Abstract
Coronavirus disease 2019 (COVID-19) emerged in Wuhan and rapidly spread throughout the world in December 2019. The present study aimed to describe the clinical characteristics and laboratory findings of 78 patients with COVID-19 in order to enhance the understanding of the disease. Medical records and data of 78 patients with COVID-19, including demographics, clinical features, laboratory findings and radiological characteristics, were collected and analyzed. Of the 78 hospitalized patients with COVID-19, the median age was 66.5 years and 48.7% of patients were male. Hypertension and diabetes were the most common chronic underlying diseases, and the most common symptoms were a cough and a fever. Furthermore, the most common findings on the chest CT were extensive ground-glass opacity and bilateral shadowing. Anemia and lymphocytopenia were the most common abnormalities identified during routine blood tests. COVID-19 caused early liver renal damage, with 52.9% of patients displaying elevated D-dimer levels, 98.7% of patients displaying elevated IL-6 levels and 80.8% of patients displaying a reduced level of low-density lipoprotein cholesterol (LDL-C). In the present single-center case study of 78 patients with COVID-19 in Wuhan, China, the patients displayed abnormal routine blood tests, liver function, renal function and levels of D-dimer, LDL-C and IL-6. Therefore, the development of drugs and vaccines that can be used to prevent and treat infections of COVID-19 is urgently required.
Keywords: clinical characteristics, coronavirus disease 2019
Introduction
In December 2019, in Wuhan, Hubei, China, a number of patients with pneumonia of an unknown cause were confirmed to be infected with a novel coronavirus, which had not been detected in humans or animals previously (1). On January 7th 2020, researchers rapidly isolated a novel coronavirus from patients with confirmed infectious pneumonia (2). The pathogen was named SARS-Cov-2 due to its similarity to the coronavirus that causes severe acute respiratory syndrome (SARS-CoV). These infections share ≥79% of the sequence of the subgenus Sarbecovirus (β-CoV lineage B). SARS-Cov-2 shares only 50% homology with the coronavirus responsible for Middle East respiratory syndrome (MERS-CoV), which is a member of the Merbecovirus subgenus (3).
The World Health Organization recently assessed that coronavirus disease 2019 (COVID-19) can be classified as a pandemic (4). As of April 25th 2020, a total of 2,719,896 laboratory-confirmed cases had been reported globally (5), but these figures are increasing every day. The spread of COVID-19 among people has been demonstrated to occur via droplets, aerosols, feces and mouth mucus membranes (1). According to recent studies, the most common symptoms were fever, cough, expectoration, myalgia or fatigue, nausea or vomiting and diarrhea. The most common radiologic finding in chest CT was ground-glass opacity (3,6).
The aim of the present study was to describe the clinical characteristics and laboratory findings of patients with COVID-19 admitted to the Z13 Unit of Union Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology to improve the understanding of COVID-19 globally.
Materials and methods
Patients
Patients with confirmed cases of COVID-19 were enrolled from Z13 Unit of Union Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology between February 14th 2020 and March 14th 2020. Only laboratory-confirmed cases were enrolled in the present study, which were previously diagnosed by a positive result from a reverse transcription-quantitative PCR (RT-qPCR) of nasal and pharyngeal swab specimens. All patients enrolled in the present study were non-severe. COVID-19 and the degree of severity was diagnosed on the basis of the latest version of the guidelines of Diagnosis and Treatment of Pneumonitis Caused by the novel coronavirus, including the fourth, fifth, and sixth versions, which were issued by the National Health Commission of China (7).
Data collection
The medical records and data of patients were extracted on admission from electronic medical records, and included demographics, clinical features, laboratory findings and characteristics of the chest CT. The aforementioned data were collected and reviewed by the doctors who had been treating the patients with COVID-19, and were then entered into a computerized database and crosschecked. As the cohort of patients enrolled in the present study and the laboratory tests conducted were not derived from random selection, the statistics of the present study are descriptive only. The normal ranges of laboratory findings are presented in Table I.
Table I.
The normal reference ranges of laboratory findings.
| Parameters | Reference ranges |
|---|---|
| Hemoglobin (male, g/l) | 130-175 |
| Hemoglobin (female, g/l) | 115-150 |
| White-cell count, x10 per mm3 | 4-10 |
| Neutrophil count, x10 per mm3 | 1.8-6.3 |
| Lymphocytes count, x10 per mm3 | 1.1-3.2 |
| Platelet count, x10 per mm3 | 125-350 |
| Eosinophilia count, x10 per mm3 | 0.02-0.52 |
| Total bilirubin, µmol/l | 5.1-19.0 |
| Direct bilirubin, µmol/l | 1.7-6.8 |
| Total protein, g/l | 64-83 |
| Albumin, g/l | 35-55 |
| Globulin, g/l | 20-30 |
| Alanine aminotransferase, IU/l | 8-40 |
| Aspartate aminotransferase, IU/l | 5-35 |
| Alkaline phosphatase, IU/l | 40-150 |
| γ-Glutamyltranspeptidase, IU/l | 7-32 |
| Blood urea nitrogen, mmol/l | 2.9-8.2 |
| Creatinine, µmol/l | 44-106 |
| Uric acid, µmol/l | 155-357 |
| Cystatin C, mg/l | ≤1.0 |
| Total carbon dioxide, mmol/l | 21-30 |
| Prothrombin time, sec | 11-16 |
| International normalized ratio | 0.8-1.31 |
| Fibrinogen degradation products, µg/ml | ≤5.0 |
| D-dimer, µg/l | ≤0.5 |
| C-reactive Protein, mg/l | ≤5.0 |
| Procalcitonin, mg/l | ≤0.5 |
| Erythrocyte sedimentation rate, mm/H | ≤15 |
| Ferritin, µg/l | ≤4.6 |
| CD3+ total T-lymphocytes, % | 58.17-84.22 |
| CD4+ T-lymphocyte, % | 25.34-51.37 |
| CD8+ T-lymphocyte, % | 14.23-38.95 |
| CD4+/CD8+ | 0.41-2.72 |
| IL-6, pg/ml | ≤2.9 |
| TNF-α, pg/ml | ≤23 |
| IL-4, pg/ml | ≤3.2 |
| IL-2, pg/ml | ≤4.1 |
| IL-10, pg/ml | ≤5.0 |
| IFN-γ, pg/ml | ≤18 |
| LDH, U/l | 109-245 |
| CK, U/l | 26-140 |
| CK-MB, U/l | ≤6.6 |
| cTnI, ng/l | ≤26.2 |
| BNP, µg/ml | ≤100 |
| TG, mmol/l | ≤1.7 |
| LDL-c, mmol/l | 2.7-3.1 |
LDH, lactic dehydrogenase; CK, creatine kinase; CK-MB, CK isoenzyme-the Muscle Brain isoenzyme; cTnI, hypersensitive troponin I; BNP, brain natriuretic peptide; TG, triglyceride; IQR, interquartile range; LDL-c, low density lipoprotein cholesterol.
Statistical analysis
For categorical variables, the percentage of patients in each category was calculated. Continuous variables were appropriately represented as the median with interquartile or simple ranges. There are no estimates of the missing data. Medians and interquartile ranges (IQRs) were calculated using SPSS software (version 22.0; IBM Corp.).
Results
General information of patients with COVID-19
Up to March 14th 2020, a total of 78 patients with COVID-19 had been admitted to the Z13 Unit of Union Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology, including 40 female patients and 38 male patients. The median age of the patients was 66.5 years (interquartile range, 53.75-70), with 5 (6.4%) patients aged 15-40 years, 27 (34.6%) patients aged 41-65 years and 46 (59%) patients aged >65 years. Coexisting conditions were observed in 50% of patients, including hypertension, diabetes, cerebral infarction, malignant tumor and chronic renal failure. Hypertension and diabetes were the most common chronic underlying diseases in the cohort (Table II).
Table II.
General information of patients with COVID-19.
| Characteristics | All patients, n=78 |
|---|---|
| Median (interquartile) age (years) | 66.5 (53.75-70) |
| Age groups (years) | |
| 15-40 | 5 (6.4) |
| 41-65 | 27 (34.6) |
| >65 | 46(59) |
| Sex (%) | |
| Male | 38 (48.7) |
| Female | 40 (51.3) |
| Coexisting conditions (%) | |
| Any | 39(50) |
| Hypertension | 24 (30.8) |
| Diabetes | 16 (20.5) |
| Cerebral infarction | 1 (1.3) |
| Malignant tumor | 3 (3.8) |
| Chronic renal failure | 3 (3.8) |
| Symptoms (%) | |
| Fever | 51 (65.4) |
| Cough | 59 (75.6) |
| Sputum production | 24 (30.8) |
| Shortness of breath | 12 (15.4) |
| Fatigue | 39(50) |
| Myalgia or arthralgia | 19 (24.4) |
| Diarrhea | 13 (16.7) |
| Nausea | 14 (17.9) |
| Headache | 0 (0) |
| Nausea or vomiting | 0 (0) |
| Abnormalities on chest CT (%) | |
| Ground-glass opacity | 42 (53.8) |
| Bilateral patchy shadowing | 20 (25.6) |
| Thread net shadowing | 14 (17.9) |
| Linear shadowing | 13 (16.7) |
| Consolidation shadowing | 22 (28.2) |
COVID-19, coronavirus disease 2019.
Symptoms
On admission, the majority of the patients presented with a fever (65.4%) or cough (75.6%) and 50% of patients reported fatigue. Other symptoms included sputum production, shortness of breath, myalgia or arthralgia, diarrhea and nausea. Out of the 78 patients, only 4 (5.1%) patients did not display any symptoms (data not shown).
CT findings
All patients enrolled in the present study displayed CT abnormalities. The most common chest CT findings of patients with COVID-19 on admission were ground-glass opacity (53.8%) and consolidation shadowing (28.2%) (Table II).
Routine blood examination
The hemoglobin levels and blood cell count of 77 patients (one patient did not receive a routine blood examination) on admission, including white cell, neutrophil, lymphocyte, platelet and eosinophil counts, are presented in Table III. Anemia was identified in 47.4% of male patients and 41% of female patients. Moreover, 14 (18.2%) patients displayed leucopenia and 3 (3.9%) patients displayed leukocytosis. Lymphocytopenia was present in 28 (36.4%) patients and thrombocytopenia was identified in 8 (10.4%) patients. Twelve patients displayed lower eosinophilia counts than the lower limit of the reference range.
Table III.
Routine blood examination.
| Parameter | Patient no. |
|---|---|
| Hemoglobin (Male, g/l) | |
| Median (IQR) | 131 (122-138.25) |
| <130 (%) | 18/38 (47.4) |
| >175 (%) | 0/38 (0) |
| Hemoglobin (Female, g/l) | |
| Median (IQR) | 118 (111-123) |
| <115 (%) | 16/39(41) |
| >150 (%) | 0/39 (0) |
| White-cell count, x10 per mm3 | |
| Median (IQR) | 5.51 (4.40-7.34) |
| <4 (%) | 14/77 (18.2) |
| >10 (%) | 3/77 (3.9) |
| Neutrophil count, x10 per mm3 | |
| Median (IQR) | 3.37 (2.56-5.28) |
| <1.8 (%) | 3/77 (3.9) |
| >6.3 (%) | 8/77 (10.4) |
| Lymphocytes count, x10 per mm3 | |
| Median (IQR) | 1.29 (0.91-1.68) |
| <1.1 (%) | 28/77 (36.4) |
| >3.2 (%) | 2/77 (2.6) |
| Platelet count, x10 per mm3 | |
| Median (IQR) | 216 (159.5-271) |
| <125 (%) | 8/77 (10.4) |
| >350 (%) | 5/77 (6.5) |
| Eosinophilia count, x10 per mm3 | |
| Median (IQR) | 0.07 (0.03-0.12) |
| <0.02 | 12/77 (15.6) |
| >0.52 | 0/77 (0) |
IQR, interquartile range.
Assessment of liver function
Among the 78 patients, 14 (17.9%) patients displayed elevated levels of total bilirubin, whereas elevated direct bilirubin was observed in 7 (9%) patients. The incidence rates of elevated alanine aminotransferase (ALT), aspartate transaminase (AST), alkaline phosphatase (ALP) and γ-glutamyl transferase (γ-GGT) were 17.9, 37.2, 1.3 and 43.6%, respectively. Moreover, 36 patients displayed lower total protein counts than the lower limit of the reference range. Levels of albumin were decreased in 27 (34.6%) the patients. In addition, 55 (70.5%) patients displayed normal serum levels of globulin (Table IV).
Table IV.
Assessment of liver function.
| Parameter | Patient no. |
|---|---|
| Total bilirubin, umol/l | |
| Median (IQR) | 12.95 (10.27-16.92) |
| <5.1 (%) | 1/78 (1.3) |
| >19.0 (%) | 14/78 (17.9) |
| Direct bilirubin, µmol/l | |
| Median (IQR) | 4.0 (3.3-5.0) |
| <1.7 (%) | 0/78 (0) |
| >6.8 (%) | 7/78 (9.0) |
| Total protein, g/l | |
| Median (IQR) | 64.9 (61.82-67.32) |
| <64 (%) | 36/78 (46.2) |
| >83(%) | 0/78 (0) |
| Albumin, g/l | |
| Median (IQR) | 36.75 (33.08-40.25) |
| <35 (%) | 27/78 (34.6) |
| >55 (%) | 0/78 (0) |
| Globulin, g/l | |
| Median (IQR) | 27.3 (24.98-30.43) |
| <20 (%) | 2/78 (2.6) |
| >30 (%) | 21/78 (26.9) |
| Alanine aminotransferase, IU/l | |
| Median (IQR) | 27 (20-37.25) |
| <8 (%) | 0/78 (0) |
| >40 (%) | 14/78 (17.9) |
| Aspartate aminotransferase, IU/l | |
| Median (IQR) | 25.5 (17.75-48) |
| <5 (%) | 0/78 (0) |
| >35 (%) | 29/78 (37.2) |
| Alkaline phosphatase, IU/l | |
| Median (IQR) | 78 (67-99.25) |
| <40 (%) | 0/78 (0) |
| >150 (%) | 1/78 (1.3) |
| γ-Glutamyltranspeptidase, IU/l | |
| Median (IQR) | 28.5 (19-48.5) |
| <7 (%) | 0/78 (0) |
| >32 (%) | 34/78 (43.6) |
IQR, interquartile range.
Assessment of renal function
The levels of blood urea nitrogen, creatinine, uric acid, cystatin C and total carbon dioxide are presented in Table V. Among the 77 patients, 64 (83.1%) patients displayed normal blood urea nitrogen levels. Total creatinine levels <44 µmol/l were observed in 2 (2.6%) patients, whereas 4 (5.2%) patients displayed total creatinine levels >106 µmol/l. Moreover, 5 (6.6%) patients out of 76 patients displayed a lower uric acid count than the lower limit of the reference range, whereas 11 (14.5%) patients displayed a higher uric acid count (one patient missed the blood examination of uric acid and cystatin C). Elevated cystatin C levels were observed in 64.5% of patients.
Table V.
Assessment of renal function.
| Parameter | Patient no. |
|---|---|
| Blood urea nitrogen, mmol/l | |
| Median (IQR) | 4.2 (3.22-5.05) |
| <2.9 (%) | 10/77(13) |
| >8.2 (%) | 3/77 (3.9) |
| Creatinine, µmol/l | |
| Median (IQR) | 75 (66.25-87.5) |
| <44 (%) | 2/77 (2.6) |
| >106 (%) | 4/77 (5.2) |
| Uric acid, µmol/l | |
| Median (IQR) | 277 (215.25-328.25) |
| <155 (%) | 5/76 (6.6) |
| >357 (%) | 11/76 (14.5) |
| Cystatin C, mg/l | |
| Median (IQR) | 1.08 (0.94-1.28) |
| >1.0 (%) | 49/76 (64.5) |
| Total carbon dioxide, mmol/l | |
| Median (IQR) | 23.6 (20.45-26.7) |
| <21 | 20/77(26) |
| >30 | 2/77 (2.6) |
IQR, interquartile range.
Assessment of coagulation function
The results of the assessment of coagulation function are presented in Table VI. Among the 51 D-dimer tests performed, 52.9% identified elevated D-dimer levels (median, 0.6 µg/l; interquartile range, 0.2-1.56 µg/l).
Table VI.
Assessment of coagulation function.
| Parameter | Patient no. |
|---|---|
| Prothrombin time, sec | |
| Median (IQR) | 12.95 (10.27-16.92) |
| <11 (%) | 0/70 (0) |
| >16 (%) | 2/7 (2.9) |
| International normalized ratio | |
| Median (IQR) | 1.04 (0.99-1.10) |
| <0.8 (%) | 0/70 (0) |
| >1.31 (%) | 2/70 (2.9) |
| Fibrinogen degradation products, µg/ml | |
| Median (IQR) | 2.2 (1.3-4.7) |
| >5 (%) | 12/51 (23.5) |
| D-dimer, µg/l | |
| Median (IQR) | 0.6 (0.21-1.56) |
| >0.5 (%) | 27/51 (52.9) |
IQR, interquartile range.
Level of infection-related biomarkers
C-reactive protein levels were increased in 34 (47.2%) patients. Only one patient displayed a procalcitonin level >0.5 mg/l. Among the 45 erythrocyte sedimentation rate (ESR) examinations performed, levels of ESR were increased in 36 (80%) patients. Only 24 patients received ferritin tests, with 16 patients displaying ferritin levels >204 µg/l (Table VII).
Table VII.
Level of infection-related biomarkers.
| Parameter | Patient no. |
|---|---|
| C-reactive protein, mg/l | |
| >5 (%) | 34/72 (47.2) |
| Procalcitonin, mg/l | |
| >0.5 (%) | 1/71(1.4) |
| Erythrocyte sedimentation rate, mm/H | |
| >15 (%) | 36/45(80) |
| Ferritin, µg/l | |
| Median(IQR) | 248.8 (132.3-492.95) |
| >4.6 (%) | 0/24 (0) |
IQR, interquartile range.
Measurement of T-lymphocyte subsets
The numbers of total T-lymphocytes were lower than the reference range in 13 (16.7%) patients, but higher in 18 patients (23.1%). Among the 78 patients, 6 (7.7%) patients displayed declined CD4+ T-lymphocyte counts and 25 (32.1%) patients displayed elevated counts. Moreover, CD8+ T-lymphocyte counts were elevated in 9 (11.5%) patients and decreased in 9 (11.5%) patients. The ratio of CD4+ T-lymphocytes to CD8+ T-lymphocytes was increased in 25 (32.1%) patients (Table VIII).
Table VIII.
Measurement of T-lymphocyte subsets.
| Parameter | Patient no. |
|---|---|
| CD3+ total T-lymphocytes, % | |
| Median (IQR) | 78.28 (67.34-83.98) |
| <58.17 (%) | 13/78 (16.7) |
| >84.22 (%) | 18/78 (23.1) |
| CD4+ T-lymphocyte, % | |
| Median (IQR) | 46.74 (36.30-54.33) |
| <25.34 (%) | 6/78 (7.7) |
| >51.37 (%) | 25/78 (32.1) |
| CD8+ T-lymphocyte, % | |
| Median (IQR) | 23.67 (17.95-31.39) |
| <14.23 (%) | 9/78 (11.5) |
| >38.95 (%) | 9/78 (11.5) |
| CD4+/CD8+ | |
| Median (IQR) | 1.79 (1.41-2.81) |
| <0.41 (%) | 2/78 (2.6) |
| >2.72 (%) | 25/78 (32.1) |
IQR, interquartile range; CD, cluster of differentiation.
Cytokine detection
A total of 77 out of the 78 patients received cytokine detection. The majority of patients displayed elevated levels of IL-6 (98.7%). The incidence rates of elevated IL-2, IL-4, IL-10 and TNF-α were 32.5, 53.2, 33.8 and 9.1%, respectively. IFN-γ levels were within the normal range (Table IX).
Table IX.
Cytokine detection.
| Parameter | Patient no. |
|---|---|
| IL-6, pg/ml | |
| Median (IQR) | 11.23 (6.16-22.78) |
| >2.9 (%) | 76/77 (98.7) |
| TNF-α, pg/ml | |
| Median (IQR) | 5.39 (3.53-11.07) |
| >23 (%) | 7/77 (9.1) |
| IL-4, pg/ml | |
| Median (IQR) | 3.34 (2.52-4.11) |
| >3.2 (%) | 41/77 (53.2) |
| IL-2, pg/ml | |
| Median (IQR) | 3.77 (3.00-4.19) |
| >4.1 (%) | 25/77 (32.5) |
| IL-10, pg/ml | |
| Median (IQR) | 4.6 (3.88-5.29) |
| >5 (%) | 26/77 (33.8) |
| IFN-γ, pg/ml | |
| Median (IQR) | 3.29 (2.56-3.69) |
| >18 (%) | 0/77 (0) |
IQR, interquartile range; IL, interleukin; TNF, tumor necrosis factors; IFN, interferon.
Levels of lactate dehydrogenase (LDH), creatine kinase (CK), creatine kinase-MB, hypersensitive troponin I (cTnI) and brain natriuretic peptide (BNP)
The levels of LDH, CK, CK-MB, cTnI and BNP in blood are presented in Table X. The results indicated that 35.9, 18.2, 1.4, 6.7 and 11.8% of patients displayed elevated levels of LDH, CK, CK-MB, cTn and BNP peptide, respectively.
Table X.
Level of LDH, CK, CK-MB, cTnI and BNP.
| Parameter | Patient no. |
|---|---|
| LDH, U/l | |
| Median (IQR) | 210 (170.25-272.5) |
| <109 (%) | 1/78 (1.3) |
| >245 (%) | 28/78 (35.9) |
| CK, U/l | |
| Median (IQR) | 65 (49.5-126) |
| <26 (%) | 1/77 (1.3) |
| >140 (%) | 14/77 (18.2) |
| CK-MB, U/l | |
| Median (IQR) | 0.6 (0.4-1.0) |
| >6.6 (%) | 1/73 (1.4) |
| cTnI, ng/l | |
| Median (IQR) | 2.7 (1.5-6.1) |
| >26.2 (%) | 5/75 (6.7) |
| BNP, µg/ml | |
| >100 (%) | 6/51 (11.8) |
IQR, interquartile range; LDH, lactic dehydrogenase; CK, creatine kinase; CK-MB, CK isoenzyme-the Muscle Brain isoenzyme; cTnI, hypersensitive troponin I; BNP, brain natriuretic peptide.
Level of triglyceride (TG) and low-density lipoprotein cholesterol (LDL-C)
Elevated levels of TG were observed in 31.5% of patients, whereas 59 (80.8%) of the 73 patients displayed reduced levels of LDL-C (Table XI).
Table XI.
Level of TG and LDL-C.
| Parameter | Patient no. |
|---|---|
| TG, mmol/l | |
| Median (IQR) | 1.28 (0.9-1.86) |
| >1.7 (%) | 23/73 (31.5) |
| LDL-c, mmol/l | |
| Median (IQR) | 2.21 (1.89-2.61) |
| <2.7 (%) | 59/73 (80.8) |
| >3.1 (%) | 7/73 (9.6) |
TG, triglyceride; IQR, interquartile range; LDL-c, low density lipoprotein cholesterol.
Discussion
In the present study, a total of 78 patients with COVID-19 were recruited. The majority of patients were elderly individuals (median age, 66.5 years), including 40 female patients and 38 male patients. Similarty to MERSCOV (8), hypertension and diabetes were the most common chronic underlying diseases, which was consistent with the results reported by Chen et al (9), and was potentially an outcome of the weaker immune functions of these patients. Common symptoms upon admission were cough, fever, fatigue, expectoration, myalgia, anepithymia and diarrhea, which were absent in four patients. Consistent with recent studies, future studies should examine asymptomatic patients who come into contact with patients with COVID-19. In the present study, the rate of acute respiratory distress syndrome (ARDS), shock and other serious complications was much lower compared with the rates in early reports (3,6). The low incidence may be associated with the fact that the majority of the cohort consisted of non-severe cases. Furthermore, cases in the previous study were from the early epidemic stage (3,6). Pathogens tend to decrease their virulence to maximize their between-host transmission (6), a phenomenon that occurred in the transmission of MERS-CoV. The global case mortality of MERS-CoV was ~40%, but was ~20% in the second generation (3).
As for the chest CT, the most common findings in the present study were extensive ground-glass opacity and bilateral patchy shadowing. All of the patients enrolled in the present study displayed CT abnormalities. However, Guan et al (6) reported that 17.9% of patients with non-severe disease and 2.9% of patients with severe disease displayed normal chest radiographic or CT upon admission. Yang et al (10) reported that 11.4% cases did not display abnormalities in the chest CT upon admission and 12 remained normal 10 days later. The aforementioned studies and the results of the present study suggested that a normal chest CT scan cannot rule out the diagnosis of COVID-19.
In terms of routine blood tests, anemia and lymphocytopenia were the most common abnormalities in the present study, which was consistent with the results of a descriptive study of 99 cases of 2019 novel coronavirus pneumonia in Wuhan (9). Guan et al (6) reported a median lymphocyte count of 1,000 per mm3 in 926 non-severe patients, but a median lymphocyte count of 800 per mm3 in severe patients. Ding et al (11) reported that lymphocytopenia was present during the admission and progression stages. Lymphocytes increase gradually during the remission stage and this may be associated with cellular immune deficiency, which suggests that the absolute value of lymphocytes correlates with the severity of new coronavirus infection, indicating that lymphocyte count may serve as a reference index in the clinical diagnosis of COVID-19 infection. Anemia in patients with COVID-19 has been rarely reported. Moreover, the underlying mechanism of action behind the development of anemia is not completely understood. As such, it was speculated that it may be associated with disease consumption.
In the present study, patients with COVID-19 displayed elevated markers of liver function injury, such as ALT and AST. Elevated ALT and AST levels have been previously reported, with an incidence of 14-53% (6,12,13). In the present study, the incidence rates of elevated ALT and AST were 17.9 and 37.2%, respectively. However, the occurrence of increased γ-GGT was the highest in all patients on admission in the present study, which may be associated with bile duct cells. A previous study reported that bile duct epithelial cells can express novel coronavirus receptor, angiotensin converting enzyme 2 (ACE2). Therefore, it was hypothesized that the compensatory proliferation of hepatic parenchymal cells derived from bile duct cells leads to upregulated overall expression of ACE2 in liver tissue, which may serve as a potential mechanism underlying COVID-19 infection-mediated liver tissue injury (14). More than a quarter of patients displayed decreased albumin and increased globulin in the present study, which were associated with disease progression and the involvement of humoral immunity. Chen et al (9) reported that severe and critically ill patients can experience a decrease in serum albumin levels to 26.3-30.9 g/l. In the present study, the albumin levels were lower, which might be due to insufficient consumption and nutrition, but could also be associated with alterations in vascular permeability leading to protein leakage into the tissue gap.
In the present study, on admission, elevated levels of cystatin C were observed in >50% of patients. To the best of our knowledge, there have been no similar reports previously. All nucleated cells can produce cystatin C, which is released constitutively to the bloodstream. Serum cystatin C is less influenced by demographic characteristics and health status compared with creatinine as a direct measurement of glomerular filtration rate (GFR) (15). Cystatin C displays stronger association than estimated GFR with cardiovascular disease, heart failure, hypertension, infection risk, frailty and mortality (15-18). The results of the present study suggested that COVID-19 may cause early renal damage, particularly by altering glomerular filtration ability.
Furthermore, >50% of patients displayed elevated levels of D-dimer, which was similar to the results reported by Chen et al (9). Dolhnikoff et al (19) observed a variable number of small fibrinous thrombi in small pulmonary arterioles in areas of damaged and more preserved lung parenchyma in 8 out of 10 cases of COVID-19. The results of the present study support the current concept of hypercoagulative status in patients with COVID-19.
In the present study, cytokine levels were measured in 77 patients with COVID-19. IL-6, IL-2, IL-4, IL-10 and TNF-α levels were demonstrated to be increased, among which increased levels of IL-6, IL-4, IL-10 and IL-2 were the most common. Cytokine storms (CSs) are defined as the excessive and uncontrolled release of proinflammatory cytokines, presenting as systemic inflammation, high inflammatory parameters and multiple organ failure. In coronavirus pneumonia, for example in SARS and MERS, massive inflammatory cell infiltration and CSs can lead to acute lung injury, and even ARDS and mortality with rapid virus replication (20-22). Huang et al (12) reported that IL-2, IL-7, IL-10, monocyte chemoattractant protein-1, macrophage inflammatory protein 1A, granulocyte colony-stimulating factor, interferon γ-induced protein 10 and TNFα levels were higher in patients with severe infection, but IL-6 levels were not significantly different in intensive care unit (ICU) and non-ICU patients. A multicentre cohort study reported significantly higher levels of IL-6 in the non-survival group of patients with COVID-19 compared with the survival group (23). A number of other studies have also reported an increase in IL-6 within patients with severe COVID-19 (9,24,25). In the present study, 76 out of the 77 patients with non-severe COVID-19 displayed elevated levels of IL-6. To date, IL-6 has been used in clinical trials as a therapeutic target for critically ill patients (tocilizumab) and has also been used as an indicator of disease severity (26,27).
In a previous study, 78 patients were analyzed for lymphocyte subsets and cytokines (28). The reduction rate of CD8+ T cells was 28.43% in the mild group and 61.9% in the severe group (28). The number of CD4+ and CD8+ T cells of deceased patients was significantly reduced, but in the state of overactivation, the proportion of highly positive CCR6+ Th17 in CD4+ T cells was increased, and the cytotoxic particles, such as perforin and granolysin, were highly expressed in CD8+ T cells (28). In the present study, increased and decreased CD8+ T cell counts were equal, and the elevated level of CD4+ T cells was more common, which may be associated with the fact that the majority of patients enrolled in the present study displayed a mild infection.
In the present study, patients with COVID-19 displayed decreased serum LDL-C levels upon admission, which was consistent with the results of a study conducted by Wei et al (29). COVID-19-mediated reductions in LDL-C biosynthesis may be associated with its damage to liver function. COVID-19 may also alter lipid metabolism by inducing acute inflammation. It has been previously reported that proinflammatory cytokines can alter liver function, and reduce cholesterol efflux and transport, thus modulating lipid metabolism (30). COVID-19 may elevate the level of free radicals, which can degrade lipids (31). Furthermore, COVID-19 may alter vascular permeability, leading to cholesterol molecules leaking into the tissue (29).
The sample size of the present study was small, which may have influenced the statistical results. Additionally, a number of patients with typical clinical symptoms or positive chest CT findings displayed negative RT-qPCR results; however, only CDC-confirmed cases were included in the present study. COVID-19 has spread rapidly worldwide. Therefore, developing drugs and vaccines against COVID-19 is of vital importance.
Acknowledgements
Not applicable.
Funding
Not applicable.
Availability of data and materials
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Authors' contributions
FC, RH and LL made substantial contributions to the conception and design of the study. FC, RH, LL, CZ, SR and HL performed the data acquisition, data analysis and interpretation. LL and CZ drafted the article or critical revision for important intellectual content. All authors read and approved the final manuscript.
Ethics approval and consent to participate
The present study was approved by the Ethics Committee of Union Hospital of Fujian Medical University (the reference number: 2020XGFKY006) and approved to exempt patients from written informed consent.
Patient consent for publication
Not applicable.
Competing interest
The authors declare that they have no competing interests.
References
- 1.Wang C, Horby PW, Hayden FG, Gao GF. A novel coronavirus outbreak of global health concern. Lancet. 2020;395:470–473. doi: 10.1016/S0140-6736(20)30185-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Jiang F, Deng L, Zhang L, Cai Y, Cheung CW, Xia Z. Review of the clinical characteristics of coronavirus disease 2019 (COVID-19) J Gen Intern Med. 2020;35:1545–1549. doi: 10.1007/s11606-020-05762-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Xu XW, Wu XX, Jiang XG, Xu KJ, Ying LJ, Ma CL, Li SB, Wang HY, Zhang S, Gao HN, et al. Clinical findings in a group of patients infected with the 2019 novel coronavirus (SARS-Cov-2) outside of Wuhan, China: Retrospective case series. BMJ. 2020;368(m606) doi: 10.1136/bmj.m606. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. World Health Organization. Coronavirus disease 2019 (COVID-19) Situation Report-51, ( https://www.who.int). [PubMed] [Google Scholar]
- 5. World Health Organization. Coronavirus disease 2019 (COVID-19) Situation Report-96, ( https://www.who.int). [PubMed] [Google Scholar]
- 6.Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, Liu L, Shan H, Lei CL, Hui DSC, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020;382:1708–1720. doi: 10.1056/NEJMoa2002032. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. General Office of National Health Committee. Notice on the issuance of a program for the diagnosis and treatment of novel coronavirus (2019-nCoV) infected pneumonia (fourth trial version to sixth trial version). http://www.nhc.gov.cn/jkj/new_index.html. [Google Scholar]
- 8.Badawi A, Ryoo SG. Prevalence of comorbidities in the Middle East respiratory syndrome coronavirus (MERS-CoV): A systematic review and meta-analysis. Int J Infect Dis. 2016;49:129–133. doi: 10.1016/j.ijid.2016.06.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, Qiu Y, Wang J, Liu Y, Wei Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: A descriptive study. Lancet. 2020;395:507–513. doi: 10.1016/S0140-6736(20)30211-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Yang W, Cao Q, Qin L, Wang X, Cheng Z, Pan A, Dai J, Sun Q, Zhao F, Qu J, Yan F. Clinical characteristics and imaging manifestations of the 2019 novel coronavirus disease (COVID-19): A multi-center study in Wenzhou city, Zhejiang, China. J Infect. 2020;80:388–393. doi: 10.1016/j.jinf.2020.02.016. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Ding Q, Lu P, Fan Y, Xia Y, Liu M. doi: 10.1002/jmv.25781. The clinical characteristics of pneumonia patients coinfected with 2019 novel coronavirus and influenza virus in Wuhan, China. J Med Virol: March 20, 2020. 10.1002/jmv.25781, 2020. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, Zhang L, Fan G, Xu J, Gu X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395:497–506. doi: 10.1016/S0140-6736(20)30183-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.The protocol for prevention, diagnosis and treatment of liver injury in coronavirus disease 2019. Zhonghua Gan Zang Bing Za Zhi. 2020;28:217–221. doi: 10.3760/cma.j.cn501113-20200309-00095. Chinese Digestion Association, Chinese Medical Doctor Association; Chinese Society of Hepatology, Chinese Medical Association. (In Chinese) [DOI] [PubMed] [Google Scholar]
- 14.Guan GW, Gao L, Wang JW, Wen XJ, Mao TH, Peng SW, Zhang T, Chen XM, Lu FM. Exploring the mechanism of liver enzyme abnormalities in patients with novel coronavirus-infected pneumonia. Zhonghua Gan Zang Bing Za Zhi. 2020;28:100–106. doi: 10.3760/cma.j.issn.1007-3418.2020.02.002. (In Chinese) [DOI] [PubMed] [Google Scholar]
- 15.Shlipak MG, Mattes MD, Peralta CA. Update on cystatin C: Incorporation into clinical practice. Am J Kidney Dis. 2013;62:595–603. doi: 10.1053/j.ajkd.2013.03.027. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Menon V, Shlipak MG, Wang X, Coresh J, Greene T, Stevens L, Kusek JW, Beck GJ, Collins AJ, Levey AS, Sarnak MJ. Cystatin C as a risk factor for outcomes in chronic kidney disease. Ann Intern Med. 2007;147:19–27. doi: 10.7326/0003-4819-147-1-200707030-00004. [DOI] [PubMed] [Google Scholar]
- 17.Sarnak MJ, Katz R, Stehman-Breen CO, Fried LF, Jenny NS, Psaty BM, Newman AB, Siscovick D, Shlipak MG. Cystatin C concentration as a risk factor for heart failure in older adults. Ann Intern Med. 2005;142:497–505. doi: 10.7326/0003-4819-142-7-200504050-00008. Cardiovascular Health Study. [DOI] [PubMed] [Google Scholar]
- 18.Shlipak MG, Sarnak MJ, Katz R, Fried LF, Seliger SL, Newman AB, Siscovick DS, Stehman-Breen C. Cystatin C and the risk of death and cardiovascular events among elderly persons. N Engl J Med. 2005;352:2049–2060. doi: 10.1056/NEJMoa043161. [DOI] [PubMed] [Google Scholar]
- 19.Dolhnikoff M, Duarte-Neto AN, de Almeida Monteiro RA, da Silva LFF, de Oliveira EP, Saldiva PHN, Mauad T, Negri EM. Pathological evidence of pulmonary thrombotic phenomena in severe COVID-19. J Thromb Haemost. 2020;18:1517–1519. doi: 10.1111/jth.14844. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Zhang W, Zhao Y, Zhang F, Wang Q, Li T, Liu Z, Wang J, Qin Y, Zhang X, Yan X, et al. The use of anti-inflammatory drugs in the treatment of people with severe coronavirus disease 2019 (COVID-19): The Perspectives of clinical immunologists from China. Clin Immunol. 2020;214(108393) doi: 10.1016/j.clim.2020.108393. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Channappanavar R, Perlman S. Pathogenic human coronavirus infections: Causes and consequences of cytokine storm and immunopathology. Semin Immunopathol. 2017;39:529–539. doi: 10.1007/s00281-017-0629-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Chousterman BG, Swirski FK, Weber GF. Cytokine storm and sepsis disease pathogenesis. Semin Immunopathol. 2017;39:517–528. doi: 10.1007/s00281-017-0639-8. [DOI] [PubMed] [Google Scholar]
- 23.Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, Xiang J, Wang Y, Song B, Gu X, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort study. Lancet. 2020;395:1054–1062. doi: 10.1016/S0140-6736(20)30566-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Ruan Q, Yang K, Wang W, Jiang L, Song J. Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China. Intensive Care Med. 2020;46:846–848. doi: 10.1007/s00134-020-05991-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Wu C, Chen X, Cai Y, Xia J, Zhou X, Xu S, Huang H, Zhang L, Zhou X, Du C, et al. Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA Intern Med. 2020;180:934–943. doi: 10.1001/jamainternmed.2020.0994. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Radbel J, Narayanan N, Bhatt PJ. Use of tocilizumab for COVID-19-induced cytokine release syndrome: A cautionary case report. Chest. 2020;158:e15–e19. doi: 10.1016/j.chest.2020.04.024. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Zhang S, Li L, Shen A, Chen Y, Qi Z. Rational use of tocilizumab in the treatment of novel coronavirus pneumonia. Clin Drug Investig. 2020;40:511–518. doi: 10.1007/s40261-020-00917-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Xu Z, Shi L, Wang Y, Zhang J, Huang L, Zhang C, Liu S, Zhao P, Liu H, Zhu L, et al. Pathological findings of COVID-19 associated with acute respiratory distress syndrome. Lancet Respir Med. 2020;8:420–422. doi: 10.1016/S2213-2600(20)30076-X. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Wei X, Zeng W, Su J, Wan H, Yu X, Cao X, Tan W, Wang H. Hypolipidemia is associated with the severity of COVID-19. J Clin Lipidol. 2020;14:297–304. doi: 10.1016/j.jacl.2020.04.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Funderburg NT, Mehta NN. Lipid abnormalities and inflammation in HIV inflection. Curr HIV/AIDS Rep. 2016;13:218–225. doi: 10.1007/s11904-016-0321-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Zidar DA, Juchnowski S, Ferrari B, Clagett B, Pilch-Cooper HA, Rose S, Rodriguez B, McComsey GA, Sieg SF, Mehta NN, et al. Oxidized LDL levels are increased in HIV infection and may drive monocyte activation. J Acquir Immune Defic Syndr. 2015;69:154–160. doi: 10.1097/QAI.0000000000000566. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.