Comorbidity and its Impact on mortality of COVID-۱۹ in Yazd province, a central part of Iran: a hospital-based study

Publish Year: 1401
نوع سند: مقاله ژورنالی
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JR_JCHR-11-2_012

تاریخ نمایه سازی: 9 مهر 1401

Abstract:

Abstract Introduction: The World Health Organization on March ۱۱, ۲۰۲۰ declared the outbreak of severe acute respiratory syndrome Corona virus ۲ disease (COVID-۱۹) a pandemic situation. The main aim of this study was investigating mortality of COVID ۱۹ by considering chronic diseases. Materials and methods: this study was conducted as a cross-sectional in which all confirmed cases were examined. The variables considered in this study were age, sex, diabetes mellitus, cancers, hypertension, heart diseases, kidney diseases, and liver diseases. Independent sample t test, Chi-square and binary logistic regression were used to data analysis. All statistical analysis was done in SPSS ۱۶ and significant level was set at ۰.۰۵. Results: Out of ۲۲۸۴۹ PCR and CT scan tests, ۱۶۰۶۱ ones were positive. According to the confirmed cases, prevalence of COVID-۱۹ was calculated about ۰.۰۱۹. Also hospital case fatality rate and mortality rate were calculated ۱۵۶ and about ۸.۲ per ۱۰۰۰۰۰ respectively.  Hypertension, and age had significant relationship with morbidity of COVID-۱۹, in other hand, age (OR: ۴.۵۱, p<۰.۰۰۱), kidney diseases (OR: ۱.۸۴, p<۰.۰۰۱), diabetes mellitus (OR: ۱.۳۱, p<۰.۰۰۱), cancer (OR: ۲.۷۳, p<۰.۰۰۱), liver diseases (OR: ۲.۲۷, p<۰.۰۰۱) had impact on mortality of covid-۱۹. Population Attributable Fraction (PAF) showed that diabetes mellitus, cancers, kidney diseases, and liver diseases had ۴.۲, ۲.۴, ۱.۳, and ۰.۲ percent, respectively. Conclusion: age and some underlying diseases increase odds of death due to COVID-۱۹. It seems that preventing high-risk people from being infected is an effective solution to reduce COVID-۱۹ death rate. To do this, health protocols need to be implemented more seriously for these sensitive groups.  

Authors

مسلم طاهری

Center for Healthcare Data Modeling, Department of Biostatistics and Epidemiology, School of public health, ShahidSadoughi University of Medical Sciences, Yazd, Iran

سعید حسینی

Center for Healthcare Data Modeling, Department of Biostatistics and Epidemiology, School of public health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran Department of Epidemiology, School of Public Health, Iran University of Medical Sciences

ریحانه سفیدکار

Center for Healthcare Data Modeling, Department of Biostatistics and Epidemiology, School of public health, ShahidSadoughi University of Medical Sciences, Yazd, Iran

فرزان مددی زاده

Center for Healthcare Data Modeling, Department of Biostatistics and Epidemiology, School of public health, ShahidSadoughi University of Medical Sciences, Yazd, Iran

حسین فلاح زاده

Center for Healthcare Data Modeling, Department of Biostatistics and Epidemiology, School of public health, ShahidSadoughi University of Medical Sciences, Yazd, Iran

احمد دهقان

Accident prevention and crisis research center, emergency organization, ShahidSadoughi University of Medical Sciences, Yazd, Iran

ندا دهقانی تفتی

Accident prevention and crisis research center, emergency organization, ShahidSadoughi University of Medical Sciences, Yazd, Iran

محمدحسن لطفی

Center for Healthcare Data Modeling, Department of Biostatistics and Epidemiology, School of public health, ShahidSadoughi University of Medical Sciences, Yazd, Iran

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