Simple hyperinflammation scores predict mortality in hospitalized patients with COVID-19 and offer a personalized medicine approach to dexamethasone intervention

Abstract

Background Dexamethasone is recommended for use in all patients with COVID-19 requiring supplemental oxygen, however, only some patients develop hyperinflammation (COV-HI) potentially influencing their response to corticosteroids. This study tested the ability of criteria defining COV-HI to predict response to dexamethasone. Methods A retrospective, multicentre, observational cohort study of 1313-patients with PCR-confirmed COVID-19 during first and second waves of community-acquired infection including 212 patients who received dexamethasone monotherapy. Demographic data, laboratory tests and clinical status were recorded from admission until death or discharge, with minimum 28-days follow-up. Patients were stratified at admission as COV-HI-YES/COV-HI-NO based on three published COV-HI definitions. Results Patients with COV-HI shared a biological phenotype of hypoalbuminemia/anemia, and elevated D -dimer/lactate dehydrogenase/alanine transaminase/respiratory rates. Combining these features predicted 28-day mortality and stratified COV-HI-YES from COV-HI-NO more effectively compared to individual markers/demographic features alone. In COV-HI-YES patients, dexamethasone treatment halved mortality-risk (relative risk = 0.50) compared to untreated patients. However, in COV-HI-NO patients mortality-risk was 3.03x higher (CI = 1.3-7.0) in treated versus untreated patients during a 28-day admission period. Conclusions We present a framework for a new machine-learning based scoring system for COV-HI combining clinical assessment with laboratory markers for prediction of mortality and targeting glucocorticoids in hospitalized COVID-19 patients.

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ORCID for Michael Ardern-Jones: orcid.org/0000-0003-1466-2016

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