Several previous studies have systematically summarized the features of SARS-Cov-2 pneumonia patients.[1, 5, 16, 17] Yang et al described the characteristics of critically ill patients with SARS-CoV-2 pneumonia. At present, some studies have investigated the risk factors affecting mortality in SARS-CoV-2 pneumonia, but papers constructing risk models to predict survival are very limited, which may be practical for doctors to make clinical decisions in the early stage.
In our training cohort, the mean age of non-survivors was older than survivors (68 years vs 58 years). Most of elders were accompanied by underlying diseases, including hypertension, coronary heart disease, lung underlying diseases, and diabetes mellitus, which were documented in other viral pneumonia studies, such as SARS-CoV-2 [9, 17], SARS , MERS . As for vital signs, the levels of body temperature, heart rate, and respiratory rate were all higher in non-survivors than those of survivors. However, univariate and multivariate analyses between survivors and non-survivors showed that age (≥ 60 years) and respiratory rate (≥ 30/minute) were significantly associated with hospital mortality of patients with SARS-CoV-2 pneumonia. Previous studies has shown that, the age deference between survivors and non-survivors was outstanding, such as SARS-CoV-2(mean (SD), 51.9 (12.9) vs 64.6 (11.2) ) and SARS (median (IQR), 55 (35–63) vs 70 (56–76) ) in 28 days. Higher respiratory rate was a common sign of dyspnea for patients, with a probability of disease progress to acute respiratory distress syndrome (ARDS). Zhou Fei et al. reported that respiratory rate in non-survival COVID-19 patients was much higher than that of survivors (34 [63%] vs 22 [16%], P < 0.001), and 50 of 54 (93%) non-survival patients had presented as ARDS before death. Then, it’s reasonable to consider that respiratory rate(≥ 30/minute) was an independent risk factor for predicting mortality of patients with SARS-CoV-2 pneumonia.
Similar to a previous report, our univariate analysis had also shown a decrease in the count of lymphocyte and platelet, as well as an increase in LDH and d-dimer. The other mortality risk factors were increased neutrophil count, procalcitonin, BUN, hs-cTnI, AST and etc. As shown before, the lymphocyte count was much lower in non-survival patients. Previous study indicated that lymphocyte count < 0.8 × 109/L was an independent mortality risk factor for viral pneumonia. In our study, reduced lymphocyte count was confirmed to be a vital and independent mortality associated risk factor by using multivariate logistic regression analysis(OR = 4.853). It is presumed that lymphocytes are at an exhaustion state before the patients reached death. Nevertheless, WBC count of the non-survivors was significantly increased, especially the neutrophils in non-survivors were around 2.6-fold higher than survivors. Although many patients in our study had neutrophil count below 7 × 109/L and procalcitonin below 0.25 ng/ml, most of non-survival patients showed the increased neutrophil count and procalcitonin. Elevated serum procalcitonin was regarded as one of most commonly used markers for bacterial infection. Bacterial coinfection was known as a major cause of mortality H7N9 influenza pneumonia, and the most common pathogen detected by sputum or blood culture was Acinetobacter baumannii [20, 22]. Bacterial co-infection not only indicated higher mortality but also longer hospital stay time and much more hospital care cost compared with non-bacterial co-infection. Furthermore, elevated levels of WBC and neutrophils are thought to be a major contributory factor for disease progression. Univariate and multivariate analysis indicated that increased neutrophil count (≥ 7 × 109/L) was risk factor for mortality of patients. This result was documented in other studies showing that the neutrophil count was elevated in non-survivors of novel coronavirus infected pneumonia compared with survivors. In our current study, procalcitonin was identified to be a very important mortality associated factor, because of much higher weight(OR = 5.586) than other factors. Until now, there is rare report about procalcitonin contributing to the death of patients with SARS-CoV-2 pneumonia. Therefore, we concluded that lymphocyte count reduction and bacterial co-infection (increased neutrophil count and procalcitonin) are two leading risks for the mortality of patients with SARS-CoV-2 pneumonia.
In our study, we further evaluated the importance of LDH in SARS-CoV-2 pneumonia. The level of serum LDH was found to be significantly elevated in more than 70% of patients in our study. Moreover, LDH with a level ≥ 350 U/L was found to be associated with the risk of death in SARS-CoV-2 pneumonia patients by multivariate analysis. A previous study showed that LDH level was associated with the severity of various diseases including SARS. It has been proved that the level of LDH was higher in ICU patients with SARS-CoV-2 pneumonia than that in non-ICU patients in Wuhan. Other factors, such as the platelet count, APTT, PT, ALT, AST, CRP, TP, ALB, BUN, and Scr, were associated mortality of patients by univariate analysis, however, they were not identified as the risks of mortality by multivariate analysis in our study.
Cardiac complications (including heart failure, arrhythmia, or myocardial infarction) are common in patients with pneumonia, especially in critical illness . Coronary heart disease was shown to be correlated with acute cardiac events and poor prognosis in influenza and other viral pneumonia[27, 28]. Chen C et al. showed that cTnI was increased in critically ill patients with COVID-19, which was an independent risk factor of clinical disease status. In our study, hs-cTnI or cTnI on admission was found be increased in more than half of non-survival patients. Elevated hs-cTnI or cTnI level on admission indicated myocardial injury, which was confirmed to be significantly associated with mortality of patients. This result was consistent with a recently published study. Therefore, presence of myocardial injury on admission is another important risk factor for predicting the mortality of patients with SARS-CoV-2 pneumonia.
Higher coagulation activity was found in most hospitalized pneumonia patients (almost 90%), and its main marker was increased d-dimer concentration. In this study, d-dimer greater than 1.5 µg/mL is associated with mortality of SARS-CoV-2 pneumonia, which was documented in a previous study. The elevation of d-dimer might be due to hypercoagulable state of patients during SARS-CoV-2 infection. Pathologists confirmed that hyaline thrombi were found in some microvessels of three cases with COVID-19 by minimally invasive autopsies . Furthermore, anticoagulant therapy was found to be correlated with better prognosis in severe ill COVID-19 patients with increased level of D-dimer. In addition, blood-borne tissue factor, which was found to be expressed on the cell surfaces of alveolar macrophages, neutrophils, and endothelial cells during lung infection, could highly induce systemic coagulopathy. Therefore, it may predispose to thrombosis in the pulmonary micovessels of patients with SARS-CoV-2 pneumonia, presenting as the significant elevation of d-dimer.
Currently, CT scan is considered to be an effective modality for clinical diagnosis for viral pneumonia at early periods. From our CT images in SARS-CoV-2 pneumonia, we concluded that infiltrated lesions in five lung lobes were shown in the majority of the infected patients. Ground-glass opacities and consolidation are the main features of CT. These CT imaging manifestations may have some differences from that in SARS. In SARS, CT imaging normally presents in the lower lung lobes with multifocal airspace consolidation in a short period. Therefore, CT has limited value in predicting death in the patients with SARS-CoV-2 pneumonia, mainly because most cases presented as mutiple lobular infiltration (usually 5 lobes) or diffuse lesions on CT images whether in survival or non-survival patients.
Although many predictive models are available to evaluate the prognosis of pneumonia, including IDSA/ATS minor criteria, CRB-65, CURB-65, Halm criteria, qSOFA, PSI, SCAP, SIRS-Score, SMART-COP, SOFA for community-acquired pneumonia (CAP) and MuLBSTA score for viral infection , there is a lack of predictive tool especially for coronavirus pneumonia mortality. By multivariate logistic regression analysis, age(≥ 60 years), respiratory rate(≥ 30 breaths/minute), neutrophil count (≥ 7 × 109/L), PCT(≥ 0.1 ng/mL), lymphocyte count (≤ 0.8 × 109/L), d-dimer(≥ 1.5ug/mL), LDH(≥ 350U/L), and presence of myocardial injury were identified to be eight independent risks for mortality prediction for SARS-CoV-2 pneumonia patients. Then, we employed these eight risk factors and formulated a reliable mortality risk predictive model to stratify SARS-CoV-2 pneumonia patients. This model was also validated by both internal and external validation set, and the visual expression of the model was displayed by a nomogram. The good predictive performance of the nomogram is suggested by calibration, discrimination, survival curve analysis, and DCA. Furthermore, this nomogram had a better predictive ability than that of CURB-65 score both in training and validation sets.
The research has several limitations. First, this retrospective design may cause a potential and inherent selection bias. Secondly, most patients have not been tested for the levels of cytokines and the counts of T cells subgroup. Thus, we failed to consider these factors in multiple imputation and further analysis to avoid great bias from real situation. Through a simple comparison between groups, we found some interesting differences. We are planning to explore their significance in subsequent clinical studies. Third, all the patients included in our study are Chinese. The clinical features of patients might be different in other countries or areas. Then, there may be some inherent biases by using this study format. Our results should be further validated by the multiple-center, prospective study.