The Association of CT-measured Cardiac Indices with Lung Involvement and Clinical Outcome in Patients with COVID-19

The association of radiologic right heart strain indices with the severity of pulmonary parenchymal involvement and prognosis in patients with COVID-19

Introduction

It has been demonstrated that an increase in the diameter of the right ventricle or pulmonary artery in COVID-19 patients could be associated with the severity of lung involvement and may lead to unfavorable outcomes, particularly in the presence of pulmonary vascular diseases. This study investigated the relationship between these right heart strain features, the extent of lung involvement, and their prognostic values in patients without vascular comorbidities.

Methods

This study selected 154 consecutive patients with positive chest computed tomography (CT) findings and no evidence of concurrent pulmonary disease. Clinical characteristics and adverse outcomes in in-hospital settings were collected retrospectively. Diameters of cardiac ventricles and arteries, along with lung opacification scores, were obtained using CT pulmonary angiography (CTPA) findings, and the association of these variables was evaluated.

Results

An increase in pulmonary artery (PA) to ascending aorta (AO) diameter ratio and lung parenchymal damage were significantly and positively correlated (P=0.017), but increased right ventricle (RV) to left ventricle (LV) diameter ratio showed no association with the extent of chest opacification (P=0.098). Evaluating the prognostic ability of both ratios using logistic regression and receiver operating characteristic (ROC) analysis proved no significant class separation in regards to predicting adverse outcomes (PA/AO: OR:1.081, P Value:0.638, RV/LV: OR:1.098, P Value:0.344).

Conclusion

In COVID-19 patients without vascular comorbidities, a higher PA/AO diameter ratio was significantly associated with increased lung involvement severity on CT imaging but not with adverse in-hospital outcomes. Conversely, an increased RV/LV ratio on CTPA did not correlate significantly with adverse outcomes or the severity of parenchymal lung damage.

Prevalence and prognostic role of thoracic lymphadenopathy in Covid-19

PURPOSE

 The prevalent coronavirus disease 2019 (COVID-19) pandemic has spread throughout the world and is considered a serious threat to global health. The prognostic role of thoracic lymphadenopathy in COVID-19 is unclear. The aim of the present meta-analysis was to analyze the prognostic role of thoracic lymphadenopathy for the prediction of 30-day mortality in patients with COVID-19.

MATERIALS AND METHODS

 The MEDLINE library, Cochrane, and SCOPUS databases were screened for associations between CT-defined features and mortality in COVID-19 patients up to June 2021. In total, 21 studies were included in the present analysis. The quality of the included studies was assessed by the Newcastle-Ottawa Scale. The meta-analysis was performed using RevMan 5.3. Heterogeneity was calculated by means of the inconsistency index I2. DerSimonian and Laird random-effect models with inverse variance weights were performed without any further correction.

RESULTS

 The included studies comprised 4621 patients. The prevalence of thoracic lymphadenopathy varied between 1 % and 73.4 %. The pooled prevalence was 16.7 %, 95 % CI = (15.6 %; 17.8 %). The hospital mortality was higher in patients with thoracic lymphadenopathy (34.7 %) than in patients without (20.0 %). The pooled odds ratio for the influence of thoracic lymphadenopathy on mortality was 2.13 (95 % CI = [1.80-2.52], p < 0.001).

CONCLUSION

 The prevalence of thoracic lymphadenopathy in COVID-19 is 16.7 %. The presence of thoracic lymphadenopathy is associated with an approximately twofold increase in the risk for hospital mortality in COVID-19.

KEY POINTS

  · The prevalence of lymphadenopathy in COVID-19 is 16.7 %.. · Patients with lymphadenopathy in COVID-19 have a higher risk of mortality during hospitalization.. · Lymphadenopathy nearly doubles mortality and plays an important prognostic role..

CITATION FORMAT

· Bucher AM, Sieren M, Meinel F et al. Prevalence and prognostic role of thoracic lymphadenopathy in Covid-19. Fortschr Röntgenstr 2024; DOI: 10.1055/a-2293-8132.

Pericardial Effusion Predicts Clinical Outcomes in Patients with COVID-19: A Nationwide Multicenter Study

RATIONALE AND OBJECTIVES

The prognostic role of pericardial effusion (PE) in Covid 19 is unclear. The aim of the present study was to estimate the prognostic role of PE in patients with Covid 19 in a large multicentre setting.

MATERIALS AND METHODS

This retrospective study is a part of the German multicenter project RACOON (Radiological Cooperative Network of the Covid 19 pandemic). The acquired sample comprises 1197 patients, 363 (30.3%) women and 834 (69.7%) men. In every case, chest computed tomography was analyzed for PE. Data about 30-day mortality, need for mechanical ventilation and need for intensive care unit (ICU) admission were collected. Data were evaluated by means of descriptive statistics. Group differences were calculated with Mann-Whitney test and Fisher exact test. Uni-and multivariable regression analyses were performed.

RESULTS

Overall, 46.4% of the patients were admitted to ICU, mechanical lung ventilation was performed in 26.6% and 30-day mortality was 24%. PE was identified in 159 patients (13.3%). The presence of PE was associated with 30-day mortality: HR= 1.54, CI 95% (1.05; 2.23), p = 0.02 (univariable analysis), and HR= 1.60, CI 95% (1.03; 2.48), p = 0.03 (multivariable analysis). Furthermore, density of PE was associated with the need for intubation (OR=1.02, CI 95% (1.003; 1.05), p = 0.03) and the need for ICU admission (OR=1.03, CI 95% (1.005; 1.05), p = 0.01) in univariable regression analysis. The presence of PE was associated with 30-day mortality in male patients, HR= 1.56, CI 95%(1.01-2.43), p = 0.04 (multivariable analysis). In female patients, none of PE values predicted clinical outcomes.

CONCLUSION

The prevalence of PE in Covid 19 is 13.3%. PE is an independent predictor of 30-day mortality in male patients with Covid 19. In female patients, PE plays no predictive role.

Epicardial Adipose Tissue as a Prognostic Marker in COVID-19

BACKGROUND/AIM

Epicardial adipose tissue (EAT) has been established as a quantitative imaging biomarker associated with the prognosis of several diseases, especially cardiovascular diseases. The cardiac injury by coronavirus disease 2019 (COVID-19) might be linked to the EAT. This study aimed to use this prognostic marker derived from computed tomography (CT) images to predict 30-day mortality in patients with COVID-19.

PATIENTS AND METHODS

Consecutive patients with COVID-19 were retrospectively screened between 2020 and 2022. Overall, 237 patients (78 female, 32.9%) were included in the present study. The study end-point was the 30-day mortality. EAT was measured using the diagnostic CT in a semiquantitative manner. EAT volume and density were measured for each patient.

RESULTS

Overall, 70 patients (29.5%) died within the 30-day observation period and 143 patients (60.3%) were admitted to the intensive care unit (ICU). The mean EAT volume was 140.9±89.1 cm3 in survivors and 132.9±77.7 cm3 in non-survivors, p=0.66. The mean EAT density was -71.9±8.1 Hounsfield units (HU) in survivors, and -67.3±8.4 HU in non-survivors, p=0.0001. EAT density was associated with 30-day mortality (p<0.0001) and ICU admission (p<0.0001). EAT volume was not associated with mortality and/or ICU admission.

CONCLUSION

EAT density was associated with 30-day mortality and ICU admission in patients with COVID-19.

Diagnosis of COVID-19 with simultaneous accurate prediction of cardiac abnormalities from chest computed tomographic images

COVID-19 has potential consequences on the pulmonary and cardiovascular health of millions of infected people worldwide. Chest computed tomographic (CT) imaging has remained the first line of diagnosis for individuals infected with SARS-CoV-2. However, differentiating COVID-19 from other types of pneumonia and predicting associated cardiovascular complications from the same chest-CT images have remained challenging. In this study, we have first used transfer learning method to distinguish COVID-19 from other pneumonia and healthy cases with 99.2% accuracy. Next, we have developed another CNN-based deep learning approach to automatically predict the risk of cardiovascular disease (CVD) in COVID-19 patients compared to the normal subjects with 97.97% accuracy. Our model was further validated against cardiac CT-based markers including cardiac thoracic ratio (CTR), pulmonary artery to aorta ratio (PA/A), and presence of calcified plaque. Thus, we successfully demonstrate that CT-based deep learning algorithms can be employed as a dual screening diagnostic tool to diagnose COVID-19 and differentiate it from other pneumonia, and also predicts CVD risk associated with COVID-19 infection.

Pulmonary artery diameter and NT-proBNP in patients with Covid-19: Predicting prognosis and mortality

Background

The diverse and complex presentations of COVID-19 continue to impact the world. Factors related to prognosis and mortality are still not fully illuminated.

Objectives

We aimed to asses the relationship of N-terminal pro B-type natriuretic peptide (NT-proBNP) and main pulmonary artery diameter (MPAD) with COVID-19 prognosis and mortality.

Methods

152 COVID-19 patients over the age of 18, were included in the study. Thoracic CT, NT-proBNP values, laboratory and demographic data of these patients were obtained by retrospectively examining the patient files and scanning the results through the patient registry.

Results

According to multivariate logistic regression (LR) analysis, high NT-proBNP level (OR=3.542; 95% CI=1.745-9.463; p=0.021) and MPAD/ascending aortic diameter (AAD) ratio>0.75 (OR=2.692; 95% CI=1.264-9.312; p=0.036) were determined as independent risk factors predicting mortality in COVID-19 patients. A significant positive correlation was observed between NT-proBNP level and MPA diameter (r=0.296, p<0.001). The cut-off value was measured as 27.5 mm for MPA diameter and 742 pg/ml for NT-proBNP.

Conclusions

Accurate and effective interpretation of available radiological and laboratory data is essential to reveal the factors predicting prognosis and mortality in COVID-19. In this study,we evaluated that the thorax CTs and determined that the MPAD/AAD and NT-proBNP level were independent risk factors in predicting mortality.

Lung Injury in COVID-19 Has Pulmonary Edema as an Important Component and Treatment with Furosemide and Negative Fluid Balance (NEGBAL) Decreases Mortality

The SARS-CoV2 promotes dysregulation of Renin-Angiotensin-Aldosterone. The result is excessive retention of water, producing a state of noxious hypervolemia. Consequently, in COVID-19 injury lung is pulmonary edema. Our report is a case-control study, retrospective. We included 116 patients with moderate-severe COVID-19 lung injury. A total of 58 patients received standard care (Control group). A total of 58 patients received a standard treatment with a more negative fluid balance (NEGBAL group), consisting of hydric restriction and diuretics. Analyzing the mortality of the population studied, it was observed that the NEGBAL group had lower mortality than the Control group, p = 0.001. Compared with Controls, the NEGBAL group had significantly fewer days of hospital stay (p < 0.001), fewer days of ICU stay (p < 0.001), and fewer days of IMV (p < 0.001). The regressive analysis between PaO₂/FiO₂BAL and NEGBAL demonstrated correlation (p = 0.04). Compared with Controls, the NEGBAL group showed significant progressive improvement in PaO₂/FiO₂ (p < 0.001), CT score (p < 0.001). The multivariate model, the vaccination variables, and linear trends resulted in p = 0.671 and quadratic trends p = 0.723, whilst the accumulated fluid balance is p < 0.001. Although the study has limitations, the promising results encourage more research on this different therapeutic approach, since in our research it decreases mortality.

Association of the changes in pulmonary artery diameters with clinical outcomes in hospitalized patients with COVID-19 infection: A crosssectional study

Objective: Enlarged pulmonary artery diameter (PAD) can be associated with mortality risk in coronavirus disease 2019 (COVID-19) patients. Our aim is to find the factors that cause changes in PAD and the relationship between radiological findings and clinical outcomes in COVID-19 patients. Patients and Methods: In this descriptive, retrospective, and single centered study, among the hospitalized 3264 patients, 209 patients with previous chest computed tomography (CT) were included. Findings of current chest CTs of patients obtained during COVID-19 were compared with that of previous chest CTs. Pulmonary involvements, World Health Organization (WHO) Clinical Progression Scale scores and laboratory variables were recorded. Intensive Care Unit (ICU) admission, intubation and mortality were clinical outcomes that were evaluated by using uni – and multivariate analyses. Results: Patients with high D-dimer had significantly increased risk for enlarged PAD and increase in PAD compared to previous chest CT (ΔPAD) (OR=1.18, p

Prognostic utility of cardiovascular indices in COVID-19 infection: A single-center prospective study in India

Background

Cardiac signs can show illness progression and severity in a number of respiratory and cardiovascular disorders. The possible importance of CT findings in the prognosis and result of COVID-19 patients is related to the severity of lung disease and cardiac parameters. The CT-assessed cardiac indices are known for predicting the involvement of extent of diseases. Hence, the objective of this study was to correlate the extent of cardiovascular and respiratory involvement in predicting the severity of disease using CT-assessed cardiac indices in Indian population suffering from COVID-19.

Methodology

A total of 120 COVID-19 patients were included following the inclusion criteria for one year. The confounding factors were assessed and analyzed. The correlation between the cumulative hazard function of death and duration in hospital along with survival rate were done in terms of pulmonary artery-to-aorta ratio (PA/A), and cardiothoracic ratio (CTR).

Results

The analysis showed mean age of patients to be 49.5(±15.32) years in which mean females were 38(±31.7) and males were 82(±68.3). The interquartile range of CT severity was 8. The PA/A ratio in discharged patients was 0.85 when compared to deceased patients with 1.03 having statistically significant inference (P = 0.00). The CTR (P = 0.00), epicardial adipose thickness (P = 0.00), epicardial adipose density (P = 0.00), and D-dimer (P = 0.007) were showing statistically significant inference.

Conclusion

The predictive values of CT-assessed cardiac indices might be used for predicting the involvement of cardiovascular and respiratory involvement in COVID-19 patients. It could have an impact on improving the possibilities of survival of patients suffering from COVID-19 in India.

Association of epicardial adipose tissue with the severity and adverse clinical outcomes of COVID-19: A meta-analysis

Objectives

Epicardial adipose tissue (EAT) has been proposed to be an independent predictor of visceral adiposity. EAT measures are associated with coronary artery disease, diabetes, and chronic obstructive pulmonary disease, which are risk factors for COVID-19 poor prognosis. Whether EAT measures are related to COVID-19 severity and prognosis is controversial.

Methods

We searched 6 databases for studies until January 7, 2022. The pooled effects are presented as the standard mean difference (SMD) or weighted mean difference with 95% confidence intervals (CIs). The primary end point was COVID-19 severity. Adverse clinical outcomes were also assessed.

Results

A total of 13 studies with 2482 patients with COVID-19 were identified. All patients had positive reverse transcriptase-polymerase chain reaction results. All quantitative EAT measures were based on computed tomography. Patients in the severe group had higher EAT measures compared with the nonsevere group (SMD = 0.74, 95% CI: 0.29–1.18, P = 0.001). Patients with hospitalization requirement, requiring invasive mechanical ventilation, admitted to intensive care unit, or with combined adverse outcomes had higher EAT measures compared to their controls (all P < 0.001).

Conclusions

EAT measures were associated with the severity and adverse clinical outcomes of COVID-19. EAT measures might help in prognostic risk stratification of patients with COVID-19.

Automatic Deep-Learning Segmentation of Epicardial Adipose Tissue from Low-Dose Chest CT and Prognosis Impact on COVID-19

Background: To develop a deep-learning (DL) pipeline that allowed an automated segmentation of epicardial adipose tissue (EAT) from low-dose computed tomography (LDCT) and investigate the link between EAT and COVID-19 clinical outcomes. Methods: This monocentric retrospective study included 353 patients: 95 for training, 20 for testing, and 238 for prognosis evaluation. EAT segmentation was obtained after thresholding on a manually segmented pericardial volume. The model was evaluated with Dice coefficient (DSC), inter-and intraobserver reproducibility, and clinical measures. Uni-and multi-variate analyzes were conducted to assess the prognosis value of the EAT volume, EAT extent, and lung lesion extent on clinical outcomes, including hospitalization, oxygen therapy, intensive care unit admission and death. Results: The mean DSC for EAT volumes was 0.85 ± 0.05. For EAT volume, the mean absolute error was 11.7 ± 8.1 cm3 with a non-significant bias of −4.0 ± 13.9 cm3 and a correlation of 0.963 with the manual measures (p < 0.01). The multivariate model providing the higher AUC to predict adverse outcome include both EAT extent and lung lesion extent (AUC = 0.805). Conclusions: A DL algorithm was developed and evaluated to obtain reproducible and precise EAT segmentation on LDCT. EAT extent in association with lung lesion extent was associated with adverse clinical outcomes with an AUC = 0.805.

Extrapulmonary CT Findings Predict In-Hospital Mortality in COVID-19. A Systematic Review and Meta-Analysis

RATIONALE AND OBJECTIVES

Several prognostic factors have been identified for COVID-19 disease. Our aim was to elucidate the influence of non-pulmonary findings of thoracic computed tomography (CT) on unfavorable outcomes and in-hospital mortality in COVID-19 patients based on a large patient sample.

MATERIALS AND METHODS

MEDLINE library, Cochrane and SCOPUS databases were screened for the associations between CT-defined features and mortality in COVID-19 patients up to June 2021. In total, 22 studies were suitable for the analysis, and included into the present analysis. Overall, data regarding 4 extrapulmonary findings could be pooled: pleural effusion, pericardial effusion, mediastinal lymphadenopathy, and coronary calcification.

RESULTS

The included studies comprised 7859 patients. The pooled odds ratios for the effect of the identified extrapulmonary findings on in-hospital mortality are as follows: pleural effusion, 4.60 (95% CI 2.97-7.12); pericardial effusion, 1.29 (95% CI 0.83-1.98); coronary calcification, 2.68 (95% CI 1.78-4.04); mediastinal lymphadenopathy, 2.02 (95% CI 1.18-3.45).

CONCLUSION

Pleural effusion, mediastinal lymphadenopathy and coronary calcification have a relevant association with in-hospital mortality in COVID-19 patients and should be included as prognostic biomarker into clinical routine.

Role of cardiovascular computed tomography parameters and lungs findings in predicting severe COVID-19 patients: a single-centre retrospective study

Background

Results

Conclusions

Epicardial and pericoronary adipose tissue in severe COVID-19 infection

OBJECTIVE

To investigate the association between epicardial and pericoronary adipose tissue thicknesses measured with computed tomography (CT) and severity of COVID-19 infection.

METHODS

We recruited 504 patients admitted with RT-PCR-proven diagnosis of COVID-19 infection and underwent simultaneous Chest CT scanning. Epicardial adipose tissue thickness (EAT) and pericardial adipose tissue thickness (PCAT) were measured by CT. Comparisons were performed between ICU admitting and non-ICU admitting patients were performed.

RESULTS

Of 504 patients, 423 patients were hospitalised in normal wards or followed as outpatient, and 81 patients were admitted to ICU. EAT and PCAT were significantly increased in ICU patients (5.98[5.06-7.13] mm vs. 8.05[6.90-9.89] mm, p < 0.001 and 9.3[7.4-11.5] mm vs. 11.2[10.3-13.2] mm, p < 0.001, respectively). In multiple logistic regression analyses, EAT and PCAT were independent predictors of ICU admission. A cut-off point of 6.64 mm EAT has a sensitivity of 82.7% and a specificity of 66.7% (AUC = 0.789, 95% CI: 0.744-0.833, p < 0.001) and a cut-off point of 9.85 mm PCAT has a sensitivity of 91.4% and a specificity of 61.2% (AUC = 0.744, 95% CI: 0.700-0.788, p < 0.001).

CONCLUSION

We found that both increased EAT and PCAT were associated with the severity of COVID-19 infection defined as the need for ICU admission.

Radiological Cardiothoracic Ratio as a Potential Predictor of Right Ventricular Enlargement in Patients with Suspected Pulmonary Embolism Due to COVID-19

The aim of the study was to determine the usefulness of the radiological cardiothoracic ratio (CTR) as a predictor of right ventricular enlargement in patients with suspected pulmonary embolism during COVID-19. The study group consisted of 61 patients with confirmed COVID-19, suspected of pulmonary embolism based on physical examination and laboratory tests (age: 67.18 ± 12.47 years). Computed tomography angiography (CTA) of pulmonary arteries and chest radiograph in AP projection with cardiothoracic ratio assessment were performed in all patients. Right ventricular enlargement was diagnosed by the ratio of right ventricular to left ventricular (RV/LV) dimensions in pulmonary CTA with two cut-off points: ≥0.9 and ≥1.0. Heart silhouette enlargement was found when CTR on the chest radiograph in the projection AP > 0.55. The mean values of RV/LV and CTR in the studied group were 0.96 ± 0.23 and 0.57 ± 0.05, respectively. Pulmonary embolism was diagnosed in 45.9%. Right ventricular enlargement was documented in 44.3% or 29.5% depending on the adopted criterion RV/LV ≥ 0.9 or RV/LV ≥ 1.0. Heart silhouette enlargement was found in 60.6%. Patients with confirmed pulmonary embolism (PE+) had a significantly higher RV/LV ratio and CTR than patients with excluded pulmonary embolism (PE−) (RV/LV: PE+ 1.08 ± 0.24, PE− 0.82 ± 0.12; CTR: PE+ 0.60 ± 0.05, PE− 0.54 ± 0.04; p < 0.05). The correlation analysis showed a statistically significant positive correlation between the RV/LV ratio and CTR (r = 0.59, p < 0.05). Based on the ROC curves, CTR values were determined as the optimal cut-off points for the prediction of right ventricular enlargement (RV/LV ≥ 0.9 or RV/LV ≥ 1.0), being 0.54 and 0.55, respectively. The sensitivity, specificity, and accuracy of the CTR criterion >0.54 as a predictor of RV/LV ratio ≥0.9 were 0.412, 0.963, and 0.656, respectively, while those of the CTR criterion >0.55 as a predictor of RV/LV ratio ≥1.0 were 0.488, 0.833, and 0.590, respectively. In summary, in patients with suspected pulmonary embolism during COVID-19, the radiographic cardiothoracic ratio can be considered as a prognostic factor for right ventricular enlargement, especially as a negative predictor of right ventricular enlargement in the case of lower CTR values.

Pulmonary Edema in COVID-19 Treated with Furosemide and Negative Fluid Balance (NEGBAL): A Different and Promising Approach

In COVID-19, pulmonary edema has been attributed to “cytokine storm”. However, it is known that SARS-CoV2 promotes angiotensin-converting enzyme 2 deficit, increases angiotensin II, and this triggers volume overload. Our report is based on COVID-19 patients with tomographic evidence of pulmonary edema and volume overload to whom established a standard treatment with diuretic (furosemide) guided by objectives: Negative Fluid Balance (NEGBAL approach). Retrospective observational study. We reviewed data from medical records: demographic, clinical, laboratory, blood gas, and chest tomography (CT) before and while undergoing NEGBAL, from 20 critically ill patients. Once the NEGBAL strategy was started, no patient required mechanical ventilation. All cases reverted to respiratory failure with NEGBAL, but subsequently two patients died from sepsis and acute myocardial infarction (AMI). The regressive analysis between PaO2/FiO2BAL and NEGBAL demonstrated correlation (p < 0.032). The results comparing the Pao2Fio2 between admission to NEGBAL to NEGBAL day 4, were statistically significant (p < 0.001). We noted between admission to NEGBAL and day 4 improvement in CT score (p < 0.001), decrease in the superior vena cava diameter (p < 0.001) and the decrease of cardiac axis (p < 0.001). Though our study has several limitations, we believe the promising results encourage further investigation of this different pathophysiological approach.

The effect of cardiovascular disease and acute cardiac injury on fatal COVID-19: a meta-analysis

BACKGROUND

With the continuance of the global COVID-19 pandemic, cardiovascular disease (CVD) and cardiac injury have been suggested to be risk factors for severe COVID-19.

OBJECTIVE

The aim is to evaluate the mortality risks associated with CVD and cardiac injury among hospitalized COVID-19 patients, especially in subgroups of populations in different countries.

METHODS

A comprehensive systematic literature search was performed using 9 databases from November 1, 2019 to November 9, 2020. Meta-analyses were performed for CVD and cardiac injury between non-survivors and survivors of COVID-19.

RESULTS

Although the prevalence of CVD in different populations was different, hospitalized COVID-19 patients with CVD were at a higher risk of fatal outcomes (OR = 2.72; 95% CI 2.35-3.16) than those without CVD. Separate meta-analyses of populations in four different countries also reached a similar conclusion that CVD was associated with an increase in mortality. Cardiac injury was common among hospitalized COVID-19 patients. Patients with cardiac injury had a significantly higher mortality risk than those without cardiac injury (OR = 13.25; 95% CI: 8.56-20.52).

CONCLUSIONS

Patients' CVD history and biomarkers of cardiac injury should be taken into consideration during the hospital stay and incorporated into the routine laboratory panel for COVID-19.

The Prognostic Value of Vertebral Bone Density on Chest CT in Hospitalized COVID-19 Patients

The aim of this study is to evaluate the prognostic value of the vertebral bone mineral density (BMD) on chest computed tomography (CT) in COVID-19 patients. The chest CT of hospitalized patients with COVID-19 pneumonia were evaluated for Pneumonia Severity Score (PSS) as the ratio of the volume of involved lung parenchyma to the total lung volume. In addition, BMD was manually measured from the vertebral corpus using axial CT images. The relationships of clinical variables, PSS and vertebral BMD with patient outcomes, namely mortality, intensive care unit (ICU) admission and mechanical ventilation were investigated. Lower BMD was defined as ≤100 HU. The study included 209 patients (118 males, 56.4%). As a result of the univariate analysis, the rates of mortality, ICU admission and mechanical ventilation were 17.2% (n = 36), 24.8% (n = 52), and 20.6% (n = 43), respectively, and they were significantly higher among the patients with lower BMD (38.1 vs 13.0%, p < 0.001; 33.4 vs 21.2%, p = 0.002; and 38.1 vs 8.2%, p < 0.001, respectively). In the mortality group, PSS was significantly higher (median, 9 vs 5; p < 0.001) and vertebral BMD was significantly lower (median, 83 vs 139; p < 0.001). Severe clinical incidence was significantly higher in patients with lower BMD compared to those with higher BMD (39.7 vs 24.7% and p = 0.028). There was a significant correlation between clinical classification and lower BMD (r = 0.152 and p = 0.028). The multivariate analysis revealed vertebral BMD [odds ratio (OR), 1.028; 95% CI, 1.011-1.045, p = 0.001) and lower BMD (OR, 4.682; 95% CI, 1.784-12.287, p = 0.002) as significant independent predictors of mortality. Vertebral BMD is a strong independent predictor of mortality that is reproducible and can be easily evaluated on the chest CT images of COVID-19 patients.

Predicting Severe/Critical Outcomes in Patients With SARS-CoV2 Pneumonia: Development of the prediCtion seveRe/crItical ouTcome in COVID-19 (CRITIC) Model

Objective: To create a prediction model of the risk of severe/critical disease in patients with Coronavirus disease (COVID-19). Methods: Clinical, laboratory, and lung computed tomography (CT) severity score were collected from patients admitted for COVID-19 pneumonia and considered as independent variables for the risk of severe/critical disease in a logistic regression analysis. The discriminative properties of the variables were analyzed through the area under the receiver operating characteristic curve analysis and included in a prediction model based on Fagan's nomogram to calculate the post-test probability of severe/critical disease. All analyses were conducted using Medcalc (version 19.0, MedCalc Software, Ostend, Belgium). Results: One hundred seventy-one patients with COVID-19 pneumonia, including 37 severe/critical cases (21.6%) and 134 mild/moderate cases were evaluated. Among all the analyzed variables, Charlson Comorbidity Index (CCI) was that with the highest relative importance (p = 0.0001), followed by CT severity score (p = 0.0002), and age (p = 0.0009). The optimal cut-off points for the predictive variables resulted: 3 for CCI [sensitivity 83.8%, specificity 69.6%, positive likelihood ratio (+LR) 2.76], 69.9 for age (sensitivity 94.6%, specificity 68.1, +LR 2.97), and 53 for CT severity score (sensitivity 64.9%, specificity 84.4%, +LR 4.17). Conclusion: The nomogram including CCI, age, and CT severity score, may be used to stratify patients with COVID-19 pneumonia.

Cardiac adipose tissue volume and IL-6 level at admission are complementary predictors of severity and short-term mortality in COVID-19 diabetic patients

BACKGROUND

COVID-19 diabetic adults are at increased risk of severe forms irrespective of obesity. In patients with type-II diabetes, fat distribution is characterized by visceral and ectopic adipose tissues expansion, resulting in systemic inflammation, which may play a role in driving the COVID-19 cytokine storm. Our aim was to determine if cardiac adipose tissue, combined to interleukin-6 levels, could predict adverse short-term outcomes, death and ICU requirement, in COVID-19 diabetic patients during the 21 days after admission.

METHODS

Eighty one consecutive patients with type-II diabetes admitted for COVID-19 were included. Interleukin-6 measurement and chest computed tomography with total cardiac adipose tissue index (CATi) measurement were performed at admission. The primary outcome was death during the 21 days following admission while intensive care requirement with or without early death (ICU-R) defined the secondary endpoint. Associations of CATi and IL-6 and threshold values to predict the primary and secondary endpoints were determined.

RESULTS

Of the enrolled patients (median age 66 years [IQR: 59-74]), 73% male, median body mass index (BMI) 27 kg/m² [IQR: 24-31]) 20 patients had died from COVID-19, 20 required intensive care and 41 were in conventional care at day 21 after admission. Increased CATi and IL-6 levels were both significantly related to increased early mortality (respectively OR = 6.15, p = 0.002; OR = 18.2, p < 0.0001) and ICU-R (respectively OR = 3.27, p = 0.01; OR = 4.86, p = 0.002). These associations remained significant independently of age, sex, BMI as well as troponin-T level and pulmonary lesion extension in CT. We combined CATi and IL-6 levels as a multiplicative interaction score (CATi*IL-6). The cut-point for this score was ≥ 6386 with a sensitivity of 0.90 and a specificity of 0.87 (AUC = 0.88) and an OR of 59.6 for early mortality (p < 0.0001).

CONCLUSIONS

Cardiac adipose tissue index and IL-6 determination at admission could help physicians to better identify diabetic patients with a potentially severe and lethal short term course irrespective of obesity. Diabetic patients with high CATi at admission, a fortiori associated with high IL-6 levels could be a relevant target population to promptly initiate anti-inflammatory therapies.

Prognostic utility of pulmonary artery and ascending aorta diameters derived from computed tomography in COVID-19 patients

Aim

Chest computed tomography (CT) imaging plays a diagnostic and prognostic role in Coronavirus disease 2019 (COVID‐19) patients. This study aimed to investigate and compare predictive capacity of main pulmonary artery diameter (MPA), ascending aorta diameter (AAo), and MPA‐to‐AAo ratio to determine in‐hospital mortality in COVID‐19 patients.

Materials and methods

This retrospective study included 255 hospitalized severe or critical COVID‐19 patients. MPA was measured at the level of pulmonary artery bifurcation perpendicular to the direction of the vessel through transverse axial images and AAo was measured by using the same CT slice at its maximal diameter. MPA‐to‐AAo ratio was calculated by division of MPA to AAo.

Results

Multivariate logistic regression model yielded MPA ≥29.15 mm (OR: 4.95, 95% CI: 2.01–12.2, p = 0.001), MPA (OR: 1.28, 95% CI: 1.13–1.46, p < 0.001), AAo (OR: .90, 95% CI: .81–.99, p = 0.040), and MPA‐to‐AAo ratio ≥.82 (OR: 4.67, 95% CI: 1.86–11.7, p = 0.001) as independent predictors of in‐hospital mortality. Time‐dependent multivariate Cox‐proportion regression model demonstrated MPA ≥29.15 mm (HR: 1.96, 95% CI: 1.03–3.90, p = 0.047) and MPA (HR: 1.08, 95% CI: 1.01–1.17, p = 0.048) as independent predictors of in‐hospital mortality, whereas AAo and MPA‐to‐AAo ratio did not reach statistical significance.

Conclusion

Pulmonary artery enlargement strongly predicts in‐hospital mortality in hospitalized COVID‐19 patients. MPA, which can be calculated easily from chest CT imaging, can be beneficial in the prognostication of these patients.

Epicardial adipose tissue and severe Coronavirus Disease 19

BACKGROUND

Both visceral adipose tissue and epicardial adipose tissue (EAT) have pro-inflammatory properties. The former is associated with Coronavirus Disease 19 (COVID-19) severity. We aimed to investigate whether an association also exists for EAT.

MATERIAL AND METHODS

We retrospectively measured EAT volume using computed tomography (CT) scans (semi-automatic software) of inpatients with COVID-19 and analyzed the correlation between EAT volume and anthropometric characteristics and comorbidities. We then analyzed the clinicobiological and radiological parameters associated with severe COVID-19 (O2 [Formula: see text] 6 l/min), intensive care unit (ICU) admission or death, and 25% or more CT lung involvement, which are three key indicators of COVID-19 severity.

RESULTS

We included 100 consecutive patients; 63% were men, mean age was 61.8 ± 16.2 years, 47% were obese, 54% had hypertension, 42% diabetes, and 17.2% a cardiovascular event history. Severe COVID-19 (n = 35, 35%) was associated with EAT volume (132 ± 62 vs 104 ± 40 cm³, p = 0.02), age, ferritinemia, and 25% or more CT lung involvement. ICU admission or death (n = 14, 14%) was associated with EAT volume (153 ± 67 vs 108 ± 45 cm³, p = 0.015), hypertension and 25% or more CT lung involvement. The association between EAT volume and severe COVID-19 remained after adjustment for sex, BMI, ferritinemia and lung involvement, but not after adjustment for age. Instead, the association between EAT volume and ICU admission or death remained after adjustment for all five of these parameters.

CONCLUSIONS

Our results suggest that measuring EAT volume on chest CT scans at hospital admission in patients diagnosed with COVID-19 might help to assess the risk of disease aggravation.

Machine Learning to Predict In-Hospital Mortality in COVID-19 Patients Using Computed Tomography-Derived Pulmonary and Vascular Features

Pulmonary parenchymal and vascular damage are frequently reported in COVID-19 patients and can be assessed with unenhanced chest computed tomography (CT), widely used as a triaging exam. Integrating clinical data, chest CT features, and CT-derived vascular metrics, we aimed to build a predictive model of in-hospital mortality using univariate analysis (Mann-Whitney U test) and machine learning models (support vectors machines (SVM) and multilayer perceptrons (MLP)). Patients with RT-PCR-confirmed SARS-CoV-2 infection and unenhanced chest CT performed on emergency department admission were included after retrieving their outcome (discharge or death), with an 85/15% training/test dataset split. Out of 897 patients, the 229 (26%) patients who died during hospitalization had higher median pulmonary artery diameter (29.0 mm) than patients who survived (27.0 mm, p < 0.001) and higher median ascending aortic diameter (36.6 mm versus 34.0 mm, p < 0.001). SVM and MLP best models considered the same ten input features, yielding a 0.747 (precision 0.522, recall 0.800) and 0.844 (precision 0.680, recall 0.567) area under the curve, respectively. In this model integrating clinical and radiological data, pulmonary artery diameter was the third most important predictor after age and parenchymal involvement extent, contributing to reliable in-hospital mortality prediction, highlighting the value of vascular metrics in improving patient stratification.

Coronary artery calcification and epicardial adipose tissue as independent predictors of mortality in COVID-19

Recent epidemiological studies have demonstrated that common cardiovascular risk factors are strongly associated with adverse outcomes in COVID-19. Coronary artery calcium (CAC) and epicardial fat (EAT) have shown to outperform traditional risk factors in predicting cardiovascular events in the general population. We aim to determine if CAC and EAT determined by Computed Tomographic (CT) scanning can predict all-cause mortality in patients admitted with COVID-19 disease. We performed a retrospective, post-hoc analysis of all patients admitted to Montefiore Medical Center with a confirmed COVID-19 diagnosis from March 1st, 2020 to May 2nd, 2020 who had a non-contrast CT of the chest within 5 years prior to admission. We determined ordinal CAC scores and quantified the epicardial (EAT) and thoracic (TAT) fat volume and examined their relationship with inpatient mortality. A total of 493 patients were analyzed. There were 197 deaths (39.95%). Patients who died during the index admission had higher age (72, [64–80] vs 68, [57–76]; p < 0.001), CAC score (3, [0–6] vs 1, [0–4]; p < 0.001) and EAT (107, [70–152] vs 94, [64–129]; p = 0.023). On a competing risk analysis regression model, CAC ≥ 4 and EAT ≥ median (98 ml) were independent predictors of mortality with increased mortality of 63% (p = 0.003) and 43% (p = 0.032), respectively. As a composite, the group with a combination of CAC ≥ 4 and EAT ≥ 98 ml had the highest mortality. CAC and EAT measured from chest CT are strong independent predictors of inpatient mortality from COVID-19 in this high-risk cohort.

Pathophysiology and Imaging Findings of COVID-19 Infection: An Organ-system Based Review

BACKGROUND

COVID-19 commonly presents with upper respiratory symptoms; however, studies have shown that SARS-CoV-2 infection affects multiple organ systems. Here, we review the pathophysiology and imaging characteristics of SARS-CoV-2 infection in organ systems throughout the body and explore commonalities.

OBJECTIVE

Familiarity with the underlying pathophysiology and imaging characteristics is essential for the radiologist to recognize these findings in patients with COVID-19 infection. Though pulmonary findings are the most prevalent presentation, COVID-19 may have multiple manifestations and recognition of the extrapulmonary manifestations is especially important because of the potential serious and long-term effects of COVID-19 on multiple organ systems.

Pulmonary vascular enlargement and lesion extent on computed tomography are correlated with COVID-19 disease severity

PURPOSE

To assess the relationships among pulmonary vascular enlargement, computed tomography (CT) findings quantified with software, and coronavirus disease (COVID-19) severity.

MATERIALS AND METHODS

Ultra-high-resolution (UHR) CT images of 87 patients (50 males, 37 females; median age, 63 years) with COVID-19 confirmed using real-time polymerase chain reaction were analyzed. The maximum subsegmental vascular diameter was measured on CT. Total CT lung volume (CTLV total) and lesion extent (ratio of lesion volume to CTLV total) of ground-glass opacities, reticulation, and consolidation were measured using software. Maximum pulmonary vascular diameter and lesion extent were analyzed using Spearman's correlation analysis. Logistic regression analysis was performed on CT results to predict disease severity. We also assessed changes in these measures on follow-up scans in 16 patients.

RESULTS

All 23 patients with severe and critical illness had vascular enlargement (> 4 mm). Pulmonary vascular enlargement (odds ratio 3.05, p = 0.018) and CT lesion extent (odds ratio 1.07, p = 0.002) were independent predictors of disease severity after adjustment for age and comorbidities. On follow-up CT, vascular diameter and CT lesion volume decreased (p = 0.001, p = 0.002; respectively), but CTLV total did not change significantly.

CONCLUSION

Subsegmental vascular enlargement is a notable finding to predict acute COVID-19 disease severity.