Covichem: A biochemical severity risk score of COVID-19 upon hospital admission.
Marie-Lise BatsBenoit RuchetonTara FleurArthur OrieuxClément CheminSébastien RubinBrigitte ColombiesArnaud DesclauxClaire RivoisyEtienne MériglierEtienne RivièreAlexandre BoyerDidier GrusonIsabelle PellegrinPascale TrimouletIsabelle GarrigueRana AlkouriCharles DupinFrançois Moreau-GaudryAurélie BedelSandrine DabernatPublished in: PloS one (2021)
Clinical and laboratory predictors of COVID-19 severity are now well described and combined to propose mortality or severity scores. However, they all necessitate saturable equipment such as scanners, or procedures difficult to implement such as blood gas measures. To provide an easy and fast COVID-19 severity risk score upon hospital admission, and keeping in mind the above limits, we sought for a scoring system needing limited invasive data such as a simple blood test and co-morbidity assessment by anamnesis. A retrospective study of 303 patients (203 from Bordeaux University hospital and an external independent cohort of 100 patients from Paris Pitié-Salpêtrière hospital) collected clinical and biochemical parameters at admission. Using stepwise model selection by Akaike Information Criterion (AIC), we built the severity score Covichem. Among 26 tested variables, 7: obesity, cardiovascular conditions, plasma sodium, albumin, ferritin, LDH and CK were the independent predictors of severity used in Covichem (accuracy 0.87, AUROC 0.91). Accuracy was 0.92 in the external validation cohort (89% sensitivity and 95% specificity). Covichem score could be useful as a rapid, costless and easy to implement severity assessment tool during acute COVID-19 pandemic waves.
Keyphrases
- coronavirus disease
- sars cov
- emergency department
- healthcare
- end stage renal disease
- chronic kidney disease
- insulin resistance
- liver failure
- cardiovascular disease
- metabolic syndrome
- newly diagnosed
- cardiovascular events
- intensive care unit
- skeletal muscle
- electronic health record
- machine learning
- acute care
- respiratory syndrome coronavirus
- respiratory failure
- carbon dioxide
- iron deficiency