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 coronavirusdisease 2019 (covid-19). therefore, the current study aimed to determine different patterns ofsyndromic symptoms and sensitivity and specificity of each of them in the diagnosis of covid-19in suspected patients.study design: cross-sectional studymethods: in this study, the retrospective data of 1,539 patients suspected of covid-19 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-19 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 2 (labeled as “high probability of polymerase chain reaction[pcr]+”) in the diagnosis of covid-19 were 67.43% and 76.17%, respectively. furthermore, thesensitivity and specificity of class 3 (labeled as “moderate probability of pcr+”) in the diagnosis ofcovid-19 were 75.92% and 50.23%, 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-19 patients.