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https://orcid.org/0000-0002-4748-4749
ABSTRACT
ABSTRACT
Objectives
To recognise clinical features of COVID-19 pneumonia and its differences from influenza pneumonia.
Methods
246 patients were enrolled into COVID-19 cohort and 120 patients into influenza cohort. All data were collected and analysed retrospectively. The variables under focus included demographic, epidemiological, clinical, laboratory and imaging characteristics of COVID-19 pneumonia and comparison were made with influenza pneumonia.
Results
The COVID-19 cohort included 53.25% female and 46.75% male. Their main symptom was fever; while 28.05% of patients had only initially fever; 21.54% of them remained feverless. After excluding prior kidney diseases, some patients showed abnormal urinalysis (32.11%), elevated blood creatinine (15.04%) and blood urea nitrogen (19.11%). Typical CT features included ground glass opacity, consolidation and band opacity, which could present as characteristic ‘bat wing sign’. Our data showed that male, aged 65 or above, smoking, with comorbidities including diabetes, cardiovascular and kidney diseases, would experience more severe COVID-19 pneumonia. In comparison, COVID-19 cohort showed significantly higher incidence of clustering; the influenza cohort showed higher rate of fever. Both cohorts showed reduced lymphocyte numbers; however, 6 influenza patients showed lymphocytes increased, which was statistical significant compared with COVID-19 cohort. Also, influenza cohort displayed higher white blood cell counts and PCT values.
Conclusion
There is no significant gender difference in the incidence of COVID-19 pneumonia. It predominantly affects the lung as well as the kidney. Age, smoking and comorbidities could contribute to disease severity. Although COVID-19 is more infectious, the rate of secondary bacterial infection is lower than influenza.
Introduction
The present COVID-19 pandemic has huge impacts on health and socio-economics worldwide. As of 25 March 2020, there are 81,048 officially confirmed COVID-19 cases in China; 3204 deaths that equates to mortality rate of 3.95%. A total of 72,469 cases have been reported outside China, with 2531 deaths and a mortality rate of 3.49% [1]. The COVID-19 is a novel disease, which is under intensive investigation, in hope of contributing to the development of diagnosis and treatments.
Published online:
29 July 2020![]({"type":"image","src":"/na101/home/literatum/publisher/tandf/journals/content/yacb20/2020/yacb20.v075.i05/17843286.2020.1798668/20210517/images/medium/yacb_a_1798668_f0001_oc.jpg"})
Figure 1. Morphological features of COVID-19 pneumonia on pulmonary CT images.
Published online:
29 July 2020![]({"type":"image","src":"/na101/home/literatum/publisher/tandf/journals/content/yacb20/2020/yacb20.v075.i05/17843286.2020.1798668/20210517/images/medium/yacb_a_1798668_f0002_oc.jpg"})
Figure 2. The evolution of CT images of COVID-19 as the disease progresses.
The disease is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which was previously named as novel coronavirus (2019-nCoV). It is a new strain of zoonotic virus within the Coronaviridae family [2]. Previous report showed the SARS-CoV-2 virus targets the epithelial cells that line the respiratory and digestive tracts. The virus infects these cells through binding onto angiotensin-converting enzyme 2 (ACE2) receptors that are expressed on these cell surfaces [3]. The virus is highly infectious and transmits through close contact with symptomatically or asymptomatically infected individuals or aerosols [4]. From the literature reports, the virus is noted to be highly contagious and fast spreading. The incubation period ranges from 0 to 14 days, with an average of 4–6 days before symptoms onset. In China, the basic reproductive number (R0) was estimated to be 2.2 [5].
Severe cases of COVID-19 pneumonia can lead to multiple organ failure and even death. Recent literatures have postulated that COVID-19 pneumonia is likely to turn into a chronic disease similar as a flu [6], until effective vaccines or therapeutic treatments are available. In the light of possible long-term coexistence with humans globally, current priority includes developing methods in identifying and evaluating infected individuals.
The recognition of clinical characteristics shown by COVID-19 pneumonia patients could contribute much to the early detection of infected individuals. Although there are articles that summarise the clinical or CT characteristics of COVID-19 pneumonia [2,5,7–10], the available data remained insufficient and generalised. In our case analysis, we explore the clinical features of COVID-19 such as fever and its laboratory test results in more detail. In addition, we attempt to summarise some of the differentials between COVID-19 pneumonia and influenza pneumonia as these two diseases have similarities [11].
Methods
Patients
Two groups of hospitalised patients were recruited for this study: COVID-19 group and influenza group. The severity of the disease was classified according to the ‘American Thoracic Society guidelines for community-acquired pneumonia’ [12] as either non-severe or severe.
For COVID-19 group, a total of 246 patients (226 non-severe and 20 severe) were enrolled from 4 government-designated hospitals for treating COVID-19 pneumonia: The Fourth People Hospital of Wuhan, Huanggang Dabie Mountain Regional Medical Centre in Hubei, Linyi People Hospital of Shandong Province and Lanshan People Hospital of Linyi City in Shandong Province. Each patient was confirmed SARS-CoV-2 positive via RT-PCR between 24 January 2020 and 14 March 2020. The primers for the test are listed in Table 1.
Table 1. Primers for virus.
For the influenza group, a total of 120 patients (110 non-severe and 10 severe) were enrolled from Qilu Hospital of Shandong University during January 2017 to March 2020. They were all tested positive for influenza A and/or B influenza viruses via RT-PCT, and the primers are listed in Table 1. The severity of the disease was matched between the influenza and COVID-19 cohorts. Among the influenza cohort, there are 29 cases (24.17%) of unclassified influenza type A, 69 cases (57.50%) of type H1N1, 13 cases (10.83%) of H3N2 and 9 cases (7.22%) of influenza type B. From January 2017 to December 2019, the seasonal index from January to December (seasonal index = average number of observations in the same month each year/average value of observations in all months of each year×100%) are: January 383%, February 511%, March 140%, April 13%, May 13%, June to November 0%, December 140%. As it revealed that December–March was peak season and April–November was off-peak season, the seasons are divided into December to March and April to November, and are described, respectively, in this study. During December to March, there are 27 cases (22.68%) of unclassified influenza type A, 13 cases (58.76) of type H1N1, 13 cases (11.34%) of H3N2 and 9 cases (7.22%) of influenza type B. During April to November, there are 2 cases of unclassified influenza type A (66.67%), 1 case of H1N1 type (33.33%) and no cases of H3N2 type and influenza type B. The distributions of the virus subtypes within the two seasons are not statistically significant. Through analysis of disease severity, 9 cases (7.69%) of severe pneumonia are reported during December to March, while only 1 severe case (33.33%) was recorded during April to November, and the differences among the seasons are statistically insignificant.
Research methods
The data underwent retrospective analysis to examine patient demographic characteristics, epidemiological history, as well as clinical, laboratory and imaging features. Through analysis, we attempt to identify similarities and differences among some variables between non-severe and severe type COVID-19 patients. In addition, we compare the clinical characteristics of patients between the COVID-19 and influenza cohorts.
According to the ‘Diagnosis and Treatment Guidelines for COVID-19 Pneumonia’ issued by the Chinese National Health Commission, the following conditions are regarded as positive epidemiological history which also named as positive exposure history: (1) Individual who visited Wuhan and surrounding areas (including Huanggang), or area with reported COVID-19 cases within the past 14 days. (2) Individual who had close contact with COVID-19 patients within the past 14 days. (3) Individual showing signs of fever or any respiratory symptoms after contacting with personnel from the affected regions within the past 14 days [13].
The CT images collected from the cohorts during the early, progressive and recovery stages using either of these CT machines: Brightspeed 16 Slice CT from GE, Emotion 16 Slice CT from Siemens and Aquilion 16 row spiral CT from Toshiba. The DICOM images and data of each patient were analysed on PACS (Picture Archiving and Communication Systems) on CT images.
Statistical methods
SPSS 17.0 statistical software was used for data analysis. The quantity data were expressed as mean ±standard deviation (x ± s); the t-test was used to compare between 2 groups. The counting data were expressed as percentages; χ2 were used to compare between groups for statistical analysis.
Results
General, demographic and epidemiological history characteristics of COVID-19 patients
Our data revealed that 46.75% of the COVID-19 cohort was male and 53.25% was female; all had an epidemiological history. By comparing the non-severe and severe patients within the cohort, it showed more patients that were≥65 years old, male, smoking and had underlying diseases such as cardiovascular, diabetes and kidney diseases were suffering from severe COVID-19 pneumonia than the non-severe form. Additionally, there were no significant differences found in epidemiological data and patients with liver underlying disease or malignant tumours between severe and non-severe group. All related data are summarised in Table 2.
Table 2. General characteristics of COVID-19.
Symptom characteristics
The symptoms presented by our COVID-19 patients included fever, cough, dyspnoea, fatigue and muscle aches. While fever is the most prominent symptom, however, 21.54% of the patients showed no fever symptoms. Some patients (28.05%) had fever initially, but the symptom subsided on admission. For severe COVID-19 pneumonia, there were significantly more patients that showed persistent fever, productive cough with yellow sputum and dyspnoea than the non-severe group. All related data are summarised in Table 3.
Table 3. Symptomatic characteristics of COVID-19.
Characteristics of laboratory examinations
Our data showed 24.39% of COVID-19 patients had leukopenia and lymphocytopenia. Other blood tests showed some patients (39.84%) had decreased albumin. In contrary, some patients showed elevated erythrocyte sedimentation rate (66.26%) and CRP (47.97%). After excluding any kidney diseases, 32.11% of the patients had abnormal urinalysis. In addition, 15.04% of the patients had elevated blood creatinine, and 19.11% of patients had increased blood urea nitrogen (BUN).
In comparison, the patients in the severe group had lower blood level of lymphocytes and albumin, as well as more liver and kidney dysfunctions. The differences between the groups were statistically significant. Concurrently, blood gas analysis was done on 50 COVID-19 pneumonia patients; while 36 patients (72%) had a decrease in PaO2, 30 patients (60%) had a decrease in PaCO2. In contrary, 6 patients (12%) had raised PaCO2 level and all of them were in severe group.(Table 4)
Imaging features
In general, Table 5 summarised the lesions were more commonly affecting the lung bilaterally rather than unilaterally. They were also multiple focal in nature, and were located significantly more in the lower lung field than the upper and middle lung fields. These lesions are diffused and predominantly distributed on the periphery of the lung and along the pleural membrane. Table 6 summarised the characteristic features of COVID-19 pneumonia on pulmonary CT images. ‘Bat wing sign’ was visible if the bilateral lesions were distributed symmetrically. Occasionally, these bilateral lesions on CT may present as ‘reverse bat-wing sign’. The lesions may also be distributed very close along the pleural membrane, and thus giving appearance of the fused stripped pattern opacity. Sometimes, subpleural gap was also observed. (Figure 1)
Table 4. Laboratory test features of COVID-19.
Table 5. Distribution of lesions in COVID-19 pneumonia patients (n = 246).
Table 6. Characteristic features of COVID-19 pneumonia on pulmonary CT images (n = 246).
Interestingly, we found some specific imaging features that may correlate to the disease stages: early, progressive and recovery stages. For instance, our results showed ground glass opacity exhibited as the dominant CT feature during the early stage of the disease. As disease entered progressive stage, the CT images showed more consolidation. At the recovery stage, the lesions gradually faded or absorbed, and the reticular and striped opacity became the dominant feature on CT images. (Figure 2)
For 20 severe COVID-19 patients, we examined their images that showed a huge mix of ground glass opacity and consolidation, which could give an appearance of ‘white lung’. The occurrence rates of ‘white lung’ in severe cases were statistically significant when compared with non-severe cases.
Complications
In the study, a patient suffered from unilateral pleural effusion and was given drainage of the thoracic cavity. The pleural effusion was verified as leakage. Also, one patient had no previous history of mechanical ventilation suffered from spontaneous pneumothorax. For the other two cases, patients suffered from pneumothorax after receiving invasive ventilation.
Comparison of COVID-19 pneumonia and Influenza pneumonia
According to the criteria of National Health Commission of the People’s Republic of China [14], we defined disease as cluster, if 2 or more cases were reported in same small area, such as home, office, etc. Our data showed 65.04% of COVID-19 pneumonia cases are clustered in comparison to only 10% that are seen in influenza pneumonia cases. The difference was statistically significant. While the incidences of COVID-19 and influenza were comparable among the 18–65 and >65 year age groups, the result showed the incidence of influenza pneumonia (11.67%) were much higher than COVID-19 pneumonia (0.81%) among young patients (<18 years old). The significance of these findings warrant further investigations. The difference was statistically significant (Table 7).
Table 7. Comparison of clinical features between new coronary pneumonia and influenza pneumonia.
Fever was the main symptom for both study cohorts: COVID-19 and Influenza cohorts. Though common, there are patients that had fever initially, but the fever subsided at the time of admission. Nevertheless, the rate of developing fever in the influenza group was higher than that of the COVID-19 group.
For laboratory tests, both cohorts showed lowered lymphocyte numbers generally. However, 6 patients in the influenza cohort had elevated lymphocyte numbers, which was statistically significant when compared with COVID-19 cohort. In addition, more abnormal urinary routine tests were observed in the COVID-19 cohort than in the influenza cohort, and the differences were statistically significant. The ratio of elevated white blood cells and PCT in the influenza group was higher than that of the COVID-19 group.
Both cohorts showed increase level of urea nitrogen, creatinine, transaminase, erythrocyte sedimentation rate, C-reactive protein, and LDH, but reduction in blood albumin level. Nevertheless, these differences among the 2 cohorts were statistically insignificant. All related data are summarised in Table 7.
Discussion
Since the emergence of SARS, MERS and influenza, the COVID-19 pandemic has become the latest major public health crisis worldwide [15]. Currently, no vaccine or treatment is available for dealing with the disease. Therefore, early screening, diagnosis and isolation of infected individuals are the only effective means in controlling the spread of the aetiological virus, SARS-CoV-2. Although specific tests such as RT-PCR and antibody detection test are currently available for detecting the virus, they have shortfalls [16]. The RT-PCR has a false negative rate of 56.41% [17]. The antibody test has a false positive rate of 9.38% and a false negative rate of 11.34% [18]. Also, these results fail to provide data on disease assessment. Therefore, the preliminary diagnosis would be highly dependent on the integration of full medical history, clinical manifestations and common basic laboratory tests results. In this study, we attempt to highlight some features of COVID-19 pneumonia and make comparison with influenza pneumonia. By enhancing the awareness of COVID-19, we hope to help the clinicians to make accurate diagnosis and make the next clinical decisions.
In our study, we were able to trace the epidemiological history of all our confirmed COVID-19 patients; 60.16% of them show clustering in the epidemiological study. The occurrences of these clustering are more frequent than those of influenza pneumonia, which may suggest that the SARS-CoV-2 virus is more contagious than the influenza virus. Therefore, adequate prevention and control measures must be followed by individuals or communities that are at risk of SARS-CoV-2 exposure to prevent further spread of the virus.
Early literature reported the incidence of COVID-19 pneumonia were more common in male [2,19], and associated it with higher level of ACE2 expression in male [20]. However, our study showed there is insignificant difference on the disease incidence between genders. It could be interpreted by Cai’s study which found that ACE2 expression is independent of gender [21]. In another observational study, Li had concluded the gender difference in the incidence of COVID-19 pneumonia was insignificant [22], which is similar as our conclusion. Moreover, our study showed a slight female predominance in the incidence of COVID-19 cases. Whether it has significance or not require further investigation.
Our data showed male patients suffered from more severe disease. In agreement with Cai [21], the more prevalent male smokers in China have significantly raised ACE2 gene expression; which makes the cells more prone to SARS-CoV-2 invasion resulting more severe disease. Our data had also shown male patients who are ≥65 years old and has underlying diseases were more likely to have a severe disease, which correlates with other studies [7,8,23].
Curiously, the COVID-19 cases that involved infant and children are rare. Recent literature had reported children under the age of 10 accounts for only 1% of the COVID-19 cases in China; those who were infected had milder disease [24]. This discrepancy may infer that children have altered mechanisms that regulate the interaction between the immune system and respiratory system [25]. In comparison to COVID-19 pneumonia, the incidence of influenza pneumonia was significantly higher in children in our study.
The SAR-CoV-2 triggers a cascade of events that result in inflammation by its RBD domain on the S-protein interacts with ACE2 PD domain [26]. Excessive inflammatory response in the COVID-19 pneumonia can cause cytokine storms, which eventually progress to sepsis and multiple organ damage and even death [8]. SAR-CoV-2 affects mainly the respiratory system. The virus targets type II alveolar cells that express ACE2 as their cell surface receptor. To lesser extent, ACE2 is also present on type I alveolar cells, fibroblast, endothelial cells, as well as the luminal surface of tracheobronchial and alveolar epithelium. In addition to the pulmonary system, this ACE2 is also expressed in the brain, digestive system, kidney and the heart [3,27].
Our data showed that common COVID-19 symptoms included fever, coughs, dyspnoea and fatigue; in our study, fever is the prominent clinical manifestations for COVID-19 pneumonia which is similar as the other reports [28,29]. However, we also analysed the fever course of the patients; while 50.41% patients showed persistent fever, 28.05% patients showed fever symptoms initially, but subsided later even though the disease still progressed. However, some patients (21.54%) showed no fever symptoms, although their infected status was confirmed. In comparison, fever is more prevalent in the influenza cohort. Similarly, 23.33% patients had shortly fever initially; this was not statistically different from the COVID-19 cohort. Only 10.83% of the influenza cohort showed no fever symptom.
In COVID-19 cohorts, the blood test showed lower peripheral blood lymphocytes and albumin, but an increased in ESR and CRP. The reduction in lymphocytes is more apparent in severe patients. These test results suggested the SARS-CoV-2 virus could induce inflammatory response and impair the immune system concurrently. In contrast, the influenza cohort showed also decreased lymphocytes; but some patients may even have increased lymphocytes. In arterial blood gas, it revealed the incidence of elevated arterial carbon dioxide partial pressure in the severe group. This may due to the mucus obstruction of the terminal airway during the severe period, which eventually leads to the retention of CO2.
Our data revealed COVID-19 cohorts are more susceptible to liver and kidney damages. Our data showed 23.58% of the patients show signs of liver damage that were reflected by raised ALT; these results correlated well with other reports [23,30]. In addition to measuring the blood urea nitrogen (BUN) and creatinine (Cr) level, we also performed urinalysis in hope of providing more information on kidney injury. In patients with no previous history of renal disease, we found higher proportion of COVID-19 patients to have kidney damages than previously reported [23,31]. The mechanism of damages may be related to the high expression of ACE2 in the kidney. It may also due to renal hypoxia, drugs and cytokine storms. From this finding, the clinicians should also pay attention to kidney functions, when making diagnosis and treatment planning for COVID-19 pneumonia patients.
Through imaging, the CT from COVID-19 cohorts exhibited several CT characteristics included bilateral lung involvement that predominantly affects the lower lobes. The lesions were multifocal and are diffusely distributed on the peripheral of the lungs and subpleurally. It may give ground glass shadows, cord opacity, or consolidation opacity. As disease progresses, the lesions broaden towards the centre. The lesions may appear as a band, bat-wing like or reverse bat wing opacity that distribute alongside the pleural membrane. As disease progressed, the images may evolve into a large area of consolidation or ‘white lung’ in the severe group. The CT imaging manifestations are consistent with the pathological changes seen in COVID-19 pneumonia. These changes included interstitial pneumonia, extensive exudation of mucous material in the alveolar cavity, mas inflammatory cells infiltration, hyaline membrane formation and fibrous tissue hyperplasia [32–34].
Moreover, our data showed the incidence of secondary bacterial infections of influenza pneumonia is higher than that of COVID-19 pneumonia. For these patients, common bedside observation such as purulent sputum, elevated PCT and elevated white blood cells were noted. For COVID-19 pneumonia patients, pleural effusions may often be present, but it is rarely caused by the virus, but due to abnormal cardiac, hepatic and kidney functions, as well as hypoproteinemia in patients.
For this study, the time and hospital that we collected data for the COVID-19 and influenza cohorts are different due to that COVID-19 pneumonia outbroke recently and the Chinese government policy requires that COVID-19 patients must be admitted in designated hospitals. Perhaps this may have a little bit of influence on the results. Nevertheless, the severity among the two groups of patients is not statistically significant., the clinical characteristics of the COVID-19 and influenza cohorts are comparable.
Generally, COVID-19 have characteristics in clinical manifestations, epidemiological history, laboratory tests and radiological finding, some of which were different from influenza pneumonia while some of which were similar as it. Although the current methods of detecting SARS-CoV-2 such as RT-PCR and antibody tests are specific, they have limitation to early and accurately diagnose and assess the disease. In order to accurately diagnose and assess COVID-19 as well as make clear difference from other diseases, the combination of epidemiological history, clinical manifestations, laboratory detection such as PCR and serology, and CT image are necessary and should be taken.
| Target | Target gene | Primer Forward Reverse | |
|---|---|---|---|
| 2019-nCOV | ORF1ab | CCCTGTGGGTTTTACACTTAA | ACGATTGTGCATCAGCTGA |
| 2019-nCOV | N protein | GGGGAACTTCTCCTGCTAGAAT | CAGACATTTTGCTCTCAAGCTG |
| Influenza A virus | Matrix protein2 and Matrix protein1 | TCATGGAATGGCTAAAGA | TACGCTGCAGTCCTCGCT |
| Influenza B virus | Matrix protein2 and Matrix protein1 | TGGAGTGAGACGAGAAATGCAGAT | GAATTTCCCATGGAGCTCTGCTTTA |
| H1N1 | Hemagglutinin | AGCCTGGAGACAAGATAACATTGG | GGTGTTTATAGCACCATTGGGTGTC |
| H3N2 | Hemagglutinin | GAACGTTCGTGAAAACAATCACGGA | CGGCACATAATAAGGGTAACAGTTG |
| Characteristic | Total (n = 246) | Non-severe (n = 226) | Severe (n = 20) | P value |
|---|---|---|---|---|
| Median age (mean±SD)-year | 53.63 ± 15.27 | 53.27 ± 15.25 | 61.9 ± 14.01 | >0.05 |
| Age group: no.(%) | ||||
| <18 yr | 2 (0.81) | 2 (0.88) | 0 (0) | >0.05 |
| 18–65 yr | 186 (75.61) | 178 (78.76) | 8 (40.00) | <0.05 |
| >65 yr | 58 (23.58) | 46 (20.35) | 12 (60.00) | <0.05 |
| Sex-: no.(%) | ||||
| Male | 115 (46.75) | 101 (44.69) | 14 (70.00) | <0.05 |
| Female | 131 (53.25) | 125 (55.31) | 6 (30.00) | |
| Comorbidity: no.(%) | ||||
| Respiratory diseases | 9 (3.66) | 9 (3.98) | 0 (0) | >0.05 |
| Hypertension | 40 (16.26) | 30 (13.27) | 10 (50.00) | <0.05 |
| Coronary heart disease | 10 (4.07) | 6 (2.65) | 4 (20) | <0.05 |
| Diabetes | 18 (7.32) | 10 (4.42) | 8 (40) | <0.05 |
| Kidney disease | 5 (2.03) | 3 (1.33) | 2 (10) | <0.05 |
| Liver disease | 4 (1.63) | 4 (1.77) | 0 (0) | >0.05 |
| Malignancy | 5 (2.03) | 5 (2.21) | 0 (0) | >0.05 |
| Smoking history: no.(%) | 104 (42.28) | 90 (39.82) | 14 (70) | <0.05 |
| Epidemiology: no.(%) | ||||
| Exposure | 246 (100) | 226 (100) | 20 (100) | >0.05 |
| Cluster cases | 160 (65.04) | 148 (65.47) | 12 (60) | >0.05 |
| Characteristic | Total (n = 246) | Non-severe (n = 226) | Severe (n = 20) | P value |
|---|---|---|---|---|
| Fever no.(%) | 193 (78.46) | 174 (76.99) | 19 (95) | >0.05 |
| Temperature (mean±SD)°C | 38.41 ± 0.65 | 38.39 ± 0.65 | 38.8 ± 0.51 | >0.05 |
| Course of fever | ||||
| Persistent fever no. (%) | 124 (50.41) | 108 (47.79) | 16 (80) | <0.01 |
| Initial stage fever no. (%) | 69 (28.05) | 66 (29.20) | 3 (15) | >0.05 |
| No fever | 53 (21.54) | 52 (23.01) | 1(5) | >0.05 |
| Cough no. (%) | 162 (65.85) | 150 (66.37) | 12 (60) | >0.05 |
| Sputum no. (%) | ||||
| White | 57 (23.17) | 55 (24.34) | 2 (10.00) | >0.05 |
| Yellow | 10 (4.07) | 6 (2.65) | 4 (20.00) | <0.01 |
| With blood | 10 (4.07) | 7 (3.10) | 3 (15.00) | <0.05 |
| Dyspnea no.(%) | 150 (60.98) | 130 (57.52) | 20 (100.00) | <0.01 |
| Fatigue no.(%) | 120 (48.78) | 100 (44.25) | 20 (100.00) | <0.01 |
| Muscle ache no.(%) | 90 (36.59) | 81 (35.84) | 9 (45.00) | >0.05 |
| Diarrhea no.(%) | 40 (16.26) | 36 (15.93) | 4 (20.00) | >0.05 |
| Characteristics | Total (n = 246) | Non-severe (n = 226) | Severe (n = 20) | P value |
|---|---|---|---|---|
| WBC count abnormal | ||||
| Decreased-no. (%) | 60 (24.39) | 54 (23.89) | 6 (30.00) | >0.05 |
| Increased- no. (%) | 27 (10.98) | 20 (8.85) | 7 (35.00) | <0.01 |
| Lymphocyte count abnormal | ||||
| Decreased-no. (%) | 60 (24.39) | 46 (20.35) | 14 (70.00) | <0.01 |
| Increased- no. (%) | 0 (0) | 0 (0) | 0 (0) | - |
| Platelets count decreased-no. (%) | 11 (4.47) | 8 (3.54) | 3 (15.00) | <0.05 |
| Urine routine abnormal | 79 (32.11) | 65(28.76) | 14(70.00) | <0.01 |
| Urine protein (+)-no. (%) | 40 (16.26) | 34 (15.04) | 6 (30.00) | >0.05 |
| Urine RBC (+)-no. (%) | 27 (10.98) | 23 (10.18) | 4(20.00) | >0.05 |
| Urine RBC & protein (+) | 12(4.88) | 8(3.54) | 4(20.00) | <0.01 |
| Urea nitrogen increased-no. (%) | 47 (19.11) | 31 (13.72) | 16 (80.00) | <0.01 |
| Serum creatinine increased-no. (%) | 37 (15.04) | 27 (11.95) | 10 (50.00) | <0.01 |
| ALT increased-no. (%) | 58 (23.58) | 49 (21.68) | 9(45.00) | <0.05 |
| Albumin decreased-no. (%) | 98 (39.84) | 85 (37.61) | 13(65.00) | <0.05 |
| ESR increased-no. (%) | 163 (66.26) | 147 (65.04) | 16 (80.00) | >0.05 |
| CRP increased-no. (%) | 118 (47.97) | 102 (45.13) | 16 (80.00) | <0.01 |
| LDH increased-no. (%) | 35 (14.23) | 29(12.83) | 6 (30.00) | <0.05 |
| Distribution | Number of cases | Percentages (%) |
|---|---|---|
| Bilateral | 230 | 93.50 |
| Unilateral | 16 | 6.50 |
| Mainly lower lung field | 226 | 91.87 |
| Mainly upper and Middle lung field | 20 | 8.13 |
| Mainly peripheral | 231 | 93.90 |
| Mainly central | 15 | 6.10 |
| Multiple focal lesion | 235 | 95.53 |
| Single | 11 | 4.47 |
| Features | Number of cases | % Occurrence |
|---|---|---|
| Ground glass opacity | 200 | 81.30 |
| Consolidation | 186 | 75.61 |
| Striped and banded opacity | 173 | 70.33 |
| Reticular pattern opacity | 150 | 60.98 |
| Subpleural curvilinear line | 136 | 55.28 |
| Thickening of interlobular septa | 130 | 52.85 |
| Crazy paving sign | 110 | 44.72 |
| Thickening of blood vessels | 103 | 41.87 |
| Air Bronchogram | 68 | 27.64 |
| Bronchial wall thickening | 58 | 23.58 |
| Bat wing sign | 58 | 23.58 |
| Nodules opacity | 56 | 22.76 |
| Subpleural space | 50 | 20.33 |
| Halo sign | 40 | 16.26 |
| Reverse bat wing sign | 40 | 16.26 |
| Pleural stretch | 38 | 15.45 |
| Reversed halo sign | 22 | 8.94 |
| White lung | 20 | 8.13 |
| Pleural effusion | 10 | 4.07 |
| Pleural thickening | 10 | 4.07 |
| Pneumothorax | 6 | 2.44 |
| Enlarged lymph node | 3 | 1.22 |
| Characteristics | COVID-19 (n = 246) | Influenza pneumonia (n = 120) | P value |
|---|---|---|---|
| Age (mean±SD)-year | 53.63 ± 15.27 | 55.41 ± 24.7 | >0.05 |
| Age group -no. (%) | |||
| <18 yr | 2 (0.81) | 14 (11.67) | <0.01 |
| 18–65 yr | 186 (75.61) | 84 (70.00) | >0.05 |
| >65 yr | 58 (23.58) | 22 (18.33) | >0.05 |
| Sex-no. (%) | |||
| Male | 115 (46.75) | 68 (56.67) | >0.05 |
| Female | 131 (53.25) | 52 (43.33) | |
| Cluster cases-no. (%) | 160 (65.04) | 12 (10.00) | <0.01 |
| Fever | |||
| Patients-no. (%) | 193 (78.46) | 107 (89.17) | <0.05 |
| Persistent fever-no. (%) | 124 (50.41) | 89(74.17) | <0.01 |
| Initial stage fever-no. (%) | 69 (28.05) | 28(23.33) | >0.05 |
| WBC count abnormal | |||
| Decreased-no. (%) | 60(24.39) | 13(10.83) | <0.01 |
| Increased- no. (%) | 27(10.98) | 49(40.83) | <0.01 |
| Lymphocyte count abnormal | |||
| Decreased-no. (%) | 60(24.39) | 39(32.50) | >0.05 |
| Increased- no. (%) | 0(0) | 6 (5.00) | <0.01 |
| Urine routine abnormal | 79(32.11) | 26(21.67) | <0.05 |
| Urine protein(+) | 40(16.26) | 10(8.33) | <0.05 |
| Urine RBC (+) | 27(10.98) | 7(5.83) | >0.05 |
| Urine RBC & protein (+) | 12(4.88) | 9(7.50) | >0.05 |
| Urea nitrogen increased-no. (%) | 47(19.11) | 33(27.50) | >0.05 |
| Serum creatinine increased-no. (%) | 37(15.04) | 26(21.67) | >0.05 |
| ALT increased-no. (%) | 58(23.58) | 19(15.83) | >0.05 |
| Albumin decreased-no. (%) | 98 (39.84) | 60 (50.00) | >0.05 |
| ESR increased-no. (%) | 163 (66.26) | 79 (65.83) | >0.05 |
| CRP increased-no. (%) | 118 (47.97) | 69 (57.50) | >0.05 |
| LDH increased-no. (%) | 35 (14.23) | 19(15.83) | >0.05 |
| PCT increased-no. (%) | 66 (26.83) | 90 (75.00) | <0.01 |
Disclosure statement
No potential conflict of interest was reported by the authors.
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