Development of a novel score model to predict hyperinflammation in COVID-19 as a forecast of optimal steroid administration timing.

Objectives: This study aims to create and validate a useful score system predicting the hyper-inflammatory conditions of COVID-19, by comparing it with the modified H-score.

Methods: A total of 98 patients with pneumonia (without oxygen therapy) who received initial administration of casirivimab/imdevimab or remdesivir were included in the study. The enrolled patients were divided into two groups: patients who required corticosteroid due to deterioration of pneumonia, assessed by chest X-ray or CT or respiratory failure, and those who did not, and clinical parameters were compared.

Results: Significant differences were detected in respiratory rate, breaths/min, SpO, body temperature, AST, LDH, ferritin, and IFN-λ3 between the two groups. Based on the data, we created a corticosteroid requirement score: (1) the duration of symptom onset to treatment initiation ≥ 7 d, (2) the respiratory rate ≥ 22 breaths/min, (3) the SpO ≤ 95%, (4) BT ≥ 38.5°C, (5) AST levels ≥ 40 U/L, (6) LDH levels ≥ 340 U/L, (7) ferritin levels ≥ 800 ng/mL, and (8) IFN-λ3 levels ≥ 20 pg/mL. These were set as parameters of the steroid predicting score. Results showed that the area under the curve (AUC) of the steroid predicting score (AUC: 0.792, 95%CI: 0.698-0.886) was significantly higher than that of the modified H-score (AUC: 0.633, 95%CI: 0.502-0.764).

Conclusion: The steroid predicting score may be useful to predict the requirement of corticosteroid therapy in patients with COVID-19. The data may provide important information to facilitate a prospective study on a larger scale in this field.