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Severe COVID-19 among Admitted COVID-19 Patients in a Tertiary Care Centre: A Descriptive Cross-sectional Study

INTRODUCTION: Severe COVID-19 patients experience elevated levels of serologic indicators of inflammation which can alter blood cell lineages and cause lymphopenia. The objective of this study was to find out the prevalence of severe COVID-19 among admitted COVID-19 patients in a tertiary care centr...

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Detalles Bibliográficos
Autores principales: Sedhain, Sapana, Sinha, Amrita, Kafle, Neeta, Thakur, Dipak Kumar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Journal of the Nepal Medical Association 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10089021/
https://www.ncbi.nlm.nih.gov/pubmed/37208888
http://dx.doi.org/10.31729/jnma.8074
Descripción
Sumario:INTRODUCTION: Severe COVID-19 patients experience elevated levels of serologic indicators of inflammation which can alter blood cell lineages and cause lymphopenia. The objective of this study was to find out the prevalence of severe COVID-19 among admitted COVID-19 patients in a tertiary care centre. METHODS: A descriptive cross-sectional study was conducted in a tertiary care centre from 22 June 2021 to 30 September 2021 after obtaining ethical approval from the Institutional Review Committee (Reference number: IRC-PA-146/2077-78). Confirmed COVID-19 patients by reverse transcriptase polymerase chain reaction and admitted in the COVID block during the study period were included and those who were discharged on request or referred or unavailable blood tests were excluded. A convenience sampling method was used. Point estimate and 95% Confidence Interval were calculated. RESULTS: Among 72 admitted COVID-19 patients, 63 (87.5%) (79.86-95.14, 95% Confidence Interval) patients had severe disease. The mean neutrophil to lymphocyte ratio and mean lymphocyte to C-reactive protein ratio were 11.60±8.15 and 25.55±20.96 respectively. CONCLUSIONS: The prevalence of severe COVID-19 was higher than in other studies done in similar settings. We suggest clinical parameter-based early categorisation of COVID-19 cases to utilize limited resources during the pandemic.