Coagulation abnormalities in COVID-19 patients have not been addressed in depth.
To perform a longitudinal evaluation of coagulation profile of patients admitted to the ICU with COVID-19.
...Conventional coagulation tests, rotational thromboelastometry (ROTEM), platelet function, fibrinolysis, antithrombin, protein C and S were measured at days 0, 1, 3, 7 and 14. Based on median total maximum SOFA score, patients were divided in two groups: SOFA ≤ 10 and SOFA > 10.
Thirty patients were studied. Some conventional coagulation tests, as aPTT, PT and INR remained unchanged during the study period, while alterations on others coagulation laboratory tests were detected. Fibrinogen levels were increased in both groups. ROTEM maximum clot firmness increased in both groups from Day 0 to Day 14. Moreover, ROTEM-FIBTEM maximum clot firmness was high in both groups, with a slight decrease from day 0 to day 14 in group SOFA ≤ 10 and a slight increase during the same period in group SOFA > 10. Fibrinolysis was low and decreased over time in all groups, with the most pronounced decrease observed in INTEM maximum lysis in group SOFA > 10. Also, D-dimer plasma levels were higher than normal reference range in both groups and free protein S plasma levels were low in both groups at baseline and increased over time, Finally, patients in group SOFA > 10 had lower plasminogen levels and Protein C than patients with SOFA <10, which may represent less fibrinolysis activity during a state of hypercoagulability.
COVID-19 patients have a pronounced hypercoagulability state, characterized by impaired endogenous anticoagulation and decreased fibrinolysis. The magnitude of coagulation abnormalities seems to correlate with the severity of organ dysfunction. The hypercoagulability state of COVID-19 patients was not only detected by ROTEM but it much more complex, where changes were observed on the fibrinolytic and endogenous anticoagulation system.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Severe coronavirus disease 2019 (COVID-19) patients frequently require mechanical ventilation (MV) and undergo prolonged periods of bed rest with restriction of activities during the intensive care ...unit (ICU) stay. Our aim was to address the degree of mobilization in critically ill patients with COVID-19 undergoing to MV support. Retrospective single-center cohort study. We analyzed patients' mobility level, through the Perme ICU Mobility Score (Perme Score) of COVID-19 patients admitted to the ICU. The Perme Mobility Index (PMI) was calculated PMI = DELTAPerme Score (ICU discharge-ICU admission)/ICU length of stay, and patients were categorized as "improved" (PMI > 0) or "not improved" (PMI less than or equal to 0). Comparisons were performed with stratification according to the use of MV support. From February 2020, to February 2021, 1,297 patients with COVID-19 were admitted to the ICU and assessed for eligibility. Out of those, 949 patients were included in the study 524 (55.2%) were classified as "improved" and 425 (44.8%) as "not improved", and 396 (41.7%) received MV during ICU stay. The overall rate of patients out of bed and able to walk greater than or equal to 30 meters at ICU discharge were, respectively, 526 (63.3%) and 170 (20.5%). After adjusting for confounders, independent predictors of improvement of mobility level were frailty (OR: 0.52; 95% CI: 0.29-0.94; p = 0.03); SAPS III Score (OR: 0.75; 95% CI: 0.57-0.99; p = 0.04); SOFA Score (OR: 0.58; 95% CI: 0.43-0.78; p < 0.001); use of MV after the first hour of ICU admission (OR: 0.41; 95% CI: 0.17-0.99; p = 0.04); tracheostomy (OR: 0.54; 95% CI: 0.30-0.95; p = 0.03); use of extracorporeal membrane oxygenation (OR: 0.21; 95% CI: 0.05-0.8; p = 0.03); neuromuscular blockade (OR: 0.53; 95% CI: 0.3-0.95; p = 0.03); a higher Perme Score at admission (OR: 0.35; 95% CI: 0.28-0.43; p < 0.001); palliative care (OR: 0.05; 95% CI: 0.01-0.16; p < 0.001); and a longer ICU stay (OR: 0.79; 95% CI: 0.61-0.97; p = 0.04) were associated with a lower chance of mobility improvement, while non-invasive ventilation within the first hour of ICU admission and after the first hour of ICU admission (OR: 2.45; 95% CI: 1.59-3.81; p < 0.001) and (OR: 2.25; 95% CI: 1.56-3.26; p < 0.001), respectively; and vasopressor use (OR: 2.39; 95% CI: 1.07-5.5; p = 0.03) were associated with a higher chance of mobility improvement. The use of MV reduced mobility status in less than half of critically ill COVID-19 patients.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Coexistence of cancer and COVID-19 is associated with worse outcomes. However, the studies on cancer-related characteristics associated with worse COVID-19 outcomes have shown controversial results. ...The objective of the study was to evaluate cancer-related characteristics associated with invasive mechanical ventilation use or in-hospital mortality in patients with COVID-19 admitted to intensive care unit (ICU).
We designed a cohort multicenter study including adults with active cancer admitted to ICU due to COVID-19. Seven cancer-related characteristics (cancer status, type of cancer, metastasis occurrence, recent chemotherapy, recent immunotherapy, lung tumor, and performance status) were introduced in a multilevel logistic regression model as first-level variables and hospital was introduced as second-level variable (random effect). Confounders were identified using directed acyclic graphs.
We included 274 patients. Required to undergo invasive mechanical ventilation were 176 patients (64.2%) and none of the cancer-related characteristics were associated with mechanical ventilation use. Approximately 155 patients died in hospital (56.6%) and poor performance status, measured with the Eastern Cooperative Oncology Group (ECOG) score was associated with increased in-hospital mortality, with odds ratio = 3.54 (1.60-7.88, 95% CI) for ECOG =2 and odds ratio = 3.40 (1.60-7.22, 95% CI) for ECOG = 3 to 4. Cancer status, cancer type, metastatic tumor, lung cancer, and recent chemotherapy or immunotherapy were not associated with in-hospital mortality.
In patients with active cancer and COVID-19 admitted to ICU, poor performance status was associated with in-hospital mortality but not with mechanical ventilation use. Cancer status, cancer type, metastatic tumor, lung cancer, and recent chemotherapy or immunotherapy were not associated with invasive mechanical ventilation use or in-hospital mortality.
OBJECTIVEThe incidence of thrombotic events and acute kidney injury is high in critically ill patients with COVID-19. We aimed to evaluate and compare the coagulation profiles of patients with ...COVID-19 developing acute kidney injury versus those who did not, during their intensive care unit stay. METHODSConventional coagulation and platelet function tests, fibrinolysis, endogenous inhibitors of coagulation tests, and rotational thromboelastometry were conducted on days 0, 1, 3, 7, and 14 following intensive care unit admission. RESULTSOut of 30 patients included, 13 (43.4%) met the criteria for acute kidney injury. Comparing both groups, patients with acute kidney injury were older: 73 (60-84) versus 54 (47-64) years, p=0.027, and had a lower baseline glomerular filtration rate: 70 (51-81) versus 93 (83-106) mL/min/1.73m2, p=0.004. On day 1, D-dimer and fibrinogen levels were elevated but similar between groups: 1780 (1319-5517) versus 1794 (726-2324) ng/mL, p=0.145 and 608 (550-700) versus 642 (469-722) g/dL, p=0.95, respectively. Rotational thromboelastometry data were also similar between groups. However, antithrombin activity and protein C levels were lower in patients who developed acute kidney injury: 82 (75-92) versus 98 (90-116), p=0.028 and 70 (52-82) versus 88 (78-101) µ/mL, p=0.038, respectively. Mean protein C levels were lower in the group with acute kidney injury across multiple time points during their stay in the intensive care unit. CONCLUSIONCritically ill patients experiencing acute kidney injury exhibited lower endogenous anticoagulant levels. Further studies are needed to understand the role of natural anticoagulants in the pathophysiology of acute kidney injury within this population.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
To describe and compare the clinical characteristics and outcomes of patients admitted to intensive care units during the first and second waves of the COVID-19 pandemic.
In this retrospective ...single-center cohort study, data were retrieved from the Epimed Monitor System; all adult patients admitted to the intensive care unit between March 4, 2020, and October 1, 2021, were included in the study. We compared the clinical characteristics and outcomes of patients admitted to the intensive care unit of a quaternary private hospital in São Paulo, Brazil, during the first (May 1, 2020, to August 31, 2020) and second (March 1, 2021, to June 30, 2021) waves of the COVID-19 pandemic.
In total, 1,427 patients with COVID-19 were admitted to the intensive care unit during the first (421 patients) and second (1,006 patients) waves. Compared with the first wave group median (IQR), the second wave group was younger 57 (46-70) versus 67 (52-80) years; p<0.001, had a lower SAPS 3 Score 45 (42-52) versus 49 (43-57); p<0.001, lower SOFA Score on intensive care unit admission 3 (1-6) versus 4 (2-6); p=0.018, lower Charlson Comorbidity Index 0 (0-1) versus 1 (0-2); p<0.001, and were less frequently frail (10.4% versus 18.1%; p<0.001). The second wave group used more noninvasive ventilation (81.3% versus 53.4%; p<0.001) and high-flow nasal cannula (63.2% versus 23.0%; p<0.001) during their intensive care unit stay. The intensive care unit (11.3% versus 10.5%; p=0.696) and in-hospital mortality (12.3% versus 12.1%; p=0.998) rates did not differ between both waves.
In the first and second waves, patients with severe COVID-19 exhibited similar mortality rates and need for invasive organ support, despite the second wave group being younger and less severely ill at the time of intensive care unit admission.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
OBJECTIVETo investigate the impact of intensive care unit admission during medical handover on mortality. METHODSPost-hoc analysis of data extracted from a prior study aimed at addressing the impacts ...of intensive care unit readmission on clinical outcomes. This retrospective, single-center, propensity-matched cohort study was conducted in a 41-bed general open-model intensive care unit. Patients were assigned to one of two cohorts according to time of intensive care unit admission: Handover Group (intensive care unit admission between 6:30 am and 7:30 am or 6:30 pm and 7:30 pm) or Control Group (intensive care unit admission between 7:31 am and 6:29 pm or 7:31 pm and 6:29 am). Patients in the Handover Group were propensity-matched to patients in the Control Group at a 1:2 ratio. RESULTSA total of 6,650 adult patients were admitted to the intensive care unit between June 1st 2013 and May 31st 2015. Following exclusion of non-eligible participants, 5,779 patients (389; 6.7% and 5,390; 93.3%, Handover and Control Group) were deemed eligible for propensity score matching. Of these, 1,166 were successfully matched (389; 33.4% and 777; 66.6%, Handover and Control Group). Following propensity-score matching, intensive care unit admission during handover was not associated with increased risk of intensive care unit (OR: 1.40; 95%CI: 0.92-2.11; p=0.113) or in-hospital (OR: 1.23; 95%CI: 0.85-1.75; p=0.265) mortality. CONCLUSIONIntensive care unit admission during medical handover did not affect in-hospital mortality in this propensity-matched, single-center cohort study.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Background Severe coronavirus disease 2019 (COVID-19) patients frequently require mechanical ventilation (MV) and undergo prolonged periods of bed rest with restriction of activities during the ...intensive care unit (ICU) stay. Our aim was to address the degree of mobilization in critically ill patients with COVID-19 undergoing to MV support. Methods Retrospective single-center cohort study. We analyzed patients’ mobility level, through the Perme ICU Mobility Score (Perme Score) of COVID-19 patients admitted to the ICU. The Perme Mobility Index (PMI) was calculated PMI = ΔPerme Score (ICU discharge–ICU admission)/ICU length of stay, and patients were categorized as “improved” (PMI > 0) or “not improved” (PMI ≤ 0). Comparisons were performed with stratification according to the use of MV support. Results From February 2020, to February 2021, 1,297 patients with COVID-19 were admitted to the ICU and assessed for eligibility. Out of those, 949 patients were included in the study 524 (55.2%) were classified as “improved” and 425 (44.8%) as “not improved”, and 396 (41.7%) received MV during ICU stay. The overall rate of patients out of bed and able to walk ≥ 30 meters at ICU discharge were, respectively, 526 (63.3%) and 170 (20.5%). After adjusting for confounders, independent predictors of improvement of mobility level were frailty (OR: 0.52; 95% CI: 0.29–0.94; p = 0.03); SAPS III Score (OR: 0.75; 95% CI: 0.57–0.99; p = 0.04); SOFA Score (OR: 0.58; 95% CI: 0.43–0.78; p < 0.001); use of MV after the first hour of ICU admission (OR: 0.41; 95% CI: 0.17–0.99; p = 0.04); tracheostomy (OR: 0.54; 95% CI: 0.30–0.95; p = 0.03); use of extracorporeal membrane oxygenation (OR: 0.21; 95% CI: 0.05–0.8; p = 0.03); neuromuscular blockade (OR: 0.53; 95% CI: 0.3–0.95; p = 0.03); a higher Perme Score at admission (OR: 0.35; 95% CI: 0.28–0.43; p < 0.001); palliative care (OR: 0.05; 95% CI: 0.01–0.16; p < 0.001); and a longer ICU stay (OR: 0.79; 95% CI: 0.61–0.97; p = 0.04) were associated with a lower chance of mobility improvement, while non-invasive ventilation within the first hour of ICU admission and after the first hour of ICU admission (OR: 2.45; 95% CI: 1.59–3.81; p < 0.001) and (OR: 2.25; 95% CI: 1.56–3.26; p < 0.001), respectively; and vasopressor use (OR: 2.39; 95% CI: 1.07–5.5; p = 0.03) were associated with a higher chance of mobility improvement. Conclusion The use of MV reduced mobility status in less than half of critically ill COVID-19 patients.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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