Please wait a minute...
Frontiers of Medicine

ISSN 2095-0217

ISSN 2095-0225(Online)

CN 11-5983/R

Postal Subscription Code 80-967

2018 Impact Factor: 1.847

Front. Med.    2022, Vol. 16 Issue (1) : 111-125    https://doi.org/10.1007/s11684-021-0854-5
RESEARCH ARTICLE
Clinical characteristics and risk factors of COVID-19 patients with chronic hepatitis B: a multi-center retrospective cohort study
Jing Wang1, Zequn Lu2, Meng Jin3, Ying Wang4, Kunming Tian5,6, Jun Xiao1, Yimin Cai2, Yanan Wang1, Xu Zhang7, Tao Chen8, Zhi Yao9, Chunguang Yang1, Renli Deng10, Qiang Zhong11, Xiongbo Deng12, Xin Chen13, Xiang-ping Yang14, Gonghong Wei15, Zhihua Wang1(), Jianbo Tian2(), Xiao-ping Chen16()
1. Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
2. Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
3. Department of Respiratory and Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan 430060, China
4. Department of Virology, Wuhan Centers for Disease Prevention and Control, Wuhan 430024, China
5. Institute of Reproductive Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
6. School of Nursing, Zunyi Medical University, Zunyi 563099, China
7. Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
8. Department and Institute of Infectious Disease, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
9. Department of Respirology and Tuberculosis Specialty, Wuhan Pulmonary Hospital, Wuhan 430030, China
10. The Fifth Affiliated (Zhuhai) Hospital of Zunyi Medical University, Zhuhai 519199, China
11. Department of Critical Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
12. Department of Radiology, Wuhan Jinyintan Hospital, Wuhan 430048, China
13. Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
14. Department of Immunology, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
15. Biocenter Oulu, Faculty of Biochemistry and Molecular Medicine, University of Oulu, Oulu 90014, Finland
16. Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
 Download: PDF(792 KB)   HTML
 Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract

The coronavirus disease 2019 (COVID-19) has spread globally. Although mixed liver impairment has been reported in COVID-19 patients, the association of liver injury caused by specific subtype especially chronic hepatitis B (CHB) with COVID-19 has not been elucidated. In this multi-center, retrospective, and observational cohort study, 109 CHB and 327 non-CHB patients with COVID-19 were propensity score matched at an approximate ratio of 3:1 on the basis of age, sex, and comorbidities. Demographic characteristics, laboratory examinations, disease severity, and clinical outcomes were compared. Furthermore, univariable and multivariable logistic and Cox regression models were used to explore the risk factors for disease severity and mortality, respectively. A higher proportion of CHB patients (30 of 109 (27.52%)) developed into severe status than non-CHB patients (17 of 327 (5.20%)). In addition to previously reported liver impairment markers, such as alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, and total bilirubin, we identified several novel risk factors including elevated lactate dehydrogenase (≥245 U/L, hazard ratio (HR) = 8.639, 95% confidence interval (CI) = 2.528–29.523; P <0.001) and coagulation-related biomarker D-dimer (≥0.5 μg/mL, HR= 4.321, 95% CI= 1.443–12.939; P = 0.009) and decreased albumin (<35 g/L, HR= 0.131, 95% CI= 0.048–0.361; P <0.001) and albumin/globulin ratio (<1.5, HR= 0.123, 95% CI= 0.017–0.918; P = 0.041). In conclusion, COVID-19 patients with CHB were more likely to develop into severe illness and die. The risk factors that we identified may be helpful for early clinical surveillance of critical progression.

Keywords COVID-19      chronic hepatitis B      liver injury      coagulation dysfunction     
Corresponding Author(s): Zhihua Wang,Jianbo Tian,Xiao-ping Chen   
About author:

Tongcan Cui and Yizhe Hou contributed equally to this work.

Just Accepted Date: 12 July 2021   Online First Date: 13 August 2021    Issue Date: 28 March 2022
 Cite this article:   
Jing Wang,Zequn Lu,Meng Jin, et al. Clinical characteristics and risk factors of COVID-19 patients with chronic hepatitis B: a multi-center retrospective cohort study[J]. Front. Med., 2022, 16(1): 111-125.
 URL:  
https://academic.hep.com.cn/fmd/EN/10.1007/s11684-021-0854-5
https://academic.hep.com.cn/fmd/EN/Y2022/V16/I1/111
Fig.1  Flowchart of this study. This multi-center, retrospective, and observational study was conducted at three hospitals designated for COVID-19 treatment. From January 13 to April 15, 2020, 7013 laboratory-confirmed COVID-19 patients were admitted at these hospitals. Among them, all CHB patients (N = 109) were ultimately enrolled, and 327 non-CHB patients that were statistically matched by propensity score at an approximate ratio of 3:1 on the basis of age, sex, and comorbidities were recruited. To explore the potential risk factors associated with COVID-19 severity in CHB patients, we classified these patients into non-severe (n = 79) and severe groups (n = 30) at admission according to the guidance of the WHO for COVID-19 and the Seventh Revised Trial Version of the COVID-19 Diagnosis and Treatment Guidance (2020) of China.
Variables Total CHB Non-CHB P value
N = 436 N = 109 N = 327
Characteristics N = 436 N = 109 N = 327
Age, year, M (IQR) 57.00 (43.00–66.00) N = 109 55.00 (44.00–64.50) N = 327 57.00 (43.00–66.00) 0.669
Sex, n (%) 0.144
Male 258 (59.17) 71 (65.14) 187 (57.19)
Female 178 (40.83) 38 (34.86) 140 (42.81)
Comorbidities, n (%) N = 436 N = 109 N = 327
Hypertension 89 (20.41) 19 (17.43) 70 (21.41) 0.373
Diabetes 56 (12.84) 13 (11.93) 43 (13.15) 0.741
Coronary heart disease 30 (6.88) 7 (6.42) 23 (7.03) 0.827
Cerebral infarction 10 (2.29) 4 (3.67) 6 (1.83) 0.276a
Pulmonary tuberculosis 6 (1.38) 1 (0.92) 5 (1.53) 1.000a
Laboratory examinations
Blood routine, M (IQR)
Leukocytes, # (N = 434), × 109/L 5.46 (4.28–7.22) N = 107 6.15 (4.75–8.63) N = 327 5.24 (4.23–6.67) <0.001*
Erythrocytes, # (N = 434), × 1012/L 4.10 (3.71–4.50) N = 107 4.10 (3.62–4.55) N = 327 4.10 (3.71–4.48) 0.768
Monocytes, # (N = 429), × 109/L 0.47 (0.36–0.62) N = 102 0.48 (0.35–0.70) N = 327 0.47 (0.36–0.62) 0.423
Neutrophils, # (N = 434), × 109/L 3.40 (2.41–4.81) N = 107 4.26 (2.92–7.98) N = 327 3.25 (2.31–4.24) <0.001*
Eosinophils, # (N = 429), × 109/L 0.06 (0.02–0.13) N = 102 0.08 (0.02–0.21) N = 327 0.06 (0.01–0.11) 0.003*
Basophils, # (N = 429), × 109/L 0.01 (0.01–0.03) N = 102 0.02 (0.01–0.03) N = 327 0.01 (0.01–0.03) 0.087
Immune cell subsets, M (IQR)
Lymphocytes, # (N = 436), × 109/L 1.35 (0.97–1.81) N = 109 1.24 (0.80–1.56) N = 327 1.42 (1.00–1.84) <0.001*
CD3+CD19- T cells, # (N = 112), /μL 846.67 (617.07–1279.75) N = 35 552.80 (309.48–718.07) N = 77 1112.00 (781.50–1352.00) <0.001*
CD4+ T cells, # (N = 112), /μL 483.00 (350.03–806.50) N = 35 481.00 (236.00–644.87) N = 77 564.00 (353.97–946.00) 0.001*
CD8+ T cells, # (N = 112), /μL 352.50 (231.75–471.25) N = 35 345.00 (135.29–492.90) N = 77 353.00 (258.00–456.00) 0.366
CD3-CD19+ B cells, # (N = 97), /μL 181.00 (124.00–284.50) N = 20 129.50 (83.75–173.25) N = 77 207.00 (127.00–301.00) 0.001*
CD3-CD16+CD56+ NK cells, # (N = 97), /μL 174.00 (115.00–274.00) N = 20 150.50 (90.25–221.75) N = 77 181.00 (122.00–276.00) 0.256
T cells+ B cells+ NK cells, # (N = 97), /μL 1386.00 (936.50–1902.00) N = 20 792.04 (652.17–1103.02) N = 77 1580.00 (1161.50–1958.00) <0.001*
Inflammatory cytokines and biomarkers, M (IQR)
IL-6 (N = 352), pg/mL 3.59 (1.50–11.36) N = 69 9.92 (2.83–25.60) N = 283 3.08 (1.50–7.93) <0.001*
IL-10 (N = 337), pg/mL 5.20 (5.00–7.50) N = 58 5.00 (5.00–6.88) N = 279 5.30 (5.00–7.50) 0.373
IL-8 (N = 337), pg/mL 12.40 (6.50–24.10) N = 58 12.80 (7.15–25.68) N = 279 12.20 (6.40–23.90) 0.292
TNF-α (N = 342), pg/mL 7.30 (5.30–9.33) N = 58 9.15 (7.30–13.08) N = 284 7.00 (5.03–8.98) <0.001*
IL-1β (N = 337), pg/mL 5.00 (5.00–5.00) N = 58 5.00 (5.00–5.53) N = 279 5.00 (5.00–5.00) 0.075
IL-2R (N = 334), U/mL 497.00 (351.00–673.25) N = 58 509.00 (334.50–776.50) N = 276 495.50 (354.25–657.50) 0.401
Ferritin (N = 225), μg/L 368.90 (181.00–609.70) N = 44 470.05 (173.05–1162.50) N = 181 349.80 (183.10–582.50) 0.051
hs-CRP (N = 416), mg/L 4.50 (1.10–29.88) N = 94 19.25 (2.18–62.73) N = 322 3.70 (1.00–15.10) <0.001*
Organ damage indexes, M (IQR)
ALT (N = 435), U/L 19.00 (14.00–30.00) N = 108 31.00 (19.00–72.25) N = 327 18.00 (13.00–25.00) <0.001*
AST (N = 435), U/L 22.00 (18.00–33.00) N = 108 35.50 (21.25–64.25) N = 327 21.00 (17.00–28.00) <0.001*
TBIL (N = 435), μmol/L 8.70 (6.50–12.10) N = 108 10.25 (7.65–15.63) N = 327 8.20 (6.30–11.30) <0.001*
DBIL (N = 431), μmol/L 3.40 (2.60–4.40) N = 104 3.60 (2.90–5.93) N = 327 3.30 (2.60–4.30) 0.003*
ALB (N = 433), g/L 38.50 (34.95–41.75) N = 106 33.95 (29.28–38.55) N = 327 39.40 (36.70–42.20) <0.001*
GLO (N = 433), g/L 29.10 (25.70–31.60) N = 106 27.55 (24.68–30.33) N = 327 29.40 (26.10–31.90) 0.002*
TP (N = 433), g/L 67.80 (63.50–71.70) N = 106 61.55 (55.88–65.63) N = 327 69.30 (65.90–72.70) <0.001*
ALB/GLO (N = 433) 1.33 (1.15–1.57) N = 106 1.23 (1.03–1.50) N = 327 1.35 (1.19–1.57) <0.001*
LDH (N = 400), U/L 217.00 (180.00–265.50) N = 105 238.00 (175.00–319.00) N = 295 211.00 (180.00–251.00) 0.019*
ALP (N = 400), U/L 64.00 (48.00–87.00) N = 104 68.00 (53.25–88.50) N = 296 62.50 (46.00–84.75) 0.049*
CK-MB (N = 303), U/L 0.70 (0.40–1.20) N = 72 1.10 (0.58–9.15) N = 231 0.70 (0.40–1.00) <0.001*
PT (N = 432), s 13.60 (13.10–14.20) N = 105 14.40 (13.55–16.50) N = 327 13.50 (13.00–14.00) <0.001*
APTT (N = 428), s 37.90 (35.60–40.30) N = 101 38.10 (34.70–41.40) N = 327 37.90 (35.70–40.00) 0.512
D-dimer (N = 431), μg/mL 0.42 (0.24–0.90) N = 104 0.95 (0.32–2.64) N = 327 0.36 (0.23–0.62) <0.001*
Complication, n (%) N = 436 N = 109 N = 327 0.026*,a
DIC 8 (1.83) 5 (4.59) 3 (0.92)
Non-DIC 428 (98.17) 104 (95.41) 324 (99.08)
Severity, n (%) N = 436 N = 109 N = 327 <0.001*
Severe 72 (16.51) 30 (27.52) 42 (12.84)
Non-severe 364 (83.49) 79 (72.48) 285 (87.16)
Outcomes, n (%) N = 436 N = 109 N = 327 <0.001*
Survivor 415 (95.18) 96 (88.07) 319 (97.55)
Non-survivor 21 (4.82) 13 (11.93) 8 (2.45)
Tab.1  Demographic, clinical, radiographic, and laboratory findings of COVID-19 patients with and without CHB
Variables Total Severe Non-severe P value
N = 109 N = 30 N = 79
Characteristics N = 109 N = 30 N = 79
Age, year, M (IQR) 55.00 (44.00–64.50) N = 30 58.50 (49.25–62.75) N = 79 54.00 (42.00–65.00) 0.461
Sex, n (%) 0.269
Male 71 (65.14) 22 (73.33) 49 (62.03)
Female 38 (34.86) 8 (26.67) 30 (37.97)
Comorbidities, n (%) N = 109 N = 30 N = 79
Hypertension 19 (17.43) 5 (16.67) 14 (17.72) 0.897
Diabetes 13 (11.93) 7 (23.33) 6 (7.59) 0.042*, a
Coronary heart disease 7 (6.42) 3 (10.00) 4 (5.06) 0.391a
Cerebral infarction 4 (3.67) 1 (3.33) 3 (3.80) 1.000a
Pulmonary tuberculosis 1 (0.92) 1 (3.33) 0 (0.00) 0.275a
Laboratory examinations
Blood routine, M (IQR)
Leukocytes, # (N = 107), × 109/L 6.15 (4.75–8.63) N = 28 7.48 (5.09–8.97) N = 79 6.09 (4.72–8.46) 0.436
Erythrocytes, # (N = 107), × 1012/L 4.10 (3.62–4.55) N = 28 4.02 (2.74–4.31) N = 79 4.15 (3.80–4.55) 0.085
Monocytes, # (N = 102), × 109/L 0.48 (0.35–0.70) N = 25 0.58 (0.40–0.71) N = 77 0.46 (0.35–0.63) 0.581
Neutrophils, # (N = 107), × 109/L 4.26 (2.92–7.98) N = 28 6.18 (4.08–11.37) N = 79 4.01 (2.66–6.67) 0.001*
Eosinophils, # (N = 102), × 109/L 0.08 (0.02–0.21) N = 25 0.07 (0.00–0.24) N = 77 0.09 (0.03–0.18) 0.183
Basophils, # (N = 102), × 109/L 0.02 (0.01–0.03) N = 25 0.02 (0.01–0.04) N = 77 0.02 (0.01–0.03) 0.235
Immune cell subsets, M (IQR)
Lymphocytes, # (N = 109), × 109/L 1.24 (0.80–1.56) N = 30 1.02 (0.55–1.33) N = 79 1.28 (0.90–1.65) 0.006*
CD3+CD19- T cells, # (N = 35), /μL 552.80 (309.48–718.07) N = 10 340.25 (165.13–467.28) N = 25 582.45 (361.59–799.46) 0.014*
CD4+ T cells, # (N = 35), /μL 481.00 (236.00–644.87) N = 10 271.11 (124.73–411.50) N = 25 508.00 (291.38–721.17) 0.024*
CD8+ T cells, # (N = 35), /μL 345.00 (135.29–492.90) N = 10 295.08 (130.25–564.75) N = 25 345.00 (175.08–454.00) 0.927
CD3-CD19+ B cells, # (N = 20), /μL 129.50 (83.75–173.25) N = 8 91.50 (60.00–124.50) N = 12 161.50 (131.00–177.25) 0.012*
CD3-CD16+CD56+ NK cells, # (N = 20), /μL 150.50 (90.25–221.75) N = 8 142.00 (73.75–234.75) N = 12 158.00 (129.50–219.50) 0.440
T cells+ B cells+ NK cells, # (N = 20), /μL 792.04 (652.17–1103.02) N = 8 677.08 (358.04–797.06) N = 12 1000.33 (773.49–1145.04) 0.021*
Inflammatory cytokines and biomarkers, M (IQR)
IL-6 (N = 69), pg/mL 9.92 (2.83–25.60) N = 21 32.00 (10.92–119.47) N = 48 6.69 (2.44–14.92) <0.001*
IL-10 (N = 58), pg/mL 5.00 (5.00–6.58) N = 15 5.00 (5.00–10.00) N = 43 5.00 (5.00–6.25) 0.776
IL-8 (N = 58), pg/mL 12.80 (7.15–25.68) N = 15 13.10 (8.10–45.00) N = 43 12.40 (6.70–21.80) 0.248
TNF-α (N = 58), pg/mL 9.15 (7.30–13.08) N = 15 13.00 (9.40–17.90) N = 43 8.70 (6.40–11.30) 0.001*
IL-1β (N = 58), pg/mL 5.00 (5.00–5.53) N = 15 5.00 (5.00–5.00) N = 43 5.00 (5.00–6.30) 0.074
IL-2R (N = 58), U/mL 509.00 (334.50–776.50) N = 15 696.00 (404.50–1042.50) N = 43 502.00 (315.50–697.50) 0.153
Ferritin (N = 44), μg/L 470.05 (173.05–1162.50) N = 13 511.78 (235.10–1787.00) N = 31 417.60 (156.00–949.25) 0.286
hs-CRP (N = 94), mg/L 19.25 (2.18–62.73) N = 25 30.90 (14.25–93.85) N = 69 13.34 (1.40–47.43) 0.015*
Organ damage indexes, M (IQR)
ALT (N = 108), U/L 31.00 (19.00–72.25) N = 30 71.50 (25.50–177.25) N = 78 27.50 (17.00–52.25) 0.001*
AST (N = 108), U/L 35.50 (21.25–64.25) N = 30 52.50 (30.50–121.00) N = 78 27.50 (20.00–47.25) 0.003*
TBIL (N = 108), μmol/L 10.25 (7.65–15.63) N = 30 18.50 (10.80–33.60) N = 78 9.10 (6.60–12.05) <0.001*
DBIL (N = 104), μmol/L 3.60 (2.90–5.93) N = 26 5.65 (3.23–13.63) N = 78 3.49 (2.70–4.50) 0.008*
ALB (N = 106), g/L 33.95 (29.28–38.55) N = 28 28.20 (22.95–33.33) N = 78 35.30 (30.88–39.63) <0.001*
GLO (N = 106), g/L 27.55 (24.68–30.33) N = 28 25.70 (22.45–29.28) N = 78 27.85 (25.45–30.68) 0.013*
TP (N = 106), g/L 61.55 (55.88–65.63) N = 28 58.00 (50.40–61.35) N = 78 63.20 (58.20–66.60) <0.001*
ALB/GLO (N = 106) 1.23 (1.03–1.50) N = 28 1.12 (0.90–1.23) N = 78 1.30 (1.08–1.60) 0.001*
LDH (N = 105), U/L 238.00 (175.00–319.00) N = 28 282.00 (186.75–427.50) N = 77 224.00 (175.00–286.00) 0.025*
ALP (N = 104), U/L 68.00 (53.25–88.50) N = 26 76.50 (65.75–116.75) N = 78 64.00 (49.75–84.00) 0.012*
CK-MB (N = 72), U/L 1.10 (0.58–9.15) N = 18 1.50 (0.50–11.78) N = 54 0.95 (0.60–7.30) 0.658
PT (N = 105), s 14.40 (13.55–16.50) N = 28 16.65 (15.65–17.95) N = 77 14.10 (13.50–14.80) <0.001*
APTT (N = 101), s 38.10 (34.70–41.40) N = 26 41.15 (35.20–59.08) N = 75 37.30 (34.75–40.15) 0.017*
D-dimer (N = 104), μg/mL 0.95 (0.32–2.64) N = 28 2.02 (1.02–11.46) N = 76 0.60 (0.22–2.13) <0.001*
Complication, n (%) N = 109 N = 30 N = 79 0.020*, a
DIC 5 (4.59) 4 (13.33) 1 (1.27)
Non-DIC 104 (95.41) 26 (86.67) 78 (98.73)
Hepatitis B virus serological markers, n (%) N = 109 N = 30 N = 79 0.020*,a
HBsAg+ 102 (93.58) 28 (93.33) 74 (93.67) 1.000 a
HBsAb+ 8 (7.34) 1 (3.33) 7 (8.86) 0.441 a
HBeAg+ 11 (10.09) 11 (36.67) 0 <0.001*
HBeAb+ 92 (84.40) 18 (60.00) 74 (93.67) <0.001*
HBcAb+ 106 (97.25) 29 (96.67) 77 (97.47) 0.819
HBV DNA, # (N = 84), × 105/L 2.35 (0.73–5.68) N = 23 2.70 (0.94–4.40) N = 61 1.90 (0.69–6.40) 0.964
Anti-hepatitis therapies, n (%) N = 109 N = 30 N = 79
Past anti-HBV therapyb 74 (67.89) 22 (73.33) 52 (65.82) 0.453
Liver protective therapyc 86 (78.90) 27 (90.00) 59 (74.68) 0.080
Outcomes, n (%) N = 109 N = 30 N = 79 0.042*,a
Survivor 96 (88.07) 23 (76.67) 73 (92.41)
Non-survivor 13 (11.93) 7 (23.33) 6 (7.59)
Tab.2  Demographic, clinical, radiographic, and laboratory findings of severe and non-severe COVID-19 patients with CHB
Variables All patients
Total CHB Non-CHB P value
N = 436 N = 109 N = 327
Treatmentsb, n (%)
?Antiviral therapy 194 (44.50) 49 (44.95) 145 (44.34) 0.911
?Antibiotics 287 (65.83) 74 (67.89) 213 (65.14) 0.600
?Intravenous immunoglobulin therapy 129 (29.59) 51 (46.79) 78 (23.85) <0.001*
Glucocorticoid therapy 128 (29.36) 42 (38.53) 86 (26.30) 0.015*
High-flow oxygen therapy 19 (4.36) 6 (5.50) 13 (3.98) 0.587
Mechanical ventilation 51 (11.70) 25 (22.49) 26 (7.95) <0.001*
?Non-invasive 26 (5.96) 7 (6.42) 19 (5.81) 0.815
?Invasive 11 (2.52) 4 (3.67) 7 (2.14) 0.479a
?Transfusion 22 (5.05) 7 (6.42) 15 (4.59) 0.448
Variables CHB patients
Total Severe Non-severe P value
N = 109 N = 30 N = 79
Treatmentsb, n (%)
?Antiviral therapy 49 (44.95) 16 (53.33) 33 (41.77) 0.278
?Antibiotics 74 (67.89) 22 (73.33) 52 (65.82) 0.453
?Intravenous immunoglobulin therapy 51 (46.79) 20 (66.67) 31 (39.24) 0.010*, a
Glucocorticoid therapy 42 (38.53) 14 (46.67) 28 (35.44) 0.282
High-flow oxygen therapy 6 (5.50) 1 (3.33) 5 (6.33) 1.000a
Mechanical ventilation 25 (22.94) 9 (30.00) 16 (20.25) 0.280
?Non-invasive 7 (6.42) 6 (20.00) 1 (1.27) 0.002*, a
?Invasive 4 (3.67) 3 (10.00) 1 (1.27) 0.063a
?Transfusion 7 (6.42) 2 (6.67) 5 (6.33) 1.000a
Tab.3  Clinical treatments and complications of COVID-19 patients
Variables Univariable logistic regression Multivariable logistic regression
OR (95% CI) P value OR (95% CI) P valuea
Laboratory examinations
?Blood routine
??Neutrophils, # (N = 107), × 109/L 1.243 (1.095–1.412) 0.001* 1.236 (1.078–1.418) 0.002*
?Immune cell subsets
??Lymphocytes, # (N = 109), × 109/L 0.274 (0.110–0.683) 0.005* 0.274 (0.100–0.749) 0.012*
??CD3+CD19 T cells, # (N = 15), /μL 0.995 (0.991–0.999) 0.022* 0.995 (0.990–1.000) 0.031*
??CD4+ T cells, # (N = 35), /μL 0.996 (0.992–1.000) 0.029* 0.995 (0.991–1.000) 0.038*
?Inflammatory cytokines and biomarkers
??IL-6 (N = 69), pg/mL 1.032 (1.005–1.060) 0.021* 1.032 (1.007–1.058) 0.013*
??TNF-α (N = 58), pg/mL 1.211 (1.046–1.402) 0.010* 1.184 (1.007–1.393) 0.040*
??hs-CRP (N = 94), mg/L 1.013 (1.003–1.023) 0.013* 1.014 (1.002–1.025) 0.018*
?Organ damage indexes
??ALT (N = 108), U/L 1.011 (1.003–1.019) 0.005* 1.012 (1.004–1.020) 0.003*
??AST (N = 108), U/L 1.006 (1.000–1.012) 0.040* 1.007 (1.001–1.013) 0.027*
??ALP (N = 104), U/L 1.008 (1.000–1.017) 0.044* 1.009 (1.001–1.017) 0.030*
??TBIL (N = 108), μmol/L 1.056 (1.022–1.092) 0.001* 1.054 (1.018–1.091) 0.003*
??ALB (N = 106), g/L 0.807 (0.732–0.890) <0.001* 0.803 (0.723–0.891) <0.001*
??ALB/GLO (N = 106) 0.073 (0.014–0.386) 0.002* 0.062 (0.010–0.385) 0.003*
??LDH (N = 105), U/L 1.003 (1.000–1.006) 0.023* 1.004 (1.001–1.007) 0.021*
??Amylase (N = 44), U/L 0.983 (0.964–1.003) 0.089 0.968 (0.937–1.000) 0.048*
??hs-cTnI (N = 79), pg/mL 1.001 (1.000–1.001) 0.029* 1.001 (1.000–1.001) 0.040*
??APTT (N = 101), s 1.098 (1.034–1.165) 0.002* 1.115 (1.042–1.192) 0.002*
??D-dimer (N = 104), μg/mL 1.097 (1.021–1.178) 0.011* 1.100 (1.022–1.185) 0.012*
Tab.4  Factors associated with the illness severity of COVID-19 patients with CHB
Fig.2  Survival of COVID-19 patients during hospitalization. (A) Survival curve of COVID-19 patients with and without CHB. (B–I) Survival curves of COVID-19 patients with different levels of liver test parameters, such as ALT (B), AST (C), ALP (D), TBIL (E), and LDH (F); D-dimer coagulation index (G); ALB (H); and ALB/GLO (I). The survival curves were compared and analyzed, and the hazard ratios (HRs) and 95% confidence intervals (CIs) were analyzed by the Cox proportional hazards regression models. P<0.05 was considered statistically significant.
1 World Health Organization. Rolling updates on coronavirus disease (COVID-19). 2020
2 J Tian, X Yuan, J Xiao, Q Zhong, C Yang, B Liu, Y Cai, Z Lu, J Wang, Y Wang, S Liu, B Cheng, J Wang, M Zhang, L Wang, S Niu, Z Yao, X Deng, F Zhou, W Wei, Q Li, X Chen, W Chen, Q Yang, S Wu, J Fan, B Shu, Z Hu, S Wang, XP Yang, W Liu, X Miao, Z Wang. Clinical characteristics and risk factors associated with COVID-19 disease severity in patients with cancer in Wuhan, China: a multicentre, retrospective, cohort study. Lancet Oncol 2020; 21(7): 893–903
https://doi.org/10.1016/S1470-2045(20)30309-0 pmid: 32479790
3 Epidemiology Working Group for NCIP Epidemic Response, Chinese Center for Disease Control and Prevention. The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) in China. Chin J Epidemiol (Zhonghua Liu Xing Bing Xue Za Zhi) 2020; 41(2): 145–151 (in Chinese)
https://doi.org/10.3760/cma.j.issn.0254-6450.2020.02.003 pmid: 32064853
4 F Zhou, T Yu, R Du, G Fan, Y Liu, Z Liu, J Xiang, Y Wang, B Song, X Gu, L Guan, Y Wei, H Li, X Wu, J Xu, S Tu, Y Zhang, H Chen, B Cao. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020; 395(10229): 1054–1062
https://doi.org/10.1016/S0140-6736(20)30566-3 pmid: 32171076
5 GBD 2017 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018; 392(10159): 1789–1858
https://doi.org/10.1016/S0140-6736(18)32279-7 pmid: 30496104
6 Q Cai, D Huang, H Yu, Z Zhu, Z Xia, Y Su, Z Li, G Zhou, J Gou, J Qu, Y Sun, Y Liu, Q He, J Chen, L Liu, L Xu. COVID-19: abnormal liver function tests. J Hepatol 2020; 73(3): 566–574
https://doi.org/10.1016/j.jhep.2020.04.006 pmid: 32298767
7 OK Fix, B Hameed, RJ Fontana, RM Kwok, BM McGuire, DC Mulligan, DS Pratt, MW Russo, ML Schilsky, EC Verna, R Loomba, DE Cohen, JA Bezerra, KR Reddy, RT Chung. Clinical best practice advice for hepatology and liver transplant providers during the COVID-19 pandemic: AASLD expert panel consensus statement. Hepatology 2020; 72(1): 287–304
https://doi.org/10.1002/hep.31281 pmid: 32298473
8 Z Xu, L Shi, Y Wang, J Zhang, L Huang, C Zhang, S Liu, P Zhao, H Liu, L Zhu, Y Tai, C Bai, T Gao, J Song, P Xia, J Dong, J Zhao, FS Wang. Pathological findings of COVID-19 associated with acute respiratory distress syndrome. Lancet Respir Med 2020; 8(4): 420–422
https://doi.org/10.1016/S2213-2600(20)30076-X pmid: 32085846
9 J Veselka, L Faber, M Liebregts, R Cooper, J Januska, M Kashtanov, M Dabrowski, PR Hansen, H Seggewiss, E Hansvenclova, H Bundgaard, J Ten Berg, RH Stables, MK Jensen. Short- and long-term outcomes of alcohol septal ablation for hypertrophic obstructive cardiomyopathy in patients with mild left ventricular hypertrophy: a propensity score matching analysis. Eur Heart J 2019; 40(21): 1681–1687
https://doi.org/10.1093/eurheartj/ehz110 pmid: 31152553
10 SK Sarin, M Kumar, GK Lau, Z Abbas, HL Chan, CJ Chen, DS Chen, HL Chen, PJ Chen, RN Chien, AK Dokmeci, E Gane, JL Hou, W Jafri, J Jia, JH Kim, CL Lai, HC Lee, SG Lim, CJ Liu, S Locarnini, M Al Mahtab, R Mohamed, M Omata, J Park, T Piratvisuth, BC Sharma, J Sollano, FS Wang, L Wei, MF Yuen, SS Zheng, JH Kao. Asian-Pacific clinical practice guidelines on the management of hepatitis B: a 2015 update. Hepatol Int 2016; 10(1): 1–98
https://doi.org/10.1007/s12072-015-9675-4 pmid: 26563120
11 World Health Organization. Clinical management of severe acute respiratory infection when Novel coronavirus (nCoV) infection is suspected: interim guidance. 2020
12 National Health Commission of the People’s Republic of China. Chinese management guideline for COVID-19 (version 7.0, in Chinese). Updated: March 3, 2020. 2020
13 M Levi, CH Toh, J Thachil, HG Watson. Guidelines for the diagnosis and management of disseminated intravascular coagulation. British Committee for Standards in Haematology. Br J Haematol 2009; 145(1): 24–33
https://doi.org/10.1111/j.1365-2141.2009.07600.x pmid: 19222477
14 G Chen, D Wu, W Guo, Y Cao, D Huang, H Wang, T Wang, X Zhang, H Chen, H Yu, X Zhang, M Zhang, S Wu, J Song, T Chen, M Han, S Li, X Luo, J Zhao, Q Ning. Clinical and immunological features of severe and moderate coronavirus disease 2019. J Clin Invest 2020; 130(5): 2620–2629
https://doi.org/10.1172/JCI137244 pmid: 32217835
15 Y Bai, L Yao, T Wei, F Tian, DY Jin, L Chen, M Wang. Presumed asymptomatic carrier transmission of COVID-19. JAMA 2020; 323(14): 1406–1407
https://doi.org/10.1001/jama.2020.2565 pmid: 32083643
16 F Lei, YM Liu, F Zhou, JJ Qin, P Zhang, L Zhu, XJ Zhang, J Cai, L Lin, S Ouyang, X Wang, C Yang, X Cheng, W Liu, H Li, J Xie, B Wu, H Luo, F Xiao, J Chen, L Tao, G Cheng, ZG She, J Zhou, H Wang, J Lin, P Luo, S Fu, J Zhou, P Ye, B Xiao, W Mao, L Liu, Y Yan, L Liu, G Chen, H Li, X Huang, BH Zhang, Y Yuan. Longitudinal association between markers of liver injury and mortality in COVID-19 in China. Hepatology 2020; 72(2): 389–398
https://doi.org/10.1002/hep.31301 pmid: 32359177
17 J Ding, JE Karp, A Emadi. Elevated lactate dehydrogenase (LDH) can be a marker of immune suppression in cancer: interplay between hematologic and solid neoplastic clones and their microenvironments. Cancer Biomark 2017; 19(4): 353–363
https://doi.org/10.3233/CBM-160336 pmid: 28582845
18 M Al Ghamdi, KM Alghamdi, Y Ghandoora, A Alzahrani, F Salah, A Alsulami, MF Bawayan, D Vaidya, TM Perl, G Sood. Treatment outcomes for patients with Middle Eastern respiratory syndrome coronavirus (MERS CoV) infection at a coronavirus referral center in the Kingdom of Saudi Arabia. BMC Infect Dis 2016; 16(1): 174
https://doi.org/10.1186/s12879-016-1492-4 pmid: 27097824
19 PT Tsui, ML Kwok, H Yuen, ST Lai. Severe acute respiratory syndrome: clinical outcome and prognostic correlates. Emerg Infect Dis 2003; 9(9): 1064–1069
https://doi.org/10.3201/eid0909.030362 pmid: 14519241
20 R Spinella, R Sawhney, R Jalan. Albumin in chronic liver disease: structure, functions and therapeutic implications. Hepatol Int 2016; 10(1): 124–132
https://doi.org/10.1007/s12072-015-9665-6 pmid: 26420218
21 M Saad, AS Omrani, K Baig, A Bahloul, F Elzein, MA Matin, MA Selim, M Al Mutairi, D Al Nakhli, AY Al Aidaroos, N Al Sherbeeni, HI Al-Khashan, ZA Memish, AM Albarrak. Clinical aspects and outcomes of 70 patients with Middle East respiratory syndrome coronavirus infection: a single-center experience in Saudi Arabia. Int J Infect Dis 2014; 29: 301–306
https://doi.org/10.1016/j.ijid.2014.09.003 pmid: 25303830
22 Y Wang, S Liu, H Liu, W Li, F Lin, L Jiang, X Li, P Xu, L Zhang, L Zhao, Y Cao, J Kang, J Yang, L Li, X Liu, Y Li, R Nie, J Mu, F Lu, S Zhao, J Lu, J Zhao. SARS-CoV-2 infection of the liver directly contributes to hepatic impairment in patients with COVID-19. J Hepatol 2020; 73(4): 807–816
https://doi.org/10.1016/j.jhep.2020.05.002 pmid: 32437830
23 L Zhang, X Yan, Q Fan, H Liu, X Liu, Z Liu, Z Zhang. D-dimer levels on admission to predict in-hospital mortality in patients with Covid-19. J Thromb Haemost 2020; 18(6): 1324–1329
https://doi.org/10.1111/jth.14859 pmid: 32306492
24 T Qi, C Zhu, G Lu, J Hao, Q He, Y Chen, F Zhou, J Chen, J Hou. Elevated D-dimer is associated with increased 28-day mortality in acute-on-chronic liver failure in China: a retrospective study. BMC Gastroenterol 2019; 19(1): 20
https://doi.org/10.1186/s12876-019-0941-0 pmid: 30704397
25 A Tripodi. Hemostasis in acute and chronic liver disease. Semin Liver Dis 2017; 37(1): 28–32
https://doi.org/10.1055/s-0036-1597770 pmid: 28201846
26 JM Connors, JH Levy. COVID-19 and its implications for thrombosis and anticoagulation. Blood 2020; 135(23): 2033–2040
https://doi.org/10.1182/blood.2020006000 pmid: 32339221
27 ZP Duan, Y Chen, J Zhang, J Zhao, ZW Lang, FK Meng, XL Bao. Clinical characteristics and mechanism of liver injury in patients with severe acute respiratory syndrome. Chin J Hepatol (Zhonghua Gan Zang Bing Za Zhi) 2003; 11(8): 493–496 (in Chinese)
pmid: 12939186
28 X Cao. COVID-19: immunopathology and its implications for therapy. Nat Rev Immunol 2020; 20(5): 269–270
https://doi.org/10.1038/s41577-020-0308-3 pmid: 32273594
29 T Chen, D Wu, H Chen, W Yan, D Yang, G Chen, K Ma, D Xu, H Yu, H Wang, T Wang, W Guo, J Chen, C Ding, X Zhang, J Huang, M Han, S Li, X Luo, J Zhao, Q Ning. Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study. BMJ 2020; 368: m1091
https://doi.org/10.1136/bmj.m1091 pmid: 32217556
[1] FMD-21008-OF-CXP_suppl_1 Download
[1] Wei Zhang, Xiaoguang Xu, Ziyu Fu, Jian Chen, Saijuan Chen, Yun Tan. PathogenTrack and Yeskit: tools for identifying intracellular pathogens from single-cell RNA-sequencing datasets as illustrated by application to COVID-19[J]. Front. Med., 2022, 16(2): 251-262.
[2] Xiaoguang Xu, Wei Zhang, Mingquan Guo, Chenlu Xiao, Ziyu Fu, Shuting Yu, Lu Jiang, Shengyue Wang, Yun Ling, Feng Liu, Yun Tan, Saijuan Chen. Integrated analysis of gut microbiome and host immune responses in COVID-19[J]. Front. Med., 2022, 16(2): 263-275.
[3] Huai-yu Wang, Suyuan Peng, Zhanghui Ye, Pengfei Li, Qing Li, Xuanyu Shi, Rui Zeng, Ying Yao, Fan He, Junhua Li, Liu Liu, Shuwang Ge, Xianjun Ke, Zhibin Zhou, Gang Xu, Ming-hui Zhao, Haibo Wang, Luxia Zhang, Erdan Dong. Renin--angiotensin system inhibitor is associated with the reduced risk of all-cause mortality in COVID-19 among patients with/without hypertension[J]. Front. Med., 2022, 16(1): 102-110.
[4] Zehong Huang, Yingying Su, Tianying Zhang, Ningshao Xia. A review of the safety and efficacy of current COVID-19 vaccines[J]. Front. Med., 2022, 16(1): 39-55.
[5] Yuntao Zhang, Yunkai Yang, Niu Qiao, Xuewei Wang, Ling Ding, Xiujuan Zhu, Yu Liang, Zibo Han, Feng Liu, Xinxin Zhang, Xiaoming Yang. Early assessment of the safety and immunogenicity of a third dose (booster) of COVID-19 immunization in Chinese adults[J]. Front. Med., 2022, 16(1): 93-101.
[6] Qiaoli Shi, Fei Xia, Qixin Wang, Fulong Liao, Qiuyan Guo, Chengchao Xu, Jigang Wang. Discovery and repurposing of artemisinin[J]. Front. Med., 2022, 16(1): 1-9.
[7] Li Ni, Zheng Wen, Xiaowen Hu, Wei Tang, Haisheng Wang, Ling Zhou, Lujin Wu, Hong Wang, Chang Xu, Xizhen Xu, Zhichao Xiao, Zongzhe Li, Chene Li, Yujian Liu, Jialin Duan, Chen Chen, Dan Li, Runhua Zhang, Jinliang Li, Yongxiang Yi, Wei Huang, Yanyan Chen, Jianping Zhao, Jianping Zuo, Jianping Weng, Hualiang Jiang, Dao Wen Wang. Effects of Shuanghuanglian oral liquids on patients with COVID-19: a randomized, open-label, parallel-controlled, multicenter clinical trial[J]. Front. Med., 2021, 15(5): 704-717.
[8] Nan Qin, Guang Xu, Yan Wang, Xiaoyan Zhan, Yuan Gao, Zhilei Wang, Shubin Fu, Wei Shi, Xiaorong Hou, Chunyu Wang, Ruisheng Li, Yan Liu, Jiabo Wang, Haiping Zhao, Xiaohe Xiao, Zhaofang Bai. Bavachin enhances NLRP3 inflammasome activation induced by ATP or nigericin and causes idiosyncratic hepatotoxicity[J]. Front. Med., 2021, 15(4): 594-607.
[9] Weijian Hang, Chen Chen, Xin A. Zhang, Dao Wen Wang. Endothelial dysfunction in COVID-19 calls for immediate attention: the emerging roles of the endothelium in inflammation caused by SARS-CoV-2[J]. Front. Med., 2021, 15(4): 638-643.
[10] Rongtao Lai, Tianhui Zhou, Xiaogang Xiang, Jie Lu, Haiguang Xin, Qing Xie. Neutralizing monoclonal antibodies present new prospects to treat SARS-CoV-2 infections[J]. Front. Med., 2021, 15(4): 644-648.
[11] Dongsheng Wang, Binqing Fu, Zhen Peng, Dongliang Yang, Mingfeng Han, Min Li, Yun Yang, Tianjun Yang, Liangye Sun, Wei Li, Wei Shi, Xin Yao, Yan Ma, Fei Xu, Xiaojing Wang, Jun Chen, Daqing Xia, Yubei Sun, Lin Dong, Jumei Wang, Xiaoyu Zhu, Min Zhang, Yonggang Zhou, Aijun Pan, Xiaowen Hu, Xiaodong Mei, Haiming Wei, Xiaoling Xu. Tocilizumab in patients with moderate or severe COVID-19: a randomized, controlled, open-label, multicenter trial[J]. Front. Med., 2021, 15(3): 486-494.
[12] Junnan Liang, Guannan Jin, Tongtong Liu, Jingyuan Wen, Ganxun Li, Lin Chen, Wei Wang, Yuwei Wang, Wei Liao, Jia Song, Zeyang Ding, Xiao-ping Chen, Bixiang Zhang. Clinical characteristics and risk factors for mortality in cancer patients with COVID-19[J]. Front. Med., 2021, 15(2): 264-274.
[13] Guohua Chen, Wen Su, Jiayao Yang, Dan Luo, Ping Xia, Wen Jia, Xiuyang Li, Chuan Wang, Suping Lang, Qingbin Meng, Ying Zhang, Yuhe Ke, An Fan, Shuo Yang, Yujiao Zheng, Xuepeng Fan, Jie Qiao, Fengmei Lian, Li Wei, Xiaolin Tong. Chinese herbal medicine reduces mortality in patients with severe and critical coronavirus disease 2019: a retrospective cohort study[J]. Front. Med., 2020, 14(6): 752-759.
[14] Zhengqian Li, Taotao Liu, Ning Yang, Dengyang Han, Xinning Mi, Yue Li, Kaixi Liu, Alain Vuylsteke, Hongbing Xiang, Xiangyang Guo. Neurological manifestations of patients with COVID-19: potential routes of SARS-CoV-2 neuroinvasion from the periphery to the brain[J]. Front. Med., 2020, 14(5): 533-541.
[15] Zhihang Peng, Wenyu Song, Zhongxing Ding, Quanquan Guan, Xu Yang, Qiaoqiao Xu, Xu Wang, Yankai Xia. Linking key intervention timings to rapid declining effective reproduction number to quantify lessons against COVID-19[J]. Front. Med., 2020, 14(5): 623-629.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed