Risk Stratification Based on a Pattern of Immunometabolic Host Factors Is Superior to Body Mass Index-Based Prediction of COVID-19-Associated Respiratory Failure.

Overweight and obesity are associated with chronic low-grade inflammation and represent risk factors for various diseases, including COVID-19. However, most published studies on COVID-19 defined obesity by the body mass index (BMI), which does not encounter adipose tissue distribution, thus neglecting immunometabolic high-risk patterns. Therefore, we comprehensively analyzed baseline anthropometry (BMI, waist-to-height-ratio (WtHR), visceral (VAT), epicardial (EAT), subcutaneous (SAT) adipose tissue masses and liver fat, inflammation markers (CRP, ferritin, interleukin-6), and immunonutritional scores (CRP-to-albumin ratio (CAR), modified Glasgow prognostic score, neutrophile-to-lymphocyte ratio, prognostic nutritional index)) in 58 consecutive COVID-19 patients of the early pandemic phase with regard to the necessity of invasive mechanical ventilation (IMV). Here, metabolically high-risk adipose tissues represented by increased VAT, liver fat, and WtHR strongly correlated with higher levels of inflammation, pathologic immunonutritional scores, and the need for IMV. In contrast, the prognostic value of BMI was inferior and absent with regard to SAT. Multivariable logistic regression analysis identified an optimized IMV risk prediction model employing liver fat, WtHR, and CAR. In summary, we suggest an immunometabolically risk-adjusted model to predict COVID-19-induced respiratory failure better than BMI-based stratification, which warrants prospective validation.

PBI-0451 AN ORALLY ADMINISTERED 3CL PROTEASE INHIBITOR of SARS-CoV-2 for COVID-19

Background: The 3CL protease (3CLpro) of coronaviruses (CoV) is responsible for essential & early steps of viral replication. Early treatment of SARS-CoV2 infection with a 3CLpro inhibitor has shown to substantially reduce the rate of hospitalization & death from COVID-19. There is a need for a protease inhibitor that can be used as a stand-alone agent to treat and prevent SARS-CoV-2 infection globally, in the setting of remote testing & healthcare delivery, and as unsupervised outpatient use by a significant number of people who take other medications. Methods: PBI-0451 was assessed in cultures of inducible pluripotent stem cell-derived alveolar type II (iPS-AT2) cells, in nonclinical PK and toxicity studies, and an ongoing randomized, double-blind first-in-human (FIH) study evaluating the tolerability, safety, and PK of single and multiple doses administered as an oral suspension to healthy adult subjects. The effect of food and the potential for a drug-drug interaction (DDI) with ritonavir were also explored. Results: PBI-0451 potently inhibited SARS-CoV-2 replication in iPS-AT2 cells with multi-log reductions in viral titer and mean (SD) IC50 & EC90 values of 32 (25) & 106 (90) nM, respectively. No clinically relevant adverse effects of PBI-0451 were observed in 14-day GLP toxicity studies in mice and dogs, including on the cardiovascular, CNS, or respiratory systems. PBI-0451 was not genotoxic in Ames and micronucleus tests. In the ongoing FIH study to date, study treatments were generally well tolerated with no study drug or study discontinuations. No Grade 2, 3, 4, or severe adverse events were reported. Preliminary single-dose concentration-time profile of PBI-0451 following administration with food demonstrated a 2-compartment PK profile with a median terminal elimination t1/2 ranging from 11-14 hours. PBI-0451 demonstrated good oral bioavailability and a linear increase in exposure over a 10-fold dose range when administered with food, achieving concentrations >1-, 3-& 10-fold the plasma protein binding-adjusted EC90 value (374 ng/mL) against SARS-CoV-2 at doses of 100, 300 & 1050 mg, respectively. The PK of PBI-0451 was unaffected by coadministration with ritonavir. Conclusion: PBI-0451 has shown favorable nonclinical properties and early clinical safety & PK that supports its continued evaluation as a stand-alone agent. Ongoing multiple-dose evaluation will further elucidate its clinical profile and inform the dose & dosing regimen selection for potential Phase II/III studies.

Sequential Organ Failure Assessment Outperforms Quantitative Chest CT Imaging Parameters for Mortality Prediction in COVID-19 ARDS.

(1) Background: Respiratory insufficiency with acute respiratory distress syndrome (ARDS) and multi-organ dysfunction leads to high mortality in COVID-19 patients. In times of limited intensive care unit (ICU) resources, chest CTs became an important tool for the assessment of lung involvement and for patient triage despite uncertainties about the predictive diagnostic value. This study evaluated chest CT-based imaging parameters for their potential to predict in-hospital mortality compared to clinical scores. (2) Methods: 89 COVID-19 ICU ARDS patients requiring mechanical ventilation or continuous positive airway pressure mask ventilation were included in this single center retrospective study. AI-based lung injury assessment and measurements indicating pulmonary hypertension (PA-to-AA ratio) on admission CT, oxygenation indices, lung compliance and sequential organ failure assessment (SOFA) scores on ICU admission were assessed for their diagnostic performance to predict in-hospital mortality. (3) Results: CT severity scores and PA-to-AA ratios were not significantly associated with in-hospital mortality, whereas the SOFA score showed a significant association (p < 0.001). In ROC analysis, the SOFA score resulted in an area under the curve (AUC) for in-hospital mortality of 0.74 (95%-CI 0.63-0.85), whereas CT severity scores (0.53, 95%-CI 0.40-0.67) and PA-to-AA ratios (0.46, 95%-CI 0.34-0.58) did not yield sufficient AUCs. These results were consistent for the subgroup of more critically ill patients with moderate and severe ARDS on admission (oxygenation index <200, n = 53) with an AUC for SOFA score of 0.77 (95%-CI 0.64-0.89), compared to 0.55 (95%-CI 0.39-0.72) for CT severity scores and 0.51 (95%-CI 0.35-0.67) for PA-to-AA ratios. (4) Conclusions: Severe COVID-19 disease is not limited to lung (vessel) injury but leads to a multi-organ involvement. The findings of this study suggest that risk stratification should not solely be based on chest CT parameters but needs to include multi-organ failure assessment for COVID-19 ICU ARDS patients for optimized future patient management and resource allocation.

Differences in Cardiac Magnetic Resonance Imaging Markers Between Patients With COVID-19-associated Myocardial Injury and Patients With Clinically Suspected Myocarditis.

PURPOSE: Coronavirus 2019 disease (COVID-19) has been shown to affect the myocardium, resulting in a worse clinical outcome. In this registry study, we aimed to identify differences in cardiac magnetic resonance imaging (CMRI) between COVID-19 and all-cause myocarditis. MATERIALS AND METHODS: We examined CMRI of patients with COVID-19 and elevated high-sensitivity serum troponin levels performed between March 31st and May 5th and compared them to CMRI of patients without SARS-CoV-2 infection with suspected myocarditis in the same time period. For this purpose, we evaluated Lake-Louise Criteria for myocarditis by determining nonischemic myocardial injury via T1-mapping, extracellular volume, late gadolinium enhancement, and myocardial edema (ME) by T2-mapping and fat-saturated T2w imaging (T2Q). RESULTS: A total of 15 of 18 (89%) patients with COVID-19 had abnormal findings. The control group consisted of 18 individuals. There were significantly fewer individuals with COVID-19 who had increased T2 (5 vs. 10; P=0.038) and all-cause ME (7 vs. 15; P=0.015); thus, significantly fewer patients with COVID-19 fulfilled Lake-Louise Criteria (6 vs. 17; P<0.001). In contrast, nonischemic myocardial injury was not significantly different. In the COVID-19 group, indexed end-diastolic volume of the left ventricle showed a significant correlation to the extent of abnormal T1 (R2=0.571; P=0.017) and extracellular volume (R2=0.605; P=0.013) and absolute T1, T2, and T2Q (R2=0.644; P=0.005, R2=0.513; P=0.035 and R2=0.629; P=0.038, respectively); in the control group, only extracellular volume showed a weak correlation (R2=0.490; P=0.046). CONCLUSIONS: Cardiac involvement in COVID-19 seems to show less ME than all-cause myocarditis. Abnormal CMRI markers correlated to left ventricle dilation only in the COVID-19 group. Larger comparative studies are needed to verify our findings.

Risk Stratification for ECMO Requirement in COVID-19 ICU Patients Using Quantitative Imaging Features in CT Scans on Admission.

(1) Background: Extracorporeal membrane oxygenation (ECMO) therapy in intensive care units (ICUs) remains the last treatment option for Coronavirus disease 2019 (COVID-19) patients with severely affected lungs but is highly resource demanding. Early risk stratification for the need of ECMO therapy upon admission to the hospital using artificial intelligence (AI)-based computed tomography (CT) assessment and clinical scores is beneficial for patient assessment and resource management; (2) Methods: Retrospective single-center study with 95 confirmed COVID-19 patients admitted to the participating ICUs. Patients requiring ECMO therapy (n = 14) during ICU stay versus patients without ECMO treatment (n = 81) were evaluated for discriminative clinical prediction parameters and AI-based CT imaging features and their diagnostic potential to predict ECMO therapy. Reported patient data include clinical scores, AI-based CT findings and patient outcomes; (3) Results: Patients subsequently allocated to ECMO therapy had significantly higher sequential organ failure (SOFA) scores (p < 0.001) and significantly lower oxygenation indices on admission (p = 0.009) than patients with standard ICU therapy. The median time from hospital admission to ECMO placement was 1.4 days (IQR 0.2-4.0). The percentage of lung involvement on AI-based CT assessment on admission to the hospital was significantly higher in ECMO patients (p < 0.001). In binary logistic regression analyses for ECMO prediction including age, sex, body mass index (BMI), SOFA score on admission, lactate on admission and percentage of lung involvement on admission CTs, only SOFA score (OR 1.32, 95% CI 1.08-1.62) and lung involvement (OR 1.06, 95% CI 1.01-1.11) were significantly associated with subsequent ECMO allocation. Receiver operating characteristic (ROC) curves showed an area under the curve (AUC) of 0.83 (95% CI 0.73-0.94) for lung involvement on admission CT and 0.82 (95% CI 0.72-0.91) for SOFA scores on ICU admission. A combined parameter of SOFA on ICU admission and lung involvement on admission CT yielded an AUC of 0.91 (0.84-0.97) with a sensitivity of 0.93 and a specificity of 0.84 for ECMO prediction; (4) Conclusions: AI-based assessment of lung involvement on CT scans on admission to the hospital and SOFA scoring, especially if combined, can be used as risk stratification tools for subsequent requirement for ECMO therapy in patients with severe COVID-19 disease to improve resource management in ICU settings.

Evaluation of patients with respiratory infections during the first pandemic wave in Germany: characteristics of COVID-19 versus non-COVID-19 patients.

BACKGROUND: Characteristics of COVID-19 patients have mainly been reported within confirmed COVID-19 cohorts. By analyzing patients with respiratory infections in the emergency department during the first pandemic wave, we aim to assess differences in the characteristics of COVID-19 vs. Non-COVID-19 patients. This is particularly important regarding the second COVID-19 wave and the approaching influenza season. METHODS: We prospectively included 219 patients with suspected COVID-19 who received radiological imaging and RT-PCR for SARS-CoV-2. Demographic, clinical and laboratory parameters as well as RT-PCR results were used for subgroup analysis. Imaging data were reassessed using the following scoring system: 0 - not typical, 1 - possible, 2 - highly suspicious for COVID-19. RESULTS: COVID-19 was diagnosed in 72 (32,9%) patients. In three of them (4,2%) the initial RT-PCR was negative while initial CT scan revealed pneumonic findings. 111 (50,7%) patients, 61 of them (55,0%) COVID-19 positive, had evidence of pneumonia. Patients with COVID-19 pneumonia showed higher body temperature (37,7 ± 0,1 vs. 37,1 ± 0,1 °C; p = 0.0001) and LDH values (386,3 ± 27,1 vs. 310,4 ± 17,5 U/l; p = 0.012) as well as lower leukocytes (7,6 ± 0,5 vs. 10,1 ± 0,6G/l; p = 0.0003) than patients with other pneumonia. Among abnormal CT findings in COVID-19 patients, 57 (93,4%) were evaluated as highly suspicious or possible for COVID-19. In patients with negative RT-PCR and pneumonia, another third was evaluated as highly suspicious or possible for COVID-19 (14 out of 50; 28,0%). The sensitivity in the detection of patients requiring isolation was higher with initial chest CT than with initial RT-PCR (90,4% vs. 79,5%). CONCLUSIONS: COVID-19 patients show typical clinical, laboratory and imaging parameters which enable a sensitive detection of patients who demand isolation measures due to COVID-19.

COVID-19 Pandemic and Upcoming Influenza Season-Does an Expert's Computed Tomography Assessment Differentially Identify COVID-19, Influenza and Pneumonias of Other Origin?

(1) Background: Time-consuming SARS-CoV-2 RT-PCR suffers from limited sensitivity in early infection stages whereas fast available chest CT can already raise COVID-19 suspicion. Nevertheless, radiologists' performance to differentiate COVID-19, especially from influenza pneumonia, is not sufficiently characterized. (2) Methods: A total of 201 pneumonia CTs were identified and divided into subgroups based on RT-PCR: 78 COVID-19 CTs, 65 influenza CTs and 62 Non-COVID-19-Non-influenza (NCNI) CTs. Three radiology experts (blinded from RT-PCR results) raised pathogen-specific suspicion (separately for COVID-19, influenza, bacterial pneumonia and fungal pneumonia) according to the following reading scores: 0-not typical/1-possible/2-highly suspected. Diagnostic performances were calculated with RT-PCR as a reference standard. Dependencies of radiologists' pathogen suspicion scores were characterized by Pearson's Chi2 Test for Independence. (3) Results: Depending on whether the intermediate reading score 1 was considered as positive or negative, radiologists correctly classified 83-85% (vs. NCNI)/79-82% (vs. influenza) of COVID-19 cases (sensitivity up to 94%). Contrarily, radiologists correctly classified only 52-56% (vs. NCNI)/50-60% (vs. COVID-19) of influenza cases. The COVID-19 scoring was more specific than the influenza scoring compared with suspected bacterial or fungal infection. (4) Conclusions: High-accuracy COVID-19 detection by CT might expedite patient management even during the upcoming influenza season.

COVID-19 Pandemic and Upcoming Influenza Season—Does an Expert’s Computed Tomography Assessment Differentially Identify COVID-19, Influenza and Pneumonias of Other Origin?

(1) Background: Time-consuming SARS-CoV-2 RT-PCR suffers from limited sensitivity in early infection stages whereas fast available chest CT can already raise COVID-19 suspicion. Nevertheless, radiologists’performance to differentiate COVID-19, especially from influenza pneumonia, is not sufficiently characterized. (2) Methods: A total of 201 pneumonia CTs were identified and divided into subgroups based on RT-PCR: 78 COVID-19 CTs, 65 influenza CTs and 62 Non-COVID-19-Non-influenza (NCNI) CTs. Three radiology experts (blinded from RT-PCR results) raised pathogen-specific suspicion (separately for COVID-19, influenza, bacterial pneumonia and fungal pneumonia) according to the following reading scores: 0—not typical/1—possible/2—highly suspected. Diagnostic performances were calculated with RT-PCR as a reference standard. Dependencies of radiologists’pathogen suspicion scores were characterized by Pearson’s Chi2 Test for Independence. (3) Results: Depending on whether the intermediate reading score 1 was considered as positive or negative, radiologists correctly classified 83–85% (vs. NCNI)/79–82% (vs. influenza) of COVID-19 cases (sensitivity up to 94%). Contrarily, radiologists correctly classified only 52–56% (vs. NCNI)/50–60% (vs. COVID-19) of influenza cases. The COVID-19 scoring was more specific than the influenza scoring compared with suspected bacterial or fungal infection. (4) Conclusions: High-accuracy COVID-19 detection by CT might expedite patient management even during the upcoming influenza season.

Prognostic Value of Admission Chest CT Findings for Invasive Ventilation Therapy in COVID-19 Pneumonia

(1) Background: To assess the value of chest CT imaging features of COVID-19 disease upon hospital admission for risk stratification of invasive ventilation (IV) versus no or non-invasive ventilation (non-IV) during hospital stay. (2) Methods: A retrospective single-center study was conducted including all patients admitted during the first three months of the pandemic at our hospital with PCR-confirmed COVID-19 disease and admission chest CT scans (n = 69). Using clinical information and CT imaging features, a 10-point ordinal risk score was developed and its diagnostic potential to differentiate a severe (IV-group) from a more moderate course (non-IV-group) of the disease was tested. (3) Results: Frequent imaging findings of COVID-19 pneumonia in both groups were ground glass opacities (91.3%), consolidations (53.6%) and crazy paving patterns (31.9%). Characteristics of later stages such as subpleural bands were observed significantly more often in the IV-group (52.2% versus 26.1%, p = 0.032). Using information directly accessible during a radiologist’s reporting, a simple risk score proved to reliably differentiate between IV- and non-IV-groups (AUC: 0.89 (95% CI 0.81–0.96), p <0.001). (4) Conclusions: Information accessible from admission CT scans can effectively and reliably be used in a scoring model to support risk stratification of COVID-19 patients to improve resource and allocation management of hospitals.

Safety guidelines for nonsurgical facial procedures during COVID-19 outbreak.

BACKGROUND: The novel coronavirus (COVID-19) pandemic is expected to last for an extended time, making strict safety precautions for office procedures unavoidable. The lockdown is going to be lifted in many areas, and strict guidelines detailing the infection control measures for aesthetic clinics are going to be of particular importance. METHODS: A virtual meeting was conducted with the members (n = 12) of the European Academy of Facial Plastic Surgery Focus Group to outline the safety protocol for the nonsurgical facial aesthetic procedures for aesthetic practices in order to protect the clinic staff and the patients from SARS-CoV-2 infection. The data analysis was undertaken by thematic and iterative approach. RESULTS: Consensus guidelines for nonsurgical facial aesthetic procedures based on current knowledge are provided for three levels: precautions before visiting the clinic, precautions during the clinic visit, and precautions after the clinic visit. CONCLUSIONS: Sound infection control measures are mandatory for nonsurgical aesthetic practices all around the world. These may vary from country to country, but this logical approach can be customized according to the respective country laws and guidelines.