Integrative multi-omics analysis unravels the host response landscape and reveals a serum protein panel for early prognosis prediction for ARDS.

BACKGROUND: The multidimensional biological mechanisms underpinning acute respiratory distress syndrome (ARDS) continue to be elucidated, and early biomarkers for predicting ARDS prognosis are yet to be identified. METHODS: We conducted a multicenter observational study, profiling the 4D-DIA proteomics and global metabolomics of serum samples collected from patients at the initial stage of ARDS, alongside samples from both disease control and healthy control groups. We identified 28-day prognosis biomarkers of ARDS in the discovery cohort using the LASSO method, fold change analysis, and the Boruta algorithm. The candidate biomarkers were validated through parallel reaction monitoring (PRM) targeted mass spectrometry in an external validation cohort. Machine learning models were applied to explore the biomarkers of ARDS prognosis. RESULTS: In the discovery cohort, comprising 130 adult ARDS patients (mean age 72.5, 74.6% male), 33 disease controls, and 33 healthy controls, distinct proteomic and metabolic signatures were identified to differentiate ARDS from both control groups. Pathway analysis highlighted the upregulated sphingolipid signaling pathway as a key contributor to the pathological mechanisms underlying ARDS. MAP2K1 emerged as the hub protein, facilitating interactions with various biological functions within this pathway. Additionally, the metabolite sphingosine 1-phosphate (S1P) was closely associated with ARDS and its prognosis. Our research further highlights essential pathways contributing to the deceased ARDS, such as the downregulation of hematopoietic cell lineage and calcium signaling pathways, contrasted with the upregulation of the unfolded protein response and glycolysis. In particular, GAPDH and ENO1, critical enzymes in glycolysis, showed the highest interaction degree in the protein-protein interaction network of ARDS. In the discovery cohort, a panel of 36 proteins was identified as candidate biomarkers, with 8 proteins (VCAM1, LDHB, MSN, FLG2, TAGLN2, LMNA, MBL2, and LBP) demonstrating significant consistency in an independent validation cohort of 183 patients (mean age 72.6 years, 73.2% male), confirmed by PRM assay. The protein-based model exhibited superior predictive accuracy compared to the clinical model in both the discovery cohort (AUC: 0.893 vs. 0.784; Delong test, P < 0.001) and the validation cohort (AUC: 0.802 vs. 0.738; Delong test, P = 0.008). INTERPRETATION: Our multi-omics study demonstrated the potential biological mechanism and therapy targets in ARDS. This study unveiled several novel predictive biomarkers and established a validated prediction model for the poor prognosis of ARDS, offering valuable insights into the prognosis of individuals with ARDS.

TM9SF1 offers utility as an efficient predictor of clinical severity and mortality among acute respiratory distress syndrome patients.

Introduction: Acute respiratory distress syndrome (ARDS) is a major cause of death among critically ill patients in intensive care settings, underscoring the need to identify biomarkers capable of predicting ARDS patient clinical status and prognosis at an early time point. This study specifically sought to explore the utility and clinical relevance of TM9SF1 as a biomarker for the early prediction of disease severity and prognostic outcomes in patients with ARDS. Methods: This study enrolled 123 patients with severe ARDS and 116 patients with non-severe ARDS for whom follow-up information was available. The mRNA levels of TM9SF1 and cytokines in peripheral blood mononuclear cells from these patients were evaluated by qPCR. The predictive performance of TM9SF1 and other clinical indicators was evaluated using received operating characteristic (ROC) curves. A predictive nomogram was developed based on TM9SF1 expression and evaluated for its ability in the early prediction of severe disease and mortality in patients with ARDS. Results: TM9SF1 mRNA expression was found to be significantly increased in patients with severe ARDS relative to those with non-severe disease or healthy controls. ARDS severity increased in correspondence with the level of TM9SF1 expression (odds ratio [OR] = 2.43, 95% confidence interval [CI] = 2.15-3.72, P = 0.005), and high TM9SF1 levels were associated with a greater risk of mortality (hazard ratio [HR] = 2.27, 95% CI = 2.20-4.39, P = 0.001). ROC curves demonstrated that relative to other clinical indicators, TM9SF1 offered superior performance in the prediction of ARDS severity and mortality. A novel nomogram incorporating TM9SF1 expression together with age, D-dimer levels, and C-reactive protein (CRP) levels was developed and was used to predict ARDS severity (AUC = 0.887, 95% CI = 0.715-0.943). A separate model incorporating TM9SF1 expression, age, neutrophil-lymphocyte ratio (NLR), and D-dimer levels (C-index = 0.890, 95% CI = 0.627-0.957) was also developed for predicting mortality. Conclusion: Increases in ARDS severity and patient mortality were observed with rising levels of TM9SF1 expression. TM9SF1 may thus offer utility as a novel biomarker for the early prediction of ARDS patient disease status and clinical outcomes.

Postoperative bioactive adrenomedullin is associated with the onset of ARDS and adverse outcomes in patients undergoing open thoracoabdominal aortic surgery.

Cytokine-mediated systemic inflammation after open thoracoabdominal aortic aneurysm (TAAA) repairs plays a pivotal role in disrupting circulatory homeostasis, potentially leading to organ dysfunction. The bioactive form of adrenomedullin (bio-ADM) is a peptide hormone with immunomodulatory and vasomotor effects, making it a potential diagnostic agent in these cases. This retrospective, bicentric study, conducted between January 2019 and December 2022, recruited 36 elective open TAAA repair patients in two German centres. Serum and plasma samples were collected at multiple time points to measure bio-ADM levels. The primary objective was to evaluate the association of bio-ADM levels with the onset of acute respiratory distress syndrome (ARDS), with secondary endpoints focusing on mortality and SIRS-related morbidity. Results showed a significant association between postoperative bio-ADM levels (12-48 h after surgery) and the onset of ARDS (p < .001), prolonged ventilation (p = .015 at 12h after surgery), atrial fibrillation (p < .001), and mortality (p = .05 at 24h). The biomarker was also strongly associated with sepsis (p = .01 at 12 h) and multi-organ dysfunction syndrome (MODS) (p = .02 at 24 h after surgery). The study underscores the potential utility of bio-ADM as a diagnostic tool for identifying patients at risk of postoperative complications following open TAAA repairs.

High Levels of Triggering Receptor Expressed in Myeloid Cells-Like Transcript-1 Positive, but Not Glycoprotein 1b+, Microparticles Are Associated With Poor Outcomes in Acute Respiratory Distress Syndrome.

OBJECTIVES: To identify triggering receptor expressed in myeloid cells-like transcript-1 positive (TLT-1+) microparticles (MPs) and evaluate if their presence is associated with clinical outcomes and/or disease severity in acute respiratory distress syndrome (ARDS). DESIGN: Retrospective cohort study. SETTING: ARDS Network clinical trials. PATIENTS: A total of 564 patients were diagnosed with ARDS. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Using flow cytometry, we demonstrated the presence of TLT-1+ platelet-derived microparticles (PMP) that bind fibrinogen in plasma samples from fresh donors. We retrospectively quantified TLT-1, glycoprotein (Gp) 1b, or αIIbßIIIa immunopositive microparticles in plasma samples from patients with ARDS enrolled in the ARMA, KARMA, and LARMA (Studies 01 and 03 lower versus higher tidal volume, ketoconazole treatment, and lisofylline treatment Clincial Trials) ARDS Network clinical trials and evaluated the relationship between these measures and clinical outcomes. No associations were found between Gp1b+ MPs and clinical outcomes for any of the cohorts. When stratified by quartile, associations were found for survival, ventilation-free breathing, and thrombocytopenia with αIIbßIIIa+ and TLT-1+ MPs (χ2p < 0.001). Notably, 63 of 64 patients in this study who failed to achieve unassisted breathing had TLT+ PMP in the 75th percentile. In all three cohorts, patients whose TLT+ MP counts were higher than the median had higher Acute Physiology and Chronic Health Evaluation III scores, were more likely to present with thrombocytopenia and were 3.7 times (p < 0.001) more likely to die than patients with lower TLT+ PMP after adjusting for other risk factors. CONCLUSIONS: Although both αIIbßIIIa+ and TLT+ microparticles (αIIbßIIIa, TLT-1) were associated with mortality, TLT-1+ MPs demonstrated stronger correlations with Acute Physiology and Chronic Health Evaluation III scores, unassisted breathing, and multiple system organ failure. These findings warrant further exploration of the mechanistic role of TLT-1+ PMP in ARDS or acute lung injury progression.

Nonlinear relationship between platelet count and 30-day in-hospital mortality in ICU acute respiratory failure patients: a multicenter retrospective cohort study.

BACKGROUND: Limited evidence exists regarding the link between platelet count and 30-day in-hospital mortality in acute respiratory failure (ARF) patients. Thus, this study aims to investigate this association among ICU patients experiencing acute respiratory failure. METHODS: We conducted a retrospective cohort study across multiple centers, utilizing data from the US eICU-CRD v2.0 database covering 22,262 patients with ARF in the ICU from 2014 to 2015. Our aim was to investigate the correlation between platelet count and 30-day in-hospital mortality using binary logistic regression, subgroup analyses, and smooth curve fitting. RESULTS: The 30-day in-hospital mortality rate was 19.73% (4393 out of 22,262), with a median platelet count of 213 × 109/L. After adjusting for covariates, our analysis revealed an inverse association between platelet count and 30-day in-hospital mortality (OR = 0.99, 95% CI 0.99, 0.99). Subgroup analyses supported the robustness of these findings. Furthermore, a nonlinear relationship was identified between platelet count and 30-day in-hospital mortality, with the inflection point at 120 × 109/L. Below the inflection point, the effect size (OR) was 0.89 (0.87, 0.91), indicating a significant association. However, beyond this point, the relationship was not statistically significant. CONCLUSION: This study establishes a clear negative association between platelet count and 30-day in-hospital mortality among ICU patients with ARF. Furthermore, we have identified a nonlinear relationship with saturation effects, indicating that among ICU patients with acute respiratory failure, the lowest 30-day in-hospital mortality rate occurs when the baseline platelet count is approximately 120 × 109/L.

A deep dive into burn-mediated ARDS severity assessment: a retrospective study on hematological markers.

Acute Respiratory Distress Syndrome (ARDS) is a critical form of Acute Lung Injury (ALI), challenging clinical diagnosis and severity assessment. This study evaluates the potential utility of various hematological markers in burn-mediated ARDS, including Neutrophil-to-Lymphocyte Ratio (NLR), Mean Platelet Volume (MPV), MPV-to-Lymphocyte Ratio (MPVLR), Platelet count, and Platelet Distribution Width (PDW). Employing a retrospective analysis of data collected over 12 years, this study focuses on the relationship between these hematological markers and ARDS diagnosis and severity in hospitalized patients. The study establishes NLR as a reliable systemic inflammation marker associated with ARDS severity. Elevated MPV and MPVLR also emerged as significant markers correlating with adverse outcomes. These findings suggest these economical, routinely measured markers can enhance traditional clinical criteria, offering a more objective approach to ARDS diagnosis and severity assessment. Hematological markers such as NLR, MPV, MPVLR, Platelet count, and PDW could be invaluable in clinical settings for diagnosing and assessing ARDS severity. They offer a cost-effective, accessible means to improve diagnostic accuracy and patient stratification in ARDS. However, further prospective studies are necessary to confirm these findings and investigate their integration with other diagnostic tools in diverse clinical settings.

Endotyping in ARDS: one step forward in precision medicine.

BACKGROUND: The Berlin definition of acute respiratory distress syndrome (ARDS) includes only clinical characteristics. Understanding unique patient pathobiology may allow personalized treatment. We aimed to define and describe ARDS phenotypes/endotypes combining clinical and pathophysiologic parameters from a Canadian ARDS cohort. METHODS: A cohort of adult ARDS patients from multiple sites in Calgary, Canada, had plasma cytokine levels and clinical parameters measured in the first 24 h of ICU admission. We used a latent class model (LCM) to group the patients into several ARDS subgroups and identified the features differentiating those subgroups. We then discuss the subgroup effect on 30 day mortality. RESULTS: The LCM suggested three subgroups (n1 = 64, n2 = 86, and n3 = 30), and 23 out of 69 features made these subgroups distinct. The top five discriminating features were IL-8, IL-6, IL-10, TNF-a, and serum lactate. Mortality distinctively varied between subgroups. Individual clinical characteristics within the subgroup associated with mortality included mean PaO2/FiO2 ratio, pneumonia, platelet count, and bicarbonate negatively associated with mortality, while lactate, creatinine, shock, chronic kidney disease, vasopressor/ionotropic use, low GCS at admission, and sepsis were positively associated. IL-8 and Apache II were individual markers strongly associated with mortality (Area Under the Curve = 0.84). PERSPECTIVE: ARDS subgrouping using biomarkers and clinical characteristics is useful for categorizing a heterogeneous condition into several homogenous patient groups. This study found three ARDS subgroups using LCM; each subgroup has a different level of mortality. This model may also apply to developing further trial design, prognostication, and treatment selection.

Time to split: biomarker trajectories in pediatric acute respiratory distress syndrome hint at underlying disease.

Pediatric acute respiratory distress syndrome (ARDS) is severe, noncardiac hypoxemic respiratory failure that carries a substantial risk of death. Given the complexity of this clinically defined syndrome and the repeated failure of therapeutic trials, there has been an effort to identify subphenotypes of ARDS that may share targetable mechanisms of disease. In this issue of the JCI, Yehya and colleagues measured 19 plasma biomarkers in 279 children over the first seven days of ARDS. Increases in select tissue injury makers and inflammatory cytokines in peripheral blood were associated with multiple organ dysfunction syndrome and death, but not persistent ARDS. These findings argue that splitting patients by clinical and molecular phenotype may be more informative than lumping them under the umbrella diagnosis of ARDS. However, future studies are needed to determine whether these plasma factors represent targetable pathways in lung injury or are a consequence of systemic organ dysfunction.

Extracorporeal membrane oxygenation aggravates platelet glycoprotein V shedding and δ-granule deficiency in COVID-19-associated acute respiratory distress syndrome.

BACKGROUND: Extracorporeal membrane oxygenation (ECMO) is a lifesaving therapy in patients with acute respiratory distress syndrome (ARDS). Hemostatic complications are frequently observed in patients on ECMO and limit the success of this therapy. Platelets are key mediators of hemostasis enabling activation, aggregation, and thrombus formation by coming in contact with exposed matrix proteins via their surface receptors such as glycoprotein (GP) VI or GPIb/V/IX. Recent research has elucidated a regulatory role of the GPV subunit. The cleaved soluble GPV (sGPV) ectodomain was identified to spatiotemporally control fibrin formation through complex formation with thrombin. OBJECTIVES: We aimed to decipher the impact of ECMO on platelet phenotype and function, including the role of GPV and plasmatic sGPV. METHODS: We recruited 36 patients with ARDS in the wake of COVID-19 pneumonia and performed a longitudinal comparison of platelet phenotype and function in non-ECMO (n = 23) vs ECMO (n = 13) compared with those of healthy controls. Patients were assessed at up to 3 time points (t1 = days 1-3; t2 = days 4-6; and t3 = days 7-14 after cannulation/study inclusion). RESULTS: Agonist-induced platelet activation was assessed by flow cytometry and revealed decreased GPIIb/IIIa activation and α-granule release in all ARDS patients. During ECMO treatment, agonist-induced δ-granule release continuously decreased, which was independently confirmed by electron microscopy and was associated with a prolonged in vitro bleeding time. GPV expression on the platelet surface markedly decreased in ECMO patients compared with that in non-ECMO patients. Plasma sGPV levels were increased in ECMO patients and were associated with poor outcome. CONCLUSION: Our data demonstrate an ECMO-intrinsic platelet δ-granule deficiency and hemostatic dysfunction beyond the underlying ARDS.

Inflammatory subphenotypes previously identified in ARDS are associated with mortality at intensive care unit discharge: a secondary analysis of a prospective observational study.

BACKGROUND: Intensive care unit (ICU)-survivors have an increased risk of mortality after discharge compared to the general population. On ICU admission subphenotypes based on the plasma biomarker levels of interleukin-8, protein C and bicarbonate have been identified in patients admitted with acute respiratory distress syndrome (ARDS) that are prognostic of outcome and predictive of treatment response. We hypothesized that if these inflammatory subphenotypes previously identified among ARDS patients are assigned at ICU discharge in a more general critically ill population, they are associated with short- and long-term outcome. METHODS: A secondary analysis of a prospective observational cohort study conducted in two Dutch ICUs between 2011 and 2014 was performed. All patients discharged alive from the ICU were at ICU discharge adjudicated to the previously identified inflammatory subphenotypes applying a validated parsimonious model using variables measured median 10.6 h [IQR, 8.0-31.4] prior to ICU discharge. Subphenotype distribution at ICU discharge, clinical characteristics and outcomes were analyzed. As a sensitivity analysis, a latent class analysis (LCA) was executed for subphenotype identification based on plasma protein biomarkers at ICU discharge reflective of coagulation activation, endothelial cell activation and inflammation. Concordance between the subphenotyping strategies was studied. RESULTS: Of the 8332 patients included in the original cohort, 1483 ICU-survivors had plasma biomarkers available and could be assigned to the inflammatory subphenotypes. At ICU discharge 6% (n = 86) was assigned to the hyperinflammatory and 94% (n = 1397) to the hypoinflammatory subphenotype. Patients assigned to the hyperinflammatory subphenotype were discharged with signs of more severe organ dysfunction (SOFA scores 7 [IQR 5-9] vs. 4 [IQR 2-6], p < 0.001). Mortality was higher in patients assigned to the hyperinflammatory subphenotype (30-day mortality 21% vs. 11%, p = 0.005; one-year mortality 48% vs. 28%, p < 0.001). LCA deemed 2 subphenotypes most suitable. ICU-survivors from class 1 had significantly higher mortality compared to class 2. Patients belonging to the hyperinflammatory subphenotype were mainly in class 1. CONCLUSIONS: Patients assigned to the hyperinflammatory subphenotype at ICU discharge showed significantly stronger anomalies in coagulation activation, endothelial cell activation and inflammation pathways implicated in the pathogenesis of critical disease and increased mortality until one-year follow up.

Neutrophil-to-Lymphocyte Ratio: A Promising Predictor of Mortality in Patients With Acute Respiratory Distress Syndrome. A Retrospective Analysis of a Single Hospital Center.

OBJECTIVES: To examine how the neutrophil-to-lymphocyte ratio (NLR) affects both short-term and long-term mortality in individuals with acute respiratory distress syndrome (ARDS). DESIGN: A retrospective study. SETTING: Critical care unit. PARTICIPANTS: A total of 785 patients with ARDS. INTERVENTIONS: There were three groups in the NLR study. A Cox proportional hazards regression model was used to calculate the hazard ratio (HR) between the NLR and 30-day, 90-day, and 1-year mortality. MEASUREMENTS AND MAIN RESULTS: The 785 patients included 329 women (41.9%) and 456 men (58.1%), with a mean age of 63.4 ± 16.7 years and a mean NLR of 14.2 ± 9.8. The study population was divided into 3 groups based on NLR value. In the unadjusted model, compared to group 1 (NLR <6.0), group 2 (NLR 6.0-11.3) and group 3 (NLR >11.3) had HR values of 1.12 (95% confidence interval [CI], 0.83-1.52) and 2.39 (95% CI, 1.87-3.04), respectively, for 30-day all-cause mortality. This association remained significant after adjusting for potential confounding variables (HR, 1.54; 95% CI, 1.18-2.02), with a statistically significant trend (p = 0.0004) in group 3 (NLR >11.3). A similar effect was seen on both 90-day and 1-year all-cause mortality. The R2 value in a 2-piecewise linear regression was 1.25 (95% CI, 1.06-1.48; p < 0.0001) on the left side of the inflection point (NLR 17.1). CONCLUSIONS: In this retrospective single-center study, the NLR was a potential predictor of both short- and long-term mortality in patients with ARDS and may aid risk stratification.

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.

Respiratory drive heterogeneity associated with systemic inflammation and vascular permeability in acute respiratory distress syndrome.

BACKGROUND: In acute respiratory distress syndrome (ARDS), respiratory drive often differs among patients with similar clinical characteristics. Readily observable factors like acid-base state, oxygenation, mechanics, and sedation depth do not fully explain drive heterogeneity. This study evaluated the relationship of systemic inflammation and vascular permeability markers with respiratory drive and clinical outcomes in ARDS. METHODS: ARDS patients enrolled in the multicenter EPVent-2 trial with requisite data and plasma biomarkers were included. Neuromuscular blockade recipients were excluded. Respiratory drive was measured as PES0.1, the change in esophageal pressure during the first 0.1 s of inspiratory effort. Plasma angiopoietin-2, interleukin-6, and interleukin-8 were measured concomitantly, and 60-day clinical outcomes evaluated. RESULTS: 54.8% of 124 included patients had detectable respiratory drive (PES0.1 range of 0-5.1 cm H2O). Angiopoietin-2 and interleukin-8, but not interleukin-6, were associated with respiratory drive independently of acid-base, oxygenation, respiratory mechanics, and sedation depth. Sedation depth was not significantly associated with PES0.1 in an unadjusted model, or after adjusting for mechanics and chemoreceptor input. However, upon adding angiopoietin-2, interleukin-6, or interleukin-8 to models, lighter sedation was significantly associated with higher PES0.1. Risk of death was less with moderate drive (PES0.1 of 0.5-2.9 cm H2O) compared to either lower drive (hazard ratio 1.58, 95% CI 0.82-3.05) or higher drive (2.63, 95% CI 1.21-5.70) (p = 0.049). CONCLUSIONS: Among patients with ARDS, systemic inflammatory and vascular permeability markers were independently associated with higher respiratory drive. The heterogeneous response of respiratory drive to varying sedation depth may be explained in part by differences in inflammation and vascular permeability.

Biomarker-Based Risk Stratification Tool in Pediatric Acute Respiratory Distress Syndrome: Single-Center, Longitudinal Validation in a 2014-2019 Cohort.

OBJECTIVES: The Pediatric Acute Respiratory Distress Syndrome Biomarker Risk Model (PARDSEVERE) used age and three plasma biomarkers measured within 24 hours of pediatric acute respiratory distress syndrome (ARDS) onset to predict mortality in a pilot cohort of 152 patients. However, longitudinal performance of PARDSEVERE has not been evaluated, and it is unclear whether the risk model can be used to prognosticate after day 0. We, therefore, sought to determine the test characteristics of PARDSEVERE model and population over the first 7 days after ARDS onset. DESIGN: Secondary unplanned post hoc analysis of data from a prospective observational cohort study carried out 2014-2019. SETTING: University-affiliated PICU. PATIENTS: Mechanically ventilated children with ARDS. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Between July 2014 and December 2019, 279 patients with ARDS had plasma collected at day 0, 266 at day 3 (11 nonsurvivors, two discharged between days 0 and 3), and 207 at day 7 (27 nonsurvivors, 45 discharged between days 3 and 7). The actual prevalence of mortality on days 0, 3, and 7, was 23% (64/279), 14% (38/266), and 13% (27/207), respectively. The PARDSEVERE risk model for mortality on days 0, 3, and 7 had area under the receiver operating characteristic curve (AUROC [95% CI]) of 0.76 (0.69-0.82), 0.68 (0.60-0.76), and 0.74 (0.65-0.83), respectively. The AUROC data translate into prevalence thresholds for the PARDSEVERE model for mortality (i.e., using the sensitivity and specificity values) of 37%, 27%, and 24% on days 0, 3, and 7, respectively. Negative predictive value (NPV) was high throughout (0.87-0.90 for all three-time points). CONCLUSIONS: In this exploratory analysis of the PARDSEVERE model of mortality risk prediction in a population longitudinal series of data from days 0, 3, and 7 after ARDS diagnosis, the diagnostic performance is in the "acceptable" category. NPV was good. A major limitation is that actual mortality is far below the prevalence threshold for such testing. The model may, therefore, be more useful in cohorts with higher mortality rates (e.g., immunocompromised, other countries), and future enhancements to the model should be explored.

Inflammatory and tissue injury marker dynamics in pediatric acute respiratory distress syndrome.

BACKGROUNDThe molecular signature of pediatric acute respiratory distress syndrome (ARDS) is poorly described, and the degree to which hyperinflammation or specific tissue injury contributes to outcomes is unknown. Therefore, we profiled inflammation and tissue injury dynamics over the first 7 days of ARDS, and associated specific biomarkers with mortality, persistent ARDS, and persistent multiple organ dysfunction syndrome (MODS).METHODSIn a single-center prospective cohort of intubated pediatric patients with ARDS, we collected plasma on days 0, 3, and 7. Nineteen biomarkers reflecting inflammation, tissue injury, and damage-associated molecular patterns (DAMPs) were measured. We assessed the relationship between biomarkers and trajectories with mortality, persistent ARDS, or persistent MODS using multivariable mixed effect models.RESULTSIn 279 patients (64 [23%] nonsurvivors), hyperinflammatory cytokines, tissue injury markers, and DAMPs were higher in nonsurvivors. Survivors and nonsurvivors showed different biomarker trajectories. IL-1α, soluble tumor necrosis factor receptor 1, angiopoietin 2 (ANG2), and surfactant protein D increased in nonsurvivors, while DAMPs remained persistently elevated. ANG2 and procollagen type III N-terminal peptide were associated with persistent ARDS, whereas multiple cytokines, tissue injury markers, and DAMPs were associated with persistent MODS. Corticosteroid use did not impact the association of biomarker levels or trajectory with mortality.CONCLUSIONSPediatric ARDS survivors and nonsurvivors had distinct biomarker trajectories, with cytokines, endothelial and alveolar epithelial injury, and DAMPs elevated in nonsurvivors. Mortality markers overlapped with markers associated with persistent MODS, rather than persistent ARDS.FUNDINGNIH (K23HL-136688, R01-HL148054).

HAPTOGLOBIN DEPLETION DURING THE FIRST 7 DAYS OF VENO-VENOUS EXTRACORPOREAL MEMBRANE OXYGENATION THERAPY IS ASSOCIATED WITH INCREASED MORTALITY AND ADVERSE OUTCOMES IN PATIENTS WITH ACUTE RESPIRATORY DISTRESS SYNDROME.

ABSTRACT: Background: Hemolysis is a frequent complication in patients with sepsis, ARDS, or extracorporeal membrane oxygenation (ECMO). Haptoglobin (Hp) can scavenge released cell-free hemoglobin (CFH). Hemolysis and low plasma concentrations of Hp may be independently associated with mortality in critically ill patients. Methods: This study used a retrospective analysis of 435 patients with ARDS and veno-venous ECMO therapy, admitted to a tertiary ARDS referral center (01/2007-12/2018). Hp depletion was defined as decrease in plasma Hp concentration <0.39 g/L within the first week after ECMO initiation. Patients with Hp depletion were compared to patients without Hp depletion. The primary endpoint was 28-day mortality. Secondary endpoints included organ dysfunction-free, renal replacement therapy-free, vasopressor-free, and ECMO-free composites. Results: Patients with Hp depletion (n = 269) had a significantly higher mortality 28 days after ECMO initiation compared to patients without Hp depletion (43.5% [95% CI 37.52-49.66] vs. 25.3% [19.03-32.74], P < 0.001). Furthermore, patients with Hp depletion had fewer organ dysfunction-free days (subdistribution hazard ratio [SHR] 0.35 [95% CI 0.25-0.50], P < 0.001), lower chances for successful weaning from renal replacement therapy (SHR 0.50 [0.32-0.79], P < 0.001), vasopressor therapy (SHR 0.39 [0.28-0.54], P < 0.001), and ECMO therapy (SHR 0.41 [0.30-0.57], P < 0.001) within 28 days after ECMO initiation. Patients with initial Hp <0.66 g/L had higher risks for Hp depletion than patients with initial Hp ≥0.66 g/L. Conclusion: Patients with Hp depletion within the first week of ECMO therapy might benefit from close monitoring of hemolysis with early detection and elimination of the underlying cause. They might be potential candidates for future Hp supplementation therapy to prevent overload of the CFH-scavenger system.

Association of coagulation function with the risk of in-hospital mortality in patients with severe acute respiratory distress syndrome.

BACKGROUND: To evaluate the association of coagulation disorder score with the risk of in-hospital mortality in acute respiratory distress syndrome (ARDS) patients. METHODS: In this cohort study, 7,001 adult patients with ARDS were identified from the Medical Information Mart for Intensive Care Database-IV (MIMIC-IV). Univariate and multivariate Logistic stepwise regression models were used to explore the associations of coagulation-associated biomarkers with the risk of in-hospital mortality in patients with ADRS. Restricted cubic spline (RCS) was plotted to explore the association between coagulation disorder score and in-hospital mortality of ARDS patients. RESULTS: The follow-up time for in-hospital death was 7.15 (4.62, 13.88) days. There were 1,187 patients died and 5,814 people survived in hospital. After adjusting for confounding factors, increased risk of in-hospital mortality in ARDS patients was observed in those with median coagulation disorder score [odds ratio (OR) = 1.22, 95% confidence interval (CI): 1.01-1.47) and high coagulation disorder score (OR = 1.38, 95% CI: 1.06-1.80). The results of RCS indicated that when the coagulation disorder score >2, the trend of in-hospital mortality rose gradually, and OR was >1. CONCLUSIONS: Poor coagulation function was associated with increased risk of in-hospital mortality in ARDS patients. The findings implied that clinicians should regularly detect the levels of coagulation-associated biomarkers for the management of ARDS patients.

Patient stratification using plasma cytokines and their regulators in sepsis: relationship to outcomes, treatment effect and leucocyte transcriptomic subphenotypes.

RATIONALE: Heterogeneity of the host response within sepsis, acute respiratory distress syndrome (ARDS) and more widely critical illness, limits discovery and targeting of immunomodulatory therapies. Clustering approaches using clinical and circulating biomarkers have defined hyper-inflammatory and hypo-inflammatory subphenotypes in ARDS associated with differential treatment response. It is unknown if similar subphenotypes exist in sepsis populations where leucocyte transcriptomic-defined subphenotypes have been reported. OBJECTIVES: We investigated whether inflammatory clusters based on cytokine protein abundance were seen in sepsis, and the relationships with previously described transcriptomic subphenotypes. METHODS: Hierarchical cluster and latent class analysis were applied to an observational study (UK Genomic Advances in Sepsis (GAinS)) (n=124 patients) and two clinical trial datasets (VANISH, n=155 and LeoPARDS, n=484) in which the plasma protein abundance of 65, 21, 11 circulating cytokines, cytokine receptors and regulators were quantified. Clinical features, outcomes, response to trial treatments and assignment to transcriptomic subphenotypes were compared between inflammatory clusters. MEASUREMENTS AND MAIN RESULTS: We identified two (UK GAinS, VANISH) or three (LeoPARDS) inflammatory clusters. A group with high levels of pro-inflammatory and anti-inflammatory cytokines was seen that was associated with worse organ dysfunction and survival. No interaction between inflammatory clusters and trial treatment response was found. We found variable overlap of inflammatory clusters and leucocyte transcriptomic subphenotypes. CONCLUSIONS: These findings demonstrate that differences in response at the level of cytokine biology show clustering related to severity, but not treatment response, and may provide complementary information to transcriptomic sepsis subphenotypes. TRIAL REGISTRATION NUMBER: ISRCTN20769191, ISRCTN12776039.

Increased platelet to red blood cell transfusion ratio associated with acute kidney injury in children with life-threatening bleeding.

INTRODUCTION: Transfusion may increase the risk of organ failure through immunomodulatory effects. The primary objective of this study was to assess for patient or transfusion-related factors that are independently associated with the risk of acute kidney injury (AKI) and acute respiratory distress syndrome (ARDS) in a cohort of children with life-threatening bleeding from all etiologies. METHODS: In a secondary analysis of the prospective observational massive transfusion in children (MATIC) study, multivariable logistic regression was performed in an adjusted analysis to determine if blood product ratios or deficits were independently associated with AKI or ARDS in children with life-threatening bleeding. RESULTS: There were 449 children included with a median (interquartile range, IQR) age of 7.3 years (1.7-14.7). Within 5 days of the life-threatening bleeding event, AKI occurred in 18.5% and ARDS occurred in 20.3% of the subjects. Every 10% increase in the platelet to red blood cell transfusion ratio is independently associated with a 12.7% increase in the odds of AKI (adjusted odds ratio 1.127; 95% confidence interval 1.025-1.239; p-value .013). Subjects with operative or medical etiologies were independently associated with an increased risk of AKI compared to those with traumatic injury. No transfusion-related variables were independently associated with the risk of developing ARDS. CONCLUSION: The use of increased platelet to red blood cell transfusion ratios in children with life-threatening bleeding of any etiology may increase the risk of AKI but not ARDS. Prospective trials are needed to determine if increased platelet use in this cohort increases the risk of AKI to examine possible mechanisms.

The Triglycerides and Glucose Index Is an Independent Risk Factor for Acute Respiratory Distress Syndrome in Patients with COVID-19.

Introduction: Although it has been observed that the triglycerides and glucose (TyG) index, a biomarker of insulin resistance, is associated with severity and morbidity by COVID-19, evidence is still scarce. Therefore, the objective of this study was to determine whether the TyG index is associated with both the degree of severity and mortality by acute respiratory distress syndrome (ARDS) in patients with COVID-19. Methods: Men and women aged 20 years or more with diagnosis of COVID-19 were included in a case-control study. Exclusion criteria were pregnancy, cancer, autoimmune diseases, autoimmune treatment, and incomplete data. Patients with severe COVID-19 ARDS were allocated into the case group, and those with mild or moderate COVID-19 ARDS in the control group. COVID-19 was defined by a positive reverse transcriptase-polymerase chain reaction test for SARS-CoV-2, and ARDS was defined according to the Berlin criteria. Results: A total of 206 patients were included and allocated into the case (n = 103) and control (n = 103) groups. The logistic regression analysis adjusted by age, sex, and body mass index showed that the TyG index is significantly associated with moderate [odds ratio (OR) = 6.0; 95% confidence interval (CI): 1.1-30.6] and severe (OR = 9.5; 95% CI: 2.4-37.5) COVID-19 ARDS, and death (OR = 10.1; 95% CI: 2.2-46.5). Conclusion: The results of our study show a significant and independent association of the TyG index with ARDS and mortality in patients with COVID-19.