Prediction for Progression Risk in Patients with COVID-19 Pneumonia: the CALL Score

Abstract

Background

We aimed to clarify the high-risk factors with multivariate analysis and establish a prediction of disease progression, so as to help clinicians to better choose therapeutic strategy.

Methods

All the consecutive patients with COVID-19 admitted to Fuyang second people’s hospital or the fifth medical center of Chinese PLA general hospital between January 20 and February 22, 2020, were enrolled and their clinical data were retrospectively collected. Multivariate COX regression was used to identify the risk factors associated with progression, and then were incorporated into the nomogram to establish a novel prediction scoring model. ROC was used to assess the performance of the novel model.

Results

Overall, 208 patients were divided into stable group (n=168, 80.8%) and progressive group (n=40,19.2%) based on whether their conditions worsened during the hospitalization Univariate and multivariate analysis showed that comorbidity, older age, lower lymphocyte and higher lactate dehydrogenase at presentation were independent high-risk factors for COVID-19 progression. Incorporating these 4 factors, the nomogram achieved good concordance indexes of 0.86 (95%CI 0.81 - 0.91), and had well-fitted calibration curves. A novel scoring model, named as CALL, was established, and its area under ROC was 0.91 (95% CI 0.86 to 0.94). Using a cutoff value of 6 points, the positive and negative predictive values were 50.7% (38.9% - 62.4%) and 98.5% (94.7% - 99.8%), respectively.

Conclusion

Using the CALL score model, clinicians can improve the therapeutic effect and reduce the mortality of COVID-19 with more accurate and reasonable resolutions on medical resources.