Convalescent plasma treatment for SARS-CoV-2 infected high-risk patients: a matched pair analysis to the LEOSS cohort.

Establishing the optimal treatment for COVID-19 patients remains challenging. Specifically, immunocompromised and pre-diseased patients are at high risk for severe disease course and face limited therapeutic options. Convalescent plasma (CP) has been considered as therapeutic approach, but reliable data are lacking, especially for high-risk patients. We performed a retrospective analysis of 55 hospitalized COVID-19 patients from University Hospital Duesseldorf (UKD) at high risk for disease progression, in a substantial proportion due to immunosuppression from cancer, solid organ transplantation, autoimmune disease, dialysis. A matched-pairs analysis (1:4) was performed with 220 patients from the Lean European Open Survey on SARS-CoV-2-infected Patients (LEOSS) who were treated or not treated with CP. Both cohorts had high mortality (UKD 41.8%, LEOSS 34.1%). A matched-pairs analysis showed no significant effect on mortality. CP administration before the formation of pulmonary infiltrates showed the lowest mortality in both cohorts (10%), whereas mortality in the complicated phase was 27.8%. CP administration during the critical phase revealed the highest mortality: UKD 60.9%, LEOSS 48.3%. In our cohort of COVID-19 patients with severe comorbidities CP did not significantly reduce mortality in a retrospective matched-pairs analysis. However, our data supports the concept that a reduction in mortality is achievable by early CP administration.

Free-Breathing Low-Field MRI of the Lungs Detects Functional Alterations Associated With Persistent Symptoms After COVID-19 Infection.

OBJECTIVES: With the COVID-19 pandemic, repetitive lung examinations have become necessary to follow-up symptoms and associated alterations. Low-field MRI, benefiting from reduced susceptibility effects, is a promising alternative for lung imaging to limit radiations absorbed by patients during CT examinations, which also have limited capability to assess functional alterations. The aim of this investigative study was to explore the functional abnormalities that free-breathing 0.55 T MRI in combination with the phase-resolved functional lung (PREFUL) analysis could identify in patients with persistent symptoms after COVID-19 infection. MATERIALS AND METHODS: Seventy-four COVID-19 patients and 8 healthy volunteers were prospectively scanned in free-breathing with a balanced steady-state free-precession sequence optimized at 0.55 T, 5 months postinfection on average. Normalized perfusion (Q), fractional ventilation (FV), and flow-volume loop correlation (FVLc) maps were extracted with the PREFUL technique. Q, FV, and FVLc defects as well as defect overlaps between these metrics were quantified. Morphological turbo-spin-echo images were also acquired, and the extent of abnormalities was scored by a board-certified radiologist. To investigate the functional correlates of persistent symptoms, a recursive feature elimination algorithm was applied to find the most informative variables to detect the presence of persistent symptoms with a logistic regression model and a cross-validation strategy. All MRI metrics, sex, age, body mass index, and the presence of preexisting lung conditions were included. RESULTS: The most informative variables to detect persistent symptoms were the percentage of concurrent Q and FVLc defects and of areas free of those defects. A detection accuracy of 71.4% was obtained with these 2 variables when fitting the model on the entire dataset. Although none of the single variables differed between patients with and without persistent symptoms ( P > 0.05), the combined score of these 2 variables did ( P < 0.02). This score also showed a consistent increase from healthy volunteers (7.7) to patients without persistent symptoms (8.2) and with persistent symptoms (8.6). The morphological abnormality score showed poor correlation with the functional parameters. CONCLUSIONS: Functional pulmonary examinations using free-breathing 0.55 T MRI with PREFUL analysis revealed potential quantitative markers of impaired lung function in patients with persistent symptoms after COVID-19 infection, potentially complementing morphologic imaging. Future work is needed to explore the translational relevance and clinical implication of these findings.

Aspergillosis: Emerging risk groups in critically ill patients.

Information on invasive aspergillosis (IA) and other invasive filamentous fungal infections is limited in non-neutropenic patients admitted to the intensive care unit (ICU) and presenting with no classic IA risk factors. This review is based on the critical appraisal of relevant literature, on the authors' own experience and on discussions that took place at a consensus conference. It aims to review risk factors favoring aspergillosis in ICU patients, with a special emphasis on often overlooked or neglected conditions. In the ICU patients, corticosteroid use to treat underlying conditions such as chronic obstructive pulmonary disease (COPD), sepsis, or severe COVID-19, represents a cardinal risk factor for IA. Important additional host risk factors are COPD, decompensated cirrhosis, liver failure, and severe viral pneumonia (influenza, COVID-19). Clinical observations indicate that patients admitted to the ICU because of sepsis or acute respiratory distress syndrome are more likely to develop probable or proven IA, suggesting that sepsis could also be a possible direct risk factor for IA, as could small molecule inhibitors used in oncology. There are no recommendations for prophylaxis in ICU patients; posaconazole mold-active primary prophylaxis is used in some centers according to guidelines for other patient populations and IA treatment in critically ill patients is basically the same as in other patient populations. A combined evaluation of clinical signs and imaging, classical biomarkers such as the GM assay, and fungal cultures examination, remain the best option to assess response to treatment. LAY SUMMARY: The use of corticosteroids and the presence of co-morbidities such as chronic obstructive pulmonary disease, acute or chronic advanced liver disease, or severe viral pneumonia caused by influenza or Covid-19, may increase the risk of invasive aspergillosis in intensive care unit patients.

Successful treatment of COVID-19 infection with convalescent plasma in B-cell-depleted patients may promote cellular immunity.

Treatment with convalescent plasma has been shown to be safe in coronavirus disease in 2019 (COVID-19) infection, although efficacy reported in immunocompetent patients varies. Nevertheless, neutralizing antibodies are a key requisite in the fight against viral infections. Patients depleted of antibody-producing B cells, such as those treated with rituximab (anti-CD20) for hematological malignancies, lack a fundamental part of their adaptive immunity. Treatment with convalescent plasma appears to be of general benefit in this particularly vulnerable cohort. We analyzed clinical course and inflammation markers of three B-cell-depleted patients suffering from COVID-19 who were treated with convalescent plasma. In addition, we measured serum antibody levels as well as peripheral blood CD38/HLA-DR-positive T-cells ex vivo and CD137-positive T-cells after in vitro stimulation with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-derived peptides in these patients. We observed that therapy with convalescent plasma was effective in all three patients and analysis of CD137-positive T-cells after stimulation with SARS-CoV-2 peptides showed an increase in peptide-specific T-cells after application of convalescent plasma. In conclusion, we here demonstrate efficacy of convalescent plasma therapy in three B-cell-depleted patients and present data that suggest that while application of convalescent plasma elevates systemic antibody levels only transiently, it may also boost specific T-cell responses.

Retinal Microcirculation as a Correlate of a Systemic Capillary Impairment After Severe Acute Respiratory Syndrome Coronavirus 2 Infection.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), affects the pulmonary systems via angiotensin-converting enzyme-2 (ACE-2) receptor, being an entry to systemic infection. As COVID-19 disease features ACE-2 deficiency, a link to microcirculation is proposed. Optical coherence tomography angiography (OCT-A) enables non-invasive analysis of retinal microvasculature. Thus, an impaired systemic microcirculation might be mapped on retinal capillary system. As recent OCT-A studies, analyzing microcirculation in two subdivided layers, yielded contrary results, an increased subdivision of retinal microvasculature might offer an even more fine analysis. The aim of the study was to investigate retinal microcirculation by OCT-A after COVID-19 infection in three subdivided layers (I). In addition, short-term retinal affections were monitored during COVID-19 disease (II). Considering (I), a prospective study (33 patientspost-COVID and 28 controls) was done. Macula and peripapillary vessel density (VD) were scanned with the Spectralis II. Macula VD was measured in three layers: superficial vascular plexus (SVP), intermediate capillary plexus (ICP), and deep capillary plexus (DCP). Analysis was done by the EA-Tool, including an Anatomical Positioning System and an analysis of peripapillary VD by implementing Bruch's membrane opening (BMO) landmarks. Overall, circular (c1, c2, and c3) and sectorial VD (s1-s12) was analyzed. Considering (II), in a retrospective study, 29 patients with severe complications of COVID-19 infection, hospitalized at the intensive care unit, were monitored for retinal findings at bedside during hospitalization. (I) Overall (p = 0.0133) and circular (c1, p = 0.00257; c2, p = 0.0067; and c3, p = 0.0345). VD of the ICP was significantly reduced between patientspost-COVID and controls, respectively. Overall (p = 0.0179) and circular (c1, p = 0.0189) peripapillary VD was significantly reduced between both groups. Subgroup analysis of hospitalized vs. non-hospitalized patientspost-COVID yielded a significantly reduced VD of adjacent layers (DCP and SVP) with increased severity of COVID-19 disease. Clinical severity parameters showed a negative correlation with VD (ICP) and peripapillary VD. (II) Funduscopy yielded retinal hemorrhages and cotton wool spots in 17% of patients during SARS-CoV-2 infection. As VD of the ICP and peripapillary regions was significantly reduced after COVID-19 disease and showed a link to clinical severity markers, we assume that the severity of capillary impairment after COVID-19 infection is mapped on retinal microcirculation, visualized by non-invasive OCT-A.

Prediction of COVID-19 deterioration in high-risk patients at diagnosis: an early warning score for advanced COVID-19 developed by machine learning.

PURPOSE: While more advanced COVID-19 necessitates medical interventions and hospitalization, patients with mild COVID-19 do not require this. Identifying patients at risk of progressing to advanced COVID-19 might guide treatment decisions, particularly for better prioritizing patients in need for hospitalization. METHODS: We developed a machine learning-based predictor for deriving a clinical score identifying patients with asymptomatic/mild COVID-19 at risk of progressing to advanced COVID-19. Clinical data from SARS-CoV-2 positive patients from the multicenter Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS) were used for discovery (2020-03-16 to 2020-07-14) and validation (data from 2020-07-15 to 2021-02-16). RESULTS: The LEOSS dataset contains 473 baseline patient parameters measured at the first patient contact. After training the predictor model on a training dataset comprising 1233 patients, 20 of the 473 parameters were selected for the predictor model. From the predictor model, we delineated a composite predictive score (SACOV-19, Score for the prediction of an Advanced stage of COVID-19) with eleven variables. In the validation cohort (n = 2264 patients), we observed good prediction performance with an area under the curve (AUC) of 0.73 ± 0.01. Besides temperature, age, body mass index and smoking habit, variables indicating pulmonary involvement (respiration rate, oxygen saturation, dyspnea), inflammation (CRP, LDH, lymphocyte counts), and acute kidney injury at diagnosis were identified. For better interpretability, the predictor was translated into a web interface. CONCLUSION: We present a machine learning-based predictor model and a clinical score for identifying patients at risk of developing advanced COVID-19.

First results of the "Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS)".

PURPOSE: Knowledge regarding patients' clinical condition at severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection is sparse. Data in the international, multicenter Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) cohort study may enhance the understanding of COVID-19. METHODS: Sociodemographic and clinical characteristics of SARS-CoV-2-infected patients, enrolled in the LEOSS cohort study between March 16, 2020, and May 14, 2020, were analyzed. Associations between baseline characteristics and clinical stages at diagnosis (uncomplicated vs. complicated) were assessed using logistic regression models. RESULTS: We included 2155 patients, 59.7% (1,287/2,155) were male; the most common age category was 66-85 years (39.6%; 500/2,155). The primary COVID-19 diagnosis was made in 35.0% (755/2,155) during complicated clinical stages. A significant univariate association between age; sex; body mass index; smoking; diabetes; cardiovascular, pulmonary, neurological, and kidney diseases; ACE inhibitor therapy; statin intake and an increased risk for complicated clinical stages of COVID-19 at diagnosis was found. Multivariable analysis revealed that advanced age [46-65 years: adjusted odds ratio (aOR): 1.73, 95% CI 1.25-2.42, p = 0.001; 66-85 years: aOR 1.93, 95% CI 1.36-2.74, p < 0.001; > 85 years: aOR 2.38, 95% CI 1.49-3.81, p < 0.001 vs. individuals aged 26-45 years], male sex (aOR 1.23, 95% CI 1.01-1.50, p = 0.040), cardiovascular disease (aOR 1.37, 95% CI 1.09-1.72, p = 0.007), and diabetes (aOR 1.33, 95% CI 1.04-1.69, p = 0.023) were associated with complicated stages of COVID-19 at diagnosis. CONCLUSION: The LEOSS cohort identified age, cardiovascular disease, diabetes and male sex as risk factors for complicated disease stages at SARS-CoV-2 diagnosis, thus confirming previous data. Further data regarding outcomes of the natural course of COVID-19 and the influence of treatment are required.