Mechanistic model for booster doses effectiveness in healthy, cancer, and immunosuppressed patients infected with SARS-CoV-2.

SARS-CoV-2 vaccines are effective at limiting disease severity, but effectiveness is lower among patients with cancer or immunosuppression. Effectiveness wanes with time and varies by vaccine type. Moreover, previously prescribed vaccines were based on the ancestral SARS-CoV-2 spike-protein that emerging variants may evade. Here, we describe a mechanistic mathematical model for vaccination-induced immunity. We validate it with available clinical data and use it to simulate the effectiveness of vaccines against viral variants with lower antigenicity, increased virulence, or enhanced cell binding for various vaccine platforms. The analysis includes the omicron variant as well as hypothetical future variants with even greater immune evasion of vaccine-induced antibodies and addresses the potential benefits of the new bivalent vaccines. We further account for concurrent cancer or underlying immunosuppression. The model confirms enhanced immunogenicity following booster vaccination in immunosuppressed patients but predicts ongoing booster requirements for these individuals to maintain protection. We further studied the impact of variants on immunosuppressed individuals as a function of the interval between multiple booster doses. Our model suggests possible strategies for future vaccinations and suggests tailored strategies for high-risk groups.

In silico dynamics of COVID-19 phenotypes for optimizing clinical management.

Understanding the underlying mechanisms of COVID-19 progression and the impact of various pharmaceutical interventions is crucial for the clinical management of the disease. We developed a comprehensive mathematical framework based on the known mechanisms of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, incorporating the renin-angiotensin system and ACE2, which the virus exploits for cellular entry, key elements of the innate and adaptive immune responses, the role of inflammatory cytokines, and the coagulation cascade for thrombus formation. The model predicts the evolution of viral load, immune cells, cytokines, thrombosis, and oxygen saturation based on patient baseline condition and the presence of comorbidities. Model predictions were validated with clinical data from healthy people and COVID-19 patients, and the results were used to gain insight into identified risk factors of disease progression including older age; comorbidities such as obesity, diabetes, and hypertension; and dysregulated immune response. We then simulated treatment with various drug classes to identify optimal therapeutic protocols. We found that the outcome of any treatment depends on the sustained response rate of activated CD8+ T cells and sufficient control of the innate immune response. Furthermore, the best treatment-or combination of treatments-depends on the preinfection health status of the patient. Our mathematical framework provides important insight into SARS-CoV-2 pathogenesis and could be used as the basis for personalized, optimal management of COVID-19.

Evidence-Based Management of the Critically Ill Adult With SARS-CoV-2 Infection.

Human infection by the novel viral pathogen SARS-CoV-2 results in a clinical syndrome termed Coronavirus Disease 2019 (COVID-19). Although the majority of COVID-19 cases are self-limiting, a substantial minority of patients develop disease severe enough to require intensive care. Features of critical illness associated with COVID-19 include hypoxemic respiratory failure, acute respiratory distress syndrome (ARDS), shock, and multiple organ dysfunction syndrome (MODS). In most (but not all) respects critically ill patients with COVID-19 resemble critically ill patients with ARDS due to other causes and are optimally managed with standard, evidence-based critical care protocols. However, there is naturally an intense interest in developing specific therapies for severe COVID-19. Here we synthesize the rapidly expanding literature around the pathophysiology, clinical presentation, and management of COVID-19 with a focus on those points most relevant for intensivists tasked with caring for these patients. We specifically highlight evidence-based approaches that we believe should guide the identification, triage, respiratory support, and general ICU care of critically ill patients infected with SARS-CoV-2. In addition, in light of the pressing need and growing enthusiasm for targeted COVID-19 therapies, we review the biological basis, plausibility, and clinical evidence underlying these novel treatment approaches.

Filter clotting with continuous renal replacement therapy in COVID-19.

Coronavirus disease 2019 (COVID-19) appears to be associated with increased arterial and venous thromboembolic disease. These presumed abnormalities in hemostasis have been associated with filter clotting during continuous renal replacement therapy (CRRT). We aimed to characterize the burden of CRRT filter clotting in COVID-19 infection and to describe a CRRT anticoagulation protocol that used anti-factor Xa levels for systemic heparin dosing. Multi-center study of consecutive patients with COVID-19 receiving CRRT. Primary outcome was CRRT filter loss. Sixty-five patients were analyzed, including 17 using an anti-factor Xa protocol to guide systemic heparin dosing. Fifty-four out of 65 patients (83%) lost at least one filter. Median first filter survival time was 6.5 [2.5, 33.5] h. There was no difference in first or second filter loss between the anti-Xa protocol and standard of care anticoagulation groups, however fewer patients lost their third filter in the protocolized group (55% vs. 93%) resulting in a longer median third filter survival time (24 [15.1, 54.2] vs. 17.3 [9.5, 35.1] h, p = 0.04). The rate of CRRT filter loss is high in COVID-19 infection. An anticoagulation protocol using systemic unfractionated heparin, dosed by anti-factor Xa levels is reasonable approach to anticoagulation in this population.

Long-range stress transmission guides endothelial gap formation.

In endothelial gap formation, local tractions exerted by the cell upon its basal adhesions are thought to exceed balancing tensile stresses exerted across the cell-cell junction, thus causing the junction to rupture. To test this idea, we mapped evolving tractions, intercellular stresses, and corresponding growth of paracellular gaps in response to agonist challenge. Contrary to expectation, we found little to no relationship between local tensile stresses and gap formation. Instead, we discovered that intercellular stresses were aligned into striking multi-cellular domains punctuated by defects in stress alignment. Surprisingly, gaps emerged preferentially not at stress hotspots, as predicted, but rather at stress defects. This unexpected behavior is captured by a minimal model of the cell layer as a jammed assembly of cohesive particles undergoing plastic rearrangements under tension. Together, experiments and model suggest a new physical picture in which gap formation, and its consequent effect on endothelial permeability, is determined not by a local stress imbalance at a cell-cell junction but rather by emergence of non-local, cooperative stress reorganization across the cellular collective.