Literature DB >> 32470606

Clinical characteristics of critically ill patients co-infected with SARS-CoV-2 and the influenza virus in Wuhan, China.

Simin Ma1, Xiaoquan Lai1, Zhe Chen2, Shenghao Tu2, Kai Qin3.   

Abstract

OBJECTIVE: To delineate the clinical characteristics of critically ill COVID-19 patients co-infected with influenza.
METHODS: This study included adult patients with laboratory-confirmed COVID-19 form Tongji Hospital (Wuhan, China), with or without influenza, and compared their clinical characteristics.
RESULTS: Among 93 patients, 44 died and 49 were discharged. Forty-four (47.3%) were infected with influenza virus A and two (2.2%) with influenza virus B. Twenty-two (50.0%) of the non-survivors and 24 (49.0%) of the survivors were infected with the influenza virus. Critically ill COVID-19 patients with influenza were more prone to cardiac injury than those without influenza. For the laboratory indicators at admission the following were higher in non-survivors with influenza than in those without influenza: white blood cell counts, neutrophil counts, levels of tumor necrosis factor-α, D-dimer value, and proportion of elevated creatinine.
CONCLUSION: The results showed that a high proportion of COVID-19 patients were co-infected with influenza in Tongji Hospital, with no significant difference in the proportion of co-infection between survivors and non-survivors. The critically ill COVID-19 patients with influenza exhibited more severe inflammation and organ injury, indicating that co-infection with the influenza virus may induce an earlier and more frequently occurring cytokine storm.
Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  COVID-19; Co-infection; Cytokine storm; Influenza; Organ injury

Mesh:

Substances:

Year:  2020        PMID: 32470606      PMCID: PMC7250072          DOI: 10.1016/j.ijid.2020.05.068

Source DB:  PubMed          Journal:  Int J Infect Dis        ISSN: 1201-9712            Impact factor:   3.623


Introduction

The World Health Organization (WHO) named the coronavirus disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as 2019 novel coronavirus disease (COVID-19) and declared it as a pandemic. Similar to the influenza virus, SARS-CoV-2 is commonly transmitted through respiratory droplets and contact. The world’s population is generally susceptible to SARS-CoV-2 infection. Most COVID-19 patients show mild influenza-like symptoms, such as fever, cough and fatigue. However, approximately 5% of patients rapidly progress to acute respiratory distress syndrome (ARDS), septic shock and multiple organ failure, and are admitted to intensive care units. The COVID-19-associated mortality rate in China is approximately 2.3% (Guan et al., 2020, Novel Coronavirus Pneumonia Emergency Response Epidemiology Team, 2020). To date, no studies have reported on critically ill COVID-19 patients who also present with influenza. Human cases of influenza in Wuhan most often occur in winter (He and Tao, 2018, Wang et al., 2018), which overlapped with the peak of COVID-19 in Wuhan. This study speculated whether co-infection with SARS-CoV-2 and the influenza virus exist. And if so, the influence of this co-infection on clinical features needs to be investigated. The Southern hemisphere is yet to enter its flu season for the year and in many of these countries the incidence of COVID-19 is still increasing. Meanwhile, many Western hemisphere countries are still experiencing COVID-19 outbreaks. A great many countries around the world will be looking to start planning for flu season 2020/21, with many public health experts warning of the need to avoid second peaks of COVID-19 during flu season. Therefore, it is crucial to answer the above questions so as to formulate treatment strategies to manage co-infection with SARS-CoV-2 and the influenza virus. The present study extracted the clinical data for 95 patients with laboratory-confirmed COVID-19 from Tongji Hospital (Wuhan) and discussed the clinical characteristics of critically ill COVID-19 patients co-infected with influenza. The results may provide new insights into the treatment and control of co-infection with SARS-CoV-2 and the influenza virus.

Materials and Methods

Study design and participants

The study was conducted among 95 adult patients with laboratory-confirmed COVID-19 (including 50 discharged cases and 45 non-survivors) who were discharged or died in Tongji Hospital (Wuhan, China) from 28 January 2020 to 29 February 2020. The discharge criteria were based on the fifth version of diagnosis and treatment guidance for COVID-19 published by the National Health Commission of People’s Republic of China (2020). Patients met the discharge criteria if they had normal body temperature for 3 consecutive days, greatly improved respiratory symptoms and pulmonary imaging manifestations, and were negative for the presence of SARS-CoV-2 nucleic acid twice in succession. Owing to limited medical resources, the nucleic acid test for the presence of influenza virus in respiratory specimens was not widely carried out. Influenza virus diagnosis in this study was based on serology. None of the 95 patients had a history of influenza vaccination in the recent flu season. This study was approved by the Ethics Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology. The need for written informed consent was waived by the Ethics Committee of the hospital for the rapid emergence of this infectious disease.

Data collection

Data were extracted from electronic medical records, and included: age; gender; history of recent exposure; history of chronic diseases (hypertension, diabetes, coronary disease, chronic lung disease, chronic kidney disease, malignant tumors, etc.); symptoms from illness onset to admission (fever, cough, dyspnea, fatigue, myalgia, diarrhea, chest pain, headache, etc.); laboratory assessments (including complete blood count, C-reactive protein [CRP], arterial blood gas, coagulation function, D-dimer, alanine aminotransferase [ALT], aspartate aminotransferase [AST], lactate dehydrogenase [LDH], creatinine, amino-terminal pro-brain natriuretic peptide precursor [NT-proBNP], cardiac troponin I [cTnI], tumor necrosis factor-α [TNF-α], and interleukin-6 [IL-6] and respiratory virus-specific IgM antibodies); detailed medication; and tests for SARS-CoV-2 from respiratory tract specimens (including nasopharyngeal swabs, bronchoalveolar lavage fluid, sputum, or bronchial aspiration fluid). Specimen collection and lung CT scanning were completed for all patients within 24 hours of admission.

Real-time reverse-transcription polymerase chain reaction assay

A confirmed COVID-19 case was defined as a positive result in a real-time reverse-transcription polymerase chain reaction (RT-PCR) assay of nasal and pharyngeal swab specimens according to WHO guidelines. On receipt of the samples, viral RNA extraction was performed using a Magnetic Viral RNA/DNA Extraction Kit (Tianlong, Xi'an, China) following the manufacturer's instructions. This was followed by PCR screening for the specific detection of SARS-CoV-2 using a commercial kit (Tianlong). A cycle threshold value (Ct-value) ≤37 was defined as a positive test based on the recommendation of the National Institute for Viral Disease Control and Prevention (China).

Indirect immunofluorescence assay (IIFA) of IgM antibodies

A respiratory tract profile (IgM) kit (EUROIMMUN, Luebeck, Germany) was employed according to the manufacturer's instructions. Based on the Titerplane™ technique using infected cells/cultured bacteria, this kit is designed for the in vitro detection of human IgM antibodies against influenza virus A, influenza virus B and six atypical respiratory pathogens: adenovirus, respiratory syncytial virus, parainfluenza virus, Chlamydia pneumoniae, Legionella pneumophila, and Mycoplasma pneumonia in serum/plasma samples. Fluorescence results were analyzed by experienced technicians.

Statistical analysis

Statistical analysis was performed using SPSS 20.0. Continuous variables were expressed as means ± standard deviation (SD) using the Student's t-test or as medians and interquartile range (IQR) using the Mann-Whitney U test. Categorical variables were expressed as numbers (%) and compared by the χ2 test or Fisher’s exact test. P < 0.05 was considered significant.

Results

Demographic and clinical characteristics

Of the 95 COVID-19 patients, 44 were infected with influenza virus A, two with influenza virus B, one with adenovirus, and one with parainfluenza; 47 were uninfected. A total of 93 patients were finally included, 46 (49.5%) of whom were infected with influenza virus A or B (classified as the flu group), while 47 (50.5%) were uninfected (classified as the non-flu group). Of these 93 patients, 44 were non-survivors and 49 were discharged. Twenty-two (50.0%) non-survivors and 24 (49.0%) survivors were infected with the influenza virus. There was no significant difference in the proportion of patients co-infected with SARS-CoV-2 and the influenza virus between survivors and non-survivors. The median age of the 93 patients was 67.0 years (IQR 54.0–72.0) and females accounted for 45.2% of the total number of patients (Table 1 ). The median time from illness onset to admission was 12.0 days (IQR 7.0–16.0) (Table 1). Chronic diseases were found in 53.8% of the patients, with hypertension being the most common, followed by diabetes and coronary disease (Table 1). The most common symptoms on admission were fever, cough and dyspnea, followed by chest distress/chest pain and fatigue (Table 1). The most common complication was ARDS, followed by acute cardiac injury, acute kidney injury and liver dysfunction. Among the non-survivors, the incidence of acute cardiac injury was significantly higher in the flu group (86.4%) than in the non-flu group (54.5%) (p < 0.05) (Table 2 ).
Table 1

Clinical characteristics of the 93 COVID-19 patients.

Clinical characteristicsAll patients (n = 93)Flu (n = 46)Non-flu (n = 47)P-value
Female42 (45.2)24 (52.2)18 (38.3)0.18
Age (years)67.0 (54.0, 72.0)65.0 (57.5, 69.8)69.0 (54.0, 74.0)0.34
Onset to admission (days)12.0 (7.0, 16.0)12.0 (7.0, 17.8)10.0 (7.0, 15.0)0.23



Chronic diseases
Hypertension34 (36.6)20 (43.5)14 (29.8)0.17
Diabetes18 (19.4)12 (26.1)6 (12.8)0.10
Coronary disease12 (12.9)7 (15.2)5 (10.6)0.51
Chronic pulmonary disease8 (8.6)5 (10.9)3 (6.4)0.44
Chronic kidney disease2 (2.2)0 (0.0)2 (4.3)0.16
Malignant tumor2 (2.2)0 (0.0)2 (4.3)0.16



Symptoms
Fever76 (81.7)34 (73.9)42 (89.4)0.05
Cough75 (80.6)35 (76.1)40 (85.1)0.27
Dyspnea60 (64.5)28 (60.9)32 (68.1)0.47
Fatigue40 (43.0)14 (30.4)26 (55.3)0.02
Myalgia20 (21.5)9 (19.6)11 (23.4)0.65
Diarrhea29 (31.2)16 (34.8)13 (27.7)0.46
Chest distress/chest pain43 (46.2)21 (45.7)22 (46.8)0.91
Headache14 (15.1)6 (13.0)8 (17.0)0.59



Complications
ARDS39 (41.9)19 (41.3)20 (42.6)0.90
Acute kidney injury28 (30.1)17 (37.0)11 (23.4)0.15
Acute cardiac injury31 (33.3)19 (41.3)12 (25.5)0.11
Liver dysfunction17 (18.3)8 (17.4)9 (19.1)0.83

Data are expressed as the median (IQR) or n (%), p-values are from the Mann-Whitney U test, χ² test or Fisher’s exact test.

COVID-19, coronavirus disease 2019; ARDS, acute respiratory distress syndrome.

Table 2

Clinical characteristics of the non-surviving COVID-19 patients.

Clinical characteristicsNon-survivors (n = 44)Flu (n = 22)Non-flu (n = 22)P-value
Female16 (36.4)11 (50.0)5 (22.7)0.06
Age (years)70.0 (64.0, 75.5)68.5 (64, 71.5)72.0 (70.0, 77.8)0.13
Onset to admission (days)10.0 (6.0, 12.5)9.5 (6.3, 12)10.0 (6.3, 13.5)0.91
Onset to death (days)20.5 (14.8, 28.3)17.5 (12.3, 27.8)22.0 (18.3, 28.5)0.16



Chronic disease
Hypertension17 (38.6)10 (45.5)7 (31.8)0.35
Diabetes13 (29.5)9 (40.9)4 (18.2)0.10
Coronary disease7 (15.9)3 (13.6)4 (18.2)0.68
Chronic pulmonary disease5 (11.4)4 (18.2)1 (4.5)0.15
Chronic kidney disease1 (2.3)0 (0.0)1 (4.5)0.31
Malignant tumor1 (2.3)0 (0.0)1 (4.5)0.31



Symptoms
Fever38 (86.4)16 (72.7)22 (100.0)0.008
Cough32 (72.7)14 (63.6)18 (81.8)0.18
Dyspnea29 (65.9)15 (68.2)14 (63.6)0.75
Fatigue17 (38.6)6 (27.3)11 (50.0)0.12
Myalgia5 (11.4)1 (4.5)4 (18.2)0.15
Diarrhea13 (29.5)6 (27.3)7 (31.8)0.74
Chest distress/chest pain20 (45.5)11 (50.0)9 (40.9)0.55
Headache6 (13.6)3 (13.6)3 (13.6)1.00



Complication
ARDS38 (86.4)18 (81.8)20 (90.9)0.38
Acute kidney injury25 (56.8)15 (68.2)10 (45.5)0.13
Acute cardiac injury31 (70.5)19 (86.4)12 (54.5)0.04
Liver dysfunction10 (22.7)5 (22.7)5 (22.7)1.00

Data are expressed as the median (IQR) or n (%), p-values are from the Mann-Whitney U test, χ² test or Fisher’s exact test.

COVID-19, coronavirus disease 2019; ARDS, acute respiratory distress syndrome.

Clinical characteristics of the 93 COVID-19 patients. Data are expressed as the median (IQR) or n (%), p-values are from the Mann-Whitney U test, χ² test or Fisher’s exact test. COVID-19, coronavirus disease 2019; ARDS, acute respiratory distress syndrome. Clinical characteristics of the non-surviving COVID-19 patients. Data are expressed as the median (IQR) or n (%), p-values are from the Mann-Whitney U test, χ² test or Fisher’s exact test. COVID-19, coronavirus disease 2019; ARDS, acute respiratory distress syndrome.

Analysis of laboratory indicators

Among the 93 patients, there was a significant difference in the proportion of patients with D-dimer levels >5 μg/mL (ten times the normal D-dimer value) between the flu group (38.6%) and the non-flu group (11.4%) (p < 0.01), but no difference in white blood cell counts, neutrophil counts, lymphocyte counts, or levels of CRP, ALT, AST, LDH, creatinine, cTnI, NT-proBNP, TNF-α, and IL-6 (p > 0.05) (data not shown). Among the non-survivors, the white blood cell count, neutrophil count, TNF-α, D-dimer value, proportion of patients with D-dimer levels >5 μg/mL, and proportion of patients with elevated creatinine levels were higher in the flu group than in the non-flu group (p < 0.05) (Table 3 ). Among the survivors, there were no significant differences in the laboratory indicators between the flu group and the non-flu group (p > 0.05) (data not shown).
Table 3

Laboratory characteristics of the non-surviving COVID-19 patients.

Laboratory characteristicsNon-survivors (n = 44)Flu (n = 22)Non-flu (n = 22)P-value
White blood cell count (×109/L)9.5 (6.1, 13.6)12.9 (8.9, 15.4)7.4 (5.1, 11.0)0.01
Neutrophil count (×109/L)8.7 (5.1, 12.6)11.5 (7.5, 13.6)6.5 (4.0, 10.0)0.01
Neutrophil >6.3 × 109/L30/44 (68.2)18/22 (81.8)12/22 (54.5)0.05
Lymphocyte count (×109/L)0.5 (0.4, 0.8)0.6 (0.4, 0.8)0.5 (0.4, 0.7)0.64
Lymphopenia <1 × 109/L41/44 (93.2)20/22 (90.9)21/22 (95.5)0.55
C-reactive protein (mg/L)78.2 (47.4, 153.1)86.4 (48.4, 146.5)78.2 (48.9, 158.4)0.95
C-reactive protein >10 mg/L41/44 (93.2)20/22 (90.9)21/22 (95.5)0.55
ALT (U/L)28.5 (18.8, 40.5)27.5 (19.5, 33.8)35.0 (19.0, 42.3)0.31
AST (U/L)45.0 (29.0, 59.5)40.0 (24.3, 52.0)48.0 (36.8, 63.5)0.12
ALT>45 U/L or AST>35 U/L28/44 (63.6)13/22 (59.1)15/22 (68.2)0.53
Creatinine (μmol/L)91.0 (72.8, 118.5)87.5 (67.3, 135.8)92.5 (79.5, 102.8)0.61
Creatinine >1 × 106 μmol/L13/44 (29.5)10/22 (45.5)3/21 (14.3)0.03
Cardiac troponin I (pg/mL)22.5 (10.3, 111.3)27.8 (17.8, 599)15.6 (10.3, 59.5)0.28
Cardiac troponin I > 130 pg/mL10/41 (24.4)7/20 (35.0)3/21 (14.3)0.12
NT-proBNP (pg/mL)756 (246, 2566)1319 (309, 2691.5)663 (225, 2524)0.42
NT-proBNP >300 pg/mL31/41 (75.6)16/20 (80.0)15/21 (71.4)0.52
D-dimer (μg/mL)5.1 (1.7, 21.0)16.5 (5.0, 21.0)2.3 (1.1, 7.6)0.01
D-dimer >5 μg/mL20/44 (45.5)14/22 (63.6)6/22 (27.3)0.02
Tumor necrosis factor –α (pg/mL)11.4 (8.1, 16.0)15.9 (10.3, 20.7)8.35 (7.5, 13.0)0.03
Interleukin-6 (pg/mL)57.9 (36.0, 152.9)57.9 (47.5, 345.2)57.3 (19.2, 124.1)0.27

Data are expressed as the median (IQR) or n/N (%), p-values are from the Mann–Whitney U test, χ² test or Fisher’s exact test.

COVID-19, coronavirus disease 2019; ALT, alanine aminotransferase; AST, aspartate aminotransferase; NT-proBNP, amino-terminal pro-brain natriuretic peptide precursor.

Laboratory characteristics of the non-surviving COVID-19 patients. Data are expressed as the median (IQR) or n/N (%), p-values are from the Mann–Whitney U test, χ² test or Fisher’s exact test. COVID-19, coronavirus disease 2019; ALT, alanine aminotransferase; AST, aspartate aminotransferase; NT-proBNP, amino-terminal pro-brain natriuretic peptide precursor.

Discussion

The COVID-19 pandemic has reached most countries throughout the world, making the global situation serious. Due to the insufficient diagnostic sensitivity of the tests used to detect SARS-CoV-2 in upper respiratory tract specimens and the similarity between COVID-19 and influenza, early diagnosis of SARS-CoV-2 and influenza virus co-infection may be more problematic (Wu et al., 2020b). Among the COVID-19 patients included in this study, approximately 50% were co-infected with influenza virus, and most were co-infected with influenza virus A. Moreover, the similarity between the early clinical symptoms of the two diseases likely increased the false-negative rate of COVID-19 detection, thereby exacerbating the spread of SARS-CoV-2. The COVID-19 outbreak resulted in a large number of people gathering in hospitals, which intensified the spread of the influenza virus and increased the likelihood of co-infection with SARS-CoV-2. Recent studies have reported that females accounted for approximately 33% of the critically ill/non-surviving COVID-19 patients in Wuhan (Guan et al., 2020, Yang et al., 2020). In the current study, females comprised 36.4% of the non-surviving COVID-19 patients, including 50% of those with influenza and 22.7% of those without influenza (p = 0.06). Due to insignificant statistical difference, whether the co-infection may reduce sex difference in the non-surviving COVID-19 patients requires a larger sample of research. COVID-19 patients co-infected with the influenza virus did not demonstrate different clinical symptoms, which further compounded the diagnostic difficulties. Most patients with severe COVID-19 exhibit substantially elevated serum levels of pro-inflammatory cytokines, characterized as cytokine storm (Cao, 2020, Mehta et al., 2020). Elevated cytokines also mediate extensive pulmonary pathology, leading to massive infiltration of neutrophils and macrophages (Cao 2020). Neutrophil counts are increased in both the peripheral blood (Wang et al. 2004) and lung (Nicholls et al. 2003) among critically ill patients with severe acute respiratory syndrome. Extensive pulmonary infiltration of neutrophils in patients with influenza induces lung tissue injury and worsens the disease (Kulkarni et al. 2019). In the current study, neutrophil and cytokine levels were generally elevated among the non-survivors, and the increment was more apparent among the non-survivors with influenza. Co-infection with the influenza virus may further enhance neutrophil activation, thereby contributing to an excessive immune response against the virus and also to the development of a cytokine storm. Studies have reported that elevated D-dimer levels are a risk factor for death in COVID-19 patients (Wu et al., 2020a, Zhou et al., 2020). The current study also found that the D-dimer levels of non-survivors were substantially higher than those of survivors. Among the non-survivors, the D-dimer value was higher among patients with influenza than in those without influenza, which may have been due to local vascular injury, ischemia and thrombosis caused by a viral infection-associated cytokine storm (Davidson and Warren-Gash 2019). The current results further confirmed that co-infection with the influenza virus may induce an earlier and more severe cytokine storm in critically ill COVID-19 patients, leading to serious complications such as shock, ARDS, fulminant myocarditis, acute kidney injury or multiple organ failure (Cao, 2020, Ruan et al., 2020, Wu et al., 2020a, Zhou et al., 2020). The current research had some limitations. First, the results of serological tests may have been false-negative, especially within 1 week of infection or reinfection; or they may have been false-positive due to long-term infections or carrier states. Second, the study was unable to determine the strains of influenza, and the infecting strain might have affected the clinical characteristics. Third, the included cases originated from Wuhan, but differences in races and influenza strains among different countries may cause COVID-19 patients with influenza to present different clinical characteristics. In addition, the number of included cases was small, and other factors such as gender, age, chronic disease, and time from illness onset to admission may have affected the results of this study. Under the background of the COVID-19 global pandemic, the number of patients co-infected with SARS-CoV-2 and the influenza virus in some countries may increase as the flu season approaches. The clinical research of this co-infection, especially in critically ill patients, will benefit global control efforts for 2020–2021. Research on different regions, races, age brackets, and influenza strains can more accurately reveal the epidemiological and clinical characteristics of co-infected patients, which requires larger sample sizes from multiple countries. Furthermore, research from larger sample could contribute to unveiling whether this co-infection is a higher risk for severe disease or death associated with COVID-19. It is believed that this is the first study of co-infection with SARS-CoV-2 and the influenza virus among critically ill COVID-19 patients. The results showed that a high proportion of COVID-19 patients were co-infected with influenza in Tongji Hospital. Co-infection with SARS-CoV-2 and the influenza virus may lead to a much earlier occurrence of cytokine storm and organ damage in critically ill COVID-19 patients. The results suggest that detection of the influenza virus should be considered in patients with COVID-19, and that treatment strategies for anti-influenza virus and dampening inflammatory responses may be helpful for critically ill patients co-infected with SARS-CoV-2 and the influenza virus.

Author contributions

KQ and SMM contributed to the conception and design of the study, had full access to all data in the study and take responsibility for the integrity and accuracy of data analysis. SMM and XQL contributed to data acquisition. ZC, SHT and KQ contributed to the analysis and interpretation of the data. All authors participated in manuscript writing and revision and approved the final version of the manuscript.

Funding

This research was funded by the 2020 Second Batch of COVID-19 Emergency Science and Technology Projects (2020kfyXGY072) and the 2019 Tongji Hospital Research Fund Project (2201300852).

Conflicts of interest

The authors declare no conflict of interest.
  14 in total

1.  [The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) in China].

Authors: 
Journal:  Zhonghua Liu Xing Bing Xue Za Zhi       Date:  2020-02-10

2.  Risk Factors Associated With Acute Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease 2019 Pneumonia in Wuhan, China.

Authors:  Chaomin Wu; Xiaoyan Chen; Yanping Cai; Jia'an Xia; Xing Zhou; Sha Xu; Hanping Huang; Li Zhang; Xia Zhou; Chunling Du; Yuye Zhang; Juan Song; Sijiao Wang; Yencheng Chao; Zeyong Yang; Jie Xu; Xin Zhou; Dechang Chen; Weining Xiong; Lei Xu; Feng Zhou; Jinjun Jiang; Chunxue Bai; Junhua Zheng; Yuanlin Song
Journal:  JAMA Intern Med       Date:  2020-07-01       Impact factor: 21.873

3.  Cardiovascular complications of acute respiratory infections: current research and future directions.

Authors:  Jennifer A Davidson; Charlotte Warren-Gash
Journal:  Expert Rev Anti Infect Ther       Date:  2019-11-08       Impact factor: 5.091

4.  Excessive neutrophil levels in the lung underlie the age-associated increase in influenza mortality.

Authors:  Upasana Kulkarni; Rachel L Zemans; Candice A Smith; Sherri C Wood; Jane C Deng; Daniel R Goldstein
Journal:  Mucosal Immunol       Date:  2019-01-07       Impact factor: 7.313

5.  Co-infection with SARS-CoV-2 and Influenza A Virus in Patient with Pneumonia, China.

Authors:  Xiaojing Wu; Ying Cai; Xu Huang; Xin Yu; Li Zhao; Fan Wang; Quanguo Li; Sichao Gu; Teng Xu; Yongjun Li; Binghuai Lu; Qingyuan Zhan
Journal:  Emerg Infect Dis       Date:  2020-06-17       Impact factor: 6.883

6.  Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China.

Authors:  Qiurong Ruan; Kun Yang; Wenxia Wang; Lingyu Jiang; Jianxin Song
Journal:  Intensive Care Med       Date:  2020-03-03       Impact factor: 17.440

7.  Clinical Characteristics of Coronavirus Disease 2019 in China.

Authors:  Wei-Jie Guan; Zheng-Yi Ni; Yu Hu; Wen-Hua Liang; Chun-Quan Ou; Jian-Xing He; Lei Liu; Hong Shan; Chun-Liang Lei; David S C Hui; Bin Du; Lan-Juan Li; Guang Zeng; Kwok-Yung Yuen; Ru-Chong Chen; Chun-Li Tang; Tao Wang; Ping-Yan Chen; Jie Xiang; Shi-Yue Li; Jin-Lin Wang; Zi-Jing Liang; Yi-Xiang Peng; Li Wei; Yong Liu; Ya-Hua Hu; Peng Peng; Jian-Ming Wang; Ji-Yang Liu; Zhong Chen; Gang Li; Zhi-Jian Zheng; Shao-Qin Qiu; Jie Luo; Chang-Jiang Ye; Shao-Yong Zhu; Nan-Shan Zhong
Journal:  N Engl J Med       Date:  2020-02-28       Impact factor: 91.245

8.  COVID-19: immunopathology and its implications for therapy.

Authors:  Xuetao Cao
Journal:  Nat Rev Immunol       Date:  2020-05       Impact factor: 53.106

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

Authors:  Fei Zhou; Ting Yu; Ronghui Du; Guohui Fan; Ying Liu; Zhibo Liu; Jie Xiang; Yeming Wang; Bin Song; Xiaoying Gu; Lulu Guan; Yuan Wei; Hui Li; Xudong Wu; Jiuyang Xu; Shengjin Tu; Yi Zhang; Hua Chen; Bin Cao
Journal:  Lancet       Date:  2020-03-11       Impact factor: 79.321

10.  A cluster of patients with severe acute respiratory syndrome in a chest ward in southern Taiwan.

Authors:  Yi-Hsi Wang; An-Shen Lin; Tung-Ying Chao; Sheng-Nan Lu; Jien-Wei Liu; Shun-Sheng Chen; Meng-Chih Lin
Journal:  Intensive Care Med       Date:  2004-04-23       Impact factor: 17.440

View more
  37 in total

1.  [Clinical characteristics of influenza pneumonia in the elderly and relationship between D-dimer and disease severity].

Authors:  J Li; Y Xu; Y Y Wang; Z C Gao
Journal:  Beijing Da Xue Xue Bao Yi Xue Ban       Date:  2022-02-18

2.  Coinfection of SARS-CoV-2 and Other Respiratory Pathogens.

Authors:  Ling Ma; Wenjing Wang; Jehane Michael Le Grange; Xiaorong Wang; Shuaixian Du; Chen Li; Jia Wei; Jin-Nong Zhang
Journal:  Infect Drug Resist       Date:  2020-08-26       Impact factor: 4.003

Review 3.  Post-COVID lung fibrosis: The tsunami that will follow the earthquake.

Authors:  Zarir F Udwadia; Parvaiz A Koul; Luca Richeldi
Journal:  Lung India       Date:  2021-03

4.  Prevalence and outcomes of co-infection and superinfection with SARS-CoV-2 and other pathogens: A systematic review and meta-analysis.

Authors:  Jackson S Musuuza; Lauren Watson; Vishala Parmasad; Nathan Putman-Buehler; Leslie Christensen; Nasia Safdar
Journal:  PLoS One       Date:  2021-05-06       Impact factor: 3.240

5.  Macrophages and Dendritic Cells Are Not the Major Source of Pro-Inflammatory Cytokines Upon SARS-CoV-2 Infection.

Authors:  Marc A Niles; Patricia Gogesch; Stefanie Kronhart; Samira Ortega Iannazzo; Georg Kochs; Zoe Waibler; Martina Anzaghe
Journal:  Front Immunol       Date:  2021-05-26       Impact factor: 7.561

Review 6.  Viral coinfections in COVID-19.

Authors:  Parisa S Aghbash; Narges Eslami; Milad Shirvaliloo; Hossein B Baghi
Journal:  J Med Virol       Date:  2021-06-12       Impact factor: 20.693

7.  Protecting Vulnerable Patients from Influenza During the COVID-19 Pandemic: An Urgent Call to Action for Health Care Professionals.

Authors:  William Schaffner; Robert A Gabbay; Allen J Taylor
Journal:  Infect Dis Clin Pract (Baltim Md)       Date:  2021-07-08

8.  COVID-19 and Mycoplasma pneumoniae: SARS-CoV-2 false positive or coinfection?

Authors:  Juan Monte Serrano; Miguel Fernando García-Gil; Joana Cruañes Monferrer; Beatriz Aldea Manrique; Lucía Prieto-Torres; Mar García García; Cristina Matovelle Ochoa; Mariano Ara-Martín
Journal:  Int J Dermatol       Date:  2020-08-07       Impact factor: 2.736

9.  Can Coinfection With Influenza Worsen COVID-19 Outcomes?

Authors:  Kulachanya Suwanwongse; Nehad Shabarek
Journal:  J Investig Med High Impact Case Rep       Date:  2020 Jan-Dec

10.  Expanding global and national influenza vaccine systems to match the COVID-19 pandemic response.

Authors:  Bruce A Ruscio; Peter Hotez
Journal:  Vaccine       Date:  2020-10-21       Impact factor: 3.641

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.