Clinical characteristics and risk factors of fatal patients with COVID-19: a retrospective cohort study in Wuhan, China

Abstract

Background: The coronavirus disease 2019 (COVID-19) has caused a global pandemic, resulting in considerable mortality. The risk factors, clinical treatments, especially comprehensive risk models for COVID-19 death are urgently warranted.

Methods: In this retrospective study, 281 non-survivors and 712 survivors with propensity score matching by age, sex, and comorbidities were enrolled from January 13, 2020 to March 31, 2020.

Results: Higher SOFA, qSOFA, APACHE II and SIRS scores, hypoxia, elevated inflammatory cytokines, multi-organ dysfunction, decreased immune cell subsets, and complications were significantly associated with the higher COVID-19 death risk. In addition to traditional predictors for death risk, including APACHE II (AUC = 0.83), SIRS (AUC = 0.75), SOFA (AUC = 0.70) and qSOFA scores (AUC = 0.61), another four prediction models that included immune cells subsets (AUC = 0.90), multiple organ damage biomarkers (AUC = 0.89), complications (AUC = 0.88) and inflammatory-related indexes (AUC = 0.75) were established. Additionally, the predictive accuracy of combining these risk factors (AUC = 0.950) was also significantly higher than that of each risk group alone, which was significant for early clinical management for COVID-19.

Conclusions: The potential risk factors could help to predict the clinical prognosis of COVID-19 patients at an early stage. The combined model might be more suitable for the death risk evaluation of COVID-19.

Keywords: COVID-19; Death risk; Immune cells subsets; Risk prediction models.

Fig. 1

Representative chest computed tomographic images of fatal and recovered patients with COVID-19. a-c. An elderly male recovered case confirmed with COVID-19 at different disease stages. a Axial chest CT image obtained at the onset shows diffuse ground-glass opacity (GGO) and fibrous stripes; b axial chest CT image obtained at the middle stage shows bilateral, peripheral GGO and fibrous stripes associated with smooth interlobular and intralobular septal thickening; c axial chest CT image obtained at discharge stage shows bilateral fibrous stripes and nodules. d–f An elderly male fatal case confirmed with COVID-19 at different disease stages. a Axial chest CT obtained at the onset shows bilateral diffuse GGO associated with round cystic change, local bronchial meteorology and left pleural effusion; e axial chest CT image obtained at the middle stage shows the progression of bilateral GGO, bronchial meteorology and pleural effusion; f axial chest CT image obtained near stage of death shows the progression of bilateral GGO, round cystic change, bronchial meteorology, and increase of pleural effusion

Fig. 2

Comprehensive prediction models for death risk of COVID-19 patients. Time-dependent receiver operating characteristic (ROC) curves and area under the curve (AUC) were employed to assess the predictive accuracy of models evaluating the death risk of COVID-19 with SOFA, qSOFA, APACHE II and SIRS scores, inflammatory-related indexes, complications, organ damage indexes, immune cell subsets and combined group integrating abovementioned these factors. The multivariate Cox proportional hazards model analysis were used to establish a risk model. The stepwise regression was used for the selection of the prediction for the model. ROC curves and AUCs (95% CIs) values were generated to assess prognostic accuracy for each model. A two-sided P value < 0.05 was considered statistically significant