Quantitative chest CT imaging characteristics and outcome of patients with COVID-19 associated pulmonary artery thrombosis: A single-center retrospective cohort study.

Coronavirus disease 2019 (COVID-19)-associated pulmonary thrombotic events occur frequently and are associated with disease severity and worse clinical outcomes. We aimed to describe the clinical and quantitative chest computed tomography (CT) imaging characteristics based on density ranges (Hounsfield units) and the outcomes of patients with COVID-19 associated pulmonary artery thrombosis. This retrospective cohort study included all patients with COVID-19 hospitalized in a tertiary care hospital between March 2020 and June 2022 who underwent a CT pulmonary angiography. We included 73 patients: 36 (49.3%) with and 37 (50.7%) without pulmonary artery thrombosis. The in-hospital all-cause mortality was 22.2 versus 18.9% ( P  = .7), and the intensive care unit admission rates were 30.5 versus 8.1% ( P  = .01) at the time of diagnosis of pulmonary artery thrombosis. Except for D-dimers (median of 3142 vs 533, P  = .002), the other clinical, coagulopathy, and inflammatory markers were similar. Logistic regression analysis revealed that only D-dimers were associated with pulmonary artery thrombosis ( P  = .012). ROC curve analysis of D-dimers showed that a value greater than 1716 ng/mL predicted pulmonary artery thrombosis with an area under the curve of 0.779, 72.2% sensitivity, and 73% specificity (95% CI 0.672-0.885). Peripheral distribution of pulmonary artery thrombosis was recorded in 94.5% of cases. In the lower lobes of the lungs, the incidence of pulmonary artery thrombosis was 6 times higher than that in the upper lobes (58-64%), with a percentage of lung injury of 80% to 90%. Analysis of the distribution of arterial branches with filling defects revealed that 91.6% occurred in lung areas with inflammatory lesions. Quantitative chest CT imaging provides valuable information regarding the extent of COVID-19 associated lung damage and can be used to anticipate the co-location of pulmonary immunothrombotic events. In patients with severe COVID-19, in-hospital all-cause mortality was similar regardless of the presence of associated distal pulmonary thrombosis.

Pericardial Involvement in Severe COVID-19 Patients.

Background and Objectives: SARS-CoV-2 has an extensive tissue tropism due to its ability to attach to the surfaces of cells through different receptors, leading to systemic complications. In this article, we aim to present the prevalence of pericardial effusions in patients with severe COVID-19, to identify the risk factors/predictors for pericardial involvement, and to evaluate its impact on overall mortality. Materials and Methods: We enrolled 100 patients with severe COVID-19 in our observational cohort study and divided them in two groups: Group A (27 patients with pericardial effusion) and Group B (73 patients without pericardial effusion). We recorded demographic and lifestyle parameters, anthropometric parameters, clinical parameters, inflammation markers, respiratory function parameters, complete blood count, coagulation parameters, and biochemical serum parameters. All patients were evaluated by computer tomography scans within 48 h of admission. Results: The median age was 61 years in both groups and the male/female ratio was 3.5 vs. 2.8 in Group A vs. Group B. We identified mild pericardial effusion (3-4 mm) in 62.9% patients and moderate pericardial effusion (5-9 mm) in 37.1% patients, with a median value of 4 [3;6] mm. The patients with pericardial effusion presented with higher percentages of obesity, type-2 diabetes mellitus, arterial hypertension, and congestive heart failure, without statistical significance. Increased values in cardiac enzymes (myoglobin, CK, CK-MB) and LDH were statistically associated with pericardial effusion. The overall mortality among the participants of the study was 24% (24 patients), 33.3% in Group A and 20.8% in Group B. Conclusions: Pericardial effusion has a high prevalence (27%) among patients with severe forms of COVID-19 and was associated with higher mortality. Pericardial effusion in our study was not associated with the presence of comorbidities or the extent of lung involvement. Overall mortality was 60% higher in patients with pericardial effusion.

Mortality Predictors in Severe SARS-CoV-2 Infection.

Background and Objectives: The severe forms of SARS-CoV-2 pneumonia are associated with acute hypoxic respiratory failure and high mortality rates, raising significant challenges for the medical community. The objective of this paper is to present the importance of early quantitative evaluation of radiological changes in SARS-CoV-2 pneumonia, including an alternative way to evaluate lung involvement using normal density clusters. Based on these elements we have developed a more accurate new predictive score which includes quantitative radiological parameters. The current evolution models used in the evaluation of severe cases of COVID-19 only include qualitative or semi-quantitative evaluations of pulmonary lesions which lead to a less accurate prognosis and assessment of pulmonary involvement. Materials and Methods: We performed a retrospective observational cohort study that included 100 adult patients admitted with confirmed severe COVID-19. The patients were divided into two groups: group A (76 survivors) and group B (24 non-survivors). All patients were evaluated by CT scan upon admission in to the hospital. Results: We found a low percentage of normal lung densities, PaO2/FiO2 ratio, lymphocytes, platelets, hemoglobin and serum albumin associated with higher mortality; a high percentage of interstitial lesions, oxygen flow, FiO2, Neutrophils/lymphocytes ratio, lactate dehydrogenase, creatine kinase MB, myoglobin, and serum creatinine were also associated with higher mortality. The most accurate regression model included the predictors of age, lymphocytes, PaO2/FiO2 ratio, percent of lung involvement, lactate dehydrogenase, serum albumin, D-dimers, oxygen flow, and myoglobin. Based on these parameters we developed a new score (COV-Score). Conclusions: Quantitative assessment of lung lesions improves the prediction algorithms compared to the semi-quantitative parameters. The cluster evaluation algorithm increases the non-survivor and overall prediction accuracy.COV-Score represents a viable alternative to current prediction scores, demonstrating improved sensitivity and specificity in predicting mortality at the time of admission.

The Impact of Tocilizumab on Radiological Changes Assessed by Quantitative Chest CT in Severe COVID-19 Patients.

(1) Background: We aimed to analyze the characteristics associated with the in-hospital mortality, describe the early CT changes expressed quantitatively after tocilizumab (TOC), and assess TOC timing according to the oxygen demands. (2) Methods: We retrospectively studied 101 adult patients with severe COVID-19, who received TOC and dexamethasone. The lung involvement was assessed quantitatively using native CT examination before and 7−10 days after TOC administration. (3) Results: The in-hospital mortality was 17.8%. Logistic regression analysis found that interstitial lesions above 50% were associated with death (p = 0.01). The other variables assessed were age (p = 0.1), the presence of comorbidities (p = 0.9), the oxygen flow rate at TOC administration (p = 0.2), FiO2 (p = 0.4), lymphocyte count (p = 0.3), and D-dimers level (p = 0.2). Survivors had a statistically significant improvement at 7−10 days after TOC of interstitial (39.5 vs. 31.6%, p < 0.001), mixt (4.3 vs. 2.3%, p = 0.001) and consolidating (1.7 vs. 1.1%, p = 0.001) lesions. When TOC was administered at a FiO2 ≤ 57.5% (oxygen flow rate ≤ 13 L/min), the associated mortality was significantly lower (4.3% vs. 29.1%, p < 0.05). (4) Conclusions: Quantitative imaging provides valuable information regarding the extent of lung damage which can be used to anticipate the in-hospital mortality. The timing of TOC administration is important and FiO2 could be used as a clinical predictor.