Altered somatic hypermutation patterns in COVID-19 patients classifies disease severity.

Introduction: The success of the human body in fighting SARS-CoV2 infection relies on lymphocytes and their antigen receptors. Identifying and characterizing clinically relevant receptors is of utmost importance. Methods: We report here the application of a machine learning approach, utilizing B cell receptor repertoire sequencing data from severely and mildly infected individuals with SARS-CoV2 compared with uninfected controls. Results: In contrast to previous studies, our approach successfully stratifies non-infected from infected individuals, as well as disease level of severity. The features that drive this classification are based on somatic hypermutation patterns, and point to alterations in the somatic hypermutation process in COVID-19 patients. Discussion: These features may be used to build and adapt therapeutic strategies to COVID-19, in particular to quantitatively assess potential diagnostic and therapeutic antibodies. These results constitute a proof of concept for future epidemiological challenges.

Distribution of Aeration and Pulmonary Blood Volume in Healthy, ARDS and COVID-19 Lungs: A Dual-Energy Computed Tomography Retrospective Cohort Study.

RATIONALE AND OBJECTIVES: Few reports have studied lung aeration and perfusion in normal lungs, COVID-19, and ARDS from other causes (NC-ARDS) using dual-energy computed tomography pulmonary angiograms (DE-CTPA). To describe lung aeration and blood-volume distribution using DE-CTPAs of patients with NC-ARDS, COVID-19, and controls with a normal DE-CTPA ("healthy lungs"). We hypothesized that each of these conditions has unique ranges of aeration and pulmonary blood volumes. MATERIALS AND METHODS: This retrospective, single-center study of DE-CTPAs included patients with COVID-19, NC-ARDS (Berlin criteria), and controls. Patients with macroscopic pulmonary embolisms were excluded. The outcomes studied were the (1) lung blood-volume in areas with different aeration levels (normal, ground glass opacities [GGO], consolidated lung) and (2) aeration/blood-volume ratios. RESULTS: Included were 20 patients with COVID-19 (10 milds, 10 moderate-severe), six with NC-ARDS, and 12 healthy-controls. Lung aeration was lowest in patients with severe COVID-19 24% (IQR13%-31%) followed by those with NC-ARDS 40%(IQR21%-46%). Blood-volume in GGO was lowest in patients with COVID-19 [moderate-severe:-28.6 (IQR-33.1-23.2); mild: -30.1 (IQR-33.3-23.4)] and highest in normally aerated areas in NC-ARDS -37.4 (IQR-52.5-30.2-) and moderate-severe COVID-19 -33.5(IQR-44.2-28.5). The median aeration/blood-volume ratio was lowest in severe COVID-19 but some values overlapped with those observed among patients with NC-ARDS. CONCLUSION: Severe COVID-19 disease is associated with low total aerated lung volume and blood-volume in areas with GGO and overall aeration/blood volume ratios, and with high blood volume in normal lung areas. In this hypothesis-generating study, these findings were most pronounced in severe COVID disease. Larger studies are needed to confirm these preliminary findings.

Experimental and Compassionate Drug Use During the First Wave of the COVID-19 Pandemic: A Retrospective Single-Center Study.

INTRODUCTION: Concomitant experimental/compassionate drug administration has been all-pervasive in the treatment of COVID-19 patients. The objective of this study was to study the relationship between patient severity, the number of experimental/compassionate medications received (main outcome measure), and patient outcomes [survival to hospital discharge and length of hospital stay (LOS)]. METHODS: Retrospective analysis of data collected in real time during the first pandemic wave in a tertiary care hospital. Data included patient demographics, comorbidities, admission vital signs, laboratory values, most extreme respiratory intervention during hospitalization, and data regarding treatment with compassionate/experimental drugs during their stay. RESULTS: Overall, 292 PCR-confirmed patients with symptoms of COVID-19 were studied (March/April, 2020). Increasing respiratory support correlated with both LOS and mortality. Patients were more likely to receive more than 1 experimental/compassionate drugs as respiratory support escalated, ranging from 3% (n = 4/136) among patients on room air to 77.3% (n = 17/22) of mechanically ventilated/ECMO patients (P < 0.001, linear by linear association). The mean number of experimental/compassionate drugs received also increased with escalating respiratory support (P < 0.001, one-way ANOVA). After adjustment for severity of patient condition, administration of more experimental/compassionate drugs was unrelated to survival (P = 0.24), but was related to increased LOS (P < 0.001). CONCLUSION: Patients that were hospitalized in worse condition were more likely to receive more experimental/compassionate drugs. Treatment was unrelated to survival but may have been related to LOS. This finding raises questions regarding the results of studies on medication effects that adjusted for multiple drug administration.

Predictors of Hypoxemia and Related Adverse Outcomes in Patients Hospitalized with COVID-19: A Double-Center Retrospective Study.

Hypoxemia is a hallmark of coronavirus disease 2019 (COVID-19) severity. We sought to determine predictors of hypoxemia and related adverse outcomes among patients hospitalized with COVID-19 in the two largest hospitals in Jerusalem, Israel, from 9 March through 16 July 2020. Patients were categorized as those who developed reduced (<94%) vs. preserved (≥94%) arterial oxygen saturation (SpO2) within the first 48 h after arrival to the emergency department. Overall, 492 hospitalized patients with COVID-19 were retrospectively analyzed. Patients with reduced SpO2 were significantly older, had more comorbidities, higher body surface area (BSA) and body mass index (BMI), lower lymphocyte counts, impaired renal function, and elevated liver enzymes, c-reactive protein (CRP), and D-dimer levels as compared to those with preserved SpO2. In the multivariable regression analysis, older age (odds ratio (OR) 1.02 per year, p < 0.001), higher BSA (OR 1.16 per 0.10 m2, p = 0.003) or BMI (OR 1.05 per 1 kg/m2, p = 0.011), lower lymphocyte counts (OR 1.72 per 1 × 103/µL decrease, p = 0.002), and elevated CRP (1.11 per 1 mg/dL increase, p < 0.001) were found to be independent predictors of low SpO2. Severe hypoxemia requiring ventilatory support, older age, and pre-existing comorbidities, including underlying renal dysfunction and heart failure, were found to be significantly associated with in-hospital mortality. These findings suggest that assessment of predictors of hypoxemia early at the time of hospitalization with COVID-19 may be helpful in risk stratification and management.

Cardiac arrhythmias amongst hospitalised Coronavirus 2019 (COVID-19) patients: Prevalence, characterisation, and clinical algorithm to classify arrhythmic risk.

OBJECTIVES: A significant proportion of COVID-19 patients may have cardiac involvement including arrhythmias. Although arrhythmia characterisation and possible predictors were previously reported, there are conflicting data regarding the exact prevalence of arrhythmias. Clinically applicable algorithms to classify COVID patients' arrhythmic risk are still lacking, and are the aim of our study. METHODS: We describe a single-centre cohort of hospitalised patients with a positive nasopharyngeal swab for COVID-19 during the initial Israeli outbreak between 1/2/2020 and 30/5/2020. The study's outcome was any documented arrhythmia during hospitalisation, based on daily physical examination, routine ECG's, periodic 24-hour Holter, and continuous monitoring. Multivariate analysis was used to find predictors for new arrhythmias and create classification trees for discriminating patients with high and low arrhythmic risk. RESULTS: Out of 390 COVID-19 patients included, 28 (7.2%) had documented arrhythmias during hospitalisation, including 23 atrial tachyarrhythmias, combined atrial fibrillation (AF), and ventricular fibrillation, ventricular tachycardia storm, and 3 bradyarrhythmias. Only 7/28 patients had previous arrhythmias. Our study showed a significant correlation between disease severity and arrhythmia prevalence (P < .001) with a low arrhythmic prevalence amongst mild disease patients (2%). Multivariate analysis revealed background heart failure (CHF) and disease severity are independently associated with overall arrhythmia while age, CHF, disease severity, and arrhythmic symptoms are associated with tachyarrhythmias. A novel decision tree using age, disease severity, CHF, and troponin levels was created to stratify patients into high and low risk for developing arrhythmia. CONCLUSIONS: Dominant arrhythmia amongst COVID-19 patients is AF. Arrhythmia prevalence is associated with age, disease severity, CHF, and troponin levels. A novel simple Classification tree, based on these parameters, can discriminate between high and low arrhythmic risk patients.