| Literature DB >> 34172614 |
Sara Fernández1, Ana B Moreno-Castaño2,3,4, Marta Palomo3,5, Julia Martinez-Sanchez3,5, Sergi Torramadé-Moix2,3,4, Adrián Téllez1, Helena Ventosa1, Ferran Seguí1, Ginés Escolar2,3,4, Enric Carreras3,5, Josep M Nicolás1,4,6, Edward Richardson7,8, David García-Bernal9, Carmelo Carlo-Stella10,11, José M Moraleda9, Paul G Richardson12, Maribel Díaz-Ricart2,3,4, Pedro Castro1,4,6.
Abstract
BACKGROUND: Endotheliopathy is a key element in COVID-19 pathophysiology, contributing to both morbidity and mortality. Biomarkers distinguishing different COVID-19 phenotypes from sepsis syndrome remain poorly understood.Entities:
Mesh:
Substances:
Year: 2022 PMID: 34172614 PMCID: PMC8662948 DOI: 10.1097/SHK.0000000000001823
Source DB: PubMed Journal: Shock ISSN: 1073-2322 Impact factor: 3.533
Clinical characteristics of patients with COVID-19
| Overall n = 49 | Moderate disease n = 24 (49%) | Severe disease n = 15 (31%) | Critical disease n = 10 (20%) | |
| Male, n (%) | 26 (53%) | 10 (42%) | 9 (60%) | 7 (70%) |
| Age (years) | 61 (49–74) | 53 (43–71) | 68 (48–78) | 66 (52–75) |
| Comorbidities | ||||
| Hypertension | 20 (41%) | 6 (25%) | 7 (47%) | 7 (70%) |
| Diabetes | 12 (24.5%) | 6 (25%) | 4 (27%) | 2 (20%) |
| Pneumopathy | 5 (10%) | 0 | 2 (13%) | 3 (30%) |
| Heart disease | 9 (18%) | 4 (17%) | 2 (13%) | 3 (30%) |
| Active malignancy | 1 (2%) | 0 | 1 (7%) | 0 |
| Other immunosuppression | 3 (6%) | 0 | 1 (7%) | 2 (20%) |
| Chronic kidney disease | 4 (8%) | 1 (4%) | 1 (7%) | 2 (20%) |
| CRP (mg/dL) | 5 (3–9) | 4 (2–6) | 6 (4–9) | 14 (4–24)∗ |
| Ferritin (ng/mL) | 558 (268–1,026) | 278 (180–632) | 636 (422–1,230)∗ | 988 (562–1,436)∗ |
| D-dimer (ng/mL) | 600 (400–1,150) | 500 (400–775) | 800 (500–1,800)∗ | 1,050 (400–4,050)∗ |
| Acute Kidney Injury | 2 (4%) | 0 | 0 | 2 (20%) |
| Immunomodulatory therapy | 22 (45%) | 6 (25%) | 6 (40%) | 10 (100%)∗,† |
| Hospital length of stay (days) | 9 (4–15) | 6 (3–14) | 9 (4–11) | 20 (12–33)∗,† |
| Days of symptoms | 7 (5–10) | 6,5 (4–9) | 7 (5–13) | 6,5 (5–9) |
| 28-day mortality | 1 (2%) | 0 | 0 | 1 (10%) |
Data are expressed as median (interquartile range) or absolute count (percentage).
P < 0.05 compared with moderate disease group.
P < 0.05 compared with severe disease group.
CRP indicates C-reactive protein.
Comparison between worsening and not worsening non-ICU COVID-19 patients
| WG n = 12 (31%) | NWG n = 27 (69%) | ||
| Male, n (%) | 8 (67%) | 11 (41%) | |
| Age (years) | 71 (60–79) | 52 (42–72) | |
| Comorbidities | |||
| Hypertension | 6 (50%) | 7 (26%) | |
| Diabetes | 5 (42%) | 5 (19%) | |
| Pneumopathy | 0 | 2 (7%) | |
| Heart disease | 4 (33%) | 2 (7%) | |
| Active malignancy | 1 (8%) | 0 | |
| Other immunosuppression | 0 | 1 (4%) | |
| Chronic kidney disease | 1 (8%) | 1 (4%) | |
| CRP (mg/dL) | 5.3 (4–8) | 4.5 (2–7,6) | |
| Ferritin | 632 (292–1,451) | 431 (180–636) | |
| D-dimer | 650 (400–1,025) | 500 (400–1,100) | |
| Hospital length of stay (days) | 11 (8–22) | 6 (3–10) | |
| Days of symptoms | 6 (4–10) | 8 (6–11) | |
| Supplemental oxygen | 6 (50%) | 9 (33%) | |
| Causes of worsening | |||
| Increased oxygen requirements | 7 (58%) | ||
| Progression of radiological pulmonary infiltrates | 7 (58%) | ||
| Increased inflammation biomarkers∗ | 8 (66%) | ||
| Immunomodulatory treatment | |||
| Corticosteroids | 8 (67%) | ||
| Tocilizumab | 5 (42%) | ||
| Anakinra | 2 (17%) | ||
| Siltuximab | 1 (8%) | ||
| More than 1 treatment | 3 (24%) | ||
Data are expressed as median (interquartile range) or absolute count (percentage).
Defined as increased CRP and/or ferritin levels above twice the baseline levels.
CRP indicates C-reactive protein; NWG, non-worsening group; WG, worsening group.
Clinical characteristics of patients with critical COVID-19 disease, NI-SIRS, sepsis, and septic shock
| Critical COVID-19 n = 10 | NI-SIRS n = 7 | Sepsis n = 7 | Septic shock n = 14 | |
| Male, n (%) | 7 (70%) | 4 (57%) | 5 (71%) | 8 (57%) |
| Age (years) | 66 (52–75) | 54 (46–59) | 68 (56–75) | 60 (48–72) |
| Comorbidities | ||||
| Hypertension | 7 (70%) | 2 (29%) | 4 (57%) | 6 (43%) |
| Diabetes | 2 (20%) | 1 (14%) | 2 (29%) | 3 (21%) |
| Pneumopathy | 3 (30%) | 0 | 0 | 0 |
| Heart disease | 3 (30%) | 1 (14%) | 1 (14%) | 1 (7%) |
| Active malignancy | 0 | 0 | 0 | 0 |
| Other immunosuppression | 2 (20%) | 0 | 1 (14%) | 0 |
| Chronic kidney disease | 2 (20%) | 0 | 0 | 0 |
| Primary diagnoses | ||||
| Infection source | 0 | |||
| Urinary | 2 (29%) | 3 (22%) | ||
| Pulmonary | 3 (43%) | 5 (71%) | 3 (22%) | |
| Soft tissues | 1 (14%) | 0 | 3 (22%) | |
| Endovascular | 2 (29%) | 0 | 2 (14%) | |
| Central Nervous System | 1 (14%) | 0 | 2 (14%) | |
| Abdominal | 0 | 1 (7%) | ||
| Cardiac surgery | 0 | 0 | ||
| Pulmonary surgery | 0 | 0 | ||
| Cardiovascular disease | 0 | 0 | ||
| Pulmonary Thromboembolism | 0 | 0 | ||
| APACHE II score | 14 (8–16) | 10 (9–20) | 15 (12–25) | 21 (14–25)∗ |
| SOFA II score | 4 (3–6) | 6 (5–12) | 7 (6–8)† | 11 (9–14)† |
| CRP (mg/dL) | 14 (4–24) | 6 (2,5–13) | 23 (3–30) | 28 (22–34)∗ |
| Platelet count (109/L) | 244 (187–302) | 132 (115–214) | 255 (171–280) | 153 (65–196)∗ |
| ICU length of stay (days) | 14 (6–34) | 4 (2–7)∗ | 3 (2–7)† | 10 (4–16) |
| Hospital length of stay (days) | 20 (12–33) | 11 (7–14)∗ | 10 (8–17)∗ | 18 (13–54) |
| 28-day mortality | 1 (10%) | 0 | 0 | 5 (36%) |
| Invasive Mechanical ventilation | 3 (30%) | 5 (57%) | 1 (14%) | 6 (43%) |
| Renal replacement therapy | 3 (30%) | 1 (14%) | 1 (14%) | 3 (21%) |
Data are expressed as median (interquartile range) or absolute count (percentage).
P < 0.05 compared with critical COVID-19 group.
P < 0.01 compared with critical COVID-19 group.
APACHE indicates Acute Physiology and Chronic Health Evaluation; CRP, C-reactive protein; ICU, intensive care unit; NI-SIRS, noninfectious systemic inflammatory response syndrome; SOFA, Sequential Organ Failure Assessment.
Fig. 1Comparison of circulating endothelial biomarkers between different COVID-19 groups. Datapoints indicate individual measurements, whereas horizontal bars show median and interquartile ranges. ∗P < 0.05 compared with control group. ∗∗P < 0.001 compared with control group. C5b9 deposits are expressed as fold increase versus control. ADAMTS-13 indicates a disintegrin-like and metalloprotease with thrombospondin type 1 motif no. 13; NETs, neutrophil extracellular traps; PAI-1, plasminogen activator inhibitor-1; sC5b9, soluble C5b9; sTNF-RI, soluble tumor necrosis factor receptor I; sVCAM-1, soluble vascular cell adhesion molecule-1; VWF, Von Willebrand Factor.
Fig. 2Complement C5b9 deposits on endothelial cells in culture. Representative micrographs showing deposits of C5b9 on human microvascular endothelial cells (HMEC-1) after exposure to plasma samples from healthy donors (Control), a critical COVID-19 patient and a patient with septic shock. C5b9 deposits were detected by using a specific primary antibody followed by a secondary antibody conjugated with Alexa594 (red). Cell nuclei were stained with DAPI (blue). Each field encloses 75,922 μm2 of cell culture preparation.
Fig. 3Comparison of circulating endothelial biomarkers between worsening and not worsening non-ICU COVID-19 patients. Datapoints indicate individual measurements, whereas horizontal bars show median and interquartile ranges. C5b9 deposits are expressed as fold increase versus control. ADAMTS-13 indicates a disintegrin-like and metalloprotease with thrombospondin type 1 motif no. 13; NETs, neutrophil extracellular traps; PAI-1, plasminogen activator inhibitor-1; sC5b9: soluble C5b9; sTNF-RI, soluble tumor necrosis factor receptor I; sVCAM-1, soluble vascular cell adhesion molecule-1; VWF, Von Willebrand Factor.
Fig. 4Comparison of circulating endothelial biomarkers between critical COVID-19 and septic shock patients. Datapoints indicate individual measurements, whereas horizontal bars show median and interquartile ranges. C5b9 deposits are expressed as fold increase versus control. ADAMTS-13 indicates a disintegrin-like and metalloprotease with thrombospondin type 1 motif no. 13; NETs, neutrophil extracellular traps; PAI-1, plasminogen activator inhibitor-1; sC5b9: soluble C5b9; sTNF-RI, soluble tumor necrosis factor receptor I; sVCAM-1, soluble vascular cell adhesion molecule-1; VWF, Von Willebrand Factor.
Fig. 5Comparison of circulating endothelial biomarkers between critical COVID-19, NI-SIRS, sepsis, and septic shock patients. Datapoints indicate individual measurements, whereas horizontal bars show median and interquartile ranges. C5b9 deposits are expressed as fold increase versus control. ADAMTS-13 indicates a disintegrin-like and metalloprotease with thrombospondin type 1 motif no. 13; NETs, neutrophil extracellular traps; NI-SIRS, noninfectious systemic inflammatory response syndrome; PAI-1, plasminogen activator inhibitor-1; sC5b9, soluble C5b9; sTNF-RI, soluble tumor necrosis factor receptor I; sVCAM-1, soluble vascular cell adhesion molecule-1; VWF, Von Willebrand Factor.