Knowledge, Attitude, and Practice Regarding Cardiovascular Disease among Coronary Artery Disease and Premature Coronary Artery Disease Patients Referred to Imam Hossein Hospital, Tehran, Iran.

Background: Knowledge, attitudes, and practices (KAP) studies are widely used in public health. This study aimed to investigate and compare KAP among patients with coronary artery disease (CAD) and premature coronary artery disease (PCAD) regarding cardiovascular disease (CVD). Methods: This cross-sectional study was conducted on 100 PCAD patients and 100 CAD patients in a general hospital in Tehran, Iran, between April and October 2022. A valid questionnaire was utilized to gather information, and descriptive analysis and logistic regression were employed for analysis using SPSS, version 23. Results: This study involved 100 CAD and 100 PCAD patients with average ages of 68.09±7.20 and 50.20±7.65 years, respectively. Men accounted for 58% of the PCAD group and 73% of the CAD group. The PCAD group had a higher level of knowledge and exhibited a more positive attitude toward CVD than the CAD group (P=0.007 and P<0.001, respectively). The PCAD patients and those with a family history of chronic diseases had a higher level of knowledge (P=0.045 and P=0.27, respectively) and showed a more positive attitude (P=0.030 and P<0.001, respectively). However, participants with a self-reported history of chronic diseases and those who were employed exhibited a less positive attitude. Occupation was associated with nutritional and smoking status (P=0.037). Conclusion: Higher levels of knowledge and more positive attitudes regarding CVD were observed; still, the study population's behaviors were unsatisfactory. Educational interventions are needed to promote positive health behaviors, emphasizing the link between knowledge and risk reduction and decreased CVD and mortality rates.

Risk Factors of Readmission in COVID-19 Patients; a Retrospective 6-Month Cohort Study.

Introduction: The available literature regarding the rate of readmission of COVID-19 patients after discharge is rather scarce. Thus, the aim in the current study was to evaluate the readmission rate of COVID-19 patients and the components affecting it, including clinical symptoms and relevant laboratory findings. Methods: In this retrospective cohort study, COVID-19 patients who were discharged from Imam Hossein hospital, Tehran, Iran, were followed for six months. Data regarding their readmission status were collected through phone calls with COVID-19 patients or their relatives, as well as hospital registry systems. Eventually, the relationship between demographic and clinical characteristics and readmission rate was assessed. Results: 614 patients were entered to the present study (mean age 58.7±27.2 years; 51.5% male). 53 patients were readmitted (8.6%), of which 47 patients (7.6%) had a readmission during the first 30 days after discharge. The reasons for readmission were relapse of COVID-19 symptoms and its pulmonary complications in 40 patients (6.5%), COVID-19 related cardiovascular complications in eight patients (1.3%), and non-COVID-19 related causes in five patients (0.8%). Older age (OR=1.04; 95% CI: 1.01, 1.06; p=0.002) and increased mean arterial pressure during the first admission (OR=1.04; 95% CI: 1.01, 1.08; p=0.022) were found to be independent prognostic factors for the readmission of COVID-19 patients. Conclusion: Readmission is relatively frequent in COVID-19 patients. Lack of adequate hospital space may be the reason behind the early discharge of COVID-19 patients. Hence, to reduce readmission rate, extra care should be directed towards the discharge of older or hypertensive patients.

Comparing the Characteristics of Mucormycosis Between Cases with and without COVID-19; a Cross-sectional Study.

Introduction: Mucormycosis as a rare but life-threatening disease with 46-96% mortality, which challenged the healthcare system during the COVID-19 pandemic. This study aimed to compare the characteristics of mucormycosis between cases with and without COVID-19. Methods: This cross-sectional study was done in two referral hospitals, Imam Hossein and Labbafinezhad Hospitals, Tehran, Iran, between 21 March to 21 December 2021. Data related to all hospitalized adults subject with the diagnosis of mucormycosis during the study period was collected from patients' profiles and they were divided into two groups of with and without COVID-19 based on the results of real time PCR. Then demographic, clinical, and laboratory findings as well as outcomes were compared between the two groups. Results: 64 patients with the mean age of 53.40±10.32 (range: 33-74) years were studied (53.1% male). Forty-three (67.2%) out of the 64 subjects had a positive COVID-19 PCR test. The two groups had significant differences regarding some symptoms (cough (p < 0.001), shortness of breath (p = 0.006)), acute presentation (p = 0.027), using immunosuppressive (p = 0.013), using corticosteroid (p < 0.001), and outcomes (mortality (p = 0.018), need for intubation (p < 0.001)). 22 (34.3%) patients expired during hospital admission. Univariate analysis showed the association of in-hospital mortality with need for ventilation (p < 0.001), sinus involvement (p = 0.040), recent use of dexamethasone (p = 0.011), confirmed COVID-19 disease (p = 0.025), mean body mass index (BMI) (p =0.035), hemoglobin A1c (HbA1c) (p = 0.022), and median of blood urea nitrogen (BUN) (p =0.034). Based on the multivariate model, confirmed COVID-19 disease (OR = 5.01; 95% CI: 1.14-22.00; p = 0.033) and recent use of dexamethasone (OR= 4.08, 95% CI: 1.05-15.84, p = 0.042) were independent predictors of mortality in this series. Conclusion: The mucormycosis cases with concomitant COVID-19 disease had higher frequency of cough and shortness of breath, higher frequency of acute presentation, higher need for immunosuppressive, corticosteroid, and ventilator support, and higher mortality rate. The two groups were the same regarding age, gender, BMI, risk factors, underlying diseases, symptoms, and sites of involvement.

Electrodiagnostic signs of carpal tunnel syndrome in ocular pseudoexfoliation syndrome.

PURPOSE: To assess the occurrence and severity of electrodiagnostic signs of carpal tunnel syndrome (ED-CTS) in patients with ocular pseudoexfoliation (PEX) and compare them with normal subjects. METHOD: A cross-sectional study with comparison group was designed and 60 patients with PEX were recruited from May 2019 to February 2021, and the findings were compared with 59 healthy subjects. All patients underwent complete ophthalmologic examination and nerve conduction velocity test at the median nerve was used to assess the occurrence and severity of ED-CTS in both hands. RESULTS: The mean age of participants was 59.8 ± 4.5 years. Occurrence of ED-CTS was 38.3% in PEX patients and 20.3% in control subjects (P = 0.025). There was also a significant difference in the severityand presence of asymptomatic CTS (P < 0.05). Adjusting other variables, including; age and sex, having severe ED-CTS showed a 3.07fold higher chance in the PEX group (P = 0.005). CONCLUSION: According to our finding, it seems there is a direct association between PEX and the occurrence, as well as severity of ED-CTS.

Six-Month Follow-up of COVID-19 Patients: Mortality and Related Factors.

BACKGROUND: Currently, there is lack of evidence regarding the long-term follow-up of coronavirus disease 2019 (COVID-19) patients. The aim of this study is to present a 6-month follow-up of COVID-19 patients who were discharged from hospital after their recovery. METHODS: This retrospective cohort study was performed to assess the six-month follow-up of COVID-19 patients who were discharged from the hospital between February 18 and July 20, 2020. The primary outcome was 6-month all-cause mortality. RESULTS: Data related to 614 patients were included to this study. Of these 614 patients, 48 patients died (7.8%). The cause of death in 26 patients (54.2%) was the relapse of COVID-19. Also, 44.2% of deaths happened in the first week after discharge and 74.4% in the first month. Risk factors of all-cause mortality included increase in age (odds ratio [OR]=1.09; P<0.001), increase in neutrophil percentage (OR=1.05; P=0.009) and increase in heart rate (OR=1.06; P=0.002) on the first admission. However, the risk of all-cause death was lower in patients who had higher levels of hematocrit (OR=0.93; P=0.021), oxygen saturation (OR=0.90; P=0.001) and mean arterial pressure (OR=0.93; P=0.001). In addition, increase in age (OR=1.11; P<0.001) was an independent risk factor for COVID-19-related death, while higher levels of lymphocyte percentage (OR=0.96; P=0.048), mean arterial pressure (OR=0.93; P=0.006) and arterial oxygen saturation (OR=0.91; P=0.009) were protective factors against COVID-19-related deaths during the 6-month period after discharge. CONCLUSION: Death is relatively common in COVID-19 patients after their discharge from hospital. In light of our findings, we suggest that elderly patients who experience a decrease in their mean arterial pressure, oxygen saturation and lymphocyte count during their hospitalization, should be discharged cautiously. In addition, we recommend that one-month follow-up of discharged patients should be take place, and urgent return to hospital should be advised when the first signs of COVID-19 relapse are observed.

Development of a scoring system for the prediction of in-hospital mortality among COVID-19 patients.

BACKGROUND: The aim of this study is to develop and validate a scoring system as a tool for predicting the in-hospital mortality in COVID-19 patients in early stage of disease. METHODS: This retrospective cohort study, conducted on 893 COVID-19 patients in Tehran from February 18 to July 20, 2020. Potential factors were chosen via stepwise selection and multivariable logistic regression model. Cross-validation method was employed to assess the predictive performance of the model as well as the scoring system such as discrimination, calibration, and validity indices. RESULTS: The COVID-19 patients' median age was 63 yrs (54.98% male) and 233 (26.09%) patients expired during the study. The scoring system was developed based on 8 selected variables: age ≥55 yrs (OR = 5.67, 95% CI: 3.25-9.91), males (OR = 1.51, 95% CI: 1.007-2.29), ICU need (OR = 16.32, 95% CI 10.13-26.28), pulse rate >90 (OR = 1.89, 95% CI: 1.26-2.83), lymphocytes <17% (OR = 2.33, 95%CI: 1.54-3.50), RBC ≤4, 10 6/L (OR = 2.10, 95% CI: 1.35-3.26), LDH >700 U/L (OR = 1.68, 95%CI: 1.13-2.51) and troponin I level >0.03 ng/mL (OR = 1.75, 95%CI: 1.17-2.62). The AUC and the accuracy of scoring system after cross-validation were 79.4% and 79.89%, respectively. CONCLUSION: This study showed that developed scoring system has a good performance and can use to help physicians for identifying high-risk patients in early stage of disease .

Electrocardiographic Findings and In-Hospital Mortality of COVID-19 Patients; a Retrospective Cohort Study.

BACKGROUND: Although current evidence points to the possible prognostic value of electrocardiographic (ECG) findings for in-hospital mortality of COVID-19 patients, most of these studies have been performed on a small sample size. In this study, our aim was to investigate the ECG changes as prognostic indicators of in-hospital mortality. METHODS: In a retrospective cohort study, the findings of the first and the second ECGs of COVID-19 patients were extracted and changes in the ECGs were examined. Any abnormal finding in the second ECG that wasn't present in the initial ECG at the time of admission was defined as an ECG change. ECGs were interpreted by a cardiologist and the prognostic value of abnormal ECG findings for in-hospital mortality of COVID-19 patients was evaluated using multivariate analysis and the report of the relative risk (RR). RESULTS: Data of the ECGs recorded at the time of admission were extracted from the files of 893 patients; likewise, the second ECGs could be extracted from the records of 328 patients who had an initial ECG. The presence of sinus tachycardia (RR = 2.342; p <0.001), supraventricular arrhythmia (RR = 1.688; p = 0.001), ventricular arrhythmia (RR = 1.854; p = 0.011), interventricular conduction delays (RR = 1.608; p = 0.009), and abnormal R wave progression (RR = 1.766; p = 0.001) at the time of admission were independent prognostic factors for in-hospital mortality. In the second ECG, sinus tachycardia (RR = 2.222; p <0.001), supraventricular arrhythmia (RR = 1.632; p <0.001), abnormal R wave progression (RR = 2.151; p = 0.009), and abnormal T wave (RR = 1.590; p = 0.001) were also independent prognostic factors of in-hospital mortality. Moreover, by comparing the first and the second ECGs, it was found that the incidence of supraventricular arrhythmia (RR = 1.973; p = 0.005) and ST segment elevation/depression (RR = 2.296; p <0.001) during hospitalization (ECG novel changes) are two independent prognostic factors of in-hospital mortality in COVID-19 patients. CONCLUSION: Due to the fact that using electrocardiographic data is easy and accessible and it is easy to continuously monitor patients with this tool, ECGs can be useful in identifying high-risk COVID-19 patients for mortality.

Deep Learning Analysis in Prediction of COVID-19 Infection Status Using Chest CT Scan Features.

Background and aims Non-contrast chest computed tomography (CT) scanning is one of the important tools for evaluating of lung lesions. The aim of this study was to use a deep learning approach for predicting the outcome of patients with COVID-19 into two groups of critical and non-critical according to their CT features. Methods This was carried out as a retrospective study from March to April 2020 in Baqiyatallah Hospital, Tehran, Iran. From total of 1078 patients with COVID-19 pneumonia who underwent chest CT, 169 were critical cases and 909 were non-critical. Deep learning neural networks were used to classify samples into critical or non-critical ones according to the chest CT results. Results The best accuracy of prediction was seen by the presence of diffuse opacities and lesion distribution (both=0.91, 95% CI: 0.83-0.99). The largest sensitivity was achieved using lesion distribution (0.74, 95% CI: 0.55-0.93), and the largest specificity was for presence of diffuse opacities (0.95, 95% CI: 0.9-1). The total model showed an accuracy of 0.89 (95% CI: 0.79-0.99), and the corresponding sensitivity and specificity were 0.71 (95% CI: 0.51-0.91) and 0.93 (95% CI: 0.87-0.96), respectively. Conclusions The results showed that CT scan can accurately classify and predict critical and non-critical COVID-19 cases.

A doubly-inflated Poisson regression for correlated count data.

Count data have emerged in many applied research areas. In recent years, there has been a considerable interest in models for count data. In modelling such data, it is common to face a large frequency of zeroes. The data are regarded as zero-inflated when the frequency of observed zeroes is larger than what is expected from a theoretical distribution such as Poisson distribution, as a standard model for analysing count data. Data analysis, using the simple Poisson model, may lead to over-dispersion. Several classes of different mixture models were proposed for handling zero-inflated data. But they do not apply to cases when inflated counts happen at some other points, in addition to zero. In these cases, a doubly-inflated Poisson model has been suggested which only be used for cross-sectional data and cannot consider correlations between observations. However, correlated count data have a large application, especially in the health and medical fields. The present study aims to introduce a Doubly-Inflated Poisson models with random effect for correlated doubly-inflated data. Then, the best performance of the proposed method is shown via different simulation scenarios. Finally, the proposed model is applied to a dental study.

Global Incidence and Mortality Rate of COVID-19; Special Focus on Iran, Italy and China.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a new coronavirus, was diagnosed in China in December 2019. Around the globe, a total of 71429 were infected up to February 17, 2020, with 98.9% of cases in China. On March 11, 2020, the World Health Organization (WHO) characterized the COVID-19 as 'pandemic'. Rapid positive worldwide incidence was the motivation behind this study to investigate the incidence and mortality globally. METHODS: We used the data published by the WHO until March 9, 2020. Non-parametric tests and change point analysis were used for inferences. RESULTS: Change point analysis for Iran and China and the world excluding China for the first 20 days revealed around 78, 195 and 2 further new cases per day, respectively. Italy had a big jump in incidence on the 36th day. Similarly, a sharp rise of positive cases was reported for the world on the 35th day. China successfully controlled the ascending reports of incidence on the 23rd day. Mortality in China and the world were almost similar for the first 20 days. There was an ascending incidence trend with two change points in Italy (30th and 36th days) and one change point in Iran on the 17th day. Mortality in the world jumped remarkably after day 42 with an estimation of almost more than 25 deaths per day. CONCLUSION: The incidence of COVID-19 varied by regions; however, after March 11, it became 'pandemic'. It was observed that after about 6 days with an emergence of sharp increase in incidences, there would be a mutation in mortality rate. On the other hand, the importance of 'on-time' quarantine programs in controlling this virus was confirmed.

Bayesian Zero- Inflated Poisson model for prognosis of demographic factors associated with using crystal meth in Tehran population.

Background: Use of methamphetamine (MA) and other stimulants has increased steadily over the past 10 years. Risk factor evaluation to reduce the problem in the community is one solution to protect people from addiction. This study aimed at using Bayesian zeroinflated Poisson (ZIP) model to investigate the relationship between the number of using crystal meth and some demographic factors in Tehran population. Methods: A cross-sectional study was conducted to investigate crystal meth abuse in Tehran, the capital of Iran, in 2012. Stratified sampling method was used to select samples from 22 urban areas of Tehran. Trained researchers referred to the public places, such as streets, parks, squares, and libraries, to perform face-to-face interviews with the randomly selected samples. Bayesian ZIP model was used to perform the analysis, and SAS 9.3 program was used for data analysis. Results: A total of 993 individuals were studied. According to Bayesian ZIP model, sex (mean= -0.27, 95%CI (-0.485, -0.061)), age (mean= 0.03, 95%CI (0.018, 0.043)), high school level education (mean= 1.276, 95%CI (0.699, 01.9)), diploma level education (mean= 10.4, 95%CI (0.511, 1.69)), and university level education (mean= 0.69, 95%CI (0.142, 1.33)) were all found to have significant associations with crystal meth usage, being the dependent variable. Conclusion: Males, those with higher education levels, and older people in Tehran population are more likely to use crystal meth. This demographic information may be useful in designing preventive programs. Moreover, it is better to analyze count data with excessive zeroes using Bayesian zero- inflated model instead of the usual count models.

Application of zero-inflated poisson mixed models in prognostic factors of hepatitis C.

BACKGROUND AND OBJECTIVES: In recent years, hepatitis C virus (HCV) infection represents a major public health problem. Evaluation of risk factors is one of the solutions which help protect people from the infection. This study aims to employ zero-inflated Poisson mixed models to evaluate prognostic factors of hepatitis C. METHODS: The data was collected from a longitudinal study during 2005-2010. First, mixed Poisson regression (PR) model was fitted to the data. Then, a mixed zero-inflated Poisson model was fitted with compound Poisson random effects. For evaluating the performance of the proposed mixed model, standard errors of estimators were compared. RESULTS: The results obtained from mixed PR showed that genotype 3 and treatment protocol were statistically significant. Results of zero-inflated Poisson mixed model showed that age, sex, genotypes 2 and 3, the treatment protocol, and having risk factors had significant effects on viral load of HCV patients. Of these two models, the estimators of zero-inflated Poisson mixed model had the minimum standard errors. CONCLUSIONS: The results showed that a mixed zero-inflated Poisson model was the almost best fit. The proposed model can capture serial dependence, additional overdispersion, and excess zeros in the longitudinal count data.

Direct medical care costs associated with patients diagnosed with chronic HCV.

BACKGROUND: HCV virus (HCV) is a significant global problem with wide-ranging socio-economic impacts. Because of the high morbidity and mortality associated with end-stage liver disease, cirrhosis, and hepatocellular carcinoma (HCC), the economic burden of HCV infection is substantial. OBJECTIVES: This study aimed to estimate the direct medical care costs of chronic HCV infection. PATIENTS AND METHODS: For this cross-sectional study, 365 courses of HCV treatment were extracted from medical records of 284 patients being referred to Tehran HCV clinic, a clinical clinic of Baqiyatallah Research Center for Gastroenterology and Liver diseases, from 2005 to 2010. All the patients had been diagnosed with HCV. Direct medical care costs for each course of HCV treatment have been calculated based on Purchasing Power Parity Dollar (PPP$). RESULTS: Average direct medical costs for the courses treated with conventional interferon plus ribavirin (INF-RBV) were 4,403 PPP$, and 20,010 PPP$ for peg-interferon plus ribavirin (PEG-RBV) courses. There was an increase of the direct costs in both courses of treatment to achieve Sustain Viral Response (SVR). The costs amounted to 10,072 PPP$ in (INF-RBV) treatment and 34,035 PPP$ in (PEG-RBV). The significant difference between the costs of these two courses of treatment is attributable to high cost of Peg-interferon. This indicates that the medication costs are the dominant costs. CONCLUSIONS: According to the results, total direct medical costs for HCV patients in Iran exceeded 12 billion PPP$ in (INF-RBV) treatment and 55 billion PPP$ in (PEG-RBV).

Statistical count models for prognosis the risk factors of hepatitis C.

AIM: The aim of this study was to compare alternatives methods for analysis of zero inflated count data and compare them with simple count models that are used by researchers frequently for such zero inflated data. BACKGROUND: Analysis of viral load and risk factors could predict likelihood of achieving sustain virological response (SVR). This information is useful to protect a person from acquiring Hepatitis C virus (HCV) infection. The distribution of viral load contains a large proportion of excess zeros (HCV-RNA under 100), that can lead to over-dispersion. PATIENTS AND METHODS: This data belonged to a longitudinal study conducted between 2005 and 2010. The response variable was the viral load of each HCV patient 6 months after the end of treatment. Poisson regression (PR), negative binomial regression (NB), zero inflated Poisson regression (ZIP) and zero inflated negative binomial regression (ZINB) models were carried out to the data respectively. Log likelihood, Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) were used to compare performance of the models. RESULTS: According to all criterions, ZINB was the best model for analyzing this data. Age, having risk factors genotype 3 and protocol of treatment were being significant. CONCLUSION: Zero inflated negative binomial regression models fit the viral load data better than the Poisson, negative binomial and zero inflated Poisson models.

Specific count model for investing the related factors of cost of GERD and functional dyspepsia.

AIM: The purpose of this study is to analyze the cost of GERD and functional dyspepsia for investing its related factors. BACKGROUND: Gastro-oesophageal reflux disease GERD and dyspepsia are the most common symptoms of gastrointestinal disorders. Recent studies showed high prevalence and variety of clinical presentation of these two symptoms imposed enormous economic burden to the society. Cost data that related to economics burden have specific characteristics. So this kind of data needs to specific models. Poisson regression (PR) and negative binomial regression (NB) are the models that were used for analyzing cost data in this paper. PATIENTS AND METHODS: This study designed as a cross-sectional household survey from May 2006 to December 2007 on a random sample of individual in the Tehran province, Iran to find the prevalence of gastrointestinal symptoms and disorders and its related factors. The Cost in each item was counted. PR and NB were carried out to the data respectively. Likelihood ratio test was performed for comparison between models. Also Log likelihood, Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) were used to compare performance of the models. RESULTS: According to Likelihood ratio test and all three criterions that we used to compare performance of the models, NB was the best model for analyzing this cost data. Sex, age and insurance statues were being significant. CONCLUSION: PR and NB models were carried out for this data and according the results improved fit of the NB model over PR, it clearly indicates that over-dispersion is involved due to unobserved heterogeneity and/or clustering. NB model in cost data more appropriate fit than PR.

Random effect model for identifying related factors to virological response in HCV patients.

AIM: This study aims to employ random effect model to evaluate prognostic factors of hepatitis C. BACKGROUND: In recent years, Hepatitis C virus (HCV) infection has been a major cause of liver diseases worldwide and represents a major public health problem. Evaluation of risk factors and a community intervention in order to decrease the problem is one of the solutions which help protect people from the infection. PATIENTS AND METHODS: The data was collected from a longitudinal study during 2005-2010. The response variable in this study was the viral load of each HCV patient during the treatment, immediately after the treatment and 3 to 4 months after the end of the treatment. The outcome variable of interest is the viral load of HCV patients. For analyzing repeated measure viral load of HCV patients, random effect models were used. RESULTS: The results obtained from random effect model showed that treatment protocol and time statistically significant. The variance component was statistically differing with zero. CONCLUSION: According to the results time had a positive effect on rate of viral load of patient. Combination therapy of Peg-interferon plus Ribavirin increased the rate of virological response.

Zero inflated statistical count models for analysing the costs imposed by GERD and dyspepsia.

BACKGROUND AND STUDY AIMS: Recent studies have shown that the high prevalence and the various clinical presentations of gastro-oesophageal reflux disease (GERD) and dyspepsia impose an enormous economic burden on society. Economic cost data have unique characteristics: they are counts, and they have zero inflation. Therefore, these data require special models. Poisson regression (PR), negative binomial regression (NB), zero inflated Poisson (ZIP) and zero inflated negative binomial (ZINB) regression are the models used for analysing cost data in this paper. PATIENTS AND METHODS: In this study, a cross-sectional household survey was distributed to a random sample of individuals between May 2006 and December 2007 in the Tehran province of Iran to determine the prevalence of gastrointestinal symptoms and disorders and their related factors. The cost associated with each item was calculated. PR, NB, ZIP and ZINB models were used to analyse the data. The likelihood ratio test and the Voung test were used to conduct pairwise comparisons of the models. The log likelihood, the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) were used to compare the performances of the models. RESULTS: According to the likelihood ratio test and the Voung test and all three criteria used to compare the performance of the models, ZINB regression was identified as the best model for analysing the cost data. Sex, age, smoking status, BMI, insurance status and education were significant predictors. CONCLUSION: Because the NB model demonstrated a better fit than the PR and ZIP models, over-dispersion was clearly only due to unobserved heterogeneity. In contrast, according to the likelihood ratio test, the ZINB model was more appropriate than the ZIP model. The ZINB model for the cost data was more appropriate than the other models.

Increased oesophageal cancer mortality rate in Iran.

BACKGROUND AND STUDY AIMS: The aim of this study is to present the mortality trends of oesophageal cancer (EC) in the Iranian population, to provide updated information regarding time trends for this cancer. PATIENTS AND METHODS: We analysed the national death statistics reported by the Iranian Ministry of Health and Medical Education from 1995 to 2004. EC [International Classification of Diseases (ICD-9); C15] were expressed as the annual mortality rates/100000, overall, by sex and by age group (<15, 15-49 and ≥ 50 years of age) and age standardised rate (ASR). RESULTS: The age standardised mortality rate of EC increased dramatically during the study period. EC mortality was higher for males and the mortality rate also increased with age. CONCLUSION: This study provides a comprehensive projection for the burden of death due to EC, indicating that the trend of EC mortality dramatically increased in the recent decade.

Irritable bowel syndrome, gastro-oesophageal reflux disease and dyspepsia: overlap analysis using loglinear models.

BACKGROUND AND STUDY AIMS: Irritable bowel syndrome (IBS), gastro-oesophageal reflux disease (GERD) and dyspepsia are three most important gastrointestinal disorders which occur frequently together in patients. This study aims to assess the association between IBS, GERD and dyspepsia by using loglinear model analysis. PATIENTS AND METHODS: This cross-sectional household survey, the purpose of which was to find the prevalence of gastrointestinal symptoms, disorders and the related factors, has been done from May 2006 to December 2007 in Tehran province, Iran. Subjects were interviewed by trained personnel. GERD was diagnosed as the experience of heartburn and/or acid regurgitation at least once a week for the last 3 months. IBS and dyspepsia were diagnosed according to the Rome III criteria. Loglinear models were applied to investigate the simultaneous association between IBS, GERD and dyspepsia. RESULTS: 77.9% of IBS patients had dyspepsia symptoms and 74.7% had GERD symptoms as well at the same time. As for the other two symptoms, 66% of GERD patients were also suffering from dyspepsia. CONCLUSIONS: These three symptoms frequently overlap; the overlap is systematic and not by chance or random.

Increased trend of breast cancer mortality in Iran.

BACKGROUND: Breast cancer is the most commonly diagnosed cancer in women worldwide In Iran, it ranks first among cancers diagnosed in women and is the fifth most common cause of death. The aim of this study was to present the mortality trends from breast cancer for Iranian women during a period of almost a decade, in order to provide update information regarding the likely future. METHODS: We analyzed National death Statistic reported by the Iranian Ministry of Health and Medical Education from 1995 to 2004 to generate annual mortality rates/100,000, overall, by age group (<15, 15-49 and ≥ 50 years of age) and age standardized rate (ASR). RESULTS: The age standardized mortality rate of breast cancer increased dramatically during these years from 1.40 to 3.52 per 100,000 and its mortality was increasing 151.4% for Iranian women, although it seemed that the rate leveled off from 2002 to 2004. Moreover the increasing rate was higher for those aged between 15-49 compared to age > 50 years old. CONCLUSION: There is an increasing trend for breast cancer mortality in Iran. Thus, health education programs to rectify the lack of women awareness about breast cancer signs and effective screening are urgently needed.