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J Res Health Sci ; 21(1): e00508, 2021 Jan 18.
Artigo em Inglês | MEDLINE | ID: mdl-34024766

RESUMO

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. CONCLUSION: 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.


Assuntos
COVID-19/diagnóstico , COVID-19/epidemiologia , Avaliação de Sintomas/métodos , Avaliação de Sintomas/estatística & dados numéricos , Adulto , Idoso , Idoso de 80 Anos ou mais , Estudos Transversais , Feminino , Humanos , Irã (Geográfico)/epidemiologia , Análise de Classes Latentes , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos , SARS-CoV-2
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