Personalized mechanical ventilation guided by ultrasound in patients with acute respiratory distress syndrome (PEGASUS): study protocol for an international randomized clinical trial.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a frequent cause of hypoxemic respiratory failure with a mortality rate of approximately 30%. Identifying ARDS subphenotypes based on "focal" or "non-focal" lung morphology has the potential to better target mechanical ventilation strategies of individual patients. However, classifying morphology through chest radiography or computed tomography is either inaccurate or impractical. Lung ultrasound (LUS) is a non-invasive bedside tool that can accurately distinguish "focal" from "non-focal" lung morphology. We hypothesize that LUS-guided personalized mechanical ventilation in ARDS patients leads to a reduction in 90-day mortality compared to conventional mechanical ventilation. METHODS: The Personalized Mechanical Ventilation Guided by UltraSound in Patients with Acute Respiratory Distress Syndrome (PEGASUS) study is an investigator-initiated, international, randomized clinical trial (RCT) that plans to enroll 538 invasively ventilated adult intensive care unit (ICU) patients with moderate to severe ARDS. Eligible patients will receive a LUS exam to classify lung morphology as "focal" or "non-focal". Thereafter, patients will be randomized within 12 h after ARDS diagnosis to receive standard care or personalized ventilation where the ventilation strategy is adjusted to the morphology subphenotype, i.e., higher positive end-expiratory pressure (PEEP) and recruitment maneuvers for "non-focal" ARDS and lower PEEP and prone positioning for "focal" ARDS. The primary endpoint is all-cause mortality at day 90. Secondary outcomes are mortality at day 28, ventilator-free days at day 28, ICU length of stay, ICU mortality, hospital length of stay, hospital mortality, and number of complications (ventilator-associated pneumonia, pneumothorax, and need for rescue therapy). After a pilot phase of 80 patients, the correct interpretation of LUS images and correct application of the intervention within the safe limits of mechanical ventilation will be evaluated. DISCUSSION: PEGASUS is the first RCT that compares LUS-guided personalized mechanical ventilation with conventional ventilation in invasively ventilated patients with moderate and severe ARDS. If this study demonstrates that personalized ventilation guided by LUS can improve the outcomes of ARDS patients, it has the potential to shift the existing one-size-fits-all ventilation strategy towards a more individualized approach. TRIAL REGISTRATION: The PEGASUS trial was registered before the inclusion of the first patient, https://clinicaltrials.gov/ (ID: NCT05492344).

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.

Consensus statements on the utility of defining ARDS and the utility of past and current definitions of ARDS-protocol for a Delphi study.

INTRODUCTION: Acute respiratory distress syndrome (ARDS), marked by acute hypoxemia and bilateral pulmonary infiltrates, has been defined in multiple ways since its first description. This Delphi study aims to collect global opinions on the conceptual framework of ARDS, assess the usefulness of components within current and past definitions and investigate the role of subphenotyping. The varied expertise of the panel will provide valuable insights for refining future ARDS definitions and improving clinical management. METHODS: A diverse panel of 35-40 experts will be selected based on predefined criteria. Multiple choice questions (MCQs) or 7-point Likert-scale statements will be used in the iterative Delphi rounds to achieve consensus on key aspects related to the utility of definitions and subphenotyping. The Delphi rounds will be continued until a stable agreement or disagreement is achieved for all statements. ANALYSIS: Consensus will be considered as reached when a choice in MCQs or Likert-scale statement achieved ≥80% of votes for agreement or disagreement. The stability will be checked by non-parametric χ2 tests or Kruskal Wallis test starting from the second round of Delphi process. A p-value ≥0.05 will be used to define stability. ETHICS AND DISSEMINATION: The study will be conducted in full concordance with the principles of the Declaration of Helsinki and will be reported according to CREDES guidance. This study has been granted an ethical approval waiver by the NMC Healthcare Regional Research Ethics Committee, Dubai (NMCHC/CR/DXB/REC/APP/002), owing to the nature of the research. Informed consent will be obtained from all panellists before the start of the Delphi process. The study will be published in a peer-review journal with the authorship agreed as per ICMJE requirements. TRIAL REGISTRATION NUMBER: NCT06159465.

From ICU Syndromes to ICU Subphenotypes: Consensus Report and Recommendations For Developing Precision Medicine in ICU.

Critical care uses syndromic definitions to describe patient groups for clinical practice and research. There is growing recognition that a "precision medicine" approach is required and that integrated biologic and physiologic data identify reproducible subpopulations that may respond differently to treatment. This article reviews the current state of the field and considers how to successfully transition to a precision medicine approach. In order to impact clinical care, identified subpopulations must do more than differentiate prognosis. They must differentiate response to treatment, ideally by defining subgroups with distinct functional or pathobiological mechanisms (endotypes). There are now multiple examples of reproducible subpopulations of sepsis, acute respiratory distress syndrome, and acute kidney or brain injury described using clinical, physiological, and/or biological data. Many of these subpopulations have demonstrated the potential to define differential treatment response, largely in retrospective studies, and that the same treatment-responsive subpopulations may cross multiple clinical syndromes (treatable traits). To bring about a change in clinical practice, a precision medicine approach must be evaluated in prospective clinical studies requiring novel adaptive trial designs. Several such studies are underway but there are multiple challenges to be tackled. Such subpopulations must be readily identifiable and be applicable to all critically ill populations around the world. Subdividing clinical syndromes into subpopulations will require large patient numbers. Global collaboration of investigators, clinicians, industry and patients over many years will therefore be required to transition to a precision medicine approach and ultimately realize treatment advances seen in other medical fields. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort.

BACKGROUND: Acute respiratory distress syndrome (ARDS) can be classified into sub-phenotypes according to different inflammatory/clinical status. Prognostic enrichment was achieved by grouping patients into hypoinflammatory or hyperinflammatory sub-phenotypes, even though the time of analysis may change the classification according to treatment response or disease evolution. We aimed to evaluate when patients can be clustered in more than 1 group, and how they may change the clustering of patients using data of baseline or day 3, and the prognosis of patients according to their evolution by changing or not the cluster. METHODS: Multicenter, observational prospective, and retrospective study of patients admitted due to ARDS related to COVID-19 infection in Spain. Patients were grouped according to a clustering mixed-type data algorithm (k-prototypes) using continuous and categorical readily available variables at baseline and day 3. RESULTS: Of 6205 patients, 3743 (60%) were included in the study. According to silhouette analysis, patients were grouped in two clusters. At baseline, 1402 (37%) patients were included in cluster 1 and 2341(63%) in cluster 2. On day 3, 1557(42%) patients were included in cluster 1 and 2086 (57%) in cluster 2. The patients included in cluster 2 were older and more frequently hypertensive and had a higher prevalence of shock, organ dysfunction, inflammatory biomarkers, and worst respiratory indexes at both time points. The 90-day mortality was higher in cluster 2 at both clustering processes (43.8% [n = 1025] versus 27.3% [n = 383] at baseline, and 49% [n = 1023] versus 20.6% [n = 321] on day 3). Four hundred and fifty-eight (33%) patients clustered in the first group were clustered in the second group on day 3. In contrast, 638 (27%) patients clustered in the second group were clustered in the first group on day 3. CONCLUSIONS: During the first days, patients can be clustered into two groups and the process of clustering patients may change as they continue to evolve. This means that despite a vast majority of patients remaining in the same cluster, a minority reaching 33% of patients analyzed may be re-categorized into different clusters based on their progress. Such changes can significantly impact their prognosis.

Breath metabolomics for diagnosis of acute respiratory distress syndrome.

BACKGROUND: Acute respiratory distress syndrome (ARDS) poses challenges in early identification. Exhaled breath contains metabolites reflective of pulmonary inflammation. AIM: To evaluate the diagnostic accuracy of breath metabolites for ARDS in invasively ventilated intensive care unit (ICU) patients. METHODS: This two-center observational study included critically ill patients receiving invasive ventilation. Gas chromatography and mass spectrometry (GC-MS) was used to quantify the exhaled metabolites. The Berlin definition of ARDS was assessed by three experts to categorize all patients into "certain ARDS", "certain no ARDS" and "uncertain ARDS" groups. The patients with "certain" labels from one hospital formed the derivation cohort used to train a classifier built based on the five most significant breath metabolites. The diagnostic accuracy of the classifier was assessed in all patients from the second hospital and combined with the lung injury prediction score (LIPS). RESULTS: A total of 499 patients were included in this study. Three hundred fifty-seven patients were included in the derivation cohort (60 with certain ARDS; 17%), and 142 patients in the validation cohort (47 with certain ARDS; 33%). The metabolites 1-methylpyrrole, 1,3,5-trifluorobenzene, methoxyacetic acid, 2-methylfuran and 2-methyl-1-propanol were included in the classifier. The classifier had an area under the receiver operating characteristics curve (AUROCC) of 0.71 (CI 0.63-0.78) in the derivation cohort and 0.63 (CI 0.52-0.74) in the validation cohort. Combining the breath test with the LIPS does not significantly enhance the diagnostic performance. CONCLUSION: An exhaled breath metabolomics-based classifier has moderate diagnostic accuracy for ARDS but was not sufficiently accurate for clinical use, even after combination with a clinical prediction score.

Breath Markers of Oxidative Stress in Children with Severe Viral Lower Respiratory Tract Infection.

Severe viral lower respiratory tract infection (LRTI), resulting in both acute and long-term pulmonary disease, constitutes a substantial burden among young children. Viral LRTI triggers local oxidative stress pathways by infection and inflammation, and supportive care in the pediatric intensive care unit may further aggravate oxidative injury. The main goal of this exploratory study was to identify and monitor breath markers linked to oxidative stress in children over the disease course of severe viral LRTI. Exhaled breath was sampled during invasive ventilation, and volatile organic compounds (VOCs) were analyzed using gas chromatography and mass spectrometry. VOCs were selected in an untargeted principal component analysis and assessed for change over time. In addition, identified VOCs were correlated with clinical parameters. Seventy breath samples from 21 patients were analyzed. A total of 15 VOCs were identified that contributed the most to the explained variance of breath markers. Of these 15 VOCs, 10 were previously linked to pathways of oxidative stress. Eight VOCs, including seven alkanes and methyl alkanes, significantly decreased from the initial phase of ventilation to the day of extubation. No correlation was observed with the administered oxygen dose, whereas six VOCs showed a poor to strong positive correlation with driving pressure. In this prospective study of children with severe viral LRTI, the majority of VOCs that were most important for the explained variance mirrored clinical improvement. These breath markers could potentially help monitor the pulmonary oxidative status in these patients, but further research with other objective measures of pulmonary injury is required.

Reframing sepsis immunobiology for translation: towards informative subtyping and targeted immunomodulatory therapies.

Sepsis is a common and deadly condition. Within the current model of sepsis immunobiology, the framing of dysregulated host immune responses into proinflammatory and immunosuppressive responses for the testing of novel treatments has not resulted in successful immunomodulatory therapies. Thus, the recent focus has been to parse observable heterogeneity into subtypes of sepsis to enable personalised immunomodulation. In this Personal View, we highlight that many fundamental immunological concepts such as resistance, disease tolerance, resilience, resolution, and repair are not incorporated into the current sepsis immunobiology model. The focus for addressing heterogeneity in sepsis should be broadened beyond subtyping to encompass the identification of deterministic molecular networks or dominant mechanisms. We explicitly reframe the dysregulated host immune responses in sepsis as altered homoeostasis with pathological disruption of immune-driven resistance, disease tolerance, resilience, and resolution mechanisms. Our proposal highlights opportunities to identify novel treatment targets and could enable successful immunomodulation in the future.

HS-GC-MS analysis of volatile organic compounds after hyperoxia-induced oxidative stress: a validation study.

BACKGROUND: Exhaled volatile organic compounds (VOCs), particularly hydrocarbons from oxidative stress-induced lipid peroxidation, are associated with hyperoxia exposure. However, important heterogeneity amongst identified VOCs and concerns about their precise pathophysiological origins warrant translational studies assessing their validity as a marker of hyperoxia-induced oxidative stress. Therefore, this study sought to examine changes in VOCs previously associated with the oxidative stress response in hyperoxia-exposed lung epithelial cells. METHODS: A549 alveolar epithelial cells were exposed to hyperoxia for 24 h, or to room air as normoxia controls, or hydrogen peroxide as oxidative-stress positive controls. VOCs were sampled from the headspace, analysed by gas chromatography coupled with mass spectrometry and compared by targeted and untargeted analyses. A secondary analysis of breath samples from a large cohort of critically ill adult patients assessed the association of identified VOCs with clinical oxygen exposure. RESULTS: Following cellular hyperoxia exposure, none of the targeted VOCs, previously proposed as breath markers of oxidative stress, were increased, and decane was significantly decreased. Untargeted analysis did not reveal novel identifiable hyperoxia-associated VOCs. Within the clinical cohort, three previously proposed breath markers of oxidative stress, hexane, octane, and decane had no real diagnostic value in discriminating patients exposed to hyperoxia. CONCLUSIONS: Hyperoxia exposure of alveolar epithelial cells did not result in an increase in identifiable VOCs, whilst VOCs previously linked to oxidative stress were not associated with oxygen exposure in a cohort of critically ill patients. These findings suggest that the pathophysiological origin of previously proposed breath markers of oxidative stress is more complex than just oxidative stress from hyperoxia at the lung epithelial cellular level.

Correlation between Serum Biomarkers and Lung Ultrasound in COVID-19: An Observational Study.

Serum biomarkers and lung ultrasound are important measures for prognostication and treatment allocation in patients with COVID-19. Currently, there is a paucity of studies investigating relationships between serum biomarkers and ultrasonographic biomarkers derived from lung ultrasound. This study aims to assess correlations between serum biomarkers and lung ultrasound findings. This study is a secondary analysis of four prospective observational studies in adult patients with COVID-19. Serum biomarkers included markers of epithelial injury, endothelial dysfunction and immune activation. The primary outcome was the correlation between biomarker concentrations and lung ultrasound score assessed with Pearson's (r) or Spearman's (rs) correlations. Forty-four patients (67 [41-88] years old, 25% female, 52% ICU patients) were included. GAS6 (rs = 0.39), CRP (rs = 0.42) and SP-D (rs = 0.36) were correlated with lung ultrasound scores. ANG-1 (rs = -0.39) was inversely correlated with lung ultrasound scores. No correlations were found between lung ultrasound score and several other serum biomarkers. In patients with COVID-19, several serum biomarkers of epithelial injury, endothelial dysfunction and immune activation correlated with lung ultrasound findings. The lack of correlations with certain biomarkers could offer opportunities for precise prognostication and targeted therapeutic interventions by integrating these unlinked biomarkers.

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.

Host Response Changes and Their Association with Mortality in COVID-19 Patients with Lymphopenia.

Rationale: Lymphopenia in coronavirus disease (COVID-19) is associated with increased mortality. Objectives: To explore the association between lymphopenia, host response aberrations, and mortality in patients with lymphopenic COVID-19. Methods: We determined 43 plasma biomarkers reflective of four pathophysiological domains: endothelial cell and coagulation activation, inflammation and organ damage, cytokine release, and chemokine release. We explored if decreased concentrations of lymphocyte-derived proteins in patients with lymphopenia were associated with an increase in mortality. We sought to identify host response phenotypes in patients with lymphopenia by cluster analysis of plasma biomarkers. Measurements and Main Results: A total of 439 general ward patients with COVID-19 were stratified by baseline lymphocyte counts: normal (>1.0 × 109/L; n = 167), mild lymphopenia (>0.5 to ⩽1.0 × 109/L; n = 194), and severe lymphopenia (⩽0.5 × 109/L; n = 78). Lymphopenia was associated with alterations in each host response domain. Lymphopenia was associated with increased mortality. Moreover, in patients with lymphopenia (n = 272), decreased concentrations of several lymphocyte-derived proteins (e.g., CCL5, IL-4, IL-13, IL-17A) were associated with an increase in mortality (at P < 0.01 or stronger significance levels). A cluster analysis revealed three host response phenotypes in patients with lymphopenia: "hyporesponsive" (23.2%), "hypercytokinemic" (36.4%), and "inflammatory-injurious" (40.4%), with substantially differing mortality rates of 9.5%, 5.1%, and 26.4%, respectively. A 10-biomarker model accurately predicted these host response phenotypes in an external cohort with similar mortality distribution. The inflammatory-injurious phenotype showed a remarkable combination of relatively high inflammation and organ damage markers with high antiinflammatory cytokine levels yet low proinflammatory cytokine levels. Conclusions: Lymphopenia in COVID-19 signifies a heterogenous group of patients with distinct host response features. Specific host responses contribute to lymphopenia-associated mortality in COVID-19, including reduced CCL5 levels.

The alveolar fibroproliferative response in moderate to severe COVID-19-related acute respiratory distress syndrome and 1-yr follow-up.

COVID-19-related acute respiratory distress syndrome (ARDS) can lead to long-term pulmonary fibrotic lesions. Alveolar fibroproliferative response (FPR) is a key factor in the development of pulmonary fibrosis. N-terminal peptide of procollagen III (NT-PCP-III) is a validated biomarker for activated FPR in ARDS. This study aimed to assess the association between dynamic changes in alveolar FPR and long-term outcomes, as well as mortality in COVID-19 ARDS patients. We conducted a prospective cohort study of 154 COVID-19 ARDS patients. We collected bronchoalveolar lavage (BAL) and blood samples for measurement of 17 pulmonary fibrosis biomarkers, including NT-PCP-III. We assessed pulmonary function and chest computed tomography (CT) at 3 and 12 mo after hospital discharge. We performed joint modeling to assess the association between longitudinal changes in biomarker levels and mortality at day 90 after starting mechanical ventilation. 154 patients with 284 BAL samples were analyzed. Of all patients, 40% survived to day 90, of whom 54 completed the follow-up procedure. A longitudinal increase in NT-PCP-III was associated with increased mortality (HR 2.89, 95% CI: 2.55-3.28; P < 0.001). Forced vital capacity and diffusion for carbon monoxide were impaired at 3 mo but improved significantly at one year after hospital discharge (P = 0.03 and P = 0.004, respectively). There was no strong evidence linking alveolar FPR during hospitalization and signs of pulmonary fibrosis in pulmonary function or chest CT images during 1-yr follow-up. In COVID-19 ARDS patients, alveolar FPR during hospitalization was associated with higher mortality but not with the presence of long-term fibrotic lung sequelae within survivors.NEW & NOTEWORTHY This is the first prospective study on the longitudinal alveolar fibroproliferative response in COVID-19 ARDS and its relationship with mortality and long-term follow-up. We used the largest cohort of COVID-19 ARDS patients who had consecutive bronchoalveolar lavages and measured 17 pulmonary fibroproliferative biomarkers. We found that a higher fibroproliferative response during admission was associated with increased mortality, but not correlated with long-term fibrotic lung sequelae in survivors.

Uncovering heterogeneity in sepsis: a comparative analysis of subphenotypes.

PURPOSE: The heterogeneity in sepsis is held responsible, in part, for the lack of precision treatment. Many attempts to identify subtypes of sepsis patients identify those with shared underlying biology or outcomes. To date, though, there has been limited effort to determine overlap across these previously identified subtypes. We aimed to determine the concordance of critically ill patients with sepsis classified by four previously described subtype strategies. METHODS: This secondary analysis of a multicenter prospective observational study included 522 critically ill patients with sepsis assigned to four previously established subtype strategies, primarily based on: (i) clinical data in the electronic health record (α, ß, γ, and δ), (ii) biomarker data (hyper- and hypoinflammatory), and (iii-iv) transcriptomic data (Mars1-Mars4 and SRS1-SRS2). Concordance was studied between different subtype labels, clinical characteristics, biological host response aberrations, as well as combinations of subtypes by sepsis ensembles. RESULTS: All four subtype labels could be adjudicated in this cohort, with the distribution of the clinical subtype varying most from the original cohort. The most common subtypes in each of the four strategies were γ (61%), which is higher compared to the original classification, hypoinflammatory (60%), Mars2 (35%), and SRS2 (54%). There was no clear relationship between any of the subtyping approaches (Cramer's V = 0.086-0.456). Mars2 and SRS1 were most alike in terms of host response biomarkers (p = 0.079-0.424), while other subtype strategies showed no clear relationship. Patients enriched for multiple subtypes revealed that characteristics and outcomes differ dependent on the combination of subtypes made. CONCLUSION: Among critically ill patients with sepsis, subtype strategies using clinical, biomarker, and transcriptomic data do not identify comparable patient populations and are likely to reflect disparate clinical characteristics and underlying biology.

The diagnostic accuracy of lung ultrasound to determine PiCCO-derived extravascular lung water in invasively ventilated patients with COVID-19 ARDS.

BACKGROUND: Lung ultrasound (LUS) can detect pulmonary edema and it is under consideration to be added to updated acute respiratory distress syndrome (ARDS) criteria. However, it remains uncertain whether different LUS scores can be used to quantify pulmonary edema in patient with ARDS. OBJECTIVES: This study examined the diagnostic accuracy of four LUS scores with the extravascular lung water index (EVLWi) assessed by transpulmonary thermodilution in patients with moderate-to-severe COVID-19 ARDS. METHODS: In this predefined secondary analysis of a multicenter randomized-controlled trial (InventCOVID), patients were enrolled within 48 hours after intubation and underwent LUS and EVLWi measurement on the first and fourth day after enrolment. EVLWi and ∆EVLWi were used as reference standards. Two 12-region scores (global LUS and LUS-ARDS), an 8-region anterior-lateral score and a 4-region B-line score were used as index tests. Pearson correlation was performed and the area under the receiver operating characteristics curve (AUROCC) for severe pulmonary edema (EVLWi > 15 mL/kg) was calculated. RESULTS: 26 out of 30 patients (87%) had complete LUS and EVLWi measurements at time point 1 and 24 out of 29 patients (83%) at time point 2. The global LUS (r = 0.54), LUS-ARDS (r = 0.58) and anterior-lateral score (r = 0.54) correlated significantly with EVLWi, while the B-line score did not (r = 0.32). ∆global LUS (r = 0.49) and ∆anterior-lateral LUS (r = 0.52) correlated significantly with ∆EVLWi. AUROCC for EVLWi > 15 ml/kg was 0.73 for the global LUS, 0.79 for the anterior-lateral and 0.85 for the LUS-ARDS score. CONCLUSIONS: Overall, LUS demonstrated an acceptable diagnostic accuracy for detection of pulmonary edema in moderate-to-severe COVID-19 ARDS when compared with PICCO. For identifying patients at risk of severe pulmonary edema, an extended score considering pleural morphology may be of added value. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT04794088, registered on 11 March 2021. European Clinical Trials Database number 2020-005447-23.