Please use this identifier to cite or link to this item: https://covid-19.conacyt.mx/jspui/handle/1000/3933
Validation of reported risk factors for disease classification and prognosis in COVID-19: a descriptive and retrospective study
Tan Li.
Kang Xia.
Ji Xinran.
Wang Qi.
li Yongsheng.
Wang Qiongshu.
Miao Hongming.
Acceso Abierto
Atribución-NoComercial-SinDerivadas
10.1101/2020.04.05.20053769
Risk indicators viral load (ORF1ab Ct), lymphocyte percentage (LYM%), C-reactive protein (CRP), interleukin-6 (IL-6), procalcitonin (PCT) and lactic acid (LA) in COVID-19 patients have been proposed in recent studies. However, the predictive effects of those indicators on disease classification and prognosis remains largely unknown. We dynamically measured those reported indicators in 132 cases of COVID-19 patients including the moderate-cured (moderated and cured), severe-cured (severe and cured) and critically ill (died). Our data showed that CRP, PCT, IL-6, LYM%, lactic acid and viral load could predict prognosis and guide classification of COVID-19 patients in different degrees. CRP, IL-6 and LYM% were more effective than other three factors in predicting prognosis. For disease classification, CRP and LYM% were sensitive in identifying the types between critically ill and severe (or moderate). Notably, among the investigated factors, LYM% was the only one that could distinguish between the severe and moderate types. Collectively, we concluded that LYM% was the most sensitive and reliable predictor for disease typing and prognosis. During the COVID-19 pandemic, the precise classification and prognosis prediction are critical for saving the insufficient medical resources, stratified treatment and improving the survival rate of critically ill patients. We recommend that LYM% be used independently or in combination with other indicators in the management of COVID-19.
www.medrxiv.org
2020
Artículo
https://www.medrxiv.org/content/medrxiv/early/2020/04/07/2020.04.05.20053769.full.pdf
Inglés
VIRUS RESPIRATORIOS
Appears in Collections:Artículos científicos

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