Journal of research in health sciences最新文献

{"title":"Prediction of Helmet Use Behavior among Motorcyclists Based on the Theory of Planned Behavior.","authors":"Forouzan Rezapur-Shahkolai,&nbsp;Ehsan Vesali-Monfared,&nbsp;Majid Barati,&nbsp;Leili Tapak","doi":"10.34172/jrhs.2022.99","DOIUrl":"https://doi.org/10.34172/jrhs.2022.99","url":null,"abstract":"<p><strong>Background: </strong>Road traffic injuries (RTIs) are one of the most critical factors that endanger human health. More specifically, head and neck injuries are the main causes of deaths and disabilities among motorcyclists. This study aimed to investigate the predictive factors of helmet use behavior among motorcyclists based on the theory of planned behavior (TPB).</p><p><strong>Study design: </strong>This study followed the cross-sectional design.</p><p><strong>Methods: </strong>This study was conducted on randomly selected 730 motorcyclist employees in Qom, Iran, in 2021. The data collection tool was a self-administered researcher-made questionnaire, including items on demographic characteristics, history of RTIs, and constructs of TPB. Data were analyzed using descriptive summary statistics, analysis of variance, independent samples <i>t</i> test, Pearson correlation coefficient, and structural equation modeling (SEM).</p><p><strong>Results: </strong>In this study, only 9.8% of the participants reported that they always used a helmet while riding a motorcycle. About 60% reported a history of a motorcycle crash, and 11.5% had a history of head injuries. The direct effect of attitude, subjective norms, and perceived behavioral control on the intention to use a helmet were statistically significant, explaining 59% of the variation in behavioral intention (intention to use a helmet) (R²=0.59). Moreover, perceived behavioral control and behavioral intention had significant effects on helmet use behavior (R²=0.26).</p><p><strong>Conclusion: </strong>The prevalence of helmet use among the studied population was very low. Moreover, TPB was useful in identifying the determinants of behavior and especially behavioral intention of helmet use among motorcyclists.</p>","PeriodicalId":17164,"journal":{"name":"Journal of research in health sciences","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422160/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10361668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lung Cancer and Pleural Mesothelioma Risk Assessment for the General Population Exposed to Asbestos in Different Regions of Tehran, Iran.","authors":"Nafiseh Nasirzadeh,&nbsp;Zahra Soltanpour,&nbsp;Yousef Mohammadian,&nbsp;Bahman Pourhasan","doi":"10.34172/jrhs.2022.98","DOIUrl":"https://doi.org/10.34172/jrhs.2022.98","url":null,"abstract":"<p><strong>Background: </strong>Asbestos is a natural fiber leading to health risks like chronic lung diseases. The current study aimed to estimate pleural mesothelioma and lung cancer risk for population exposure to asbestos in Tehran, Iran.</p><p><strong>Study design: </strong>A cross-sectional study.</p><p><strong>Methods: </strong>According to the annual report of Air Quality Control Company (AQCC), from 2011-2020, carcinogenic risk and mesothelioma were assessed based on the Environmental Protection Agency (EPA) method using the Monte Carlo simulation (MCS). The relative risk (RR) of mortality cancer was calculated based on Camus and colleagues' model. Moreover, mesothelioma risk was estimated by Bourgault and colleagues' model.</p><p><strong>Results: </strong>The mean concentration and health risk of asbestos in ambient air generally reduced from 2011 to 2020. The highest mortality risk for lung cancer was 8.4 per 100000 persons in 2011 and reduced to 1.8 in 2017. For mesothelioma, the corresponding values were 8.96 per 100000 persons in 2011 and reduced to 1.92 in 2017.</p><p><strong>Conclusion: </strong>The findings of this study could be helpful to health policymakers in the management of asbestos risk.</p>","PeriodicalId":17164,"journal":{"name":"Journal of research in health sciences","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422159/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10370431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of Hypertension Alone and in Comorbidity with Diabetes on Death within 30 Days among Inpatients with COVID-19 Infection.","authors":"Erfan Ayubi,&nbsp;Fatemeh Torkaman Asadi,&nbsp;Shiva Borzouei,&nbsp;Behnaz Alafchi,&nbsp;Mobin Faghih Soleimani,&nbsp;Saman Khosronejad,&nbsp;Salman Khazaei,&nbsp;Seyed Saman Talebi","doi":"10.34172/jrhs.2022.100","DOIUrl":"https://doi.org/10.34172/jrhs.2022.100","url":null,"abstract":"<p><strong>Background: </strong>Hypertension and diabetes are common comorbidities in patients with COVID-19 and could be influencing the mortality of such patients. The present study aimed to evaluate the effects of hypertension alone and in comorbidity with diabetes on the death within 30 days among inpatients with COVID-19 in presence of well-known determinates of COVID-19 death.</p><p><strong>Study design: </strong>A case-control study.</p><p><strong>Methods: </strong>Four groups of COVID-19 inpatients including controls, diabetes alone, hypertension alone, and hypertension and diabetes comorbidities were defined. Each study groups did not have underlying diseases other than hypertension and diabetes. Demographic and general characteristics, underlying diseases, and hospital course events were extracted from medical records. The outcome of interest was alive at discharge/ death within 30 days after admission. Multivariable binary logistic analysis was employed to estimate the effect measures.</p><p><strong>Results: </strong>The number of death within 30 days among controls (n=1359), diabetes alone (159), hypertension alone (406) and hypertension and diabetes comorbidities (188) were 12.68%, 15.72%, 20.74% and 26.74%, respectively. According to three multivariable analyses after adjusting older age, hospital length of stay, and intensive care unit (ICU) admission separately, the odds of death within 30 days in COVID-19 patients with having hypertension and diabetes comorbidities was 1.58, 2.13 and 1.91 times of patients without such comorbidities, respectively (<i>P</i><0.015). The effect of hypertension alone was also significant after adjusting hospital length of stay and ICU admission but not for older age.</p><p><strong>Conclusion: </strong>Our results suggest that comorbidities, such as hypertension and diabetes may be associated with COVID-19-related deaths independent of other underlying diseases, older age, and adverse hospital course events.</p>","PeriodicalId":17164,"journal":{"name":"Journal of research in health sciences","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422163/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10370436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-term Survival Rate Following Myocardial Infarction and the Effect of Discharge Medications on the Survival Rate.","authors":"Sahar Bayat,&nbsp;Seyed Saeed Hashemi Nazari,&nbsp;Yadollah Mehrabi,&nbsp;Mohammad Sistanizad","doi":"10.34172/jrhs.2022.102","DOIUrl":"https://doi.org/10.34172/jrhs.2022.102","url":null,"abstract":"<p><strong>Background: </strong>The evaluation of the risk factors associated with the long-term survival rate of patients with myocardial infarction (MI) and the effects of discharge medications can significantly help select the most effective strategies for improving treatment.</p><p><strong>Study design: </strong>A retrospective cohort study.</p><p><strong>Methods: </strong>The participants of this retrospective cohort study were 21,181 patients who suffered from MI and were hospitalized in the cardiac care unit (CCU) of different public, private, and military hospitals in Iran from 20 March 2013 to 20 March 2014. Participants were followed up until February 2020 for any cardiovascular disease (CVD) mortality. To evaluate survival rate, the differences between groups, and the factors related to MI death, Kaplan-Meier, log-rank test, and Cox proportional-hazards model were used, respectively.</p><p><strong>Results: </strong>One, three, five, and seven-year survival rates of patients were 88%, 81%, 78%, and 74%, respectively. Regarding the interaction effect of prescribed medical drugs, the highest 7-year survival rate of 86% (95% CI: 72%, 93%) was related to people who consumed anticoagulants, aspirin, clopidogrel, beta blockers, angiotensin-converting enzymes (ACEs), and angiotensin II receptor antagonist simultaneously. Considering the effect of other variables, the consumption of anticoagulants was associated with a decrease in survival rate (HR=1.13 CI: 1.06, 1.19).</p><p><strong>Conclusion: </strong>As evidenced by the results of this study, different combinations of prescribed medication drugs had protective effects on long-term mortality compared to the group without any drug. Nonetheless, according to the drugs in each combination therapy, this protective effect ranged from HR=0.27 to HR=0.89. It is recommended that further studies compare the long-term effects of different drug combinations and also consider adherence to treatment in evaluating the effects of these combinations.</p>","PeriodicalId":17164,"journal":{"name":"Journal of research in health sciences","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422162/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10350455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Problematic Internet, Smartphone, and SMS Use among Adults: Shared and Unique Predictors.","authors":"Argyroula Kalaitzaki,&nbsp;Stéphanie Laconi,&nbsp;George Tsouvelas","doi":"10.34172/jrhs.2022.97","DOIUrl":"https://doi.org/10.34172/jrhs.2022.97","url":null,"abstract":"<p><strong>Background: </strong>Although a surge of interest has recently emerged in investigating the simultaneous problematic use of various technology-based tools, the findings are still inconclusive. The present web-based survey aimed at examining whether (a) personality traits, coping strategies, and sociodemographics are associated with problematic internet, smartphone, and SMS use among Greek users and (b) personality traits mediate the relationship between maladaptive coping strategies and problematic use of the three media.</p><p><strong>Study design: </strong>A cross-sectional study.</p><p><strong>Methods: </strong>A convenience and snowball sample of 1016 participants (84.4% female, mean age of 30.3 years) completed the Problematic Internet Use Questionnaire-9 (PIUQ-9), the Mobile Phone Problem Use Scale (MPPUS), the Self-Perception of Text Message Dependency Scale (STDS), the Personality Diagnostic Questionnaire 4+(PDQ-4+), and the Brief Coping Orientation to Problems Experienced Inventory (Brief COPE).</p><p><strong>Results: </strong>Shared predictors between problematic use of the three technology-based tools were younger age and low educational level, the coping strategy of substance use, and the narcissistic, avoidant, and dependent personality disorders. Predictors of problematic internet and smartphone use were coping strategies of emotional support, self-distraction, and behavioral disengagement. According to structural equation models (SEM) models, cluster C personality disorders fully mediate the relationship between maladaptive coping strategies and problematic use of technology-based tools.</p><p><strong>Conclusion: </strong>Addressing factors that predispose (i.e., personality traits), precipitate, or maintain problematic use (i.e., coping strategies) can lead to effective and cost-saving preventive (i.e., screening of vulnerable groups) and therapeutic efforts (i.e., teaching adaptive coping strategies).</p>","PeriodicalId":17164,"journal":{"name":"Journal of research in health sciences","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422158/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9997674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation of the Utility of Multivariate Meta-Analysis Methods in Estimating the Summary Dose Response Curve.","authors":"Melepurakkal Sadanandan Deepthy,&nbsp;Kalesh Mappilakudy Karun,&nbsp;Kotten Thazhath Harichandrakumar,&nbsp;Narayanapillai Sreekumaran Nair","doi":"10.34172/jrhs.2022.96","DOIUrl":"https://doi.org/10.34172/jrhs.2022.96","url":null,"abstract":"<p><strong>Background: </strong>Traditional meta-analyses often assess the effectiveness of different doses of the same intervention separately or examine the overall differences between intervention and placebo groups. The present study aimed to model the effect sizes obtained from different doses in multiple studies using a two-stage dose-response meta-analytic approach while taking dose variations into account.</p><p><strong>Methods: </strong>Different dose-response meta-analysis models using linear, quadratic, and restricted cubic spline (RCS) functions were fitted. A two-stage approach utilizing multivariate meta-analysis was performed and the obtained results were compared with those of the univariate meta-analysis. A random effect dose-response meta-analysis was performed using data from an existing systematic review on combination therapy with zonisamide and anti-Parkinson drugs for Parkinson's disease. The effective or optimum dose for producing maximum response was also investigated. Moreover, a sensitivity analysis was performed by changing the knots of the RCS model.</p><p><strong>Results: </strong>Dose-response meta-analysis was performed using data from four double-blinded randomized controlled trials with 724 and 309 patients with Parkinson's disease in dose and placebo arms, respectively. The quadratic model yielded the smallest Akaike information criterion (AIC), compared to the linear and RCS models, indicating it to be the best fit for the data.</p><p><strong>Conclusion: </strong>Compared to the traditional approach, the two-stage approach could model the dose-dependent effect of zonisamide on the Unified Parkinson's Disease Rating Scale (UPRDS) part III score and predict the outcome for different doses through a single analysis.</p>","PeriodicalId":17164,"journal":{"name":"Journal of research in health sciences","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422157/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10005752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a Machine Learning-Based Screening Method for Thyroid Nodules Classification by Solving the Imbalance Challenge in Thyroid Nodules Data.","authors":"Sajad Khodabandelu,&nbsp;Naser Ghaemian,&nbsp;Soraya Khafri,&nbsp;Mehdi Ezoji,&nbsp;Sara Khaleghi","doi":"10.34172/jrhs.2022.90","DOIUrl":"https://doi.org/10.34172/jrhs.2022.90","url":null,"abstract":"<p><strong>Background: </strong>This study aims to show the impact of imbalanced data and the typical evaluation methods in developing and misleading assessments of machine learning-based models for preoperative thyroid nodules screening.</p><p><strong>Study design: </strong>A retrospective study.</p><p><strong>Methods: </strong>The ultrasonography features for 431 thyroid nodules cases were extracted from medical records of 313 patients in Babol, Iran. Since thyroid nodules are commonly benign, the relevant data are usually unbalanced in classes. It can lead to the bias of learning models toward the majority class. To solve it, a hybrid resampling method called the Smote-was used to creating balance data. Following that, the support vector classification (SVC) algorithm was trained by balance and unbalanced datasets as Models 2 and 3, respectively, in Python language programming. Their performance was then compared with the logistic regression model as Model 1 that fitted traditionally.</p><p><strong>Results: </strong>The prevalence of malignant nodules was obtained at 14% (n = 61). In addition, 87% of the patients in this study were women. However, there was no difference in the prevalence of malignancy for gender. Furthermore, the accuracy, area under the curve, and geometric mean values were estimated at 92.1%, 93.2%, and 76.8% for Model 1, 91.3%, 93%, and 77.6% for Model 2, and finally, 91%, 92.6% and 84.2% for Model 3, respectively. Similarly, the results identified Micro calcification, Taller than wide shape, as well as lack of ISO and hyperechogenicity features as the most effective malignant variables.</p><p><strong>Conclusion: </strong>Paying attention to data challenges, such as data imbalances, and using proper criteria measures can improve the performance of machine learning models for preoperative thyroid nodules screening.</p>","PeriodicalId":17164,"journal":{"name":"Journal of research in health sciences","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422153/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9983146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of the Effective Reproduction Number (Rt) Estimation Methods of COVID-19 Using Simulation Data Based on Available Data from Iran, USA, UK, India, and Brazil.","authors":"Ali Karamoozian,&nbsp;Abbas Bahrampour","doi":"10.34172/jrhs.2022.94","DOIUrl":"https://doi.org/10.34172/jrhs.2022.94","url":null,"abstract":"<p><strong>Background: </strong>Accurate determination of the effective reproduction number (Rt) is a very important strategy in the epidemiology of contagious diseases, including coronavirus disease 2019 (COVID-19). This study compares different methods of estimating the Rt of susceptible population to identify the most accurate method for estimating Rt.</p><p><strong>Study design: </strong>A secondary study.</p><p><strong>Methods: </strong>The value of Rt was estimated using attack rate (AR), exponential growth (EG), maximum likelihood (ML), time-dependent (TD), and sequential Bayesian (SB) methods, for Iran, the United States, the United Kingdom, India, and Brazil from June to October 2021. In order to accurately compare these methods, a simulation study was designed using forty scenarios.</p><p><strong>Results: </strong>The lowest mean square error (MSE) was observed for TD and ML methods, with 15 and 12 cases, respectively. Therefore, considering the estimated values of Rt based on the TD method, it was found that Rt values in the United Kingdom (1.33; 95% CI: 1.14-1.52) and the United States (1.25; 95% CI: 1.12-1.38) substantially have been more than those in other countries, such as Iran (1.07; 95% CI: 0.95-1.19), India (0.99; 95% CI: 0.89-1.08), and Brazil (0.98; 95% CI: 0.84-1.14) from June to October 2021.</p><p><strong>Conclusion: </strong>The important result of this study is that TD and ML methods lead to a more accurate estimation of Rt of population than other methods. Therefore, in order to monitor and determine the epidemic situation and have a more accurate prediction of the incidence rate, as well as control COVID-19 and similar diseases, the use of these two methods is suggested to more accurately estimate Rt.</p>","PeriodicalId":17164,"journal":{"name":"Journal of research in health sciences","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422149/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10366050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risk-Taking Behaviors Considering Internet Gaming Disorder among Iranian University Students: A Latent Class Analysis.","authors":"Faeze Ghasemi Seproo,&nbsp;Leila Janani,&nbsp;Seyed Abbas Motevalian,&nbsp;Abbas Abbasi-Ghahramanloo,&nbsp;Hamed Fattahi,&nbsp;Shahnaz Rimaz","doi":"10.34172/jrhs.2022.91","DOIUrl":"https://doi.org/10.34172/jrhs.2022.91","url":null,"abstract":"<p><strong>Background: </strong>Dangerous behaviors adversely affect the health of adolescents and young adults. This study aimed to identify the subgroups of college students based on the parameters of risky behavior and analyze the impact of demographic factors and internet gaming disorder (IGD) belonging to each class.</p><p><strong>Study design: </strong>A cross-sectional study.</p><p><strong>Methods: </strong>The study was conducted on 1355 students through a multi-stage random sampling method in 2020. A survey questionnaire was used to collect data, and all students completed 1294 sets of questionnaires. The data were analyzed using t test and latent class analysis (LCA) through SPSS and PROC LCA in SAS 9.2 software.</p><p><strong>Results: </strong>Three latent classes have been identified as low-risk (75%), tobacco smoker (8%), and high-risk (17%). There was a high possibility of risky behavior in the third class. Marital status (being single) (OR = 2.28, 95% CI: 1.19-4.37), unemployment (having no job) along with education (OR = 1.56, 95% CI: 1.04-2.33), and IGD (OR = 1.06, 95% CI: 1.04-1.09) increased the risk of inclusion in the tobacco smoker class. Moreover, unemployment (having no job) along with education (OR = 1.43, 95% CI: 1.11-1.84) increased the chance of being in the high-risk class.</p><p><strong>Conclusion: </strong>According to the findings of this study, 25% of the students were tobacco smokers or were in the high-risk class. The results of this study may help develop and evaluate preventive strategies that simultaneously take into account different behaviors.</p>","PeriodicalId":17164,"journal":{"name":"Journal of research in health sciences","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422155/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9993603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation of the Factors Related to Mortality and Length of Hospitalization among COVID-19 Patients in East Azerbaijan Hospitals, Iran.","authors":"Ali Abdi Tazeh,&nbsp;Asghar Mohammadpoorasl,&nbsp;Parvin Sarbakhsh,&nbsp;Madineh Abbasi,&nbsp;Abbasali Dorosti,&nbsp;Simin Khayatzadeh,&nbsp;Hossein Akbari","doi":"10.34172/jrhs.2022.92","DOIUrl":"https://doi.org/10.34172/jrhs.2022.92","url":null,"abstract":"<p><strong>Background: </strong>It is of utmost importance to identify populations with an elevated risk for COVID-19 and the factors influencing its outcomes. The present study aimed to investigate factors affecting mortality and length of stay (LOS) among COVID-19 patients in the hospitals of East Azerbaijan province, Iran, during 15 months of this pandemic.</p><p><strong>Study design: </strong>The present study followed a retrospective cohort design.</p><p><strong>Methods: </strong>This retrospective study was conducted using data in the integrated syndromic surveillance system (ISSS) on patients admitted to the hospitals from February 21, 2020, to April 11, 2021. The association between variables of interest and death, as well as LOS, was investigated via multiple logistic regression and multiple linear regression analyses.</p><p><strong>Results: </strong>In total, 24 293 inpatients with a mean age of 54.0 ± 19.4 years were included in this study. About 15% of them lost their lives, whose mean age was 69.0 ± 14.6 years, significantly higher than the recovered ones (P < 0.001). Factors, such as above 49 years of age (P < 0.001), male gender (OR = 1.17; 95% CI: 1.08-1.26), and having chronic diseases (OR = 1.32; 95% CI: 1.22-1.42), were correlated with patient mortality. In addition, having chronic diseases (Beta = 0.06; 95% CI: 0.03-0.08) was associated with higher LOS in hospitals.</p><p><strong>Conclusion: </strong>In conclusion, older patients were at a higher risk of mortality and prolonged hospitalization. Furthermore, patients' underlying diseases could cause a severe form of COVID-19, which can lead to death and increase patients' LOS.</p>","PeriodicalId":17164,"journal":{"name":"Journal of research in health sciences","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422152/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9993604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}