A diagnostic model for serious COVID-19 infection among older adults in Shanghai during the Omicron wave.

BACKGROUND

The Omicron variant is characterized by striking infectivity and antibody evasion. The analysis of Omicron variant BA.2 infection risk factors is limited among geriatric individuals and understanding these risk factors would promote improvement in the public health system and reduction in mortality. Therefore, our research investigated BA.2 infection risk factors for discriminating severe/critical from mild/moderate geriatric patients.

METHODS

Baseline characteristics of enrolled geriatric patients (aged over 60 years) with Omicron infections were analyzed. A logistic regression analysis was conducted to evaluate factors correlated with severe/critical patients. A receiver operating characteristic (ROC) curve was constructed for predicting variables to discriminate mild/moderate patients from severe/critical patients.

RESULTS

A total of 595 geriatric patients older than 60 years were enrolled in this study. Lymphocyte subset levels were significantly decreased, and white blood cells (WBCs) and D-dimer levels were significantly increased with disease progression from a mild/moderate state to a severe/critical state. Univariate and multivariate logistic regression analyses identified a panel of WBCs, CD4 T cell, and D-dimer values that were correlated with good diagnostic accuracy for discriminating mild/moderate patients from severe/critical patients with an area under the curve of 0.962.

CONCLUSION

Some key baseline laboratory indicators change with disease development. A panel was identified for discriminating mild/moderate patients from severe/critical patients, suggesting that the panel could serve as a potential biomarker to enable physicians to provide timely medical services in clinical practice.