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Hemati, Zahra, Sayadi, Mehrab, Lotfi, Mehrzad, Hemmati, Abdulrasool, Azadian, Fatemeh, Mirahmadizadeh, Alireza, Rezaei, Fatemeh, Shirazi Yeganeh, Babak. (1401). Determining the Predictors of Covid-19 Disease Based on Data from Fars Province. سامانه مدیریت نشریات علمی, 11(1 (Supplement)), 195-201. doi: 10.30476/jhsss.2022.93049.1411
Zahra Hemati; Mehrab Sayadi; Mehrzad Lotfi; Abdulrasool Hemmati; Fatemeh Azadian; Alireza Mirahmadizadeh; Fatemeh Rezaei; Babak Shirazi Yeganeh. "Determining the Predictors of Covid-19 Disease Based on Data from Fars Province". سامانه مدیریت نشریات علمی, 11, 1 (Supplement), 1401, 195-201. doi: 10.30476/jhsss.2022.93049.1411
Hemati, Zahra, Sayadi, Mehrab, Lotfi, Mehrzad, Hemmati, Abdulrasool, Azadian, Fatemeh, Mirahmadizadeh, Alireza, Rezaei, Fatemeh, Shirazi Yeganeh, Babak. (1401). 'Determining the Predictors of Covid-19 Disease Based on Data from Fars Province', سامانه مدیریت نشریات علمی, 11(1 (Supplement)), pp. 195-201. doi: 10.30476/jhsss.2022.93049.1411
Hemati, Zahra, Sayadi, Mehrab, Lotfi, Mehrzad, Hemmati, Abdulrasool, Azadian, Fatemeh, Mirahmadizadeh, Alireza, Rezaei, Fatemeh, Shirazi Yeganeh, Babak. Determining the Predictors of Covid-19 Disease Based on Data from Fars Province. سامانه مدیریت نشریات علمی, 1401; 11(1 (Supplement)): 195-201. doi: 10.30476/jhsss.2022.93049.1411

Determining the Predictors of Covid-19 Disease Based on Data from Fars Province

Journal of Health Sciences & Surveillance System
دوره 11، 1 (Supplement)، فروردین 2023، صفحه 195-201    اصل مقاله (319.4 K)
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.30476/jhsss.2022.93049.1411
نویسندگان
Zahra Hemati1؛ Mehrab Sayadi2؛ Mehrzad Lotfi3؛ Abdulrasool Hemmati4؛ Fatemeh Azadian4؛ Alireza Mirahmadizadeh4؛ Fatemeh Rezaei5؛ Babak Shirazi Yeganeh* 6
1School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
2Non-Communicable Diseases Research Center and Cardiovascular Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
3Department of Radiology, Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
4Non-Communicable Diseases Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
5Research Center for Social Determinants of Health, Jahrom University of Medical Sciences, Jahrom, Iran
6Department of Pathology, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
چکیده
Background: The coronavirus disease 2019 (COVID-19) is rapidly spreading worldwide and becoming a pandemic. Since the diagnostic tests are relatively expensive, simple diagnostic tests are valuable for quarantining individuals suspicious of COVID- 19. This study is designed to predict the potential contributing factors of COVID-19 diagnosis.
Methods: It was a referral-based historical cohort study. 363358 individuals referred to the health centers from February to November 2020 in Fars province were entered in the study. The collected data before the lab test were symptoms, underlying diseases, some conditions, risk factors, and demographic information. The Reverse transcriptase polymerase chain reaction test was performed to identify the COVID-19 virus. Chi-square and T-tests were used to compare the variables. A logistic regression test was used to identify predictor variables.
Results: Positive COVID-19 test was reported for 119,324 (% 34.9) participations. The positive group result was compared with that of the negative group (n=244,034). The studied symptoms were significant in positive patients. According to the odds ratio (OR), smell disorder (OR=3.80, P<0.001), taste disorder (OR=3.17, P<0.001), and fever (OR=2.65, P<0.001) were common. However, diarrhea, chest pain and dyspnea showed the lowest odds ratio. According to the results, DM (OR=1.46, P<0.001), HTN (OR=1.42, P<0.001), and CVD (OR=1.27, P<0.001) were common in patients with positive COVID-19 tests. Cases whose Body Mass Index (BMI) was more than 40 (excessive obesity) showed a higher odd (OR=1.45, P<0.001) for being positive.
Conclusion: According to the results, the symptoms and underlying diseases are effective factors in predicting COVID- 19 disease. Identifying these factors for Covid-19 disease helps health policymakers to make quick decisions and take timely action.
کلیدواژه‌ها
COVID-19؛ Diagnosis؛ Risk factors؛ Signs؛ Symptoms
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