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Persistence and prevalence of clinical symptoms in SARS-CoV-2 infected patients
Research Journal of Pharmacy and Technology ; 16(3):1428-1432, 2023.
Article in English | GIM | ID: covidwho-2319665
ABSTRACT
Coronavirus disease 2019 (COVID19) is the recently reported disease caused by novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID19 spreads among population through the close/direct contact and nasal droplets when an infected person sneezes, coughs, talks or breaths. On an average, COVID19 infected patient develops clinical symptoms 5-6 days after the infection and some develops symptoms even after 14 days of infection. Detailed study on the symptoms shown by COVID19 patients can help in identifying individuals so that proper identification and isolation of patients can be done and transmission of virus can be reduced significantly. In this study, a total of 99 (66 males and 33 female) COVID19 infected symptomatic patients without any comorbidities were included. Nasopharyngeal and oropharyngeal swabs were used for the collection of samples from the suspected patients to extract total RNA and perform real time PCR for the detection of genetic material for SARS-CoV-2. Samples with Ct value = 36 in case of Orf1ab gene and E gene with good sigmoidal curve were reported as positive for novel SARS-CoV-2. Fever, shortness of breath, dry cough and cough with sputum production persisted for longer timer and were more common symptoms reported by the COVID19 infected patients. In conclusion, understanding of the clinical symptoms shown by COVID19 infected patients can help in identification and isolation of patients so that transmission of virus can be reduced significantly.
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Full text: Available Collection: Databases of international organizations Database: GIM Type of study: Observational study / Prognostic study Topics: Long Covid Language: English Journal: Research Journal of Pharmacy and Technology Year: 2023 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: GIM Type of study: Observational study / Prognostic study Topics: Long Covid Language: English Journal: Research Journal of Pharmacy and Technology Year: 2023 Document Type: Article