| Literature DB >> 35458541 |
Fabian Heinrich1, Kevin Roedl2, Dominik Jarczak2, Hanna-Lisa Goebels1, Axel Heinemann1, Ulrich Schäfer3, Frank Ludwig4, Martin Bachmann5, Berthold Bein6, Christian Friedrich Weber7, Karsten Sydow8, Marc Bota9, Hans-Richard Paschen10, Andreas de Weerth11, Carsten Veit12, Oliver Detsch13, Philipp-Alexander Brand14, Stefan Kluge2, Benjamin Ondruschka1, Dominic Wichmann2.
Abstract
Critically ill COVID-19 patients are at high risk for venous thromboembolism (VTE), namely deep vein thrombosis (DVT) and/or pulmonary embolism (PE), and death. The optimal anticoagulation strategy in critically ill patients with COVID-19 remains unknown. This study investigated the ante mortem incidence as well as postmortem prevalence of VTE, the factors predictive of VTE, and the impact of changed anticoagulation practice on patient survival. We conducted a consecutive retrospective analysis of postmortem COVID-19 (n = 64) and non-COVID-19 (n = 67) patients, as well as ante mortem COVID-19 (n = 170) patients admitted to the University Medical Center Hamburg-Eppendorf (Hamburg, Germany). Baseline patient characteristics, parameters related to the intensive care unit (ICU) stay, and the clinical and autoptic presence of VTE were evaluated and statistically compared between groups. The occurrence of VTE in critically ill COVID-19 patients is confirmed in both ante mortem (17%) and postmortem (38%) cohorts. Accordingly, comparing the postmortem prevalence of VTE between age- and sex-matched COVID-19 (43%) and non-COVID-19 (0%) cohorts, we found the statistically significant increased prevalence of VTE in critically ill COVID-19 cohorts (p = 0.001). A change in anticoagulation practice was associated with the statistically significant prolongation of survival time (HR: 2.55, [95% CI 1.41-4.61], p = 0.01) and a reduction in VTE occurrence (54% vs. 25%; p = 0.02). In summary, in the autopsy as well as clinical cohort of critically ill patients with COVID-19, we found that VTE was a frequent finding. A change in anticoagulation practice was associated with a statistically significantly prolonged survival time.Entities:
Keywords: COVID-19; SARS-CoV-2; deep vein thrombosis; pulmonary embolism; respiratory infections; venous thromboembolism
Mesh:
Substances:
Year: 2022 PMID: 35458541 PMCID: PMC9027529 DOI: 10.3390/v14040811
Source DB: PubMed Journal: Viruses ISSN: 1999-4915 Impact factor: 5.818
Baseline characteristics of consecutive COVID-19 patients from intensive care units all over the city of Hamburg, autopsied at the Institute of Legal Medicine (University Medical Center Hamburg-Eppendorf, Germany), are illustrated (n = 64). Patients were grouped according to the postmortem diagnosis of pulmonary embolisms. Numbers with frequencies and median with interquartile ranges are illustrated. Univariate and multivariate logistic regressions were performed. Odds ratios with 95% confidence intervals are given. Model estimators: Wald chi-square test: 17.29, p = 0.14; Akaike’s information criterion (AIC): 88.30. Abbreviations: BMI, body mass index; ICU, intensive care unit; ECMO, extracorporeal membrane oxygenation; RRT, renal replacement therapy; COVID-19, coronavirus disease 2019; ARDS, acute respiratory distress syndrome.
| Overall Patients | Pulmonary Embolism | Univariate Logistic Regression | Multivariate Logistic Regression | |||
|---|---|---|---|---|---|---|
| Odds ratio | Odds ratio | |||||
| 95% CI | 95% CI | |||||
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| Age | 72.5 (63.5–79.0) | 72.0 (57.0–79.0) | 0.99 (0.94–1.03) | 0.49 | 0.96 (0.91–1.01) | 0.13 |
| Sex (Ref: Female) | 47 (73.4%) | 14 (73.7%) | 1.02 (0.30–3.44) | 0.98 | 1.27 (0.21–7.49) | 0.80 |
| BMI | 27.7 (22.6–32.8) | 29.6 (24.7–36.8) | 1.02 (0.98–1.07) | 0.35 | 1.02 (0.96–1.09) | 0.53 |
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| Type II diabetes mellitus | 18 (28.1%) | 4 (21.1%) | 0.59 (0.17–2.10) | 0.42 | 0.49 (0.10–2.38) | 0.38 |
| Arterial hypertension | 33 (51.6%) | 9 (47.4%) | 0.79 (0.27–2.31) | 0.66 | 0.42 (0.08–2.12) | 0.29 |
| Chronic lung disease | 20 (31.2%) | 6 (31.6%) | 1.02 (0.32–3.24) | 0.97 | 0.96 (0.24–3.89) | 0.95 |
| Chronic kidney disease | 13 (20.3%) | 3 (15.8%) | 0.66 (0.16–2.71) | 0.56 | 0.56 (0.09–3.54) | 0.54 |
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| Mechanical ventilation | 50 (78.1%) | 17 (89.5%) | 3.09 (0.62–15.42) | 0.02 | 2.89 (0.19–43.41) | 0.44 |
| ECMO | 11 (17.2%) | 3 (15.8%) | 0.87 (0.20–3.70) | 0.85 | 0.21 (0.04–1.13) | 0.107 |
| RRT | 35 (54.7%) | 15 (78.9%) | 4.69 (1.34–16.46) | 0.02 | 11.22 (2.36–53.30) | 0.002 |
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| Remdesivir | 1 (1.6%) | 0 (0.0%) | ND | ND | ND | ND |
| Dexamethasone | 19 (29.7%) | 4 (21.1%) | 0.53 (0.15–1.89) | 0.33 | 0.76 (0.18–3.19) | 0.71 |
| Tocilizumab | 0 (0%) | 0 (0%) | ND | ND | ND | ND |
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| ARDS | 48 (75.0%) | 15 (78.9%) | 1.36 (0.38–4.93) | 0.64 | 0.57 (0.09–43.63) | 0.55 |
Figure 1Kaplan–Meier curves display the overall time interval before death of 64 consecutive COVID-19 patients from intensive care units all over the city of Hamburg, autopsied at the Institute of Legal Medicine (University Medical Center Hamburg-Eppendorf, Germany). Survival time was calculated starting from the day of the first positive molecular genetic diagnosis (by RT-qPCR). Patients were grouped according to their admission date before or after adjustments to the local therapy recommendations (in early May 2020). Kaplan–Meier estimates and 95% confidence intervals, as well as hazard ratios (Mantel-Haenszel), are illustrated.
Baseline characteristics of consecutive COVID-19 patients admitted to the Department of Intensive Care Medicine (University Medical Center Hamburg-Eppendorf, Germany) are illustrated (n = 170). Patients were grouped according to their overall survival. Numbers with frequencies and median with interquartile ranges are illustrated. Univariate and multivariate logistic regressions were performed. Odds ratios with 95% confidence intervals are given. Model estimators: Wald chi-square test: 64.96, p < 0.0001; Akaike’s information criterion (AIC): 140.73. Abbreviations: BMI, body mass index; ICU, intensive care unit; NIV, noninvasive ventilation; MV, mechanical ventilation; ECMO, extracorporeal membrane oxygenation; RRT, renal replacement therapy; COVID-19, coronavirus disease 2019; TPE, therapeutic plasma exchange; ARDS, acute respiratory distress syndrome; SAPS II, simplified acute physiology score 2; SOFA, sepsis-related organ failure assessment score.
| Overall Patients | Non-Survivors | Univariate Logistic Regression | Multivariate Logistic Regression | |||
|---|---|---|---|---|---|---|
| Odds ratio | Odds ratio | |||||
| 95% CI | 95% CI | |||||
|
| ||||||
| Age | 63.0 (55.0–73.0) | 66.0 (58.0–76.0) | 1.03 (1.00–1.05) | 0.04 | 1.03 (0.98–1.08) | 0.24 |
| Sex (Ref: Female) | 112 (65.9%) | 49 (69.0%) | 0.79 (0.41–1.50) | 0.47 | 0.61 (0.16–2.33) | 0.47 |
| BMI | 27.2 (24.2–31.9) | 26.3 (23.9–32.7) | 0.99 (0.95–1.04) | 0.78 | 0.88 (0.80–0.96) | 0.01 |
| Charlson comorbidity index | 2.0 (1.0–3.0) | 2.0 (1.0–4.0) | 1.09 (0.96–1.24) | 0.17 | 1.50 (1.02–2.21) | 0.04 |
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| Type II diabetes mellitus | 57 (33.5%) | 22 (31.0%) | 0.82 (0.43–1.57) | 0.55 | 0.69 (0.19–2.57) | 0.58 |
| Arterial hypertension | 97 (57.1%) | 42 (59.2%) | 1.16 (0.62–2.15) | 0.64 | 1.75 (0.39–7.89) | 0.47 |
| Chronic lung disease | 24 (14.1%) | 11 (15.5%) | 1.21 (0.51–2.89) | 0.66 | 0.47 (0.12–1.95) | 0.30 |
| Chronic kidney disease | 27 (15.9%) | 10 (14.1%) | 0.79 (0.34–1.85) | 0.59 | 0.15 (0.01–2.05) | 0.16 |
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| Nasal oxygen therapy | 60 (35.3%) | 24 (33.8%) | 0.89 (0.47–1.69) | 0.73 | 0.54 (0.12–2.44) | 0.43 |
| NIV | 41 (24.1%) | 19 (26.8%) | 1.28 (0.63–2.59) | 0.50 | 0.79 (0.13–4.62) | 0.79 |
| MV | 120 (70.6%) | 65 (91.5%) | 8.67 (2.43–21.87) | <0.0001 | 0.98 (0.03–34.31) | 0.99 |
| MV time (days) | 8.0 (0.0–21.5) | 12.0 (5.0–22.0) | 1.00 (0.98–1.01) | 0.68 | 0.91 (0.87–0.96) | <0.0001 |
| ECMO | 49 (28.8%) | 33 (46.5%) | 4.50 (2.22–9.16) | <0.0001 | 41.33 (5.54–308.31) | <0.0001 |
| RRT | 79 (46.5%) | 51 (71.8%) | 6.47 (3.28–12.73) | <0.0001 | 10.55 (2.59–43.02) | 0.001 |
| Catecholamines | 132 (77.6%) | 67 (94.4%) | 8.76 (2.94–26.08) | <0.0001 | 0.70 (0.03–16.54) | 0.82 |
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| Remdesivir | 32 (18.8%) | 10 (14.1%) | 0.57 (0.25–1.30) | 0.18 | 0.49 (0.10–2.46) | 0.38 |
| Dexamethasone | 73 (42.9%) | 35 (49.3%) | 1.56 (0.84–2.89) | 0.16 | 1.48 (0.29–7.65) | 0.64 |
| Tocilizumab | 3 (1.8%) | 3 (4.2%) | ND | ND | ND | ND |
| TPE | 6 (3.5%) | 3 (4.2%) | 1.41 (0.28–7.21) | 0.68 | 2.37 (0.38–14.71) | 0.36 |
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| ARDS | 113 (66.5%) | 64 (90.1%) | 9.33 (3.89–22.36) | <0.0001 | 7.59 (0.27–211.19) | 0.23 |
| ARDS severity | 3.0 (0.0–3.0) | 3.0 (3.0–3.0) | 2.29 (1.70–2.08) | <0.0001 | 1.79 (0.54–5.96) | 0.34 |
| SAPS II—on admission | 40.0 (33.0–48.0) | 43.0 (37.0–52.0) | 1.07 (1.03–1.10) | <0.0001 | 1.05 (0.98–1.13) | 0.17 |
| SOFA score—on admission | 7.0 (3.0–12.0) | 10.0 (6.0–13.0) | 1.12 (1.04–1.19) | 0.001 | 0.92 (0.79–1.07) | 0.27 |
Baseline characteristics of consecutive COVID-19 patients admitted to the Department of Intensive Care Medicine (University Medical Center Hamburg-Eppendorf, Germany) are illustrated (n = 170). Patients were grouped according to the clinical diagnosis of pulmonary embolisms. Numbers with frequencies and median with interquartile ranges are illustrated. Abbreviations: BMI, body mass index; ICU, intensive care unit; NIV, noninvasive ventilation; MV, mechanical ventilation; ECMO, extracorporeal membrane oxygenation; ILA, interventional lung assist; RRT, renal replacement therapy; COVID-19, coronavirus disease 2019; TPE, therapeutic plasma exchange; ARDS, acute respiratory distress syndrome; SAPS II, simplified acute physiology score 2; SOFA, sepsis-related organ failure assessment score.
| No Pulmonary Embolism | Pulmonary Embolism | Overall Patients | Comparative Statistics ( | |
|---|---|---|---|---|
| Sociodemographic variables | ||||
| Age | 63.0 (53.0–73.0) | 62.5 (59.0–74.5) | 63.0 (55.0–73.0) | 0.54 |
| Sex | ||||
| Male | 104 (65.8%) | 8 (66.7%) | 112 (65.9%) | 0.95 |
| Female | 54 (34.2%) | 4 (33.3%) | 58 (34.1%) | . |
| BMI | 27.2 (24.2–31.9) | 27.0 (23.7–31.8) | 27.2 (24.2–31.9) | 0.66 |
| Charlson comorbidity index | 2.0 (1.0–3.0) | 2.5 (0.5–4.5) | 2.0 (1.0–3.0) | 0.58 |
| Pre-existing medical conditions | ||||
| Type II diabetes mellitus | 49 (31.0%) | 8 (66.7%) | 57 (33.5%) | 0.01 |
| Arterial hypertension | 91 (57.6%) | 6 (50.0%) | 97 (57.1%) | 0.61 |
| Chronic lung disease | 22 (13.9%) | 2 (16.7%) | 24 (14.1%) | 0.79 |
| Chronic kidney disease | 24 (15.2%) | 3 (25.0%) | 27 (15.9%) | 0.37 |
| ICU-related therapy | ||||
| Nasal oxygen therapy | 56 (35.4%) | 4 (33.3%) | 60 (35.3%) | 0.88 |
| NIV | 36 (22.8%) | 5 (41.7%) | 41 (24.1%) | 0.14 |
| MV | 109 (69.0%) | 11 (91.7%) | 120 (70.6%) | 0.10 |
| MV time | 8.0 (0.0–19.5) | 18.5 (4.5–58.0) | 8.0 (0.0–21.5) | 0.04 |
| ECMO | 45 (28.5%) | 4 (33.3%) | 49 (28.8%) | 0.72 |
| RRT | 67 (42.4%) | 12 (100.0%) | 79 (46.5%) | <0.0001 |
| Catecholamines | 121 (76.6%) | 11 (91.7%) | 132 (77.6%) | 0.23 |
| COVID-19-related therapy | ||||
| Remdesivir | 30 (19.0%) | 2 (16.7%) | 32 (18.8%) | 0.84 |
| Dexamethasone | 67 (42.4%) | 6 (50.0%) | 73 (42.9%) | 0.61 |
| Tocilizumab | 3 (1.9%) | 0 (0.0%) | 3 (1.8%) | 0.63 |
| TPE therapy | 6 (3.8%) | 0 (0.0%) | 6 (3.5%) | 0.49 |
| COVID-19 disease severity | ||||
| ARDS | 55 (34.8%) | 2 (16.7%) | 57 (33.5%) | 0.20 |
| ARDS severity | 2.0 (0.0–3.0) | 3.0 (3.0–3.0) | 3.0 (0.0–3.0) | 0.04 |
| SAPSII | 40.0 (33.0–48.0) | 40.0 (34.0–52.5) | 40.0 (33.0–48.0) | 0.70 |
| SOFA score | 7.0 (3.0–12.0) | 7.0 (2.5–11.5) | 7.0 (3.0–12.0) | 0.80 |
Figure 2Relevant laboratory parameters of consecutive COVID-19 patients admitted to the Department of Intensive Care Medicine (University Medical Center Hamburg-Eppendorf, Germany) are illustrated (n = 170). Laboratory parameters at the time of admission (A) and peak parameters (B) are illustrated (only for platelet counts the minimum parameters are shown). Patients were grouped according to the presence of pulmonary embolisms (patients w/o pulmonary embolism are marked yellow on the left, and patients with pulmonary embolism are marked green on the right). Statistical comparisons between groups were performed using the Mann–Whitney U-test. p-values are displayed as follows: *, p < 0.05; ns, not significant.
Anticoagulation regimes of consecutive COVID-19 patients admitted to the Department of Intensive Care Medicine (University Medical Center Hamburg-Eppendorf, Germany) are illustrated (n = 170). Anticoagulation therapy was evaluated within the last 24 h prior to death. Patients were grouped according to their overall survival. Numbers with frequencies and median with interquartile ranges are illustrated. Univariate and multivariate logistic regressions were performed. Odds ratios with 95% confidence intervals are given. Model estimators: Wald chi-square test: 39.13, p < 0.0001; Akaike’s information criterion (AIC): 198.85.
| Overall Patients | Non-Survivors | Univariate Logistic Regression | Multivariate Logistic Regression | |||
|---|---|---|---|---|---|---|
| Odds ratio | Odds ratio | |||||
| Pulmonary embolism | 12 (7.1%) | 9 (12.7%) | 4.65 (1.21–17.83) | 0.03 | 2.21 (0.40–12.08) | 0.36 |
| Low-molecular-weight heparin | ||||||
| Low dose | 23 (13.5%) | 5 (7%) | 0.14 (0.48–0.43) | <0.0001 | 0.08 (0.02–0.43) | 0.003 |
| Intermediate dose | 31 (18.2%) | 5 (7%) | 0.10 (0.03–0.29) | <0.0001 | 0.06 (0.01–0.29) | 0.001 |
| High dose | 31 (18.2%) | 5 (7%) | 0.10 (0.03–0.29) | <0.0001 | 0.06 (0.01–0.28) | <0.0001 |
| Unfractionated heparin | ||||||
| Low dose | 7 (4.1%) | 6 (8.5%) | 14.06 (1.63–121.58) | 0.02 | 1.65 (0.14–19.85) | 0.69 |
| High dose | 56 (32.9%) | 33 (46.5%) | 3.36 (1.71–6.60) | <0.0001 | 0.39 (0.10–1.61) | 0.19 |
| Factor-IIa antagonist | 9 (5.3%) | 7 (9.9%) | 5.30 (1.07–26.35) | 0.04 | 0.84 (0.10–6.81) | 0.87 |