Trajectories of Host-Response Subphenotypes in Patients With COVID-19 Across the Spectrum of Respiratory Support.

BACKGROUND: Hospitalized patients with severe COVID-19 follow heterogeneous clinical trajectories, requiring different levels of respiratory support and experiencing diverse clinical outcomes. Differences in host immune responses to SARS-CoV-2 infection may account for the heterogeneous clinical course, but we have limited data on the dynamic evolution of systemic biomarkers and related subphenotypes. Improved understanding of the dynamic transitions of host subphenotypes in COVID-19 may allow for improved patient selection for targeted therapies. RESEARCH QUESTION: We examined the trajectories of host-response profiles in severe COVID-19 and evaluated their prognostic impact on clinical outcomes. STUDY DESIGN AND METHODS: In this prospective observational study, we enrolled 323 inpatients with COVID-19 receiving different levels of baseline respiratory support: (1) low-flow oxygen (37%), (2) noninvasive ventilation (NIV) or high-flow oxygen (HFO; 29%), (3) invasive mechanical ventilation (27%), and (4) extracorporeal membrane oxygenation (7%). We collected plasma samples on enrollment and at days 5 and 10 to measure host-response biomarkers. We classified patients by inflammatory subphenotypes using two validated predictive models. We examined clinical, biomarker, and subphenotype trajectories and outcomes during hospitalization. RESULTS: IL-6, procalcitonin, and angiopoietin 2 persistently were elevated in patients receiving higher levels of respiratory support, whereas soluble receptor of advanced glycation end products (sRAGE) levels displayed the inverse pattern. Patients receiving NIV or HFO at baseline showed the most dynamic clinical trajectory, with 24% eventually requiring intubation and exhibiting worse 60-day mortality than patients receiving invasive mechanical ventilation at baseline (67% vs 35%; P < .0001). sRAGE levels predicted NIV failure and worse 60-day mortality for patients receiving NIV or HFO, whereas IL-6 levels were predictive in all patients regardless of level of support (P < .01). Patients classified to a hyperinflammatory subphenotype at baseline (< 10%) showed worse 60-day survival (P < .0001) and 50% of them remained classified as hyperinflammatory at 5 days after enrollment. INTERPRETATION: Longitudinal study of the systemic host response in COVID-19 revealed substantial and predictive interindividual variability influenced by baseline levels of respiratory support.

Trajectories of host-response biomarkers and inflammatory subphenotypes in COVID-19 patients across the spectrum of respiratory support.

Purpose: Enhanced understanding of the dynamic changes in the dysregulated inflammatory response in COVID-19 may help improve patient selection and timing for immunomodulatory therapies. Methods: We enrolled 323 COVID-19 inpatients on different levels of baseline respiratory support: i) Low Flow Oxygen (37%), ii) Non-Invasive Ventilation or High Flow Oxygen (NIV_HFO, 29%), iii) Invasive Mechanical Ventilation (IMV, 27%), and iv) Extracorporeal Membrane Oxygenation (ECMO, 7%). We collected plasma samples upon enrollment and days 5 and 10 to measure host-response biomarkers. We classified subjects into inflammatory subphenotypes using two validated predictive models. We examined clinical, biomarker and subphenotype trajectories and outcomes during hospitalization. Results: IL-6, procalcitonin, and Angiopoietin-2 were persistently elevated in patients at higher levels of respiratory support, whereas sRAGE displayed the inverse pattern. Patients on NIV_HFO at baseline had the most dynamic clinical trajectory, with 26% eventually requiring intubation and exhibiting worse 60-day mortality than IMV patients at baseline (67% vs. 35%, p<0.0001). sRAGE levels predicted NIV failure and worse 60-day mortality for NIV_HFO patients, whereas IL-6 levels were predictive in IMV or ECMO patients. Hyper-inflammatory subjects at baseline (<10% by both models) had worse 60-day survival (p<0.0001) and 50% of them remained classified as hyper-inflammatory on follow-up sampling at 5 days post-enrollment. Receipt of combined immunomodulatory therapies (steroids and anti-IL6 agents) was associated with markedly increased IL-6 and lower Angiopoietin-2 levels (p<0.05). Conclusions: Longitudinal study of systemic host responses in COVID-19 revealed substantial and predictive inter-individual variability, influenced by baseline levels of respiratory support and concurrent immunomodulatory therapies.

The association of brainstem and motor recovery with awakening after out-of-hospital cardiac arrest.

Background: Coma is common following resuscitation from cardiac arrest. Few data describe the trajectory of recovery the first days following resuscitation. The objective of this study is to describe the evolution in neurological examination during the first 5 days after resuscitation and test if subjects who go on to awaken have different patterns of early recovery. Methods: Prospective study of adult subjects resuscitated from out-of-hospital cardiac arrest. We abstracted demographic information and trained clinicians completed daily neurologic examinations using the Glasgow Coma Scale (GCS) and Full Outline of UnResponsiveness brainstem (FOUR-B) and motor (FOUR-M) scores during daily sedation interruption. The change in scores between Day 1 and Day 5 was analyzed using the Kruskal-Wallis Test and logistic regression models. The relationship of FOUR-B, FOUR-M, and GCS with time to death was estimated by fitting cox proportional hazard models. Results: FOUR-M and GCS did not differ over time (p = 0.10; p = 0.07). FOUR B increased over time (p < 0.01). Time to recovery of brainstem or motor function differed between those treated at 33 °C and 36 °C (p = 0.0023 and p = 0.0032, respectively). FOUR-B, FOUR-M, and GCS differed between survivors and non-survivors (p < 0.01). Time to recovery of brainstem and motor function differed between survivors and non-survivors. FOUR-M and FOUR-B differed between those with good outcome and poor outcome. Conclusions: The brainstem clinical examination improved during the first 5 days following resuscitation. Brainstem recovery was common in entire cohort and did not differentiate between survivors and non-survivors. Recovery of motor function, however, was associated with survival.

Biomarker-Based Classification of Patients With Acute Respiratory Failure Into Inflammatory Subphenotypes: A Single-Center Exploratory Study.

OBJECTIVES: Hyper- and hypoinflammatory subphenotypes discovered in patients with acute respiratory distress syndrome predict clinical outcomes and therapeutic responses. These subphenotypes may be important in broader critically ill patient populations with acute respiratory failure regardless of clinical diagnosis. We investigated subphenotyping with latent class analysis in an inclusive population of acute respiratory failure, derived a parsimonious model for subphenotypic predictions based on a small set of variables, and examined associations with clinical outcomes. DESIGN: Prospective, observational cohort study. SETTING: Single-center, academic medical ICU. PATIENTS: Mechanically ventilated patients with acute respiratory failure. MEASUREMENTS AND MAIN RESULTS: We included 498 patients with acute respiratory failure (acute respiratory distress syndrome: 143, at-risk for acute respiratory distress syndrome: 198, congestive heart failure: 37, acute on chronic respiratory failure: 23, airway protection: 61, and multifactorial: 35) in our derivation cohort and measured 10 baseline plasma biomarkers. Latent class analysis considering clinical variables and biomarkers determined that a two-class model offered optimal fit (23% hyperinflammatory subphenotype). Distribution of hyperinflammatory subphenotype varied among acute respiratory failure etiologies (acute respiratory distress syndrome: 31%, at-risk for acute respiratory distress syndrome: 27%, congestive heart failure: 22%, acute on chronic respiratory failure 0%, airway protection: 5%, and multifactorial: 14%). Hyperinflammatory patients had higher Sequential Organ Failure Assessment scores, fewer ventilator-free days, and higher 30- and 90-day mortality (all p < 0.001). We derived a parsimonious model consisting of angiopoietin-2, soluble tumor necrosis factor receptor-1, procalcitonin, and bicarbonate and classified subphenotypes in a validation cohort (n = 139). Hyperinflammatory patients (19%) demonstrated higher levels of inflammatory biomarkers not included in the model (p < 0.01) and worse outcomes. CONCLUSIONS: Host-response subphenotypes are observable in a heterogeneous population with acute respiratory failure and predict clinical outcomes. Simple, biomarker-based models can offer prognostic enrichment in patients with acute respiratory failure. The differential distribution of subphenotypes by specific etiologies of acute respiratory failure indicates that subphenotyping may be more relevant in patients with hypoxemic causes of acute respiratory failure and not in patients intubated for airway protection or acute on chronic decompensation.

COVID-19 versus Non-COVID-19 Acute Respiratory Distress Syndrome: Comparison of Demographics, Physiologic Parameters, Inflammatory Biomarkers, and Clinical Outcomes.

Rationale: There is an urgent need for improved understanding of the mechanisms and clinical characteristics of acute respiratory distress syndrome (ARDS) due to coronavirus disease (COVID-19).Objectives: To compare key demographic and physiologic parameters, biomarkers, and clinical outcomes of COVID-19 ARDS and ARDS secondary to direct lung injury from other etiologies of pneumonia.Methods: We enrolled 27 patients with COVID-19 ARDS in a prospective, observational cohort study and compared them with a historical, pre-COVID-19 cohort of patients with viral ARDS (n = 14), bacterial ARDS (n = 21), and ARDS due to culture-negative pneumonia (n = 30). We recorded clinical demographics; measured respiratory mechanical parameters; collected serial peripheral blood specimens for measurement of plasma interleukin (IL)-6, IL-8, and IL-10; and followed patients prospectively for patient-centered outcomes. We conducted between-group comparisons with nonparametric tests and analyzed time-to-event outcomes with Kaplan-Meier and Cox proportional hazards models.Results: Patients with COVID-19 ARDS had higher body mass index and were more likely to be Black, or residents of skilled nursing facilities, compared with those with non-COVID-19 ARDS (P < 0.05). Patients with COVID-19 had lower delivered minute ventilation compared with bacterial and culture-negative ARDS (post hoc P < 0.01) but not compared with viral ARDS. We found no differences in static compliance, hypoxemic indices, or carbon dioxide clearance between groups. Patients with COVID-19 had lower IL-6 levels compared with bacterial and culture-negative ARDS at early time points after intubation but no differences in IL-6 levels compared with viral ARDS. Patients with COVID-19 had longer duration of mechanical ventilation but similar 60-day mortality in both unadjusted and adjusted analyses.Conclusions: COVID-19 ARDS bears several similarities to viral ARDS but demonstrates lower minute ventilation and lower systemic levels of IL-6 compared with bacterial and culture-negative ARDS. COVID-19 ARDS was associated with longer dependence on mechanical ventilation compared with non-COVID-19 ARDS. Such detectable differences of COVID-19 do not merit deviation from evidence-based management of ARDS but suggest priorities for clinical research to better characterize and treat this new clinical entity.

Effect of sedation on quantitative electroencephalography after cardiac arrest.

BACKGROUND: Electroencephalography (EEG) has clinical and prognostic importance after cardiac arrest (CA). Recently, interest in quantitative EEG (qEEG) analysis has grown. The qualitative effects of sedation on EEG are well known, but potentially confounding effects of sedatives on qEEG after anoxic injury are poorly characterized. We hypothesize that sedation increases suppression ratio (SR) and decreases alpha/delta ratio (ADR) and amplitude-integrated EEG (aEEG), and that the magnitude of sedation effects will be associated with outcome. METHODS: We routinely monitor comatose post-arrest patients with EEG for 48-72h. We included comatose EEG-monitored patients after CA who had protocolized daily sedation interruptions. We used Persyst v12 to quantify qEEG parameters and calculated medians for 10min immediately prior to sedation interruption and for the last 5min of interruption. We used paired t-tests to determine whether qEEG parameters changed with sedation cessation, and logistic regression to determine whether these changes predicted functional recovery or survival at discharge. RESULTS: 78 subjects were included (median age 56, 65% male). Interruptions occurred a median duration of 34h post-arrest and lasted a median duration of 60min. Prior to interruption, higher aEEG predicted survival, while lower SR predicted both survival and favorable outcome. During interruption, SR decreased (p<0.001), aEEG increased (p=0.002), and ADR did not change. Larger decreases in SR predicted decreased survival (OR=1.04 per percent change; 95% CI 1.00-1.09). CONCLUSION: Higher aEEG and lower SR predict survival after CA. Sedation alters aEEG and SR, but importantly does not appear to affect the relationship between these parameter values and outcome.

The translation inhibitor silvestrol exhibits direct anti-tumor activity while preserving innate and adaptive immunity against EBV-driven lymphoproliferative disease.

Treatment options for patients with Epstein-Barr Virus-driven lymphoproliferative diseases (EBV-LPD) are limited. Chemo-immunotherapeutic approaches often lead to immune suppression, risk of lethal infection and EBV reactivation, thus it is essential to identify agents that can deliver direct anti-tumor activity while preserving innate and adaptive host immune surveillance. Silvestrol possesses direct anti-tumor activity in multiple hematologic malignancies while causing minimal toxicity to normal mononuclear cells. However, the effects of silvestrol on immune function have not been described. We utilized in vitro and in vivo models of EBV-LPD to simultaneously examine the impact of silvestrol on both tumor and normal immune function. We show that silvestrol induces direct anti-tumor activity against EBV-transformed lymphoblastoid cell lines (LCL), with growth inhibition, decreased expression of the EBV oncogene latent membrane protein-1, and inhibition of the downstream AKT, STAT1 and STAT3 signaling pathways. Silvestrol promoted potent indirect anti-tumor effects by preserving expansion of innate and EBV antigen-specific adaptive immune effector subsets capable of effective clearance of LCL tumor targets in autologous co-cultures. In an animal model of spontaneous EBV-LPD, silvestrol demonstrated significant therapeutic activity dependent on the presence of CD8-positive T-cells. These findings establish a novel immune-sparing activity of silvestrol, justifying further exploration in patients with EBV-positive malignancies.