Dear Editor,
The outbreak of novel coronavirus disease (COVID-19) that began in December 2019 has posed a great threat to human health and been declared a global pandemic by the World Health Organization [1–3]. Shenzhen, an important and special economic zone in China, shares a large floating population with Hubei province. From the first occurrence of COVID-19 on January 11, 2020, to April 26, 2020, there were 461 cases confirmed with infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), including 12 patients who remained in the hospital, 3 deaths, and 446 discharged patients [4]. In the present study, we aimed to describe the clinical characteristics of COVID-19 patients in Shenzhen and identify risk factors for the development of SARS-CoV-2-induced sepsis in imported COVID-19 patients.
In this retrospective study, patients who were confirmed to have SARS-CoV-2 infection and admitted to the Third People’s Hospital of Shenzhen from January 11 to February 12, 2020, were enrolled. Clinical data were extracted and followed up to March 11, 2020, by using predesigned data collection forms. The baseline characteristics of all enrolled patients in the sepsis and non-sepsis groups were summarized and compared by applying Student’s t test, the Chi-square test, Fisher’s exact test, and the Mann–Whitney U test as appropriate. Continuous variables were presented as the mean (standard deviation [SD]) or median (interquartile range [IQR]), while categorical or ranked data were reported as counts and proportions.
A total of 150 hospitalized COVID-19 patients were enrolled in this study, including 49 (32.7%) patients with SARS-CoV-2-induced sepsis at hospital admission and 101 (67.3%) non-septic patients (Table 1). Patients with viral sepsis were much older than those without sepsis (63 vs. 46 years, P < 0.001) and presented with more comorbidities, including hypertension (14 [28.6%] vs. 11 [10.9%], P = 0.006) and diabetes (9 [18.4%] vs. 3 [3%], P = 0.003). Septic patients had significantly higher neutrophil counts, monocyte counts, international normalized ratios, D-dimer values, alanine aminotransferase, aspartate aminotransferase, serum creatinine, blood urea nitrogen, creatine kinase, lactate dehydrogenase, prothrombin times and activated partial thromboplastin times than non-septic patients, but their lymphocyte counts, platelet counts, and albumin levels were significantly lower. Septic patients were more likely to be transferred to the ICU (28 [57.1%] vs. 10 [9.9%]; P < 0.001) and had a significantly prolonged hospital stay (median days, 23.5 days [IQR, 16.3-32.8] vs. 15 days [IQR, 13-20]; P < 0.001) than non-septic patients. Additionally, deaths (3 [6.1%]) occurred solely among patients who developed sepsis at hospital admission. Exposure history, platelet count, T lymphocyte count, cytotoxic T lymphocyte count, IL-6, serum creatinine, erythrocyte sedimentation rate, and sodium might be useful for predicting the incidence of SARS-CoV-2-infection-induced sepsis (electronic supplementary materials).
Table 1.
Baseline characteristics of 150 patients confirmed with COVID-19 in Shenzhen, China
| No. (%) of patients | ||||
|---|---|---|---|---|
| Total (n = 150) | Sepsis (n = 49) | Non-sepsis (n = 101) | P value | |
| Demographic characteristics | ||||
| Age, median (IQR), years | 54 (37–63) | 63 (55.5–66) | 46 (34–57) | < 0.001 |
| Female | 68 (45.3) | 17 (34.7) | 51 (50.5) | 0.068 |
| BMI, mean (SD) | 23.7 (3.7) | 25.0 (3.3) | 23.1 (3.8) | 0.004 |
| Causes of infection | 0.005 | |||
| Traveling history of Hubei province | 133 (88.7) | 38 (77.6) | 95 (94.1) | |
| Contact with local confirmed cases | 1 (0.7) | 1 (2) | 0 (0) | |
| Undetermined cause of infection | 16 (10.6) | 10 (20.4) | 6 (5.9) | |
| Comorbidities | ||||
| Hypertension | 25 (16.7) | 14 (28.6) | 11 (10.9) | 0.006 |
| Diabetes | 12 (8) | 9 (18.4) | 3 (3) | 0.003 |
| Coronary heart disease | 8 (5.3) | 4 (8.2) | 4 (4) | 0.492 |
| Chronic bronchitis | 4 (2.7) | 2 (4.1) | 2 (2) | 0.835 |
| Smoking history | 3 (2) | 3 (6.1) | 0 (0) | 0.059 |
| Malignant tumor | 3 (2) | 2 (4.1) | 1 (1) | 0.518 |
| Gout | 3 (2) | 2 (4.1) | 1 (1) | 0.518 |
| Cerebrovascular disease | 2 (1.3) | 2 (4.1) | 0 (0) | 0.105 |
| Immunocompromised diseases | 1 (0.7) | 0 (0) | 1 (1) | > 0.99 |
| Signs and symptoms | ||||
| Fever | 125 (83.3) | 42 (85.7) | 83 (82.2) | 0.586 |
| Dry cough | 44 (29.3) | 16 (32.7) | 28 (27.7) | 0.534 |
| Expectoration | 35 (23.3) | 14 (28.6) | 21 (20.8) | 0.291 |
| Fatigue | 33 (22) | 16 (32.7) | 17 (16.8) | 0.028 |
| Myalgia | 32 (21.3) | 13 (26.5) | 19 (18.8) | 0.279 |
| Chest distress | 13 (8.7) | 6 (12.2) | 7 (6.9) | 0.438 |
| Dizziness | 11 (7.3) | 7 (14.3) | 4 (4) | 0.052 |
| Headache | 10 (6.7) | 3 (6.1) | 7 (6.9) | > 0.99 |
| Anorexia | 10 (6.7) | 6 (12.2) | 4 (4) | 0.119 |
| Diarrhea | 10 (6.7) | 4 (8.2) | 6 (5.9) | 0.871 |
| Nausea | 5 (3.3) | 4 (8.2) | 1 (1) | 0.070 |
| Dyspnea | 4 (2.7) | 2 (4.1) | 2 (2) | 0.835 |
| Stomachache | 2 (1.3) | 1 (2) | 1 (1) | 0.548 |
| Vomiting | 1 (0.7) | 0 (0) | 1 (1) | > 0.99 |
| No signs and symptoms | 10 (6.7) | 2 (4.1) | 8 (7.9) | 0.593 |
| Body temperature, median (IQR), °C | 37.2 (36.7–38) | 37.8 (37.2–38.3) | 36.9 (36.7–37.8) | < 0.001 |
| Heart rates, median (IQR), /min | 89.5 (83–98) | 93 (86–101) | 88 (81–96) | 0.025 |
| Respiratory rates, median (IQR), /min | 20 (19–21) | 21 (20–22.5) | 20 (19–20) | < 0.001 |
| Mean arterial pressure, median (IQR), mmHg | 95 (89.7–103.4) | 96.7 (91.8–108.8) | 94.3 (88.8–102.8) | 0.072 |
| Diastolic blood pressure, median (IQR), mmHg | 80 (74.8–89) | 82 (75–88) | 79 (74–89) | 0.432 |
| Systolic blood pressure, median (IQR), mmHg | 128 (118–139) | 128 (123.5–152) | 126 (117–138) | 0.025 |
| APACHE II, median (IQR) | 4 (2–6) | 6 (4–8.5) | 3 (1–5.5) | < 0.001 |
| SOFA, median (IQR) | 1 (0–2) | 2 (2–3) | 0 (0–1) | < 0.001 |
| Onset of symptoms to hospital admission, median (IQR), days | 4 (2–7) | 4 (2–7.5) | 3 (2–5.5) | 0.044 |
| Complications | ||||
| ARDS | 87 (58) | 47 (95.9) | 40 (39.6) | < 0.001 |
| Acute liver injury | 28 (18.7) | 20 (40.8) | 8 (7.9) | < 0.001 |
| Acute kidney injury | 11 (7.3) | 10 (20.4) | 1 (1) | < 0.001 |
| Acute cardiac injury | 11 (7.3) | 8 (16.3) | 3 (3) | 0.009 |
| Shock | 9 (6) | 7 (14.3) | 2 (2) | 0.009 |
| Coagulopathy | 9 (6) | 9 (18.4) | 0 (0) | < 0.001 |
| Secondary infection | 17 (11.3) | 9 (18.4) | 8 (7.9) | 0.058 |
| Prognosis | ||||
| Discharge from hospital | 126 (84) | 36 (73.5) | 90 (89.1) | 0.014 |
| Length of stay in hospital, median (IQR), days | 16 (13–24.3) | 23.5 (16.3–32.8) | 15 (13–20) | < 0.001 |
| Hospital admission to ICU admission, median (IQR), days | 6 (2–9) | 5 (2–8.8) | 7 (4.8–9.3) | 0.434 |
| ICU admission | 38 (25.3) | 28 (57.1) | 10 (9.9) | < 0.001 |
| Length of stay in ICU, median (IQR), days | 7 (4–16) | 9 (4–19.8) | 4 (2–11) | 0.192 |
| In-hospital death | 3 (2) | 3 (6.1) | 0 (0) | 0.059 |
Data were presented as median (IQR) or mean (SD). n (%) referred to the total number of patients with available data
ICU Intensive care unit, IQR Interquartile range, SD Standard deviation, BMI Body mass index, APACHE II Acute physiology and chronic health evaluation II, SOFA Sequential organ failure assessment, ARDS Acute respiratory distress syndrome
P values indicated differences between sepsis and non-sepsis patients, in which P < 0.05 was deemed as statistical significance
In conclusion, patients with SARS-CoV-2 infection are likely to develop sepsis at hospital admission, which are characterized by failed homeostasis between the innate and adaptive immune responses partly due to the loss of lymphocytes. The development of sepsis might be associated with greater organ dysfunction and worse outcomes in this small cohort of patients from Shenzhen.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Acknowledgements
We thank all patients included in this study, and gratefully acknowledge all the front-line physicians in fighting against SARS-CoV-2 infection. We greatly appreciate the works from Prof. Jin-xiu Li from the Department of Critical Care Medicine, the Third People’s Hospital of Shenzhen, Prof. Ying Li from the Department of Critical Care Medicine, The Second People’s Hospital of Shenzhen, Prof. Xue-yan Liu from the Department of Critical Care Medicine, The People’s Hospital of Shenzhen, Prof. Lei Huang from the Department of Critical Care Medicine, Peking University Shenzhen Hospital, Prof. Yong Liu from the Department of Critical Care Medicine, Shenzhen Hospital of Southern Medical University, Prof. Mian Peng from the Department of Critical Care Medicine, The Third Affiliated Hospital of Shenzhen University, and Dr. Yao Yao from the Center for Healthy Aging and Development Studies, National School of Development, Peking University in recruiting patients and providing technical supports.
Author’s contributions
YWF and YMY contributed equally to this paper and were joint corresponding authors. DR, CR, RQY were joint first authors. All corresponding and first authors contributed to study concept and design. DR extracted epidemiological and clinical data. CR and RQY performed the statistical analyses. DR, CR and RQY co-drafted the initial version of manuscript. All authors provided critical revision of the manuscript and approved the final draft for publication. YWF was responsible for the integrity and accuracy of the data and was the guarantor. The corresponding authors attest that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.
Funding
This work was supported by the National Natural Science Foundation of China (81730057 by YMY, 81801935 by CR), Sanming Project of Medicine in Shenzhen (SZSM20162011 by YMY and YWF), and the Military Medical Innovation Program of Chinese PLA (18CXZ026 by YMY).
Compliance with ethical standards
Conflicts of interest
The authors declare that they have no conflict of interest.
Ethical approval
This study was approved by the Committee on the Ethics of Medicine, the Second People’s Hospital of Shenzhen (20200224002), China.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Di Ren, Chao Ren and Ren-qi Yao have contributed equally to this manuscript.
Contributor Information
Yong-wen Feng, Email: fengyongwen2008@126.com.
Yong-ming Yao, Email: c_ff@sina.com.
References
- 1.World Health Organization (2020) Coronavirus disease (COVID-2019) situation reports: situation report-97. https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200426-sitrep-97-covid-19.pdf?sfvrsn = d1c3e800_6. Accessed 26 April 2020
- 2.Cucinotta D, Vanelli M. WHO declares COVID-19 a pandemic. Acta Biomed. 2020;91(1):157–160. doi: 10.23750/abm.v91i1.9397. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, Wang B, Xiang H, Cheng Z, Xiong Y, Zhao Y, Li Y, Wang X, Peng Z. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA. 2020;1:2–8. doi: 10.1001/jama.2020.1585. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Shenzhen Municipal Health Commission (2020) Updates on COVID-19 cases in Shenzhen (April 26). http://wjw.sz.gov.cn/yqxx/202004/t20200426_19190314.htm. Assessed 26 April 2020
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.