The Primary Outcomes and Epidemiological and Clinical Features of Coronavirus Disease 2019 (Covid-19) in Iran Publisher Pubmed



Vahedianazimi A¹ ; Ashtari S² ; Alishiri G³ ; Shahriary A³ ; Saberi M⁴ ; Rahimibashar F⁵ ; Panahi Y⁶ ; Samadinia H⁷ ; Ferdosi M⁸ ; Jafari I¹ ; Vahedi E³ ; Ghazvini A³ ; Nikpouraghdam M⁹ ; Goharimoghadam K¹⁰ Show All Authors
Source: Advances in Experimental Medicine and Biology Published:2021

Abstract

Aim: We aimed to describe the epidemiological and clinical characteristics of Iranian patients with COVID-19. Methods: In this single-center and retrospective study, patients with confirmed COVID-19 infections were enrolled. Univariate and multivariate logistic regression methods were used to explore the risk factors associated with outcomes. Results: Of 179 patients with confirmed COVID-19 infection, 12 remained hospitalized at the end of the study and 167 were included in the final analysis. Of these, 153 (91.6%) were discharged and 14 (8.38%) died in hospital. Approximately half (50.9%) of patients suffered from a comorbidity, with diabetes or coronary heart disease being the most common in 20 patients. The most common symptoms on admission were fever, dyspnea, and cough. The mean durations from first symptoms to hospital admission was 8.64 ± 4.14 days, whereas the mean hospitalization time to discharge or death was 5.19 ± 2.42 and 4.35 ± 2.70 days, respectively. There was a significantly higher age in non-survivor patients compared with survivor patients. Multivariate regression showed increasing odds ratio (OR) of in-hospital death associated with respiratory rates >20 breaths/min (OR: 5.14, 95% CI: 1.19–22.15, p = 0.028) and blood urea nitrogen (BUN) >19 mg/dL (OR: 4.54, 95% CI: 1.30–15.85, p = 0.017) on admission. In addition, higher respiratory rate was associated with continuous fever (OR: 4.08, 95% CI: 1.18–14.08, p = 0.026) and other clinical symptoms (OR: 3.52, 95% CI: 1.05–11.87, p = 0.04). Conclusion: The potential risk factors including high respiratory rate and BUN levels could help to identify COVID-19 patients with poor prognosis at an early stage in the Iranian population. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.