COVID-IRS: A novel predictive score for risk of invasive mechanical ventilation in patients with COVID-19

Author:

Garcia-Gordillo José Antonio,Camiro-Zúñiga AntonioORCID,Aguilar-Soto MercedesORCID,Cuenca Dalia,Cadena-Fernández ArturoORCID,Khouri Latife Salame,Rayek Jesica Naanous,Mercado MoisesORCID,

Abstract

Background Coronavirus disease 2019 (COVID-19) is a systemic disease that can rapidly progress into acute respiratory failure and death. Timely identification of these patients is crucial for a proper administration of health-care resources. Objective To develop a predictive score that estimates the risk of invasive mechanical ventilation (IMV) among patients with COVID-19. Study design Retrospective cohort study of 401 COVID-19 patients diagnosed from March 12, to August 10, 2020. The score development cohort comprised 211 patients (52.62% of total sample) whereas the validation cohort included 190 patients (47.38% of total sample). We divided participants according to the need of invasive mechanical ventilation (IMV) and looked for potential predictive variables. Results We developed two predictive scores, one based on Interleukin-6 (IL-6) and the other one on the Neutrophil/Lymphocyte ratio (NLR), using the following variables: respiratory rate, SpO2/FiO2 ratio and lactic dehydrogenase (LDH). The area under the curve (AUC) in the development cohort was 0.877 (0.823–0.931) using the NLR based score and 0.891 (0.843–0.939) using the IL-6 based score. When compared with other similar scores developed for the prediction of adverse outcomes in COVID-19, the COVID-IRS scores proved to be superior in the prediction of IMV. Conclusion The COVID-IRS scores accurately predict the need for mechanical ventilation in COVID-19 patients using readily available variables taken upon admission. More studies testing the applicability of COVID-IRS in other centers and populations, as well as its performance as a triage tool for COVID-19 patients are needed.

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

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