Clinical characteristics and risk factors of patients with severe COVID-19 in Jiangsu province, China CURRENT STATUS:

Background To describe the characteristics of patients Coronavirus Disease-2019 (COVID-19) factors associated with severe or critically ill presentation. Methods Multicentre retrospective cohort study of all individuals with confirmed Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV2) infections diagnosed at 24 COVID-19-designated hospitals in Jiangsu province between the 10th January and 15th March 2020. Demographic, clinical, laboratory, and radiological data were collected at hospital admission and data on disease severity were collected at from admission. Patients were categorised as asymptomatic/mild/moderate, and severe/critically ill according to the worst level of COVID-19 recorded during hospitalisation. Results A total of 625 patients, 64 (10.2%) were severe/critically ill and 561 (89.8%) were asymptomatic/mild/moderate. All patients were discharged and no patients died. Multivariable regression showed that odds of being a severe/critically ill case were associated with age (year) (OR, 95%CI 1.06, 1.03–1.09), lymphocyte count (10 9 /L) (OR 0.25, 0.08–0.74), and pulmonary opacity in CT (per 5%) on admission (OR 1.31, 95%CI 1.15–1.51).


Abstract Background
To describe the characteristics of patients with Coronavirus Disease-2019  and factors associated with severe or critically ill presentation.

Methods
Multicentre retrospective cohort study of all individuals with confirmed Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV2) infections diagnosed at 24 COVID-19-designated hospitals in Jiangsu province between the 10th January and 15th March 2020. Demographic, clinical, laboratory, and radiological data were collected at hospital admission and data on disease severity were collected at from admission. Patients were categorised as asymptomatic/mild/moderate, and severe/critically ill according to the worst level of COVID-19 recorded during hospitalisation.

Results
A total of 625 patients, 64 (10.2%) were severe/critically ill and 561 (89.8%) were asymptomatic/mild/moderate. All patients were discharged and no patients died. Multivariable regression showed that odds of being a severe/critically ill case were associated with age (year) (OR, China has reported the highest number of cases, with over 81,000 confirmed cases by the 13th March. 1 Although the epicentre of the epidemic was located in Wuhan, other provinces became affected in the following weeks. In a case series of the first 44,672 confirmed cases, 1023 patients had died, with a crude case fatality rate (CFR) of 2.3%, and mortality was higher among critically ill patients, who had a CFR of 49%. 3 In Hubei, the proportion of severe COVID-19 cases was higher than in other provinces (17.7% and 7.0%, respectively) and cases outside the epicentre may have other differences due to active case finding, better screening tests and increase disease awareness.
COVID-19 initial symptoms are not specific, presenting with fever, and cough, which can then resolve spontaneously or progress to shortness of breath, dyspnoea, and pneumonia, leading to severe acute respiratory syndrome (SARS), renal failure, coagulation dysfunction, multiple organ failure and death.
Understanding the factors associated with COVID-19 disease severity could support the early identification of patients with high risk for disease progression and inform prevention and control activities and reduce mortality. Furthermore, understanding differences in the epidemiology and characteristics of patients outside Hubei is important for disease forecasting and to inform prevention and control strategies. Jiangsu, a province over 600 kms from Hubei without common geographical borders and 80 million population, reported over 600 patients, but the epidemiological and clinical characteristics of these patients has not been described. We report here an analysis of all cases in Jiangsu province to describe the epidemiological and clinical characteristics of cases and to identify risk factors for severe/critically ill COVID-19 presentation.

Study Design and Population
This is a multicentre retrospective cohort study. All patients were included if they (1) were clinically Patients without medical records were excluded.
The Ethics Committee of Zhongda Hospital, Affiliated to Southeast University, approved the study protocols (2020ZDSYLL013-P01 and 2020ZDSYLL019-P01). Patient informed consent was waived due to the retrospective study and the public health emergency.

Data Measures
The primary outcome was severe or critically ill within the follow up period. Patients were categorised by disease severity into (1) asymptomatic or mild, (2) moderate, and (3)  Data was collected using case record forms and electronic medical record systems and included epidemiological, laboratory and imaging information, treatment and clinical outcome. Information of patients transferred to other hospitals was retrieved from the destination hospital. The day of admission to a COVID-19-designated hospital was considered the first day of hospitalisation. The severity of illness and the score of lung injury was assessed by two physicians and vital signs, symptoms. Severity was assessed at days 1, 2, 3, 4, 5, 6, 7 and 14 after admission and patients were followed for up to discharge. ICU admissions were recorded. Imaging grading was performed by two independent radiologists with more than 5 years' experience in pulmonary imaging. Chest CT axial sections were divided into quadrants (left and right anterior and posterior) by drawing horizontal and vertical lines through the centre of the chest. Quadrant scores were estimated as the sum of quadrants with pulmonary opacities extending from the proximal to the distal end of the chest and ranged from 0 and 4. For pulmonary opacity, bilateral lungs were scored manually and assigned an estimated percentage of pulmonary opacity relative to the whole lung, rounded to the nearest 5%.

Statistical Analysis
Continuous variables were described using means (standard deviations, SD) or medians (with interquartile range, IQR) by disease severity and were compared using ANOVA or Kruskal-Wallis tests as appropriate. Categorical variables were summarised using frequencies and percentages and compared using Fisher exact tests.
Logistic regression models were used to identify the risk factors for having a severe or critically ill status. Analysis was performed in 2 steps. Firstly, a univariate logistic regression model was fitted. As there are many potential predictors, we chose the variables for univariate regression analysis if a variable is significant at 5%. Respiratory rate and SpO 2 were not included in the regression analyses since they were part of criterion for classifying the disease severity. All variables selected for univariate regression analysis were also included in the second stage of the multivariate logistic regression. Missing covariates at admission were imputed with multiple imputation using a Markov Chain Monte Carlo simulation method with 10 iterations. In the logistic regression analysis, odds ratios for having a disease progression for each variable were calculated along with 95% confidence intervals (CIs). A sensitivity analysis was performed on the completed cases. The 2-tailed P < 0.05 was considered as statistically significant for all analyses. The analyses were performed using SAS 9.4 (SAS Institute).

Results
A total of 721 patients with confirmed SARS-CoV2 infections were admitted to the twenty-four COVID-6 (99.0%) had retrievable medical records and were included in the analysis. Table 1 describes the characteristics of patients at the time of admission by disease severity and   Table S1 provides a more detailed description of the five severity categories. 561 (89.8%) patients were asymptomatic/mild/moderate and 64 (10.2%) patients were severe or critically ill. Patients with severe/critically ill COVID-19 were more likely to be older and to be single onset (i.e. not to a cluster of cases in family/community). Patients with moderate or severe/critically ill presentation were more likely to have a medical history of hypertension, coronary heart disease, and diabetes. Patients with moderate/severe COVID-19 on admission had higher temperature, faster respiratory rates, lower peripheral capillary oxygen saturation (SpO 2 ), and higher CT image quadrant scores and pulmonary opacity percentage (Table 1 and Table S1).  Cases with severe/critically ill presentation were more likely to have increased C-reactive protein, procalcitonin, fibrinogen, and D-dimer than asymptomatic/mild/moderate cases (Table 1). Similarly, severe/critically ill cases had lower white blood cells, lymphocyte, and platelet counts and albumin. As expected, severe cases were more likely to use supportive treatments and medical drugs, including antibiotics and antivirals (Table 2).

Discussion
In this large multicentre cohort, 64 (10.2%) of 625 patients were severe or critically ill. This proportion is lower than the 17.7% reported among the 44 672 cases from Wuhan but similar to the 7.0% reported for areas outside Hubei province, 3 which are lower than reported from several case series from Wuhan including 13 (32%) ICU admission among 41 cases with 6 (15%) deaths; 5 11 (11%) deaths among 99 cases; 6 and 36 (26.1%) ICU admissions among 138 patients, with 6 deaths (4.3%). 7 Our lower proportion is likely due to several factors, including more adequate medical resources, better disease recognition and testing capacity, earlier identification of asymptomatic and mild cases and a more informed supportive care in COVID-19-designated hospitals.
Despite this being a hospital-based study, some patients had no symptoms. This is likely due to testing of contacts after the identification of an index case and the policy of hospitalization of all infected individuals at the initial stages of the epidemic, independently of the presence of symptoms.
Fever, cough, and sputum were very common among patients and more frequent in patients with severely or critically illness. Fever and cough are the most common symptoms in SARS and MERS cases. 8,9 Fever is a primary symptom for cytokine storms, with the production of high concentrations of cytokines stimulating abnormally excessive immune responses and inflammation. Vital signs showed severe or critically ill patients had higher body temperature and respiratory rate, and lower SpO 2 on admission. SpO 2 < 90% has been used as a marker for the use of glucocorticoids during the outbreak, 10 and the oxygenation saturation index is associated with ARDS severity and increased mortality. 11,12 Sex seems does not have an impact on severe COVID-19. Although early reports from Wuhan indicated more men than women had severe COVID-19, 5,6,13 following studies reported similar proportions of men and women admitted to ICUs, suggesting sex differences disappeared with higher incidence. Earlier reports may have included more males due to a higher occupational infection risk for males in the markets and congregation places. 7 Our study found that age was independently associated with severe or critically ill presentation. Older age reflects a greater likelihood of underlying medical conditions such as hypertension, coronary heart disease, and diabetes, which predisposes to immunological vulnerabilities. Also, agerelated immunosenescence may also contribute to the severe disease. 21 The mean incubation period for severe or critically ill cases in Jiangsu (7 days) was longer than the 5 days (95% CI, 4.1-7.0) reported for the first 425 Wuhan patients with confirmed COVID-19. 22 The mean incubation period was slightly longer for less severe than for severe or critically ill patients.
Although this was not statistically significant, larger series should explore this finding, as shorter incubation periods may reflect the higher infecting doses often observed at the start of epidemics, as reported for the Middle East Respiratory Syndrome (MERS). 23 In our cohort, patients with local and known exposures to confirmed COVID-19 cases were less likely to have severe/critically ill infections than patients who had been or had visitors from Wuhan and those who had no identifiable exposure. As patients with known local exposure were more likely second or third generation SARS-CoV2 transmissions and the virulence of the virus may have changed, as seen for other infections. These patients may have also been aware of the infection risk and taken protective measures which could have reduced the infection dose.
In Wuhan, many asymptomatic patients had abnormal lung CT findings on admission, which then progressed to diffuse ground-glass opacities and consolidation. 24 In Jiangsu, several asymptomatic cases also had radiological changes presented as low quadrant scores and pulmonary opacity scores on admission and severe/critically-ill cases had higher CT quadrant and pulmonary opacity scores than moderate cases. Our study also identified pulmonary opacity as an independent predictor of severe/critical illness. This is consistent with the previous study reporting that the CT visual quantitative evaluation of acute lung inflammatory lesions involving each lobe in severe or critical cases was significantly higher than less severe cases. 25 We found severe or critically ill patients had more obvious damage of white blood cells and immune cells such as lymphocytes with lymphocytes identified as an independent predictor of more severe disease. COVID-19 may cause the reduced T lymphocytes, especially CD4 + T and CD8 + T cells, leading to reduced IFN-γ production, which may be related to the severity of disease. 26 In addition, severe or critically ill patients showed more serious organ dysfunction like reduce albumin on admission which may be a sign of reduced liver production and increased gastrointestinal or renal loss, and increased fibrinogen on admission responding to systemic inflammation and tissue damage, and more fierce inflammatory response presented as much higher level of inflammatory markers, such as C-reactive protein.
This study has several strengths. Firstly, this is one of the largest studies describing the clinical characteristics of patients with COVID-19 and risk factors for severe/critically ill infection outside the Wuhan epicentre. Secondly, the cohort includes almost all COVID-19 cases in the province, which may have reduced selection bias. Thirdly, Jiangsu province, which is far from Hubei, provides an opportunity to assess the epidemiological, laboratory and clinical features of cases imported from other provinces and local cases. Fourthly, asymptomatic and mild cases were included, which provides a more comprehensive description of the characteristics of COVID-19 cases with a broad spectrum of disease severity.
There are also limitations that need mentioning. Firstly, laboratory and radiological data had a large amount of missing data preventing their integration in the analysis. Secondly, the predictive factors identified may be subject to uncontrolled confounders by unknown/unmeasured factors such as occupation and pregnancy. Medical staff and pregnant women may have different severity profiles.
Thirdly, this is a retrospective observational study and data is susceptible to measurement and information bias.
In conclusion, this study demonstrates that patients with COVID-19 in Jiangsu had a low rate of severe or critically ill presentation, with no deaths recorded. The COVID-19 severity is associated with epidemiological and clinical characteristics, laboratory tests, and radiological findings. Age, lymphocyte count, and pulmonary opacity in CT on admission were independently associated with risk of severe or critically ill COVID-19 presentation.

Declarations Declaration Of Competing Interest
We declare no competing interests.

Ethics Approval And Consent To Participate
The Ethics Committee of Zhongda Hospital, Affiliated to Southeast University, approved the study protocols (2020ZDSYLL013-P01 and 2020ZDSYLL019-P01). Patient informed consent was waived due to the retrospective study and the public health emergency.