key: cord-0997657-kkqbjtwl
authors: Wang, Fang; Cao, Jinhong; Yu, Yong; Ding, Jianbo; Eshak, Ehab S; Liu, Keyang; Mubarik, Sumaira; Shi, Fang; Wen, Haoyu; Zeng, Zixin; Bai, Jianjun; Yu, Chuanhua
title: Epidemiological characteristics of patients with severe COVID-19 infection in Wuhan, China: evidence from a retrospective observational study
date: 2020-11-05
journal: Int J Epidemiol
DOI: 10.1093/ije/dyaa180
sha: 01c32ba74233680bfcf8154e3f6abc9ad3f084b4
doc_id: 997657
cord_uid: kkqbjtwl

BACKGROUND: The new coronavirus (COVID-19) rapidly resulted in a pandemic. We report the characteristics of patients with severe or critical severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in Wuhan city, China, and the risk factors related to infection severity and death. METHODS: We extracted the demographic and clinical data of 7283 patients with severe COVID-19 infection from designated Wuhan hospitals as of 25 February 2020. Factors associated with COVID-19 critical illness and mortality were analysed using logistic- and Cox-regression analyses. RESULTS: We studied 6269 patients with severe COVID-19 illness and 1014 critically ill patients. The median (IQR) age was 64 (53–71) years; 51.2% were male, 38.9% were retirees and 7.4% had self-reported histories of chronic disease. Up to the end of the study, 1180 patients (16.2%) recovered and were discharged, 649 (8.9%) died and the remainder were still receiving treatment. The number of daily confirmed critical cases peaked between 23 January and 1 February 2020. Patients with advanced age [odds ratio (OR), 1.03; 95% confidence intervals (CIs), 1.03–1.04], male sex (OR, 1.57; 95% CI, 1.33–1.86) and pre-existing diabetes (OR, 2.11), hypertension (OR, 2.72), cardiovascular disease (OR, 2.15) or respiratory disease (OR, 3.50) were more likely to be critically ill. Compared with those who recovered and were discharged, patients who died were older [hazard ratio (HR), 1.04; 95% CI, 1.03–1.05], more likely to be male (HR, 1.74; 95% CI, 1.44–2.11) and more likely to have hypertension (HR, 5.58), cardiovascular disease (HR, 1.83) or diabetes (HR, 1.67). CONCLUSION: Advanced age, male sex and a history of chronic disease were associated with COVID-19 critical illness and death. Identifying these risk factors could help in the clinical monitoring of susceptible populations.

In early December 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which results in coronavirus disease 2019 (COVID-19), 1,2 emerged in Wuhan city, China and spread rapidly throughout China, then around the world, leading to a global pandemic. SARS-CoV-2 is the third coronavirus-induced human epidemic in the past 20 years 3-6 and one of the major pathogens that primarily targets the human respiratory system. [7] [8] [9] The World Health Organization has characterized the pandemic as an 'international public-health emergency' and defined the global risk level as very high. 10, 11 The outbreak, first reported in Wuhan, spread across the country in just a few months, with the number of infections and deaths rising rapidly. However, under the effective control of the government and the assistance of all sectors, the epidemic prevention and control situation across the country has been well developed. According to official reports, the number of newly diagnosed cases in Wuhan started to decrease on 19 February. By 30 April, China had reported a total of 84 385 confirmed cases; of these, 4643 patients died and 78 845 patients recovered. 12 China has gained valuable experience throughout the epidemic; meanwhile, the global situation is intensifying and still very serious. Therefore, it is necessary and important to analyse and share the available Chinese data and experience.

In the early stages of the epidemic, a great deal of research focused on epidemic curve modelling and prediction, as well as detection methods and virus characteristics. [13] [14] [15] [16] Recently, some epidemiological studies on COVID-19 have been reported; 17, 18 however, these studies focused mainly on the clinical and radiological characteristics or were simple studies based on public data. [19] [20] [21] [22] [23] There is a lack of large-sample studies of patients with severe or critical COVID-19 illness with an extremely high risk of death and details of the risk factors associated with severity have not yet been well described. In this study, we retrospectively analysed the clinical data of severely and critically ill COVID-19 patients in designated hospitals in Wuhan, with the aim of identifying risk factors for both the severity of COVID-19 infection and its related mortality, to provide a basis for research and prevention strategies.

The data for this retrospective observational study were collected from the Chinese infectious-disease-reporting information system. According to national Chinese laws and regulations, as a class B infectious disease, all cases of COVID-19 must be immediately reported through the infectious-disease information system, by local hospitals or municipal Centers for Disease Control and Prevention (CDCs) and aggregated to the infectious-disease-reporting system. We systematically screened the case data of patients with COVID-19 from designated third-level medical hospitals in Wuhan (details are in the Supplementary  material, eMethods and Supplementary Table 1, available as Supplementary data at IJE online).

Our team was among those who participated in obtaining the original uncleared data from the designated hospitals during the epidemic; cleaning, shortening and analysing the original data; sending the data to the CDC and the infectious-disease-reporting information system; and working with CDC staff in ensuring the quality of the data. We were given official approvals for monitoring the data of registered patients with severe and critical COVID-19 illness in Wuhan until 25 February 2020 (i.e. the final date of follow-up in this study). All identifiable personal information was deleted for privacy protection. After excluding duplicate cases, a total of 7283 patients were diagnosed as being severely or critically ill, forming the sample for this study. A flowchart of the study population is presented in Supplementary Figure 1 , available as Supplementary data at IJE online. The study design and data analysis were approved by the Ethics Committee of the Medical Department of Wuhan University.

All the patients included in this study were diagnosed with severe or critical COVID-19 illness after laboratory confirmation, according to the diagnostic criteria of the new coronavirus infection pneumonia diagnosis and treatment plan (trial fifth version). 24 The diagnostic criteria were as follows:

• Severe illness: Patients with dyspnoea or a respiratory rate 30 breaths/min (in resting state, refers to oxygen saturation 93%) and/or arterial partial pressure of oxygen (PaO 2 )/oxygen concentration (FiO 2 ) 300 mmHg (1 mmHg ¼ 0.133 kPa). • Critical illness: Patients who meet any of the following criteria: the occurrence of respiratory failure requiring mechanical ventilation, shock and/or other organ failures that require admission to the intensive care unit.

We collected hospital-admission data on patient demographics and self-reported history of chronic diseases. Clinical characteristics included the classification of severity (severe or critical illness); date of onset, divided into four periods based on the key time points of China Chunyun (Spring Festival travel season) (December 2019 to 9 January 2020), Wuhan city lockdown (10-22 January 2020), centralized quarantines (23 January to 1 February 2020) and treatment strategies (2-25 February 2020); symptoms from onset to hospital admission (e.g. fever, cough); and clinical oxygen-therapy methods. Time-related indicators included duration from the onset of symptoms to the first day of hospitalization, duration from the onset of symptoms to clinical confirmation and duration from the onset of symptoms to the endpoint (death, recovered and discharged, or end of study on 25 February 2020).

The Kolmogorov-Smirnov test was used to test the distribution of the patients' characteristics. Results of descriptive analyses are presented as medians and interquartile ranges (IQRs) for continuous variables and as counts and percentages in each category for categorical variables. The Kruskal-Wallis test was used to test the differences in normally and non-normally distributed continuous data and the chi-squared test was used to examine the difference in proportions of categorical variables between different groups. The geographical distributions of the newly confirmed COVID-19 cases throughout the four date-of-onset periods are presented using ArcGIS software version 10.6 (Environmental Systems Research Institute Inc). To explore the risk factors associated with severity of COVID-19 (critical illness) and the risk of mortality among severely and critically ill patients until 25 February 2020, univariate and multivariate logistic-regression and Cox proportionalhazards-regression models were used to estimate the odds ratios (ORs) or hazard ratios (HRs) and 95% confidence intervals (CIs). The multivariate model included age (continuous variable), sex (male or female), location (central Wuhan area or suburbs), occupation (retirees, medical workers or others), dichotomous self-reported co-morbidities (yes or no), number of presenting symptoms (continuous variable) and the three later date-of-onset periods in reference to the December 2019 to 9 January 2020 period. The interactions between occupation categories with the presence of any co-morbidities towards the risk of developing critical COVID-19 illness and death were also investigated by adding cross-product terms of these variables to the regression models. All analyses were performed using SPSS, version 22.0 (SPSS Inc).

Characteristics of patients with severe or critical COVID-19 illness Table 1 shows the general characteristics of the study population. Of the 7283 patients with COVID-19, 86.1% 

As shown in Figure 1 , the incidence of severe and critical COVID-19 illness peaked between 23 January and 1 February 2020, with nearly 50% of all cases being confirmed in this period. Severe cases accounted for a higher proportion than critically ill cases at this stage; later on, the number of confirmed severe cases decreased. The median duration from onset of symptoms to the endpoint was 22 days in severely ill patients and 19 days in critically ill patients ( Table 1) . The outbreak began in the central area in Wuhan and gradually spread to suburban and rural areas across the four time periods, with the same trend seen for severely and critically ill patients ( Figure 2 ). The geographical difference of confirmed cases was quite large, with the highest incidence in the central districts. Table 1 shows that 81.9% of patients received initial oxygen therapy, mainly via a nasal catheter (65.1%). The prevalence of initial oxygen therapy by any method was higher in 

In Table 2 , older age, male sex and having pre-existing chronic disease were associated with more severe infection (Table 3) . As a large proportion of patients were still receiving treatment, with no definite outcome of being discharged alive or death by the end of our study on 25 February 2020, in a sensitivity analysis, 

We report on 7283 severely and critically ill patients with confirmed SARS-CoV-2 infection during the epidemic in Wuhan, China. Critical illness accounted for 13.9% of the cases. Death occurred in 8.9% of patients, of whom 63.8% were critically ill at the time of hospital admission. Older age, male sex and having pre-existing chronic disease were associated with the incidence of critical illness and a higher risk of death. The number of initial symptoms was a risk factor for those presenting with critical illness and those who died. Advanced age has been previously reported as an independent predictor of mortality in SARS, MERS and COVID-19. [25] [26] [27] Some epidemiological observations have shown that all age groups were susceptible to COVID-19 infection and that older men with chronic diseases were more severely affected. 28, 29 Among the confirmed severely and critically ill patients in our study, the prevalence of chronic diseases in men (8.68%) was higher than that in women (6.03%). The proportion of critical illness and the risk of death were higher in men than in women, which is consistent with the findings of previous studies from China suggesting a higher death rate among men compared with women. 30, 31 The exact mechanism for the augmented risk profile in men compared with women is still unclear; however, studies have suggested that the higher level of angiotensin-converting enzyme-2 (ACE2) in men might interact with viruses, rendering them more capable of infecting healthy cells. 32 In addition, men generally have more risky behaviours than women, such as their higher smoking rate, which makes them vulnerable to the risk of mortality.

Our univariate analyses showed that the retired population tended to have a higher risk of developing critical illness and a high risk of mortality that vanished after adjusting for socio-demographic and clinical factors. The higher risk of more severe illness and mortality among retirees was more likely attributed to factors such as their advanced age and pre-existing chronic diseases. Controlling for such factors turned the association and interaction to null in retirees. In our study, 44% of the patients who died reported a history of at least one pre-existing chronic disease (hypertension, cardiovascular diseases or diabetes). Those comorbidities were associated with critical illness and a higher risk of mortality in COVID-19 patients. SARS-CoV-2 is an enveloped RNA virus; it can enter the cell through the ACE2. Studies have shown that the overexpression of ACE2 in highly differentiated airway epithelial cells is the basis of SARS-CoV susceptibility. ACE2 plays an important role in normal physiological activities, to control blood pressure and cardiovascular risk. When hypertensive patients are infected by the novel coronavirus, the blood-pressure-regulation process becomes more complicated and difficult to control, and the risk of cardiovascular, renal and other systemic adverse events in COVID-19 patients will be higher. 27, 33, 34 Our study confirmed that not only in general COVID-19 patients, but also in severely and critically ill patients, the role of preexisting hypertension and cardiovascular disease remains important in regard to death after COVID-19 infection. Patients with diabetes are more likely to have serious complications from the new coronavirus because their high blood-glucose level promotes viral growth, impairs the patient's immune function and their ability to resist infection, and paves the way for secondary bacterial and viral co-infections. In addition, in the event of diabetes complications, the risk of multiple organ failure and death is greatly increased. One study indicated that mortality and multi-organ damage were significantly higher in COVID-19 patients with type 2 diabetes than in non-diabetic patients (HR, 1.5). 35 Knowledge of these risk factors can guide clinicians to conduct appropriate medical management of patients with COVID-19 and co-morbid cardiovascular disease, and indicate the group of patients in whom the progression of symptoms should be vigorously monitored and controlled. 36 Moreover, our research has also found that the proportion of critically ill patients was higher among those living in suburban areas than among those living in the central areas of Wuhan, and the risk of critical pneumonia infection among residents in suburban areas was also higher than that in central areas. We consider this phenomenon to be related to the distribution of medical resources. More medical resources were concentrated in the central area of Wuhan, whereas accessibility to and the availability of medical services for residents in the suburbs were lower.

Over the four periods of the epidemic, the risk of developing critical infection tended to decline. The incidence of severe or critical illness peaked between 23 January and 1 February 2020, followed by a decline. This was largely attributed to the timely initiatives of the Chinese government and the Wuhan authorities. 29 For example, Wuhan had been closed since 23 January. On 11 February, all the residential communities in Wuhan were closed and managed, and the scope was extended to Hubei Province on 16 February. From 24 January, Hubei Province launched a Level 1 emergency response to a public-health emergency. Thanks to the improved diagnostic techniques, increased national attention and hospital treatment capacity over time, patients in the later stages of the epidemic were diagnosed and treated earlier. Under the leadership of the national organization, since 24 January, medical teams have been set up in provinces across the country to go to Wuhan and >35 000 medical staff supported Wuhan, which greatly relieved the pressure of medical care in Wuhan. All these initiatives contributed to the reduced risk of developing critical COVID-19 illness over time.

This study has several limitations. The observationalstudy design precludes causal inference. However, under such public-health emergencies, there is really no way to carry out a more comprehensive study. Moreover, the follow-up time was relatively short and, by the end of the study period, the clinical outcome of more than half of the study's patients was not yet clear. The data on pre-existing chronic diseases were based on self-report and we could not verify their validity. Also, there was a lack and incompleteness of information on other epidemiological variables, such as body mass index and history of cancer and dyslipidaemia, and clinical characteristics. However, access to such information about a nationwide epidemic is strictly regulated by higher authorities. Currently, we are seeking official approvals to obtain updated and more comprehensive data for further research.

In summary, rigorous and timely epidemiological measures are essential to help control the rapid spread of COVID-19 infection. This study sheds light on the risk factors for both the severity of COVID-19 and its related mortality, suggesting that age, sex and pre-existing chronic diseases are independent predictors of more severe disease (critical illness) and a higher risk of death. Patients with underlying diseases living in non-central areas of Wuhan, where limited resources were available, had an increased risk of developing critical COVID-19 illness. The identification of risk factors for COVID-19 severity and mortality in this study could be helpful for early clinical monitoring of disease progression in susceptible populations.

Supplementary data are available at IJE online. 

Naming the coronavirus disease (COVID-19) and the virus that causes it

Coronaviridae Study Group of the International Committee on Taxonomy of Viruses. The species severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2

Severe acute respiratory syndrome: historical, epidemiologic, and clinical features

SARS and MERS: recent insights into emerging coronaviruses

The Middle East Respiratory Syndrome (MERS)

Molecular epidemiology, evolution and phylogeny of SARS coronavirus

Coronavirus infections: epidemiological, clinical and immunological features and hypotheses

Human coronaviruses associated with upper respiratory tract infections in three rural areas of Ghana

Coronavirus envelope protein: current knowledge

First case of 2019 novel coronavirus in the United States

World Health Organization Coronavirus disease 2019 (COVID-19)-Situation Report -101-30

Update on COVID-19 outbreak as of 24:00 on 30 April

Early estimation of the case fatality rate of COVID-19 in mainland China: a data-driven analysis

Recent advances in the detection of respiratory virus infection in humans

A novel coronavirus from patients with pneumonia in China

First two months of the 2019 Coronavirus Disease (COVID-19) epidemic in China: real-time surveillance and evaluation with a second derivative model

COVID-19, immune system response, hyperinflammation and repurposing antirheumatic drugs

Preliminary results of initial testing for coronavirus (COVID-19) in the emergency department

Clinical findings in a group of patients infected with the 2019 novel coronavirus (SARS-Cov-2) outside of Wuhan, China: retrospective case series

Clinical, laboratory and imaging features of COVID-19: A systematic review and meta-analysis

Early epidemiological analysis of the coronavirus disease 2019 outbreak based on crowdsourced data: a population-level observational study

Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study

Cause analysis and treatment strategies of 'recurrence' with novel coronavirus pneumonia (COVID-19) patients after discharge from hospital

Notification on the issuance of the CoVID-19 Diagnosis and treatment Protocol (trial fifth Revision) 关于印发新型冠状病毒 肺炎诊疗方案(试行第五版 修正版)的通知

A major outbreak of severe acute respiratory syndrome in Hong Kong

Predictors of mortality in Middle East respiratory syndrome (MERS)

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

Case-fatality rate and characteristics of patients dying in relation to COVID-19 in Italy

Association of public health interventions with the epidemiology of the COVID-19 outbreak in Wuhan, China

Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study

Clinical characteristics of Coronavirus Disease 2019 in China

Circulating plasma concentrations of angiotensin-converting enzyme 2 in men and women with heart failure and effects of renin-angiotensinaldosterone inhibitors

Cardiovascular considerations for patients, health care workers, and health systems during the COVID-19 pandemic

Does comorbidity increase the risk of patients with COVID-19: evidence from meta-analysis

Association of blood glucose control and outcomes in patients with COVID-19 and pre-existing type 2 diabetes

Analysis of factors associated with disease outcomes in hospitalized patients with 2019 novel coronavirus disease

This project was supported by the National Key R&D Program of China, the National Natural Science Foundation of China and the Fundamental Research Funds for the Central Universities, and we would like to thank the funding foundations for their support. We acknowledge all the front-line medical staff who were involved in the diagnosis and treatment of patients and the public-health workers who participated in the prevention and control of the epidemic. We thank our colleagues from Osaka University Center of Medical Data Science, Advanced Clinical Epidemiology Investigator's Research Project for providing their insight and expertise for our research.

None declared.