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.

Molecular Phenotypes of Acute Respiratory Distress Syndrome in the ROSE Trial Have Differential Outcomes and Gene Expression Patterns That Differ at Baseline and Longitudinally over Time.

Rationale: Two molecular phenotypes have been identified in acute respiratory distress syndrome (ARDS). In the ROSE (Reevaluation of Systemic Early Neuromuscular Blockade) trial of cisatracurium in moderate to severe ARDS, we addressed three unanswered questions: 1) Do the same phenotypes emerge in a more severe ARDS cohort with earlier recruitment; 2) Do phenotypes respond differently to neuromuscular blockade? and 3) What biological pathways most differentiate inflammatory phenotypes?Methods: We performed latent class analysis in ROSE using preenrollment clinical and protein biomarkers. In a subset of patients (n = 134), we sequenced whole-blood RNA using enrollment and Day 2 samples and performed differential gene expression and pathway analyses. Informed by the differential gene expression analysis, we measured additional plasma proteins and evaluated their abundance relative to gene expression amounts.Measurements and Main Results: In ROSE, we identified the hypoinflammatory (60.4%) and hyperinflammatory (39.6%) phenotypes with similar biological and clinical characteristics as prior studies, including higher mortality at Day 90 for the hyperinflammatory phenotype (30.3% vs. 61.6%; P < 0.0001). We observed no treatment interaction between the phenotypes and randomized groups for mortality. The hyperinflammatory phenotype was enriched for genes associated with innate immune response, tissue remodeling, and zinc metabolism at Day 0 and collagen synthesis and neutrophil degranulation at Day 2. Longitudinal changes in gene expression patterns differed dependent on survivorship. For most highly expressed genes, we observed correlations with their corresponding plasma proteins' abundance. However, for the class-defining plasma proteins in the latent class analysis, no correlation was observed with their corresponding genes' expression.Conclusions: The hyperinflammatory and hypoinflammatory phenotypes have different clinical, protein, and dynamic transcriptional characteristics. These findings support the clinical and biological potential of molecular phenotypes to advance precision care in ARDS.

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.

Identifying molecular phenotypes in sepsis: an analysis of two prospective observational cohorts and secondary analysis of two randomised controlled trials.

BACKGROUND: In sepsis and acute respiratory distress syndrome (ARDS), heterogeneity has contributed to difficulty identifying effective pharmacotherapies. In ARDS, two molecular phenotypes (hypoinflammatory and hyperinflammatory) have consistently been identified, with divergent outcomes and treatment responses. In this study, we sought to derive molecular phenotypes in critically ill adults with sepsis, determine their overlap with previous ARDS phenotypes, and evaluate whether they respond differently to treatment in completed sepsis trials. METHODS: We used clinical data and plasma biomarkers from two prospective sepsis cohorts, the Validating Acute Lung Injury biomarkers for Diagnosis (VALID) study (N=1140) and the Early Assessment of Renal and Lung Injury (EARLI) study (N=818), in latent class analysis (LCA) to identify the optimal number of classes in each cohort independently. We used validated models trained to classify ARDS phenotypes to evaluate concordance of sepsis and ARDS phenotypes. We applied these models retrospectively to the previously published Prospective Recombinant Human Activated Protein C Worldwide Evaluation in Severe Sepsis and Septic Shock (PROWESS-SHOCK) trial and Vasopressin and Septic Shock Trial (VASST) to assign phenotypes and evaluate heterogeneity of treatment effect. FINDINGS: A two-class model best fit both VALID and EARLI (p<0·0001). In VALID, 804 (70·5%) of the 1140 patients were classified as hypoinflammatory and 336 (29·5%) as hyperinflammatory; in EARLI, 530 (64·8%) of 818 were hypoinflammatory and 288 (35·2%) hyperinflammatory. We observed higher plasma pro-inflammatory cytokines, more vasopressor use, more bacteraemia, lower protein C, and higher mortality in the hyperinflammatory than in the hypoinflammatory phenotype (p<0·0001 for all). Classifier models indicated strong concordance between sepsis phenotypes and previously identified ARDS phenotypes (area under the curve 0·87-0·96, depending on the model). Findings were similar excluding participants with both sepsis and ARDS. In PROWESS-SHOCK, 1142 (68·0%) of 1680 patients had the hypoinflammatory phenotype and 538 (32·0%) had the hyperinflammatory phenotype, and response to activated protein C differed by phenotype (p=0·0043). In VASST, phenotype proportions were similar to other cohorts; however, no treatment interaction with the type of vasopressor was observed (p=0·72). INTERPRETATION: Molecular phenotypes previously identified in ARDS are also identifiable in multiple sepsis cohorts and respond differently to activated protein C. Molecular phenotypes could represent a treatable trait in critical illness beyond the patient's syndromic diagnosis. FUNDING: US National Institutes of Health.

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.

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.

Ventilatory Ratio Is a Valuable Prognostic Indicator in an Observational Cohort of Patients With ARDS.

BACKGROUND: How indices specific to respiratory compromise contribute to prognostication in patients with ARDS is not well characterized in general clinical populations. The primary objective of this study was to identify variables specific to respiratory failure that might add prognostic value to indicators of systemic illness severity in an observational cohort of subjects with ARDS. METHODS: Fifty subjects with ARDS were enrolled in a single-center, prospective, observational cohort. We tested the contribution of respiratory variables (oxygenation index, ventilatory ratio [VR], and the radiographic assessment of lung edema score) to logistic regression models of 28-d mortality adjusted for indicators of systemic illness severity (the Acute Physiology and Chronic Health Evaluation [APACHE] III score or severity of shock as measured by the number of vasopressors required at baseline) using likelihood ratio testing. We also compared a model utilizing APACHE III with one including baseline number of vasopressors by comparing the area under the receiver operating curve (AUROC). RESULTS: VR significantly improved model performance by likelihood ratio testing when added to APACHE III (P = .036) or the number of vasopressors at baseline (P = .01). Number of vasopressors required at baseline had similar prognostic discrimination to the APACHE III. A model including the number of vasopressors and VR (AUROC 0.77 [95% CI 0.64-0.90]) was comparable to a model including APACHE III and VR (AUROC 0.81 [95% CI 0.68-0.93]; P for comparison = .58.). CONCLUSIONS: In this observational cohort of subjects with ARDS, the VR significantly improved discrimination for mortality when combined with indicators of severe systemic illness. The number of vasopressors required at baseline and APACHE III had similar discrimination for mortality when combined with VR. VR is easily obtained at the bedside and offers promise for clinical prognostication.

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.

Validation and utility of ARDS subphenotypes identified by machine-learning models using clinical data: an observational, multicohort, retrospective analysis.

BACKGROUND: Two acute respiratory distress syndrome (ARDS) subphenotypes (hyperinflammatory and hypoinflammatory) with distinct clinical and biological features and differential treatment responses have been identified using latent class analysis (LCA) in seven individual cohorts. To facilitate bedside identification of subphenotypes, clinical classifier models using readily available clinical variables have been described in four randomised controlled trials. We aimed to assess the performance of these models in observational cohorts of ARDS. METHODS: In this observational, multicohort, retrospective study, we validated two machine-learning clinical classifier models for assigning ARDS subphenotypes in two observational cohorts of patients with ARDS: Early Assessment of Renal and Lung Injury (EARLI; n=335) and Validating Acute Lung Injury Markers for Diagnosis (VALID; n=452), with LCA-derived subphenotypes as the gold standard. The primary model comprised only vital signs and laboratory variables, and the secondary model comprised all predictors in the primary model, with the addition of ventilatory variables and demographics. Model performance was assessed by calculating the area under the receiver operating characteristic curve (AUC) and calibration plots, and assigning subphenotypes using a probability cutoff value of 0·5 to determine sensitivity, specificity, and accuracy of the assignments. We also assessed the performance of the primary model in EARLI using data automatically extracted from an electronic health record (EHR; EHR-derived EARLI cohort). In Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure (LUNG SAFE; n=2813), a multinational, observational ARDS cohort, we applied a custom classifier model (with fewer variables than the primary model) to determine the prognostic value of the subphenotypes and tested their interaction with the positive end-expiratory pressure (PEEP) strategy, with 90-day mortality as the dependent variable. FINDINGS: The primary clinical classifier model had an area under receiver operating characteristic curve (AUC) of 0·92 (95% CI 0·90-0·95) in EARLI and 0·88 (0·84-0·91) in VALID. Performance of the primary model was similar when using exclusively EHR-derived predictors compared with manually curated predictors (AUC=0·88 [95% CI 0·81-0·94] vs 0·92 [0·88-0·97]). In LUNG SAFE, 90-day mortality was higher in patients assigned the hyperinflammatory subphenotype than in those with the hypoinflammatory phenotype (414 [57%] of 725 vs 694 [33%] of 2088; p<0·0001). There was a significant treatment interaction with PEEP strategy and ARDS subphenotype (p=0·041), with lower 90-day mortality in the high PEEP group of patients with the hyperinflammatory subphenotype (hyperinflammatory subphenotype: 169 [54%] of 313 patients in the high PEEP group vs 127 [62%] of 205 patients in the low PEEP group; hypoinflammatory subphenotype: 231 [34%] of 675 patients in the high PEEP group vs 233 [32%] of 734 patients in the low PEEP group). INTERPRETATION: Classifier models using clinical variables alone can accurately assign ARDS subphenotypes in observational cohorts. Application of these models can provide valuable prognostic information and could inform management strategies for personalised treatment, including application of PEEP, once prospectively validated. FUNDING: US National Institutes of Health and European Society of Intensive Care Medicine.

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.

Mesenchymal stromal cells reduce evidence of lung injury in patients with ARDS.

BACKGROUNDWhether airspace biomarkers add value to plasma biomarkers in studying acute respiratory distress syndrome (ARDS) is not well understood. Mesenchymal stromal cells (MSCs) are an investigational therapy for ARDS, and airspace biomarkers may provide mechanistic evidence for MSCs' impact in patients with ARDS.METHODSWe carried out a nested cohort study within a phase 2a safety trial of treatment with allogeneic MSCs for moderate-to-severe ARDS. Nonbronchoscopic bronchoalveolar lavage and plasma samples were collected 48 hours after study drug infusion. Airspace and plasma biomarker concentrations were compared between the MSC (n = 17) and placebo (n = 10) treatment arms, and correlation between the two compartments was tested. Airspace biomarkers were also tested for associations with clinical and radiographic outcomes.RESULTSCompared with placebo, MSC treatment significantly reduced airspace total protein, angiopoietin-2 (Ang-2), IL-6, and soluble TNF receptor-1 concentrations. Plasma biomarkers did not differ between groups. Each 10-fold increase in airspace Ang-2 was independently associated with 6.7 fewer days alive and free of mechanical ventilation (95% CI, -12.3 to -1.0, P = 0.023), and each 10-fold increase in airspace receptor for advanced glycation end-products (RAGE) was independently associated with a 6.6-point increase in day 3 radiographic assessment of lung edema score (95% CI, 2.4 to 10.8, P = 0.004).CONCLUSIONMSCs reduced biological evidence of lung injury in patients with ARDS. Biomarkers from the airspaces provide additional value for studying pathogenesis, treatment effects, and outcomes in ARDS.TRIAL REGISTRATIONClinicalTrials.gov NCT02097641.FUNDINGNational Heart, Lung, and Blood Institute.

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.

Alternative Tobacco Product Use in Critically Ill Patients.

Background: Alternative tobacco product (ATP) use has bee linked to critical illness, however, few studies have examined the use of these substances in critically ill populations. We sought to examine ATP use within critically ill patients and to define barriers in accurately assessing use within this population. Methods: We prospectively studied 533 consecutive patients from the Early Assessment of Renal and Lung Injury study, enrolled between 2013 and 2016 at a tertiary referral center and a safety-net hospital. ATP use information (electronic cigarettes, cigars, pipes, hookahs/waterpipes, and snus/chewing tobacco) was obtained from the patient or surrogate using a detailed survey. Reasons for non-completion of the survey were recorded, and differences between survey responders vs. non-responders, self- vs. surrogate responders, and ATP users vs. non-users were explored. Results: Overall, 80% (n = 425) of subjects (56% male) completed a tobacco product use survey. Of these, 12.2% (n = 52) reported current ATP use, while 5.6% reported using multiple ATP products. When restricted to subjects who were self-responders, 17% reported ATP use, while 10% reported current cigarette smoking alone. The mean age of ATP users was 57 ± 17 years. Those who did not complete a survey were sicker and more likely to have died during admission. Subjects who completed the survey as self-responders reported higher levels of ATP use than ones with surrogate responders (p < 0.0001). Conclusion: ATP use is common among critically ill patients despite them being generally older than traditional users. Survey self-responders were more likely than surrogate responders to report use. These findings highlight the importance of improving our current methods of surveillance of ATP use in older adults in the outpatient setting.

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.

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.

Acute respiratory distress syndrome-attributable mortality in critically ill patients with sepsis.

PURPOSE: Previous studies assessing impact of acute respiratory distress syndrome (ARDS) on mortality have shown conflicting results. We sought to assess the independent association of ARDS with in-hospital mortality among intensive care unit (ICU) patients with sepsis. METHODS: We studied two prospective sepsis cohorts drawn from the Early Assessment of Renal and Lung Injury (EARLI; n = 474) and Validating Acute Lung Injury markers for Diagnosis (VALID; n = 337) cohorts. ARDS was defined by Berlin criteria. We used logistic regression to compare in-hospital mortality in patients with and without ARDS, controlling for baseline severity of illness. We also estimated attributable mortality, adjusted for illness severity by stratification. RESULTS: ARDS occurred in 195 EARLI patients (41%) and 99 VALID patients (29%). ARDS was independently associated with risk of hospital death in multivariate analysis, even after controlling for severity of illness, as measured by APACHE II (odds ratio [OR] 1.65 (95% confidence interval [CI] 1.02, 2.67), p = 0.04 in EARLI; OR 2.12 (CI 1.16, 3.92), p = 0.02 in VALID). Patients with severe ARDS (P/F < 100) primarily drove this relationship. The attributable mortality of ARDS was 27% (CI 14%, 37%) in EARLI and 37% (CI 10%, 51%) in VALID. ARDS was independently associated with ICU mortality, hospital length of stay (LOS), ICU LOS, and ventilator-free days. CONCLUSIONS: Development of ARDS among ICU patients with sepsis confers increased risk of ICU and in-hospital mortality in addition to other important outcomes. Clinical trials targeting patients with severe ARDS will be best poised to detect measurable differences in these outcomes.

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.

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.

Pulmonary Dead Space Monitoring: Identifying Subjects With ARDS at Risk of Developing Right Ventricular Dysfunction.

BACKGROUND: ARDS is a highly morbid condition characterized by diffuse pulmonary inflammation, which results in hypoxemic respiratory failure. Approximately 25% of patients with ARDS develop right ventricular dysfunction, with cor pulmonale being a common final pathway in a significant number of non-survivors. ARDS-related right ventricular dysfunction occurs due to acute elevation in ventricular afterload caused by mechanisms that are associated with increased pulmonary dead space fraction. Thus, we hypothesized that changes in pulmonary dead space fraction may reflect changes in pulmonary hemodynamics. METHODS: This was a prospective single-center study of 21 subjects with ARDS who underwent serial determination of pulmonary dead space fraction and pulmonary hemodynamics via transthoracic echocardiography. Linear mixed-effects modeling was performed to test for an association between a change in pulmonary dead space and a change in pulmonary hemodynamics. RESULTS: The tricuspid regurgitation velocity to right ventricular outflow track velocity time integral ratio, an echocardiographic surrogate for pulmonary vascular resistance, increased by 0.16 Wood units (Coefficient 0.16, 95% CI 0.09-0.23; P < .001), and the tricuspid regurgitation pressure gradient increased by 3.7 mm Hg (Coefficient 3.7, 95% CI 1.74-5.63, P < .001) for every 10% increase in pulmonary dead space fraction. CONCLUSIONS: Increases in the pulmonary dead space fraction were associated with relative increases in both the tricuspid regurgitation velocity to right ventricular outflow track velocity time integral ratio and the tricuspid regurgitation pressure gradient, which likely contributed to the high incidence of ARDS-related right ventricular dysfunction encountered in clinical practice. Pulmonary dead space monitoring may serve as a clinical indicator to identify patients with ARDS at risk of developing right ventricular dysfunction and acute cor pulmonale.

Characteristics of Nonpulmonary Organ Dysfunction at Onset of ARDS Based on the Berlin Definition.

BACKGROUND: The Berlin definition of ARDS does not account for nonpulmonary organ failure, which is a major determinant of outcome. We examined whether an increasing severity of hypoxemia across the Berlin definition classifications also corresponded with evidence of multiple organ dysfunction on the day of ARDS onset. We also examined the representation of major etiologies for ARDS across the Berlin definition classifications. METHODS: This single-center, retrospective study examined 15 years of data from a quality assurance program that monitored the use of lung-protective ventilation in ARDS. We analyzed 1,747 subjects without chronic kidney disease or severe chronic liver disease at ARDS onset. The most abnormal laboratory values at ARDS onset were analyzed as cutoff values to assess organ dysfunction. Data were analyzed by using non-parametric analysis of variance (Kruskall-Wallis test) and the Dunn post test. Categorical variables were compared by using the Fisher exact test. Alpha was set at 0.05. Factors independently associated with mortality were assessed by multivariate logistic regression modeling. RESULTS: Nonpulmonary organ dysfunction was present in at least 1 system at ARDS onset that increased with severity: 80% (mild), 83% (moderate), and 90% (severe). ARDS etiologies varied as severity increased: trauma-associated lung injury steadily decreased, whereas lung injury associated with aspiration and pneumonia steadily increased. Hospital mortality also increased significantly with the Berlin definition classifications: mild (22%), moderate (30%), and severe (47%). Multivariate logistic regression modeling revealed that the Berlin definition of severe ARDS was independently associated with mortality, as were cutoff values for renal and hepatic function as well as acidemia. Normal hematologic function and the absence of standard exclusion criteria used for therapeutic clinical trials in ARDS were protective. CONCLUSIONS: Nonpulmonary organ dysfunction was present at ARDS onset in most subjects and was more pronounced as ARDS severity increased. The Berlin definition classification of ARDS provided an elegant scheme for studying the syndrome because it coincided with increasing multiple organ dysfunction.