (p< .001). CONCLUSIONS: Polyethylene eye covers significantly reduced the incidence and severity of OSD. Using polyethylene cover is suggested as a safe, effective, and accessible eye care intervention for preventing OSD in comatose patients. TRIAL REGISTRATION: (IRCT201609129014N115), Iranian Registry of Clinical Trials.

Longitudinal Joint Modelling of Ordinal and Overdispersed Count Outcomes: A Bridge Distribution for the Ordinal Random Intercept.

Associated longitudinal response variables are faced with variations caused by repeated measurements over time along with the association between the responses. To model a longitudinal ordinal outcome using generalized linear mixed models, integrating over a normally distributed random intercept in the proportional odds ordinal logistic regression does not yield a closed form. In this paper, we combined a longitudinal count and an ordinal response variable with Bridge distribution for the random intercept in the ordinal logistic regression submodel. We compared the results to that of a normal distribution. The two associated response variables are combined using correlated random intercepts. The random intercept in the count outcome submodel follows a normal distribution. The random intercept in the ordinal outcome submodel follows Bridge distribution. The estimations were carried out using a likelihood-based approach in direct and conditional joint modelling approaches. To illustrate the performance of the model, a simulation study was conducted. Based on the simulation results, assuming a Bridge distribution for the random intercept of ordinal logistic regression results in accurate estimation even if the random intercept is normally distributed. Moreover, considering the association between longitudinal count and ordinal responses resulted in estimation with lower standard error in comparison to univariate analysis. In addition to the same interpretation for the parameter in marginal and conditional estimates thanks to the assumption of a Bridge distribution for the random intercept of ordinal logistic regression, more efficient estimates were found compared to that of normal distribution.

Diet, Nutrition, Obesity, and Their Implications for COVID-19 Mortality: Development of a Marginalized Two-Part Model for Semicontinuous Data.

BACKGROUND: Nutrition is not a treatment for COVID-19, but it is a modifiable contributor to the development of chronic disease, which is highly associated with COVID-19 severe illness and deaths. A well-balanced diet and healthy patterns of eating strengthen the immune system, improve immunometabolism, and reduce the risk of chronic disease and infectious diseases. OBJECTIVE: This study aims to assess the effect of diet, nutrition, obesity, and their implications for COVID-19 mortality among 188 countries by using new statistical marginalized two-part models. METHODS: We globally evaluated the distribution of diet and nutrition at the national level while considering the variations between different World Health Organization regions. The effects of food supply categories and obesity on (as well as associations with) the number of deaths and the number of recoveries were reported globally by estimating coefficients and conducting color maps. RESULTS: The findings show that a 1% increase in supplementation of pulses reduced the odds of having a zero death by 4-fold (OR 4.12, 95% CI 11.97-1.42). In addition, a 1% increase in supplementation of animal products and meat increased the odds of having a zero death by 1.076-fold (OR 1.076, 95% CI 1.01-1.15) and 1.13-fold (OR 1.13, 95% CI 1.0-1.28), respectively. Tree nuts reduced the odds of having a zero death, and vegetables increased the number of deaths. Globally, the results also showed that populations (countries) who consume more eggs, cereals excluding beer, spices, and stimulants had the greatest impact on the recovery of patients with COVID-19. In addition, populations that consume more meat, vegetal products, sugar and sweeteners, sugar crops, animal fats, and animal products were associated with more death and less recoveries in patients. The effect of consuming sugar products on mortality was considerable, and obesity has affected increased death rates and reduced recovery rates. CONCLUSIONS: Although there are differences in dietary patterns, overall, unbalanced diets are a health threat across the world and not only affect death rates but also the quality of life. To achieve the best results in preventing nutrition-related pandemic diseases, strategies and policies should fully recognize the essential role of both diet and obesity in determining good nutrition and optimal health. Policies and programs must address the need for change at the individual level and make modifications in society and the environment to make healthier choices accessible and preferable.

Mapping Drug Prescription, Polypharmacy, and Pharmaceutical Spending in Older Adults in Iran: A Multilevel Analysis Based on Claims Data.

Background: To date, comprehensive data on drug utilization in Iranian people are lacking. The purpose of this study was to graphically describe drug prescription, polypharmacy, and pharmaceutical spending in > 3 million Iranian elderly people. Methods: In this multilevel cross-sectional study, using administrative claims data provided by the Iran Health Insurance Organization (IHIO), we assessed drug claims and drug costs in 2018 in >3 million individuals living in Iran and who have been insured with health insurance (Bimeh Salamat). In particular, we analyzed the prevalence of polypharmacy and pharmaceutical spending use according to the annual Report of Iranian Health Insurance Organization. Multilevel ordinal logistic and multilevel beta regression models were used to analyze the data. Significance level was set as P ≤ .05 and CI at 95%. Results: Nationally, the mean number of drug prescriptions per patient was 1.46 (SD, 0.81). The mean number of prescribed drugs per patient was 4.32 (SD, = 3.04). The drug cost for each elderly patient was $6.86 (interquartile range (IQR), 12.26), with $4.96 and $1.76 for the insurance and the insured shares, respectively. For elderly women, the odds of polypharmacy (excessive and nonexcessive vs no polypharmacy) were 1.164 (95% CI, 1.142 to 1.186) times that of elderly men. In addition, in the spring season, the odds of polypharmacy were 1.274 (95% CI, 1.241 to 1.309) times that of the winter. Similarly, polypharmacy was strongly higher among patients who had noncommunicable diseases (OR, 2.174; 95% CI, 2.069 to 2.275 (P < 0.001)). Conclusion: The high prevalence of hyper prescription in Iran elderly people may indicate a need for interventions aiming at deprescribing drugs with an unfavorable benefit-risk profile. The best practice guidelines should be developed for improved medical practice in the prescription of medications for such a vulnerable population.

Evaluation of Salivary Helicobacter pylori, Calcium, Urea, pH and Flow Rate in Hemodialysis Patients.

BACKGROUND: Helicobacter pylori infection is identified as a major cause of stomach ulcers, chronic inflammation and gastric cancer in hemodialysis patients. Dialysis also leads to changes in the composition and flow of saliva. OBJECTIVE: The aim of this study was to investigate the salivary Helicobacter pylori infection, Calcium, Urea, pH and flow rate in hemodialysis patients in comparison to the healthy control group. METHODS: In this study 48 hemodialysis patients and 48 healthy subjects were compared. The prevalence of Helicobacter pylori infection was determined by PCR method. Calcium, Urea, pH, salivary flow and gastrointestinal complications in both groups were measured and compared. RESULTS: Prevalence of Helicobacter pylori was 12.48 (25.0%) in the study group and 2.48 (4.2%) in the controls (P=0.000). Urea, calcium and pH were significantly higher in the patient group. The mean salivary flow rate decreased significantly in the patient group. 58.3% of patients group had gastrointestinal complications. CONCLUSION: Oral cavity as an important external source of Helicobacter pylori may play an important role in gastrointestinal problems of hemodialysis patients. Helicobacter pylori, Urea, calcium and pH were significantly higher in the patient group. Chronic renal failure can increase pH, urea and calcium in saliva and decrease salivary flow rate.

Robust inference in the joint modeling of multilevel zero-inflated Poisson and Cox models.

A popular method for simultaneously modeling of correlated count response with excess zeros and time to event is by means of the joint models. In these models, the likelihood-based methods (such as expectation-maximization algorithm and Newton-Raphson) are used for estimating the parameters, but in the presence of contaminations, these methods are unstable. To overcome this challenge, we extend the M-estimator methods and propose a robust estimator approach to obtain a robust estimation of the regression parameters in the joint model. Our proposed algorithm has two steps (Expectation and Solution). In the expectation step, the likelihood function is expected by conditioning on the observed data and in the solution step, the parameters are computed, with solving robust estimating equations. Therefore, this algorithm achieves robustness by applying robust estimating equations and weighted likelihood in the S-step. Simulation studies under various situations of contaminations show that the robust algorithm gives us consistent estimates with a smaller bias than likelihood-based methods. The application section uses data on factors affecting fertility and birth spacing.

Seroprevalence of Brucellosis among General Population in Famenin City, Western Iran in 2016: The Famenin Brucellosis Cohort Study.

BACKGROUND: Brucellosis is endemic in Iran with a higher level of endemicity in western areas, including the Hamadan province. This study aims to define the seroprevalence of brucellosis and it,s risk factors in general the population of Famenin, Hamadan province, in western Iran. METHODS: This survey was conducted on 2367 participants in Famenin and its villages from September to November 2016. After receiving written consent from subjects, demographic information was obtained through questionnaires and 10cc blood samples were taken from the participants. Blood samples were sent to the Core facility of Hamadan University of Medical Sciences and were tested using Wright and 2ME kits (Pasteur Institute, Iran) for serological detection of brucellosis. The seroprevalence of brucellosis was reported as percentage with 95% confidence interval (CI). RESULTS: Totally, 2367 individuals with the mean age (SD) of 34.6 (20.9) (range: 2 to 95) years were enrolled. Of these, 1060 (44.8%) were men and 1610 (68.0%) lived in rural areas. The seroprevalence of brucellosis according to the Wright titer (equal to or greater than 1:80) was 6.6% (95% CI: 5.62%, 7.66%). The corresponding prevalence based on 2ME titers (equal to or greater than 1:40) in subjects with positive Wright test was 37.2% (95% CI: 29.5%, 44.84%). We saw a significant association between the incidence of brucellosis and occupation (P < 0.001) and type of contact with livestock (P = 0.009) as two important risk factors. CONCLUSION: The seroprevalence of brucellosis in Famenin population was considerable. Contact with livestock, animal husbandry, farming and history of brucellosis were risk factors for brucellosis infection.