Epidemiological patterns of syndromic symptoms in suspected patients with COVID-۱۹ in Iran: A Latent Class Analysis

Background: Early diagnosis and supportive treatments are essential to patients with coronavirusdisease ۲۰۱۹ (COVID-۱۹). Therefore, the current study aimed to determine different patterns ofsyndromic symptoms and sensitivity and specificity of each of them in the diagnosis of COVID-۱۹in suspected patients.Study Design: Cross-sectional studyMethods: In this study, the retrospective data of ۱,۵۳۹ patients suspected of COVID-۱۹ wereobtained from a local registry under the supervision of the officials at Shahroud University ofMedical Sciences, Shahroud, Iran. A Latent Class Analysis (LCA) was carried out on syndromicsymptoms, and the associations of some risk factors and latent subclasses were accessed usingone-way analysis of variance and Chi-square test.Results: The LCA indicated that there were three distinct subclasses of syndromic symptomsamong the COVID-۱۹ suspected patients. The age, former smoking status, and body mass indexwere associated with the categorization of individuals into different subclasses. In addition, thesensitivity and specificity of class ۲ (labeled as “High probability of polymerase chain reaction[PCR]+”) in the diagnosis of COVID-۱۹ were ۶۷.۴۳% and ۷۶.۱۷%, respectively. Furthermore, thesensitivity and specificity of class ۳ (labeled as “Moderate probability of PCR+”) in the diagnosis ofCOVID-۱۹ were ۷۵.۹۲% and ۵۰.۲۳%, respectively.Conclusions: The findings of the present study showed that syndromic symptoms, such as drycough, dyspnea, myalgia, fatigue, and anorexia, might be helpful in the diagnosis of suspectedCOVID-۱۹ patients.