Epidemiological patterns of syndromic symptoms in suspected patients with COVID-19 in Iran: A Latent Class Analysis.
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...
| Publicado en: | Journal of Research in Health Sciences Vol. 21; no. 1; pp. 1 - 6 |
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| Autores principales: | , , , , , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Hamadan University of Medical Sciences, School of Public Health
Winter2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=149972652&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 149972652 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 22287795 903Q jtl: Journal of Research in Health Sciences issn: 22287795 maglogo: N pubinfo: dt: Winter2021 vid: 21 iid: 1 pid: 54266 pub: Hamadan University of Medical Sciences, School of Public Health artinfo: ui: 149972652 149972652 149972652 10.34172/jrhs.2021.41 149972652 ppf: 1 ppct: 5 formats: fmt: @attributes: type: P tig: atl: Epidemiological patterns of syndromic symptoms in suspected patients with COVID-19 in Iran: A Latent Class Analysis. aug: au: Hosseinzadeh, Ali Rezapour, Maysam Rohani-Rasaf, Marzieh Emamian, Mohammad Hassan Talebi, Seyedeh Solmaz Goli, Shahrbanoo Chaman, Reza Sheibani, Hossein Binesh, Ehsan Zare, Fariba Khosravi, Ahmad affil: Department of Epidemiology, School of Public Health, Shahroud University of Medical Sciences, Shahroud, Iran sug: subj: COVID-19 Epidemiology COVID-19 Symptoms COVID-19 Diagnosis Sensitivity and Specificity Human Iran Cross Sectional Studies Retrospective Design One-Way Analysis of Variance Chi Square Test Smoking Body Mass Index Polymerase Chain Reaction Descriptive Statistics Cough Muscle Pain Anorexia Disease Attributes ab: 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. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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