Increased KL-6 levels in moderate to severe COVID-19 infection.

BACKGROUND: The global coronavirus disease 2019 (COVID-19) has presented significant challenges and created concerns worldwide. Besides, patients who have experienced a SARS-CoV-2 infection could present post-viral complications that can ultimately lead to pulmonary fibrosis. Serum levels of Krebs von den Lungen 6 (KL-6), high molecular weight human MUC1 mucin, are increased in the most patients with various interstitial lung damage. Since its production is raised during epithelial damages, KL-6 could be a helpful non-invasive marker to monitor COVID-19 infection and predict post-infection sequelae. METHODS: We retrospectively evaluated KL-6 levels of 222 COVID-19 infected patients and 70 healthy control. Serum KL-6, fibrinogen, lactate dehydrogenase (LDH), platelet-lymphocytes ratio (PLR) levels and other biological parameters were analyzed. This retrospective study also characterized the relationships between serum KL-6 levels and pulmonary function variables. RESULTS: Our results showed that serum KL-6 levels in COVID-19 patients were increased compared to healthy subjects (470 U/ml vs 254 U/ml, P <0.00001). ROC curve analysis enabled us to identify that KL-6 > 453.5 U/ml was associated with COVID-19 (AUC = 0.8415, P < 0.0001). KL-6 level was positively correlated with other indicators of disease severity such as fibrinogen level (r = 0.1475, P = 0.0287), LDH level (r = 0,31, P = 0,004) and PLR level (r = 0.23, P = 0.0005). However, KL-6 levels were not correlated with pulmonary function tests (r = 0.04, P = 0.69). CONCLUSIONS: KL-6 expression was correlated with several disease severity indicators. However, the association between mortality and long-term follow-up outcomes needs further investigation. More extensive trials are required to prove that KL-6 could be a marker of disease severity in COVID-19 infection.

Automatized lung disease quantification in patients with COVID-19 as a predictive tool to assess hospitalization severity.

The pandemic of COVID-19 led to a dramatic situation in hospitals, where staff had to deal with a huge number of patients in respiratory distress. To alleviate the workload of radiologists, we implemented an artificial intelligence (AI) - based analysis named CACOVID-CT, to automatically assess disease severity on chest CT scans obtained from those patients. We retrospectively studied CT scans obtained from 476 patients admitted at the University Hospital of Liege with a COVID-19 disease. We quantified the percentage of COVID-19 affected lung area (% AA) and the CT severity score (total CT-SS). These quantitative measurements were used to investigate the overall prognosis and patient outcome: hospital length of stay (LOS), ICU admission, ICU LOS, mechanical ventilation, and in-hospital death. Both CT-SS and % AA were highly correlated with the hospital LOS, the risk of ICU admission, the risk of mechanical ventilation and the risk of in-hospital death. Thus, CAD4COVID-CT analysis proved to be a useful tool in detecting patients with higher hospitalization severity risk. It will help for management of the patients flow. The software measured the extent of lung damage with great efficiency, thus relieving the workload of radiologists.

Bone Marrow-Derived Mesenchymal Stromal Cell Therapy in Severe COVID-19: Preliminary Results of a Phase I/II Clinical Trial.

Background: Treatment of acute respiratory distress syndrome (ARDS) associated with COronaVIrus Disease-2019 (COVID-19) currently relies on dexamethasone and supportive mechanical ventilation, and remains associated with high mortality. Given their ability to limit inflammation, induce immune cells into a regulatory phenotype and stimulate tissue repair, mesenchymal stromal cells (MSCs) represent a promising therapy for severe and critical COVID-19 disease, which is associated with an uncontrolled immune-mediated inflammatory response. Methods: In this phase I-II trial, we aimed to evaluate the safety and efficacy of 3 intravenous infusions of bone marrow (BM)-derived MSCs at 3-day intervals in patients with severe COVID-19. All patients also received dexamethasone and standard supportive therapy. Between June 2020 and September 2021, 8 intensive care unit patients requiring supplemental oxygen (high-flow nasal oxygen in 7 patients, invasive mechanical ventilation in 1 patient) were treated with BM-MSCs. We retrospectively compared the outcomes of these MSC-treated patients with those of 24 matched control patients. Groups were compared by paired statistical tests. Results: MSC infusions were well tolerated, and no adverse effect related to MSC infusions were reported (one patient had an ischemic stroke related to aortic endocarditis). Overall, 3 patients required invasive mechanical ventilation, including one who required extracorporeal membrane oxygenation, but all patients ultimately had a favorable outcome. Survival was significantly higher in the MSC group, both at 28 and 60 days (100% vs 79.2%, p = 0.025 and 100% vs 70.8%, p = 0.0082, respectively), while no significant difference was observed in the need for mechanical ventilation nor in the number of invasive ventilation-free days, high flow nasal oxygenation-free days, oxygen support-free days and ICU-free days. MSC-treated patients also had a significantly lower day-7 D-dimer value compared to control patients (median 821.0 µg/L [IQR 362.0-1305.0] vs 3553 µg/L [IQR 1155.0-6433.5], p = 0.0085). Conclusions: BM-MSC therapy is safe and shows very promising efficacy in severe COVID-19, with a higher survival in our MSC cohort compared to matched control patients. These observations need to be confirmed in a randomized controlled trial designed to demonstrate the efficacy of BM-MSCs in COVID-19 ARDS. Clinical Trial Registration: (www.ClinicalTrials.gov), identifier NCT04445454.

The Role of Imaging in the Detection of Non-COVID-19 Pathologies during the Massive Screening of the First Pandemic Wave.

During the COVID-19 pandemic induced by the SARS-CoV-2, numerous chest scans were carried out in order to establish the diagnosis, quantify the extension of lesions but also identify the occurrence of potential pulmonary embolisms. In this perspective, the performed chest scans provided a varied database for a retrospective analysis of non-COVID-19 chest pathologies discovered de novo. The fortuitous discovery of de novo non-COVID-19 lesions was generally not detected by the automated systems for COVID-19 pneumonia developed in parallel during the pandemic and was thus identified on chest CT by the radiologist. The objective is to use the study of the occurrence of non-COVID-19-related chest abnormalities (known and unknown) in a large cohort of patients having suffered from confirmed COVID-19 infection and statistically correlate the clinical data and the occurrence of these abnormalities in order to assess the potential of increased early detection of lesions/alterations. This study was performed on a group of 362 COVID-19-positive patients who were prescribed a CT scan in order to diagnose and predict COVID-19-associated lung disease. Statistical analysis using mean, standard deviation (SD) or median and interquartile range (IQR), logistic regression models and linear regression models were used for data analysis. Results were considered significant at the 5% critical level (p < 0.05). These de novo non-COVID-19 thoracic lesions detected on chest CT showed a significant prevalence in cardiovascular pathologies, with calcifying atheromatous anomalies approaching nearly 35.4% in patients over 65 years of age. The detection of non-COVID-19 pathologies was mostly already known, except for suspicious nodule, thyroid goiter and the ascending thoracic aortic aneurysm. The presence of vertebral compression or signs of pulmonary fibrosis has shown a significant impact on inpatient length of stay. The characteristics of the patients in this sample, both from a demographic and a tomodensitometric point of view on non-COVID-19 pathologies, influenced the length of hospital stay as well as the risk of intra-hospital death. This retrospective study showed that the potential importance of the detection of these non-COVID-19 lesions by the radiologist was essential in the management and the intra-hospital course of the patients.

Long-term clinical follow-up of patients suffering from moderate-to-severe COVID-19 infection: a monocentric prospective observational cohort study.

OBJECTIVES: Various symptoms and considerable organ dysfunction persist following infection with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Uncertainty remains about the potential mid- and long-term health sequelae. This prospective study of patients hospitalized with coronavirus disease 2019 (COVID-19) in Liège University Hospital, Belgium aimed to determine the persistent consequences of COVID-19. METHODS: Patients admitted to the University Hospital of Liège with moderate-to-severe confirmed COVID-19, discharged between 2 March and 1 October 2020, were recruited prospectively. Follow-up at 3 and 6 months after hospital discharge included demographic and clinical data, biological data, pulmonary function tests (PFTs) and high-resolution computed tomography (CT) scans of the chest. RESULTS: In total, 199 individuals were included in the analysis. Most patients received oxygen supplementation (80.4%). Six months after discharge, 47% and 32% of patients still had exertional dyspnoea and fatigue. PFTs at 3-month follow-up revealed a reduced diffusion capacity of carbon monoxide (mean 71.6 ± 18.6%), and this increased significantly at 6-month follow-up (P<0.0001). Chest CT scans showed a high prevalence (68.9% of the cohort) of persistent abnormalities, mainly ground glass opacities. Duration of hospitalization, intensive care unit admission and mechanical ventilation were not associated with the persistence of symptoms 3 months after discharge. CONCLUSION: The prevalence of persistent symptoms following hospitalization with COVID-19 is high and stable for up to 6 months after discharge. However, biological, functional and iconographic abnormalities improved significantly over time.

Outcome Improvement Between the First Two Waves of the Coronavirus Disease 2019 Pandemic in a Single Tertiary-Care Hospital in Belgium.

OBJECTIVES: To compare patient management and outcome during the first and second waves of the coronavirus 2019 pandemic. DESIGN: Single-center prospective cohort study. SETTING: Tertiary-care University Hospital. PATIENTS: All adult patients admitted in either the first (from March 15 to May 15, 2020) or second (from October 1 to November 30, 2020) wave of coronavirus disease 2019. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Primary outcome was 30-day mortality. During the second wave of the coronavirus disease 2019 pandemic, 33 patients (4.8%) were transferred due to overcrowding and excluded from analysis. There were 341 (first wave of the coronavirus disease 2019 pandemic) and 695 (second wave of the coronavirus disease 2019 pandemic) coronavirus disease 2019 patients admitted to the hospital, with median age first wave of the coronavirus disease 2019 pandemic as 68 (57-80) and second wave of the coronavirus disease 2019 pandemic as 71 (60-80) (p = 0.15), and similar admission severity. For the first wave of the coronavirus disease 2019 pandemic versus second wave of the coronavirus disease 2019 pandemic, 30-day mortality was 74/341 (22%) and 98/662 (15%) (p = 0.007). In the ward, 11/341 (3.2%) and 404/662 (61%) received dexamethasone (p < 0.001); 6/341 (2%) and 79/662 (12%) received high-flow nasal oxygen (p < 0.0001); 2/341 (0.6%) and 88/662 (13.3%) received remdesivir (p < 0.0001); 249/341 (73%) and 0/662 (0%) received hydroxychloroquine (p < 0.0001); and 87/341 (26%) and 128/662 (19%) (p = 0.024) patients were transferred to ICU. On ICU admission, median Sequential Organ Failure Assessment was 6 (3-7) and 4 (3-6) (p = 0.02). High-flow nasal oxygen was given to 16/87 (18%) and 102/128 (80%) (p < 0.001); 69/87 (79%) and 56/128 (44%) received mechanical ventilation (p < 0.001) with durations 17 days (10-26 d) and 10 days (5-17 d) (p = 0.01). Median ICU length of stay was 14 days (5-27 d) and 6 days (3-11 d) (p < 0.001). Finally, 16/87 (18%) and 8/128 (6%) received renal replacement therapy (p = 0.0055); and 64/87 (74%) and 51/128 (40%) needed vasopressor support (p < 0.001). CONCLUSIONS: The main therapeutic changes between the first wave of the coronavirus disease 2019 pandemic and the second wave of the coronavirus disease 2019 pandemic were use of steroids, unrestrictive use of high-flow nasal oxygen for hypoxemic patients, and transfer of patients to other geographic areas in the case of ICU overcrowding. These changes were associated with a decrease in 30-day mortality, ICU admission, and organ support.

Proteinuria in COVID-19: prevalence, characterization and prognostic role.

BACKGROUND: Proteinuria has been commonly reported in patients with COVID-19. However, only dipstick tests have been frequently used thus far. Here, the quantification and characterization of proteinuria were investigated and their association with mortality was assessed. METHODS: This retrospective, observational, single center study included 153 patients, hospitalized with COVID-19 between March 28th and April 30th, 2020, in whom total proteinuria and urinary α1-microglobulin (a marker of tubular injury) were measured. Association with mortality was evaluated, with a follow-up until May 7th, 2020. RESULTS: According to the Kidney Disease Improving Global Outcomes staging, 14% (n = 21) of the patients had category 1 proteinuria (< 150 mg/g of urine creatinine), 42% (n = 64) had category 2 (between 150 and 500 mg/g) and 44% (n = 68) had category 3 proteinuria (over 500 mg/g). Urine α1-microglobulin concentration was higher than 15 mg/g in 89% of patients. After a median follow-up of 27 [14;30] days, the mortality rate reached 18%. Total proteinuria and urinary α1-microglobulin were associated with mortality in unadjusted and adjusted models. This association was stronger in subgroups of patients with normal renal function and without a urinary catheter. CONCLUSIONS: Proteinuria is frequent in patients with COVID-19. Its characterization suggests a tubular origin, with increased urinary α1-microglobulin. Tubular proteinuria was associated with mortality in COVID-19 in our restropective, observational study.

Development and Validation of an Automated Radiomic CT Signature for Detecting COVID-19.

The coronavirus disease 2019 (COVID-19) outbreak has reached pandemic status. Drastic measures of social distancing are enforced in society and healthcare systems are being pushed to and beyond their limits. To help in the fight against this threat on human health, a fully automated AI framework was developed to extract radiomics features from volumetric chest computed tomography (CT) exams. The detection model was developed on a dataset of 1381 patients (181 COVID-19 patients plus 1200 non COVID control patients). A second, independent dataset of 197 RT-PCR confirmed COVID-19 patients and 500 control patients was used to assess the performance of the model. Diagnostic performance was assessed by the area under the receiver operating characteristic curve (AUC). The model had an AUC of 0.882 (95% CI: 0.851-0.913) in the independent test dataset (641 patients). The optimal decision threshold, considering the cost of false negatives twice as high as the cost of false positives, resulted in an accuracy of 85.18%, a sensitivity of 69.52%, a specificity of 91.63%, a negative predictive value (NPV) of 94.46% and a positive predictive value (PPV) of 59.44%. Benchmarked against RT-PCR confirmed cases of COVID-19, our AI framework can accurately differentiate COVID-19 from routine clinical conditions in a fully automated fashion. Thus, providing rapid accurate diagnosis in patients suspected of COVID-19 infection, facilitating the timely implementation of isolation procedures and early intervention.

Asthma and COPD Are Not Risk Factors for ICU Stay and Death in Case of SARS-CoV2 Infection.

BACKGROUND: Asthmatics and patients with chronic obstructive pulmonary disease (COPD) have more severe outcomes with viral infections than people without obstructive disease. OBJECTIVE: To evaluate if obstructive diseases are risk factors for intensive care unit (ICU) stay and death due to coronavirus disease 2019 (COVID19). METHODS: We collected data from the electronic medical record from 596 adult patients hospitalized in University Hospital of Liege between March 18 and April 17, 2020, for severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) infection. We classified patients into 3 groups according to the underlying respiratory disease, present before the COVID19 pandemic. RESULTS: Among patients requiring hospitalization for COVID19, asthma and COPD accounted for 9.6% and 7.7%, respectively. The proportions of asthmatics, patients with COPD, and patients without obstructive airway disease hospitalized in the ICU were 17.5%, 19.6%, and 14%, respectively. One-third of patients with COPD died during hospitalization, whereas only 7.0% of asthmatics and 13.6% of patients without airway obstruction died due to SARS-CoV2. The multivariate analysis showed that asthma, COPD, inhaled corticosteroid treatment, and oral corticosteroid treatment were not independent risk factors for ICU admission or death. Male gender (odds ratio [OR]: 1.9; 95% confidence interval [CI]: 1.1-3.2) and obesity (OR: 8.5; 95% CI: 5.1-14.1) were predictors of ICU admission, whereas male gender (OR 1.9; 95% CI: 1.1-3.2), older age (OR: 1.9; 95% CI: 1.6-2.3), cardiopathy (OR: 1.8; 95% CI: 1.1-3.1), and immunosuppressive diseases (OR: 3.6; 95% CI: 1.5-8.4) were independent predictors of death. CONCLUSION: Asthma and COPD are not risk factors for ICU admission and death related to SARS-CoV2 infection.