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Journal of Research in Health Sciences، جلد ۲۱، شماره ۱، صفحات ۰-۰
عنوان فارسی
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عنوان انگلیسی Epidemiological patterns of syndromic symptoms in suspected patients with COVID-19 in Iran: A Latent Class Analysis
چکیده انگلیسی مقاله Background: Early diagnosis and supportive treatments are essential to patients with coronavirus disease 2019 (COVID-19). Therefore, the current study aimed to determine different patterns of syndromic symptoms and sensitivity and specificity of each of them in the diagnosis of COVID-19 in suspected patients. Study Design: Cross-sectional study Methods: In this study, the retrospective data of 1,539 patients suspected of COVID-19 were obtained from a local registry under the supervision of the officials at Shahroud University of Medical Sciences, Shahroud, Iran. A Latent Class Analysis (LCA) was carried out on syndromic symptoms, and the associations of some risk factors and latent subclasses were accessed using one-way analysis of variance and Chi-square test. Results: The LCA indicated that there were three distinct subclasses of syndromic symptoms among the COVID-19 suspected patients. The age, former smoking status, and body mass index were associated with the categorization of individuals into different subclasses. In addition, the sensitivity and specificity of class 2 (labeled as “High probability of polymerase chain reaction [PCR] + ”) in the diagnosis of COVID-19 were 67.43% and 76.17%, respectively. Furthermore, the sensitivity and specificity of class 3 (labeled as “Moderate probability of PCR + ”) in the diagnosis of COVID-19 were 75.92% and 50.23%, respectively. Conclusions: The findings of the present study showed that syndromic symptoms, such as dry cough, dyspnea, myalgia, fatigue, and anorexia, might be helpful in the diagnosis of suspected COVID-19 patients.
کلیدواژه‌های انگلیسی مقاله COVID-19,Latent Class Analysis,Epidemiological pattern,Diagnosis
نویسندگان مقاله | Ali Hosseinzadeh


| Maysam Rezapour


| Marzie Rohani-Rasaf


| Mohammad Hassan Emamian


| Solmaz Talebi


| Shahrbanoo Goli


| Reza Chaman


| Hossein Sheibani


| Ehsan Binesh


| Fariba Zare


| Ahmad Khosravi


نشانی اینترنتی http://jrhs.umsha.ac.ir/index.php/JRHS/article/view/6262
فایل مقاله فایلی برای مقاله ذخیره نشده است
کد مقاله (doi) 10.34172/jrhs.v0i0.6262
زبان مقاله منتشر شده en
موضوعات مقاله منتشر شده
نوع مقاله منتشر شده Original Articles
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