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.
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.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.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.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.
Introduction: Electroencephalography (EEG) has clinical and prognostic importance for comatose survivors of cardiac arrest. Recent 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 are poorly characterized in anoxic injury. Hypothesis: Sedation decreases amplitude-integrated EEG (aEEG) and alpha/delta ratio (ADR), increases suppression ratio (SR), and the magnitude of this change will predict neurological recovery. Methods: We routinely monitor comatose post-arrest patients with EEG for 48-72h, or until death or awakening. In this prospective study, we included consecutive EEG-monitored patients who had protocolized sedation interruptions, excluding those with contraindications to interruption such as seizure or hemodynamic instability. We used Persyst v12 to quantify SR, aEEG, and ADR and calculated medians for 10min immediately prior to sedation interruption and the last 5min of interruption. We used nonparametric tests to determine if the qEEG signal changed pre- to post- and whether this differed by outcome (Cerebral Performance Category 1-2 at hospital discharge vs 3-5). Results: Of 101 screened subjects, 22 met inclusion criteria (median age 58 years, 73% male). Sedation regimens varied (18 propofol; 13 fentanyl; 5 midazolam). Median duration of sedation interruption was 35min, and did not differ by sedative type. Pre-interruption, higher ADR and aEEG and lower SR predicted favorable outcome. Post-interruption, SR decreased (median change -0.85, IQR: -12.0 to 0), aEEG increased (0.38, IQR +0.02 to 1.07), but ADR did not change. SR decreased more among those with a poor outcome (P=0.01), but aEEG and ADR changes did not differ by outcome. Conclusions: In acute anoxic brain injury, sedation increases SR and decreases aEEG. Larger decreases in SR with sedation interruption predict worse outcomes, which may reflect a susceptibility of deafferentated cortex to suppress in response to sedation.
RATIONALE: There is an urgent need for improved understanding of the mechanisms and clinical characteristics of acute respiratory distress syndrome (ARDS) due to 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 non-parametric 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 to non-COVID-19 ARDS (p<0.05). COVID-19 patients had lower delivered minute ventilation compared to bacterial and culture-negative ARDS (post-hoc p<0.01), but not compared to viral ARDS. We found no differences in static compliance, hypoxemic indices or carbon dioxide clearance between groups. COVID-19 patients had lower IL-6 levels compared to bacterial and culture-negative ARDS at early time points post-intubation, but no differences in IL-6 levels compared to viral ARDS. COVID-19 patients had longer duration of mechanical ventilation but similar 60-day mortality, both in 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 to bacterial and culture-negative ARDS. COVID-19 ARDS was associated with longer dependence on mechanical ventilation compared to non-COVID 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.
Guts, Lungs, and BronchiectasisSuppose a scholar seeks to understand the American Revolutionary War: its causes, consequences, and what lessons we may learn from it.They begin by reading biographies of key participants but soon realize that the scope of these books is too narrow.Broadening the scope to study demography (e.g., census reports, immigration records) helps them understand not merely the leaders of the revolution but also the people they led.However, even this isn't enough to understand the colonists' activities, so the scope is broadened further to interactions: in governance (political science), in the marketplace (economics), and in culture (sociology).Finally, our historian realizes that they cannot understand the events of Boston, Philadelphia, and Yorktown without also studying England: the leaders, people, and interactions that influenced a revolution from across an ocean.This sequence-the broadening of one's scope of study to understand a complex historical phenomenon-provides us with a useful analogy for understanding another revolution: the introduction of culture-independent microbiology to our study of respiratory disease (1) (Table 1).For a century, the study of microbiota in the lungs relied on "biographies" of individual species: culture-based interrogation of prominent pathogens, studied by means of culturedependent bacteriology and mycology.In the past decade, the use of microbiome techniques (amplicon sequencing, metagenomics) has revealed the complex "demography" of respiratory microbiota: diverse, dynamic populations of microbiota detected in healthy and diseased airways.However, with rare exceptions (2), the field has not reached the "interactions" scale of inquiry.We know little about the complex networks that exist between respiratory microbiota, the host, and mediators of disease pathogenesis.Furthermore, studies of the microbiome's role in lung disease have been anatomically compartmentalized, sampling either respiratory microbiota or gut microbiota, but never both.We've been trying to understand a revolution with an incomplete toolkit, looking through a narrow lens.In this issue of the Journal, Narayana and colleagues (pp.908-920) move the field forward by broadening our scope of inquiry.Seeking to better understand the microbiome's role in bronchiectasis, they studied a cohort of 57 adult patients with bronchiectasis (3).Although modest in size, the cohort was extensively and exhaustively characterized, both anatomically (both respiratory and gut specimens) and taxonomically (they studied both bacteria and fungi).This integrated strategy of crosscompartmental sampling and cross-kingdom sequencing is novel and enabled them to perform interactome analyses that incorporated both gut and lung communities, both bacterial and fungal.Their core finding was that these patients with bronchiectasis cluster into two distinct subgroups, identified through their network analysis: a high gut-lung interaction group (dominated by lung
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.
Abstract 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.
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.
