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An immune-protein score combining TRAIL, IP-10 and CRP for predicting severe COVID-19 disease

COVID-19 patients are oftentimes over- or under-treated due to a deficit in predictive management tools. This study reports derivation of an algorithm that integrates the host levels of TRAIL, IP-10, and CRP into a single numeric score that is an early indicator of severe outcome for COVID-19 patien...

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Detalles Bibliográficos
Autores principales: Mastboim, Niv Samuel, Angel, Alon, Shaham, Oded, Ber, Tahel Ilan, Navon, Roy, Simon, Einav, Rosenberg, Michal, Israeli, Yael, Hainrichson, Mary, Avni, Noa, Reiner, Eran, Feigin, Paul, Oved, Kfir, Tadmor, Boaz, Singer, Pierre, Kagan, Ilya, Lev, Shaul, Diker, Dror, Jarjou'I, Amir, Kurd, Ramzi, Ben-Chetrit, Eli, Danziger, Guy, Tegethoff, Sina A., Papan, Cihan, Motov, Sergey, Shapira, Ma'anit, Stein, Michal, Gottlieb, Tanya M., Eden, Eran, Klein, Adi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier Ltd. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10235675/
https://www.ncbi.nlm.nih.gov/pubmed/37327532
http://dx.doi.org/10.1016/j.cyto.2023.156246
Descripción
Sumario:COVID-19 patients are oftentimes over- or under-treated due to a deficit in predictive management tools. This study reports derivation of an algorithm that integrates the host levels of TRAIL, IP-10, and CRP into a single numeric score that is an early indicator of severe outcome for COVID-19 patients and can identify patients at-risk to deteriorate. 394 COVID-19 patients were eligible; 29% meeting a severe outcome (intensive care unit admission/non-invasive or invasive ventilation/death). The score’s area under the receiver operating characteristic curve (AUC) was 0.86, superior to IL-6 (AUC 0.77; p = 0.033) and CRP (AUC 0.78; p < 0.001). Likelihood of severe outcome increased significantly (p < 0.001) with higher scores. The score differentiated severe patients who further deteriorated from those who improved (p = 0.004) and projected 14-day survival probabilities (p < 0.001). The score accurately predicted COVID-19 patients at-risk for severe outcome, and therefore has potential to facilitate timely care escalation and de-escalation and appropriate resource allocation.