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Frontiers of Medicine

ISSN 2095-0217

ISSN 2095-0225(Online)

CN 11-5983/R

邮发代号 80-967

2019 Impact Factor: 3.421

Frontiers of Medicine  2022, Vol. 16 Issue (1): 111-125   https://doi.org/10.1007/s11684-021-0854-5
  本期目录
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
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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.

Key wordsCOVID-19    chronic hepatitis B    liver injury    coagulation dysfunction
收稿日期: 2020-11-22      出版日期: 2022-03-28
Corresponding Author(s): Zhihua Wang,Jianbo Tian,Xiao-ping Chen   
 引用本文:   
. [J]. Frontiers of Medicine, 2022, 16(1): 111-125.
Jing Wang, Zequn Lu, Meng Jin, Ying Wang, Kunming Tian, Jun Xiao, Yimin Cai, Yanan Wang, Xu Zhang, Tao Chen, Zhi Yao, Chunguang Yang, Renli Deng, Qiang Zhong, Xiongbo Deng, Xin Chen, Xiang-ping Yang, Gonghong Wei, Zhihua Wang, Jianbo Tian, Xiao-ping Chen. Clinical characteristics and risk factors of COVID-19 patients with chronic hepatitis B: a multi-center retrospective cohort study. Front. Med., 2022, 16(1): 111-125.
 链接本文:  
https://academic.hep.com.cn/fmd/CN/10.1007/s11684-021-0854-5
https://academic.hep.com.cn/fmd/CN/Y2022/V16/I1/111
Fig.1  
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  
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  
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  
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  
Fig.2  
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
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