|Year : 2020 | Volume
| Issue : 4 | Page : 90-95
Clinical Characteristics and Analysis of Factors Associated with Severe COVID-19 Patients in Liaoning, China: A Multicenter Retrospective Study
Xin Li, Lu Li, Xiaotong Li, Zhidan Zhang, Xiaochun Ma
Department of Critical Care Medicine, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning Province, China
|Date of Submission||02-Feb-2021|
|Date of Acceptance||09-Mar-2021|
|Date of Web Publication||25-Jun-2021|
Dr. Xiaochun Ma
Department of Critical Care Medicine, The First Affiliated Hospital of China Medical University, No. 155, Nanjing North Street, Heping District, Shenyang 110001, Liaoning Provinc
Source of Support: None, Conflict of Interest: None
Background: The prevalence of clinical manifestations in severe patients with COVID-19 was highly variable across region, populations, and assessment methods. We investigated the characteristics in patients with COVID-19 and the risk factors associated with severe cases and progression to severe patients during hospitalization. Methods: In this retrospective, multicenter observational study, we collected the clinical manifestations and laboratory regarding from 125 patients with laboratory-confirmed COVID-19 in Liaoning province, China. The collected COVID-19 patients were divided into two groups, including nonsevere group and severe group which were according to the Chinese national guideline for COVID-19 diagnosis and treatment. Results: One hundred and twenty-five laboratory-confirmed COVID-19 patients from three centralized diagnosis and treatment centers were enrolled. The median age was 44 years old, 68 (54.4%) were male. One hundred and twelve (81.6%) patients were in nonsevere group and 23 (18.4%) were in severe group. The overall hospital mortality is 1.6%. About 34% patients had been to Wuhan, 35.2%patients had contact with confirmed COVID-19 patient in Wuhan. Thirty-five (28%) patients were local and 11 (8.8%) patients had a history of direct contact with wildlife. About 20.8% of the patients had comorbidity, hypertension was the most common comorbidity (14.4%). Four patients changed from nonsevere to severe during hospitalization. Most patients were admitted in January and February (98.4%). The median hospital stay was 16 days (interquartile range [IQR]: 12–21). On admission, fever was the most common symptom (60.8%). Duration from onset symptom to hospitalization was 5 days (IQR, 2–8). Compared with nonsevere group, severe cases were associated with significant increased NE (74.19 ± 13.87 vs. 62.32 ± 12.80, P = 0.001), C-reactive protein (CRP) (33.27 ± 38.60 vs. 15.53 ± 29.35, P = 0.003), D2 (1.52 ± 2.83 vs. 0.44 ± 0.93, P = 0.021), lower lymphocyte count (0.81 ± 0.41 vs. 2.32 ± 6.63, P = 0.042), and lymphocyte percentage (LY%) (15.94 ± 10.47 vs. 28.83 ± 11.66, P < 0.001). Kaletra and Chinese medicine were most widely used, the proportion was 61.6% and 66.4%, respectively. Age (odds ratio [OR] = 1.030, 95% confidence interval [CI], 0.99–1.09; P = 0.042), fever on admission (OR = 5.23, 95% CI, 1.32–20.79; P = 0.019), increased NE (OR = 10.53, 95% CI, 3.55–31.25; P = 0.000), and decreased LY% (OR = 7.72, 95% CI, 2.61–22.83; P = 0.000) were independently associated with the severe COVID-19. Age (OR, 1.12; 95% CI, 1.01–1.23; P = 0.025), myalgia (OR, 30.82; 95% CI, 1.58–600.16; P = 0.024), and CRP (OR = 1.04, 95% CI, 1.004–1.073; P = 0.030) were associated with higher risk of development to severe COVID-19 cases. Conclusions: 1. Identification of individuals at risk for severe COVID-19 after severe acute respiratory syndrome coronavirus 2 infection is important 2. The effects of conventional methods on predicting those patients who will go on to develop severe COVID-19 are limited 3. Age, fever on admission, increased NE, and decreased LY% were independently associated with the severe COVID-19 4. Age, myalgia, and CRP were independent risk factors associated with development to severe COVID-19.
Keywords: Clinical characteristics, COVID-19, disease severity, risk factor
|How to cite this article:|
Li X, Li L, Li X, Zhang Z, Ma X. Clinical Characteristics and Analysis of Factors Associated with Severe COVID-19 Patients in Liaoning, China: A Multicenter Retrospective Study. J Transl Crit Care Med 2020;2:90-5
|How to cite this URL:|
Li X, Li L, Li X, Zhang Z, Ma X. Clinical Characteristics and Analysis of Factors Associated with Severe COVID-19 Patients in Liaoning, China: A Multicenter Retrospective Study. J Transl Crit Care Med [serial online] 2020 [cited 2023 Mar 31];2:90-5. Available from: http://www.tccmjournal.com/text.asp?2020/2/4/90/319416
| Introduction|| |
A severe acute respiratory infection (SARI) named 2019 novel coronavirus disease(COVID-19) caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), began to spread from Wuhan throughout China and the world. COVID-19 is still spreading quickly in more than 100 countries. Current studies have demonstrated the clinical features and virological course of COVID-19, the mortality was 3.6%–21%.,, In China, the mortality rate of Hubei is significantly higher than in other regions. There may be regional differences in the epidemiological and clinical characteristics of patients, which is of concern. The majority of patients (80.9%) were considered asymptomatic and nonsevere pneumonia and the asymptomatic infection accounts for a proportion of 5%. The key point of prevention and control is to prevent the transition of nonsevere to severe COVID-19.
There has been reported that severe COVID-19 was associated with demographical characteristics, comorbidities, clinical manifestations, and laboratory abnormalities. Up to now, effective indicators that predicting patients who will go on to develop severe COVID-19 during hospitalization are limited. Therefore, the estimation of risk factors for severe disease and death in these earlier case series is therefore not very robust.,, Early and effective predictors of clinical outcomes are urgently needed for the risk classification of COVID-19 patients.
In this study, we have performed details of the epidemiological, clinical, and laboratory characteristics of 125 patients with laboratory-confirmed COVID-19. We aim to describe the clinical features of COVID-19 outside Hubei province and explore risk factors associated with severe cases and progression to severe patients during hospitalization.
| Methods|| |
Study design and participants
In this retrospective, multicenter study, we enrolled 221 patients who were laboratory-confirmed by RNA detection of the SARS-CoV-2 and diagnosed as COVID-19 pneumonia according to the WHO interim guidance from January 29, 2020, to March 22, 2020, at Liaoning novel coronavirus pneumonia centralized treatment centers (Shenyang, Dalian, Jinzhou), Liaoning province, China. Ethical approval or patient consent was approved by the Ethics Committee of the First Affiliated Hospital of China Medical University. All patients were divided into two subgroups, nonsevere group and severe group according to diagnosis and treatment protocol for novel coronavirus pneumonia (1st–7th edition, (New coronavirus pneumonia diagnosis and treatment program (in Chinese). 2020http://www.nhc. gov.cn/xcs/zhengcwj/202002/3b09b894ac9b4204a79db5b 8912d4440.shtml) formulated by the National Health Commission of the People's Republic of China. Severe patients should meet at least one of the following criteria: first, shortness of breath with respiration rate >30 times/min; second, oxygen saturation <93% in resting state; and third, partial pressure of arterial oxygen-to-fraction of inspired oxygen ratio <300 mmHg. Obvious lesion progression >50% within 24–48 h on pulmonary imaging was also recognized as severe cases.
A standardized data collection electronic form was used to obtain the epidemiological, clinical, laboratory features, diagnostic classification on admission to hospital, and application of drugs during hospitalization. The outcomes including discharges, death, and hospitalization were followed up to March 22, 2020. Two independent physicians double-checked all data and a third researcher adjudicated the differences according to the original data. If the data missing from the records was needed, we obtained data by direct communication with those in charge of each centralized diagnosis and treatment center.
Laboratory examinations including complete blood count, index of hemostasis and coagulation, renal and liver function, creatine kinase, lactate dehydrogenase, myocardial enzymes, serum ferritin (PCT), and C-reactive protein (CRP) were collected on admission to the hospital.
The continuous variables were expressed as mean ± standard deviation and were compared with the Mann–Whitney U-test, and the categorical variables were presented as percentage. Comparisons of categorical variables between the groups were conducted using the Pearson's Chi-squared test or Fisher's exact test, as appropriate. The skewed distributed variables were expressed as the median and interquartile range (IQR) and analyzed by Wilcoxon test between severe and nonsevere groups. All statistical analyses were performed using IBM SPSS version 20 (IBM Corp., Armonk, NY, USA) and P < 0.05 was considered statistically significant. Logistic regression analysis was performed to explore the risk factors associated with developing to severe COVID-19.
| Results|| |
Epidemiological and clinical characteristics of the study population on admission
The study enrolled 221 admitted confirmed COVID-19 patients infection in Liaoning novel coronavirus pneumonia centralized treatment centers (Shenyang, Dalian, Jinzhou), Liaoning province, China, from January 29, 2020, to March 22, 2020. Those patients were transferred from 14 cities across Liaoning Province to the centralized treatment centers. Epidemiological and clinical characteristics are shown in [Table 1]. Of these patients, 23 (18.4%) were in the severe group and 102 (81.6%) patients in the nonsevere group. The median age was 44 years old (IQR, 34–57 years) and 68 (54.4%) were male. The proportion of patients with contact history or who had contact with COVID-19 patients in Wuhan was 30.4% and 35.2%, separately. Eighteen (14.4) patients were asymptomatic infection. About 20.8% of patients had comorbidity, including hypertension (18, 14.4%), cardiovascular disease (3, 2.4%), diabetes (7, 5.6%), chronic obstructive pulmonary disease (1, 0.8%), chronic liver disease (1, 0.8%), malignant tumor (2, 1.6%), and long-term hormone application (1, 0.85). The median hospital day was 16 (IQR, 12–21 days). The mortality was 1.6%. Compared with nonsevere group, patients in severe group were older and higher proportion of cardiovascular disease (8.7% vs. 1%, P = 0.030), chronic liver disease (4.3% vs. 0, P = 0.035), long-term hormone application (4.3% vs. 0, P = 0.035), and comorbidities and hospital mortality (8.69% vs. 0, P = 0.022).
Symptom of the study population on admission
[Table 2] shows the symptom of the study population on admission. The most common symptoms of COVID-19 onset were fever (76.8%), cough (8%), fatigue (3.2%), and diarrhea (1.6%). Severe patients had a higher temperature than nonsevere patients (P = 0.033). About 60.8% of patients had fever on admission, the median temperature was 37.6°C (IQR: 36.9°C–38.3°C). Most of the symptoms of two groups had no differences, including cough (P = 0.947), sputum production (P = 0.701), shortness of breath (P = 0.146), diarrhea (P = 0.334), and myalgia (P = 0.977), except fatigue (P = 0.049) on admission. The duration from onset of symptoms to hospital admission was 5 (IQR: 2–8) days.
Admission laboratory tests and drug application of the study population on admission
[Table 3] shows the laboratory tests of the study population on admission. Compared with nonsevere group, severe cases were associated with significant increased neutrophil count (NE) (74.19 ± 13.87 vs. 62.32 ± 12.80, P = 0.001), CRP (33.27 ± 38.60 vs. 15.53 ± 29.35, P = 0.003), D-dimer (D2) (1.52 ± 2.83 vs. 44±0.93, P = 0.021), lower lymphocyte count (0.81 ± 0.41 vs. 2.32 ± 6.63, P = 0.042), and lymphocyte percentage (LY%) (15.94 ± 10.47 vs. 28.83 ± 11.66, P < 0.001). During hospitalization, antiviral drugs (e.g., lopinavir/ritonavir, arbidol) and antibiotic drugs were used after admission [Supplementary Table 1][Additional file 1]. A total of 83 (66.4%) patients used traditional Chinese medicine. The proportion of severe patients using antibiotics (69.6%, P = 0.004), methylprednisolone (56.5%, P = 0.000), and Xuebijing injection (43.5%, P = 0.005) was higher.
Factors associated with severe COVID-19
We tried to explore the risk factors associated with severe COVID-19 by comparing clinical and laboratory characters of severe COVID-19 patients. In univariate analysis, age, fever on admission, increased NE and D2, and decreased LY% were associated with the severe COVID-19 [Table 4]. In multivariate logistical analysis, age (odds ratio [OR] = 1.030, 95% confidence interval [CI], 0.99–1.09; P = 0.042), fever on admission (OR = 5.23, 95% CI, 1.32–20.79; P = 0.019), increased NE (OR = 10.53, 95% CI, 3.55–31.25; P = 0.000), and decreased LY% (OR = 7.72, 95% CI, 2.61–22.83; P = 0.000) were independently associated with the severe COVID-19 [Table 5]. We further compared the risk factors of patients associated with development to severe and critical ill COVID-19 patients. In univariate analysis, older age (OR = 1.12, 95% CI, 1.01–1.23; P = 0.025), myalgia (OR = 30.82, 95% CI, 1.58–600.16; P = 0.024), and CRP (OR = 1.04, 95% CI, 1.004–1.073; P = 0.030) were independent risk factors [Table 4].
|Table 4: Odds ratios and 95% confidence interval of different parameters associated with the development to severe cases using logistic regression analysis|
Click here to view
|Table 5: Odds ratios and 95% confidence interval of different parameters associated with severe cases using logistic regression analysis|
Click here to view
Dynamic changes of temperature and laboratory tests in 15 days during hospitalization
Supplementary Figure 1[Additional file 2] in shows dynamic changes of temperature and laboratory tests in 15 days during hospitalization. In the 1st week, the severe group had higher body temperature and higher CRP than the nonsevere group. In comparison with nonsevere group, severe cases had lower LY% during 15 days.
| Discussion|| |
With the rising incidence of COVID-19 all over the world, feasible and effective messaging about the clinical characteristics of COVID-19 is greatly needed. Therefore, the focus of this analysis was to evaluate the prevalence of symptoms, comorbidity, laboratory tests, and different outcomes of the confirmed patients. To our knowledge, this study is the most comprehensive report to date of hospitalized patients with COVID-19 in Liaoning Province. Studies on COVID-19 had described the epidemiology and clinical characteristics, but the description of risk factors associated with development to severe cases was limited. We first described the risk factors of development to severe cases during hospitalization.
Overall, most cases (81%) of China were classified as mild or common, 14% of confirmed cases were severe, and only 5% were critical, but the case-fatality rate was 49.0% among critical cases. In our study, about 18.4% of patients were severe cases, which was inconsistent with previous reports. The age of severe group was older and there was no statistically significant difference between male and female. More than half (51.2%) of the confirmed patients were diagnosed in January, and a total of 15 (65.2%) patients were severe cases. After February, most of the cases diagnosed were local family cluster cases, and the number of asymptomatic infections increased. This was consistent with the novel coronavirus pneumonia epidemic. The novel coronavirus pneumonia epidemic situation in Liaoning province was effectively prevented and controlled in March, only two patients were diagnosed.
Notably, several questions have been raised, including the route of transmission, characteristics of clinical symptoms, aggravating factors and so on. Previous studies have reported the clinical characteristics of patients with COVID-19, but there was a lack of studies on the relation of severity and development to severity with clinical characteristics. Data suggested that older age, a rapidly progressive course of fever, cough, dyspnea, and comorbidities play an important role in influencing severe disease and negative clinical outcomes. In our study, fever was the most common symptom, especially severe patients. Fever on admission was an independent risk factor of development to severe cases. At the same time, the duration from the first symptom to admission of severe cases was relatively long (7 days, IQR 2–11). This suggested that persistent fever was an important feature of disease progression. Fever was caused by virus infections, which usually accompanied by an aggressive pro-inflammatory response and insufficient control of an anti-inflammatory response. Increased neutrophil counts indicate the intensity of inflammatory response, while the decreased lymphocyte counts suggest the damage of the immune system., CRP is an acute phase reactive protein and parallels to the severity of inflammatory. Our study was in consistent with them, and considered CRP has a potential value for monitoring the condition of progression to severe COVID-19 cases.
Notably, a complete picture of the clinical course of COVID-19 has not been described thoroughly., After identifying the high-risk factors, our study described the dynamic changes of the two groups. The progress of the disease is related to the high level of CRP, suggesting that clinicians should pay attention to such patients.
There are some limitations of our study. First, the included cases discharged as of March 22 were not all confirmed cases in Liaoning Province. Therefore, continued observations are still needed. Second, some laboratory inspection items were incomplete, such as interleukin-6 and other indicators. Third, it was a retrospective multicenter study, the results had not been verified by studies of larger sample size. Additional research is needed to elucidate viral and host factors in the pathogenesis of severe and fatal infections.
| Conclusions|| |
Identification of individuals at risk for severe COVID-19 after SARS-CoV-2 infection is important. The effects of conventional methods on predicting those patients who will go on to develop severe COVID-19 are limited. Age, fever on admission, increased NE and decreased LY% were independently associated with the severe COVID-19.Age, myalgia and CRP were independently risk factors associated with development to severe COVID-19.
Thanks to the support from the Liaoning Provincial Department of science and technology emergency project.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW, et al
. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City Area. JAMA 2020;323:2052-9.
Fanelli D, Piazza F. Analysis and forecast of COVID-19 spreading in China, Italy and France. Chaos Solitons Fractals 2020;134:109761.
Du W, Han S, Li Q, Zhang Z. Epidemic update of COVID-19 in Hubei Province compared with other regions in China. Int J Infect Dis 2020;95:321-5.
Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al
. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort study. Lancet 2020;395:1054-62.
Wang Y, Wang Y, Chen Y, Qin Q. Unique epidemiological and clinical features of the emerging 2019 novel coronavirus pneumonia (COVID-19) implicate special control measures. J Med Virol 2020;92:568-76.
Hu Z, Song C, Xu C, Jin G, Chen Y, Xu X, et al
. Clinical characteristics of 24 asymptomatic infections with COVID-19 screened among close contacts in Nanjing, China. Sci China Life Sci 2020;63:706-11.
Hu Y, Sun J, Dai Z, Deng H, Li X, Huang Q, et al
. Prevalence and severity of corona virus disease 2019 (COVID-19): A systematic review and meta-analysis. J Clin Virol 2020;127:104371.
Hu H, Yao N, Qiu Y. Comparing rapid scoring systems in mortality prediction of critically ill patients with novel coronavirus disease. Acad Emerg Med 2020;27:461-8.
Zhang L, Yan X, Fan Q, Liu H, Liu X, Liu Z, et al
. D-dimer levels on admission to predict in-hospital mortality in patients with Covid-19. J Thromb Haemost 2020;18:1324-9.
Wang F, Hou H, Luo Y, Tang G, Wu S, Huang M, et al
. The laboratory tests and host immunity of COVID-19 patients with different severity of illness. JCI Insight 2020;5:e137799.
Liang W, Liang H, Ou L, Chen B, Chen A, Li C, et al
. Development and Validation of a clinical risk score to predict the occurrence of critical illness in hospitalized patients with COVID-19. JAMA Intern Med 2020;180:1081-9.
Wang X, Zhou Q, He Y, Liu L, Ma X, Wei X, et al
. Nosocomial outbreak of COVID-19 pneumonia in Wuhan, China. Eur Respir J2020;55:2000544.
Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: Summary of a Report of 72 314 cases from the Chinese center for disease control and prevention. JAMA 2020;323:1239-42.
Lipsitch M, Swerdlow DL, Finelli L. Defining the epidemiology of Covid-19-studies needed. N Engl J Med 2020;382:1194-6.
Wong JP, Viswanathan S, Wang M, Sun LQ, Clark GC, D'Elia RV. Current and future developments in the treatment of virus-induced hypercytokinemia. Future Med Chem 2017;9:169-78.
Liu J, Mi B, Hu L, Xiong Y, Xue H, Zhou W, et al
. Preventive strategy for the clinical treatment of hip fractures in the elderly during the COVID-19 outbreak: Wuhan's experience. Aging (Albany NY) 2020;12:7619-25.
Kowalewski M, Fina D, Słomka A, Raffa GM, Martucci G, Lo Coco V, et al
. COVID-19 and ECMO: The interplay between coagulation and inflammation-a narrative review. Crit Care 2020;24:205.
Wang D, Yin Y, Hu C, Liu X, Zhang X, Zhou S, et al
. Clinical course and outcome of 107 patients infected with the novel coronavirus, SARS-CoV-2, discharged from two hospitals in Wuhan, China. Crit Care 2020;24:188.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]