Abstract
During the COVID-19 pandemic, risk stratification has been used to decide patient eligibility for inpatient, critical and domiciliary care. Here, we sought to validate the MSL-COVID-19 score, originally developed to predict COVID-19 mortality in Mexicans. Also, an adaptation of the formula is proposed for the prediction of COVID-19 severity in a triage setting (Nutri-CoV). We included patients evaluated from March 16th to August 17th, 2020 at the Instituto Nacional de Ciencias Médicas y Nutrición, defining severe COVID-19 as a composite of death, ICU admission or requirement for intubation (n = 3,007). We validated MSL-COVID-19 for prediction of mortality and severe disease. Using Elastic Net Cox regression, we trained (n = 1,831) and validated (n = 1,176) a model for prediction of severe COVID-19 using MSL-COVID-19 along with clinical assessments obtained at a triage setting. The variables included in MSL-COVID-19 are: pneumonia, early onset type 2 diabetes, age > 65 years, chronic kidney disease, any form of immunosuppression, COPD, obesity, diabetes, and age <40 years. MSL-COVID-19 had good performance to predict COVID-19 mortality (c-statistic = 0.722, 95%CI 0.690-0.753) and severity (c-statistic = 0.777, 95%CI 0.753-0.801). The Nutri-CoV score includes the MSL-COVID-19 plus respiratory rate, and pulse oximetry. This tool had better performance in both training (c-statistic = 0.797, 95%CI 0.765-0.826) and validation cohorts (c-statistic = 0.772, 95%CI 0.0.745-0.800) compared to other severity scores. MSL-COVID-19 predicts inpatient COVID-19 lethality. The Nutri-CoV score is an adaptation of MSL-COVID-19 to be used in a triage environment. Both scores have been deployed as web-based tools for clinical use in a triage setting.
Highlights
The pandemic caused by the SARS-CoV2 virus, which is causative of COVID-19, has led to increased morbidity and mortality, posing challenges to healthcare systems worldwide [1]
The variables included in MSL-COVID-19 are: pneumonia, early onset type 2 diabetes, age > 65 years, chronic kidney disease, any form of immunosuppression, chronic obstructive pulmonary disease (COPD), obesity, diabetes, and age
The Nutri-CoV score is an adaptation of MSL-COVID-19 to be used in a triage environment
Summary
The pandemic caused by the SARS-CoV2 virus, which is causative of COVID-19, has led to increased morbidity and mortality, posing challenges to healthcare systems worldwide [1]. Since its arrival in Mexico in late February 2020 to date, it has caused over 800,000 cases and more than 90,000 deaths attributable to COVID-19 [2] Most of these cases will remain mild or moderate, a group of patients could develop a severe to critical form of COVID-19 which will require quick medical assessment to prevent adverse clinical outcomes [3]. Our group developed a novel mechanistic score for lethality attributable to COVID-19 (MSL-COVID-19) using age, self-reported comorbidities, and clinically suspected pneumonia, which performed adequately in a real-world scenario [12] This tool considers the major contribution of chronic diseases to develop severe forms of COVID-19.
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