Mass cytometry reveals a conserved immune trajectory of recovery in hospitalized COVID-19 patients.

While studies have elucidated many pathophysiological elements of COVID-19, little is known about immunological changes during COVID-19 resolution. We analyzed immune cells and phosphorylated signaling states at single-cell resolution from longitudinal blood samples of patients hospitalized with COVID-19, pneumonia and/or sepsis, and healthy individuals by mass cytometry. COVID-19 patients showed distinct immune compositions and an early, coordinated, and elevated immune cell signaling profile associated with early hospital discharge. Intra-patient longitudinal analysis revealed changes in myeloid and T cell frequencies and a reduction in immune cell signaling across cell types that accompanied disease resolution and discharge. These changes, together with increases in regulatory T cells and reduced signaling in basophils, also accompanied recovery from respiratory failure and were associated with better outcomes at time of admission. Therefore, although patients have heterogeneous immunological baselines and highly variable disease courses, a core immunological trajectory exists that defines recovery from severe SARS-CoV-2 infection.

Global absence and targeting of protective immune states in severe COVID-19.

Although infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has pleiotropic and systemic effects in some individuals1-3, many others experience milder symptoms. Here, to gain a more comprehensive understanding of the distinction between severe and mild phenotypes in the pathology of coronavirus disease 2019 (COVID-19) and its origins, we performed a whole-blood-preserving single-cell analysis protocol to integrate contributions from all major immune cell types of the blood-including neutrophils, monocytes, platelets, lymphocytes and the contents of the serum. Patients with mild COVID-19 exhibit a coordinated pattern of expression of interferon-stimulated genes (ISGs)3 across every cell population, whereas these ISG-expressing cells are systemically absent in patients with severe disease. Paradoxically, individuals with severe COVID-19 produce very high titres of anti-SARS-CoV-2 antibodies and have a lower viral load compared to individuals with mild disease. Examination of the serum from patients with severe COVID-19 shows that these patients uniquely produce antibodies that functionally block the production of the ISG-expressing cells associated with mild disease, by activating conserved signalling circuits that dampen cellular responses to interferons. Overzealous antibody responses pit the immune system against itself in many patients with COVID-19, and perhaps also in individuals with other viral infections. Our findings reveal potential targets for immunotherapies in patients with severe COVID-19 to re-engage viral defence.

Host and Microbe Blood Metagenomics Reveals Key Pathways Characterizing Critical Illness Phenotypes.

Rationale: Two molecular phenotypes of sepsis and acute respiratory distress syndrome, termed hyperinflammatory and hypoinflammatory, have been consistently identified by latent class analysis in numerous cohorts, with widely divergent clinical outcomes and differential responses to some treatments; however, the key biological differences between these phenotypes remain poorly understood.Objectives: We used host and microbe metagenomic sequencing data from blood to deepen our understanding of biological differences between latent class analysis-derived phenotypes and to assess concordance between the latent class analysis-derived phenotypes and phenotypes reported by other investigative groups (e.g., Sepsis Response Signature [SRS1-2], molecular diagnosis and risk stratification of sepsis [MARS1-4], reactive and uninflamed).Methods: We analyzed data from 113 patients with hypoinflammatory sepsis and 76 patients with hyperinflammatory sepsis enrolled in a two-hospital prospective cohort study. Molecular phenotypes had been previously assigned using latent class analysis.Measurements and Main Results: The hyperinflammatory and hypoinflammatory phenotypes of sepsis had distinct gene expression signatures, with 5,755 genes (31%) differentially expressed. The hyperinflammatory phenotype was associated with elevated expression of innate immune response genes, whereas the hypoinflammatory phenotype was associated with elevated expression of adaptive immune response genes and, notably, T cell response genes. Plasma metagenomic analysis identified differences in prevalence of bacteremia, bacterial DNA abundance, and composition between the phenotypes, with an increased presence and abundance of Enterobacteriaceae in the hyperinflammatory phenotype. Significant overlap was observed between these phenotypes and previously identified transcriptional subtypes of acute respiratory distress syndrome (reactive and uninflamed) and sepsis (SRS1-2). Analysis of data from the VANISH trial indicated that corticosteroids might have a detrimental effect in patients with the hypoinflammatory phenotype.Conclusions: The hyperinflammatory and hypoinflammatory phenotypes have distinct transcriptional and metagenomic features that could be leveraged for precision treatment strategies.

Rapidly improving ARDS differs clinically and biologically from persistent ARDS.

BACKGROUND: Rapidly improving acute respiratory distress syndrome (RIARDS) is an increasingly appreciated subgroup of ARDS in which hypoxemia improves within 24 h after initiation of mechanical ventilation. Detailed clinical and biological features of RIARDS have not been clearly defined, and it is unknown whether RIARDS is associated with the hypoinflammatory or hyperinflammatory phenotype of ARDS. The purpose of this study was to define the clinical and biological features of RIARDS and its association with inflammatory subphenotypes. METHODS: We analyzed data from 215 patients who met Berlin criteria for ARDS (endotracheally intubated) and were enrolled in a prospective observational cohort conducted at two sites, one tertiary care center and one urban safety net hospital. RIARDS was defined according to previous studies as improvement of hypoxemia defined as (i) PaO2:FiO2 > 300 or (ii) SpO2: FiO2 > 315 on the day following diagnosis of ARDS (day 2) or (iii) unassisted breathing by day 2 and for the next 48 h (defined as absence of endotracheal intubation on day 2 through day 4). Plasma biomarkers were measured on samples collected on the day of study enrollment, and ARDS phenotypes were allocated as previously described. RESULTS: RIARDS accounted for 21% of all ARDS participants. Patients with RIARDS had better clinical outcomes compared to those with persistent ARDS, with lower hospital mortality (13% vs. 57%; p value < 0.001) and more ICU-free days (median 24 vs. 0; p value < 0.001). Plasma levels of interleukin-6, interleukin-8, and plasminogen activator inhibitor-1 were significantly lower among patients with RIARDS. The hypoinflammatory phenotype of ARDS was more common among patients with RIARDS (78% vs. 51% in persistent ARDS; p value = 0.001). CONCLUSIONS: This study identifies a high prevalence of RIARDS in a multicenter observational cohort and confirms the more benign clinical course of these patients. We report the novel finding that RIARDS is characterized by lower concentrations of plasma biomarkers of inflammation compared to persistent ARDS, and that hypoinflammatory ARDS is more prevalent among patients with RIARDS. Identification and exclusion of RIARDS could potentially improve prognostic and predictive enrichment in clinical trials.

Causes and attributable fraction of death from ARDS in inflammatory phenotypes of sepsis.

BACKGROUND: Hypoinflammatory and hyperinflammatory phenotypes have been identified in both Acute Respiratory Distress Syndrome (ARDS) and sepsis. Attributable mortality of ARDS in each phenotype of sepsis is yet to be determined. We aimed to estimate the population attributable fraction of death from ARDS (PAFARDS) in hypoinflammatory and hyperinflammatory sepsis, and to determine the primary cause of death within each phenotype. METHODS: We studied 1737 patients with sepsis from two prospective cohorts. Patients were previously assigned to the hyperinflammatory or hypoinflammatory phenotype using latent class analysis. The PAFARDS in patients with sepsis was estimated separately in the hypo and hyperinflammatory phenotypes. Organ dysfunction, severe comorbidities, and withdrawal of life support were abstracted from the medical record in a subset of patients from the EARLI cohort who died (n = 130/179). Primary cause of death was defined as the organ system that most directly contributed to death or withdrawal of life support. RESULTS: The PAFARDS was 19% (95%CI 10,28%) in hypoinflammatory sepsis and, 14% (95%CI 6,20%) in hyperinflammatory sepsis. Cause of death differed between the two phenotypes (p < 0.001). Respiratory failure was the most common cause of death in hypoinflammatory sepsis, whereas circulatory shock was the most common cause in hyperinflammatory sepsis. Death with severe underlying comorbidities was more frequent in hypoinflammatory sepsis (81% vs. 67%, p = 0.004). CONCLUSIONS: The PAFARDS is modest in both phenotypes whereas primary cause of death among patients with sepsis differed substantially by phenotype. This study identifies challenges in powering future clinical trials to detect changes in mortality outcomes among patients with sepsis and ARDS.

Plasma metabolic profiling implicates dysregulated lipid metabolism and glycolytic shift in hyperinflammatory ARDS.

Using latent class analysis (LCA) of clinical and protein biomarkers, researchers have identified two phenotypes of the acute respiratory distress syndrome (ARDS) with divergent clinical trajectories and treatment responses. We investigated whether plasma metabolites differed among patients with LCA-derived hyperinflammatory and hypoinflammatory ARDS, and we tested the prognostic utility of adding metabolic clusters to LCA phenotypes. We analyzed data from 93 patients with ARDS and sepsis enrolled in a multicenter prospective cohort of critically ill patients, comparing 970 metabolites between the two LCA-derived phenotypes. In all, 188 metabolites were differentially abundant between the two LCA-derived phenotypes. After adjusting for age, sex, confounding medications, and comorbid liver and kidney disease, 82 metabolites remained significantly different. Patients with hyperinflammatory ARDS had reduced circulating lipids but high levels of pyruvate, lactate, and malate. Metabolic cluster and LCA-derived phenotypes were each significantly and independently associated with survival. Patients with hyperinflammatory ARDS may be experiencing a glycolytic shift leading to dysregulated lipid metabolism. Metabolic profiling offers prognostic information beyond what is captured by LCA phenotypes alone. Deeper biological profiling may identify key differences in pathogenesis among patients with ARDS and may lead to novel targeted therapies.

Exploring the Impact of COVID-19 on Women Hospitalists: A Mixed-Gender Qualitative Analysis.

BACKGROUND: Women physicians have faced persistent challenges, including gender bias, salary inequities, a disproportionate share of caregiving and domestic responsibilities, and limited representation in leadership. Data indicate the COVID-19 pandemic further highlighted and exacerbated these inequities. OBJECTIVE: To understand the pandemic's impact on women physicians and to brainstorm solutions to better support women physicians. DESIGN: Mixed-gender semi-structured focus groups. PARTICIPANTS: Hospitalists in the Hospital Medicine Reengineering Network (HOMERuN). APPROACH: Six semi-structured virtual focus groups were held with 22 individuals from 13 institutions comprised primarily of academic hospitalist physicians. Rapid qualitative methods including templated summaries and matrix analysis were applied to identify major themes and subthemes. KEY RESULTS: Four key themes emerged: (1) the pandemic exacerbated perceived gender inequities, (2) women's academic productivity and career development were negatively impacted, (3) women held disproportionate roles as caregivers and household managers, and (4) institutional pandemic responses were often misaligned with workforce needs, especially those of women hospitalists. Multiple interventions were proposed including: creating targeted workforce solutions and benefits to address the disproportionate caregiving burden placed on women, addressing hospitalist scheduling and leave practices, ensuring promotion pathways value clinical and COVID-19 contributions, creating transparency around salary and non-clinical time allocation, and ensuring women are better represented in leadership roles. CONCLUSIONS: Hospitalists perceived and experienced that women physicians faced negative impacts from the pandemic in multiple domains including leadership opportunities and scholarship, while also shouldering larger caregiving duties than men. There are many opportunities to improve workplace conditions for women; however, current institutional efforts were perceived as misaligned to actual needs. Thus, policy and programmatic changes, such as those proposed by this cohort of hospitalists, are needed to advance equity in the workplace.

Early plasma angiopoietin-2 is prognostic for ARDS and mortality among critically ill patients with sepsis.

Angiopoietin-2 (Ang-2) is associated with vascular endothelial injury and permeability in the acute respiratory distress syndrome (ARDS) and sepsis. Elevated circulating Ang-2 levels may identify critically ill patients with distinct pathobiology amenable to targeted therapy. We hypothesized that plasma Ang-2 measured shortly after hospitalization among patients with sepsis would be associated with the development of ARDS and poor clinical outcomes. To test this hypothesis, we measured plasma Ang-2 in a cohort of 757 patients with sepsis, including 267 with ARDS, enrolled in the emergency department or early in their ICU course before the COVID-19 pandemic. Multivariable models were used to test the association of Ang-2 with the development of ARDS and 30-day morality. We found that early plasma Ang-2 in sepsis was associated with higher baseline severity of illness, the development of ARDS, and mortality risk. The association between Ang-2 and mortality was strongest among patients with ARDS and sepsis as compared to those with sepsis alone (OR 1.81 vs. 1.52 per log Ang-2 increase). These findings might inform models testing patient risk prediction and strengthen the evidence for Ang-2 as an appealing biomarker for patient selection for novel therapeutic agents to target vascular injury in sepsis and ARDS.

Cigarette Smoke Exposure and Acute Respiratory Distress Syndrome in Sepsis: Epidemiology, Clinical Features, and Biologic Markers.

Rationale: Cigarette smoke exposure is associated with an increased risk of developing acute respiratory distress syndrome (ARDS) in trauma, transfusion, and nonpulmonary sepsis. It is unknown whether this relationship exists in the general sepsis population. Furthermore, it is unknown if patients with ARDS have differences in underlying biology based on smoking status. Objectives: To assess the relationship between cigarette smoke exposure and ARDS in sepsis and identify tobacco-related biomarkers of lung injury. Methods: We studied a prospective cohort of 592 patients with sepsis from 2009 to 2017. Plasma cotinine and urine NNAL [urine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol] were measured to categorize smoking status. Plasma biomarkers of inflammation and lung injury were measured, including in a smaller cohort of trauma patients with ARDS to increase generalizability. Measurements and Main Results: Passive and active smoking were associated with increased odds of developing ARDS in patients with sepsis. Among patients with sepsis and ARDS, active cigarette smokers were younger and had lower severity of illness than nonsmokers. Patients with ARDS with cigarette smoke exposure had lower plasma levels of IL-8 (P = 0.01) and sTNFR-1 (soluble tumor necrosis factor 1; P = 0.01) compared with those without exposure. Similar biomarker patterns were observed in blunt trauma patients with ARDS. Conclusions: Passive and active smoking are associated with an increased risk of developing ARDS in patients with pulmonary and nonpulmonary sepsis. Among patients with ARDS, those with cigarette smoke exposure have less systemic inflammation, while active smokers also have lower severity of illness compared with nonsmokers, suggesting that smoking contributes to biological heterogeneity in ARDS.

Latent class analysis-derived subphenotypes are generalisable to observational cohorts of acute respiratory distress syndrome: a prospective study.

RATIONALE: Using latent class analysis (LCA), two subphenotypes of acute respiratory distress syndrome (ARDS) have consistently been identified in five randomised controlled trials (RCTs), with distinct biological characteristics, divergent outcomes and differential treatment responses to randomised interventions. Their existence in unselected populations of ARDS remains unknown. We sought to identify subphenotypes in observational cohorts of ARDS using LCA. METHODS: LCA was independently applied to patients with ARDS from two prospective observational cohorts of patients admitted to the intensive care unit, derived from the Validating Acute Lung Injury markers for Diagnosis (VALID) (n=624) and Early Assessment of Renal and Lung Injury (EARLI) (n=335) studies. Clinical and biological data were used as class-defining variables. To test for concordance with prior ARDS subphenotypes, the performance metrics of parsimonious classifier models (interleukin 8, bicarbonate, protein C and vasopressor-use), previously developed in RCTs, were evaluated in EARLI and VALID with LCA-derived subphenotypes as the gold-standard. RESULTS: A 2-class model best fit the population in VALID (p=0.0010) and in EARLI (p<0.0001). Class 2 comprised 27% and 37% of the populations in VALID and EARLI, respectively. Consistent with the previously described 'hyperinflammatory' subphenotype, Class 2 was characterised by higher proinflammatory biomarkers, acidosis and increased shock and worse clinical outcomes. The similarities between these and prior RCT-derived subphenotypes were further substantiated by the performance of the parsimonious classifier models in both cohorts (area under the curves 0.92-0.94). The hyperinflammatory subphenotype was associated with increased prevalence of chronic liver disease and neutropenia and reduced incidence of chronic obstructive pulmonary disease. Measurement of novel biomarkers showed significantly higher levels of matrix metalloproteinase-8 and markers of endothelial injury in the hyperinflammatory subphenotype, whereas, matrix metalloproteinase-9 was significantly lower. CONCLUSION: Previously described subphenotypes are generalisable to unselected populations of non-trauma ARDS.

Adaptability on Shifting Ground: a Rapid Qualitative Assessment of Multi-institutional Inpatient Surge Planning and Workforce Deployment During the COVID-19 Pandemic.

BACKGROUND: During the initial wave of COVID-19 hospitalizations, care delivery and workforce adaptations were rapidly implemented. In response to subsequent surges of patients, institutions have deployed, modified, and/or discontinued their workforce plans. OBJECTIVE: Using rapid qualitative methods, we sought to explore hospitalists' experiences with workforce deployment, types of clinicians deployed, and challenges encountered with subsequent iterations of surge planning during the COVID-19 pandemic across a collaborative of hospital medicine groups. APPROACH: Using rapid qualitative methods, focus groups were conducted in partnership with the Hospital Medicine Reengineering Network (HOMERuN). We interviewed physicians, advanced practice providers (APP), and physician researchers about (1) ongoing adaptations to the workforce as a result of the COVID-19 pandemic, (2) current struggles with workforce planning, and (3) evolution of workforce planning. KEY RESULTS: We conducted five focus groups with 33 individuals from 24 institutions, representing 52% of HOMERuN sites. A variety of adaptations was described by participants, some common across institutions and others specific to the institution's location and context. Adaptations implemented shifted from the first waves of COVID patients to subsequent waves. Three global themes also emerged: (1) adaptability and comfort with dynamic change, (2) the importance of the unique hospitalist skillset for effective surge planning and redeployment, and (3) the lack of universal solutions. CONCLUSIONS: Hospital workforce adaptations to the COVID pandemic continued to evolve. While few approaches were universally effective in managing surges of patients, and successful adaptations were highly context dependent, the ability to navigate a complex system, adaptability, and comfort in a chaotic, dynamic environment were themes considered most critical to successful surge management. However, resource constraints and sustained high workload levels raised issues of burnout.

Plasma SARS-CoV-2 nucleocapsid antigen levels are associated with progression to severe disease in hospitalized COVID-19.

BACKGROUND: Studies quantifying SARS-CoV-2 have focused on upper respiratory tract or plasma viral RNA with inconsistent association with clinical outcomes. The association between plasma viral antigen levels and clinical outcomes has not been previously studied. Our aim was to investigate the relationship between plasma SARS-CoV-2 nucleocapsid antigen (N-antigen) concentration and both markers of host response and clinical outcomes. METHODS: SARS-CoV-2 N-antigen concentrations were measured in the first study plasma sample (D0), collected within 72 h of hospital admission, from 256 subjects admitted between March 2020 and August 2021 in a prospective observational cohort of hospitalized patients with COVID-19. The rank correlations between plasma N-antigen and plasma biomarkers of tissue damage, coagulation, and inflammation were assessed. Multiple ordinal regression was used to test the association between enrollment N-antigen plasma concentration and the primary outcome of clinical deterioration at one week as measured by a modified World Health Organization (WHO) ordinal scale. Multiple logistic regression was used to test the association between enrollment plasma N-antigen concentration and the secondary outcomes of ICU admission, mechanical ventilation at 28 days, and death at 28 days. The prognostic discrimination of an externally derived "high antigen" cutoff of N-antigen ≥ 1000 pg/mL was also tested. RESULTS: N-antigen on D0 was detectable in 84% of study participants. Plasma N-antigen levels significantly correlated with RAGE (r = 0.61), IL-10 (r = 0.59), and IP-10 (r = 0.59, adjusted p = 0.01 for all correlations). For the primary outcome of clinical status at one week, each 500 pg/mL increase in plasma N-antigen level was associated with an adjusted OR of 1.05 (95% CI 1.03-1.08) for worse WHO ordinal status. D0 plasma N-antigen ≥ 1000 pg/mL was 77% sensitive and 59% specific (AUROC 0.68) with a positive predictive value of 23% and a negative predictive value of 93% for a worse WHO ordinal scale at day 7 compared to baseline. D0 N-antigen concentration was independently associated with ICU admission and 28-day mechanical ventilation, but not with death at 28 days. CONCLUSIONS: Plasma N-antigen levels are readily measured and provide important insight into the pathogenesis and prognosis of COVID-19. The measurement of N-antigen levels early in-hospital course may improve risk stratification, especially for identifying patients who are unlikely to progress to severe disease.

A neutrophil subset defined by intracellular olfactomedin 4 is associated with mortality in sepsis.

Sepsis is a heterogeneous syndrome clinically and biologically, but biomarkers of distinct host response pathways for early prognostic information and testing targeted treatments are lacking. Olfactomedin 4 (OLFM4), a matrix glycoprotein of neutrophil-specific granules, defines a distinct neutrophil subset that may be an independent risk factor for poor outcomes in sepsis. We hypothesized that increased percentage of OLFM4+ neutrophils on sepsis presentation would be associated with mortality. In a single-center, prospective cohort study, we enrolled adults admitted to an academic medical center from the emergency department (ED) with suspected sepsis [identified by 2 or greater systemic inflammatory response syndrome (SIRS) criteria and antibiotic receipt] from March 2016 through December 2017, followed by sepsis adjudication according to Sepsis-3. We collected 200 µL of whole blood within 24 h of admission and stained for the neutrophil surface marker CD66b followed by intracellular staining for OLFM4 quantitated by flow cytometry. The predictors for 60-day mortality were 1) percentage of OLFM4+ neutrophils and 2) OLFM4+ neutrophils at a cut point of ≥37.6% determined by the Youden Index. Of 120 enrolled patients with suspected sepsis, 97 had sepsis and 23 had nonsepsis SIRS. The mean percentage of OLFM4+ neutrophils was significantly increased in both sepsis and nonsepsis SIRS patients who died (P ≤ 0.01). Among sepsis patients with elevated OLFM4+ (≥37.6%), 56% died, compared with 18% with OLFM4+ <37.6% (P = 0.001). The association between OLFM4+ and mortality withstood adjustment for age, sex, absolute neutrophil count, comorbidities, and standard measures of severity of illness (SOFA score, APACHE III) (P < 0.03). In summary, OLFM4+ neutrophil percentage is independently associated with 60-day mortality in sepsis and may represent a novel measure of the heterogeneity of host response to sepsis.

Using best subset regression to identify clinical characteristics and biomarkers associated with sepsis-associated acute kidney injury.

Sepsis-associated acute kidney injury (AKI) is a complex clinical disorder associated with inflammation, endothelial dysfunction, and dysregulated coagulation. With standard regression methods, collinearity among biomarkers may lead to the exclusion of important biological pathways in a single final model. Best subset regression is an analytic technique that identifies statistically equivalent models, allowing for more robust evaluation of correlated variables. Our objective was to identify common clinical characteristics and biomarkers associated with sepsis-associated AKI. We enrolled 453 septic adults within 24 h of intensive care unit admission. Using best subset regression, we evaluated for associations using a range of models consisting of 1-38 predictors (composed of clinical risk factors and plasma and urine biomarkers) with AKI as the outcome [defined as a serum creatinine (SCr) increase of ≥0.3 mg/dL within 48 h or ≥1.5× baseline SCr within 7 days]. Two hundred ninety-seven patients had AKI. Five-variable models were found to be of optimal complexity, as the best subset of five- and six-variable models were statistically equivalent. Within the subset of five-variable models, 46 permutations of predictors were noted to be statistically equivalent. The most common predictors in this subset included diabetes, baseline SCr, angiopoetin-2, IL-8, soluble tumor necrosis factor receptor-1, and urine neutrophil gelatinase-associated lipocalin. The models had a c-statistic of ∼0.70 (95% confidence interval: 0.65-0.75). In conclusion, using best subset regression, we identified common clinical characteristics and biomarkers associated with sepsis-associated AKI. These variables may be especially relevant in the pathogenesis of sepsis-associated AKI.

Peripheral blood leukocyte telomere length is associated with survival of sepsis patients.

Shorter peripheral blood leukocyte (PBL) telomere length (TL) has been associated with poor outcomes in various chronic lung diseases. Whether PBL-TL is associated with survival from critical illness was tested in this study.We analysed data from a prospective observational cohort study of 937 critically ill patients at Vanderbilt University Medical Center (VUMC). PBL-TL was measured using quantitative PCR of DNA isolated from PBLs. Findings were validated in an independent cohort of 394 critically ill patients with sepsis admitted to the University of California San Francisco (UCSF).In the VUMC cohort, shorter PBL-TL was associated with worse 90-day survival (adjusted hazard ratio (aHR) 1.3, 95% CI 1.1-1.6 per 1 kb TL decrease; p=0.004); in subgroup analyses, shorter PBL-TL was associated with worse 90-day survival for patients with sepsis (aHR 1.5, 95% CI 1.2-2.0 per 1 kb TL decrease; p=0.001), but not trauma. Although not associated with development of acute respiratory distress syndrome (ARDS), among ARDS subjects, shorter PBL-TL was associated with more severe ARDS (OR 1.7, 95% CI 1.2-2.5 per 1 kb TL decrease; p=0.006). The associations of PBL-TL with survival (adjusted HR 1.6, 95% CI 1.2-2.1 per 1 kb TL decrease; p=0.003) and risk for developing severe ARDS (OR 2.5, 95% CI 1.1-6.3 per 1 kb TL decrease; p=0.044) were validated in the UCSF cohort.Short PBL-TL is strongly associated with worse survival and more severe ARDS in critically ill patients, especially patients with sepsis. These findings suggest that telomere dysfunction may contribute to outcomes from critical illness.

Time to Recognition of Sepsis in the Emergency Department Using Electronic Health Record Data: A Comparative Analysis of Systemic Inflammatory Response Syndrome, Sequential Organ Failure Assessment, and Quick Sequential Organ Failure Assessment.

OBJECTIVES: Early identification of sepsis is critical to improving patient outcomes. Impact of the new sepsis definition (Sepsis-3) on timing of recognition in the emergency department has not been evaluated. Our study objective was to compare time to meeting systemic inflammatory response syndrome (Sepsis-2) criteria, Sequential Organ Failure Assessment (Sepsis-3) criteria, and quick Sequential Organ Failure Assessment criteria using electronic health record data. DESIGN: Retrospective, observational study. SETTING: The emergency department at the University of California, San Francisco. PATIENTS: Emergency department encounters between June 2012 and December 2016 for patients greater than or equal to 18 years old with blood cultures ordered, IV antibiotic receipt, and identification with sepsis via systemic inflammatory response syndrome or Sequential Organ Failure Assessment within 72 hours of emergency department presentation. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We analyzed timestamped electronic health record data from 16,612 encounters identified as sepsis by greater than or equal to 2 systemic inflammatory response syndrome criteria or a Sequential Organ Failure Assessment score greater than or equal to 2. The primary outcome was time from emergency department presentation to meeting greater than or equal to 2 systemic inflammatory response syndrome criteria, Sequential Organ Failure Assessment greater than or equal to 2, and/or greater than or equal to 2 quick Sequential Organ Failure Assessment criteria. There were 9,087 patients (54.7%) that met systemic inflammatory response syndrome-first a median of 26 minutes post-emergency department presentation (interquartile range, 0-109 min), with 83.1% meeting Sequential Organ Failure Assessment criteria a median of 118 minutes later (interquartile range, 44-401 min). There were 7,037 patients (42.3%) that met Sequential Organ Failure Assessment-first, a median of 113 minutes post-emergency department presentation (interquartile range, 60-251 min). Quick Sequential Organ Failure Assessment was met in 46.4% of patients a median of 351 minutes post-emergency department presentation (interquartile range, 67-1,165 min). Adjusted odds of in-hospital mortality were 39% greater in patients who met systemic inflammatory response syndrome-first compared with those who met Sequential Organ Failure Assessment-first (odds ratio, 1.39; 95% CI, 1.20-1.61). CONCLUSIONS: Systemic inflammatory response syndrome and Sequential Organ Failure Assessment initially identified distinct populations. Using systemic inflammatory response syndrome resulted in earlier electronic health record sepsis identification in greater than 50% of patients. Using Sequential Organ Failure Assessment alone may delay identification. Using systemic inflammatory response syndrome alone may lead to missed sepsis presenting as acute organ dysfunction. Thus, a combination of inflammatory (systemic inflammatory response syndrome) and organ dysfunction (Sequential Organ Failure Assessment) criteria may enhance timely electronic health record-based sepsis identification.

Clinician Recognition of the Acute Respiratory Distress Syndrome: Risk Factors for Under-Recognition and Trends Over Time.

OBJECTIVES: The acute respiratory distress syndrome is common in critically ill patients. Recognition is crucial because acute respiratory distress syndrome is associated with a high mortality rate, and low tidal volume ventilation improves mortality. However, acute respiratory distress syndrome often goes unrecognized. Risk factors for under-recognition and trends over time have not been fully described. DESIGN: Retrospective chart review of patients with acute respiratory distress syndrome from a prospective cohort study of critically ill patients. For each patient's ICU stay, we searched the chart for terms that indicated that acute respiratory distress syndrome was diagnosed, in the differential diagnosis, or treated with low tidal volume ventilation. SETTING: ICUs at a tertiary hospital at the University of California, San Francisco between 2008 and 2016. PATIENTS: Critically ill patients with acute respiratory distress syndrome. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Acute respiratory distress syndrome was recognized in 70% of patients, and recognition increased from 60% in 2008-2009 to 92% in 2016 (p = 0.004). Use of tidal volumes less than 6.5 mL/kg also increased (p < 0.001) from 20% to 92%. Increased acute respiratory distress syndrome severity (p = 0.01) and vasopressor use (p = 0.04) were associated with greater recognition. Clinician diagnosis of acute respiratory distress syndrome and inclusion of acute respiratory distress syndrome in the differential diagnosis were associated with tidal volumes less than 6.5 mL/kg (51% use of tidal volume ≤ 6.5 mL/kg if acute respiratory distress syndrome recognized vs 15% if not recognized; p = 0.002). Diagnosing acute respiratory distress syndrome was associated with lower tidal volume in multivariate analysis. CONCLUSIONS: Although acute respiratory distress syndrome recognition and low tidal volume ventilation use have increased over time, they remain less than universal. Clinician recognition of acute respiratory distress syndrome is associated with both systemic and respiratory severity of illness and is also associated with use of low tidal volume ventilation.

Plasma sTNFR1 and IL8 for prognostic enrichment in sepsis trials: a prospective cohort study.

BACKGROUND: Enrichment strategies improve therapeutic targeting and trial efficiency, but enrichment factors for sepsis trials are lacking. We determined whether concentrations of soluble tumor necrosis factor receptor-1 (sTNFR1), interleukin-8 (IL8), and angiopoietin-2 (Ang2) could identify sepsis patients at higher mortality risk and serve as prognostic enrichment factors. METHODS: In a multicenter prospective cohort study of 400 critically ill septic patients, we derived and validated thresholds for each marker and expressed prognostic enrichment using risk differences (RD) of 30-day mortality as predictive values. We then used decision curve analysis to simulate the prognostic enrichment of each marker and compare different prognostic enrichment strategies. MEASUREMENTS AND MAIN RESULTS: An admission sTNFR1 concentration > 8861 pg/ml identified patients with increased mortality in both the derivation (RD 21.6%) and validation (RD 17.8%) populations. Among immunocompetent patients, an IL8 concentration > 94 pg/ml identified patients with increased mortality in both the derivation (RD 17.7%) and validation (RD 27.0%) populations. An Ang2 level > 9761 pg/ml identified patients at 21.3% and 12.3% increased risk of mortality in the derivation and validation populations, respectively. Using sTNFR1 or IL8 to select high-risk patients improved clinical trial power and efficiency compared to selecting patients with septic shock. Ang2 did not outperform septic shock as an enrichment factor. CONCLUSIONS: Thresholds for sTNFR1 and IL8 consistently identified sepsis patients with higher mortality risk and may have utility for prognostic enrichment in sepsis trials.

Acute Respiratory Distress Syndrome Subphenotypes Respond Differently to Randomized Fluid Management Strategy.

RATIONALE: We previously identified two acute respiratory distress syndrome (ARDS) subphenotypes in two separate randomized controlled trials with differential response to positive end-expiratory pressure. OBJECTIVES: To identify these subphenotypes in a third ARDS cohort, to test whether subphenotypes respond differently to fluid management strategy, and to develop a practical model for subphenotype identification. METHODS: We used latent class analysis of baseline clinical and plasma biomarker data to identify subphenotypes in FACTT (Fluid and Catheter Treatment Trial; n = 1,000). Logistic regression was used to test for an interaction between subphenotype and treatment for mortality. We used stepwise modeling to generate a model for subphenotype identification in FACTT and validated its accuracy in the two cohorts in which we previously identified ARDS subphenotypes. MEASUREMENTS AND MAIN RESULTS: We confirmed that a two-class (two-subphenotype) model best described the study population. Subphenotype 2 was again characterized by higher inflammatory biomarkers and hypotension. Fluid management strategy had significantly different effects on 90-day mortality in the two subphenotypes (P = 0.0039 for interaction); mortality in subphenotype 1 was 26% with fluid-liberal strategy versus 18% with fluid-conservative, whereas mortality in subphenotype 2 was 40% with fluid-liberal strategy versus 50% in fluid-conservative. A three-variable model of IL-8, bicarbonate, and tumor necrosis factor receptor-1 accurately classified the subphenotypes. CONCLUSIONS: This analysis confirms the presence of two ARDS subphenotypes that can be accurately identified with a limited number of variables and that responded differently to randomly assigned fluid management. These findings support the presence of ARDS subtypes that may require different treatment approaches.