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A 2‐month post‐COVID‐19 follow‐up study on patients with dyspnea

Background and aims Dyspnea is one of the most common symptoms associated with the COVID‐19 caused by novel coronavirus SARS‐CoV‐2. This study aimed to assess the prevalence of dyspnea, observe co‐variables, and find predictors of dyspnea after 2 months of recovery from COVID‐19. Methods A total of...

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Published in:Health Science Reports 2021-12, Vol.4 (4), p.e435-n/a
Main Authors: Islam, Md. Khairul, Hossain, Mohammad Faisal, Molla, Md. Maruf Ahmed, Sharif, Md. Mohiuddin, Hasan, Pratyay, Hossain, Fahima Sharmin, Sikder, Ayesha, Uddin, Md Gias, Amin, Md. Robed
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Language:English
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Summary:Background and aims Dyspnea is one of the most common symptoms associated with the COVID‐19 caused by novel coronavirus SARS‐CoV‐2. This study aimed to assess the prevalence of dyspnea, observe co‐variables, and find predictors of dyspnea after 2 months of recovery from COVID‐19. Methods A total of 377 patients were included in the study based on their responses and clinical findings during initial admission to the hospital with COVID‐19. After excluding five deceased patients, a total of 327 patients were interviewed through telephone using a 12‐point dyspnea scale and using relevant questions to gauge the patient clinically. Interviews were carried out by trained physicians, and responses were recorded and stored. All analyses were carried out using the statistical programming language R. Results Of the total 327 participants in the study, 34% had stated that they were suffering from respiratory symptoms even after 2 months of COVID‐19. The study demonstrated that patient oxygen saturation level SpO2 (P = .03), D‐dimer (P = .001), serum ferritin (P = .006), and the presence and severity of dyspnea are significantly correlated. In addition to that, patient smoking history (P = .012) and comorbidities such as chronic obstructive pulmonary disease (COPD) (P = .021) were found to be statistically significant among groups. Conclusion These findings of this study can be useful for predicting and managing long‐term complications of COVID‐19.
ISSN:2398-8835
2398-8835
DOI:10.1002/hsr2.435