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

Evaluation of the Kinetics of Pancreatic Stone Protein as a Predictor of Ventilator-Associated Pneumonia

Funding Information: This study was partially supported by Abionic, CIBERES, and Research and Innovation Institute Parc Tauli (I3PT). A.C. acknowledges receiving financial support from Instituto de Salud Carlos III (ISCIII; Sara Borrell 2021: CD21/00087). The funding sources had no role in the design and conduct of the study; the collection, management, analysis, and interpretation of the data; the preparation, review, or approval of the manuscript; or in the decision to submit the manuscript for publication. Publisher Copyright: © 2023 by the authors.BACKGROUND: Ventilator-associated pneumonia (VAP) is a severe condition. Early and adequate antibiotic treatment is the most important strategy for improving prognosis. Pancreatic Stone Protein (PSP) has been described as a biomarker that increases values 3–4 days before the clinical diagnosis of nosocomial sepsis in different clinical settings. We hypothesized that serial measures of PSP and its kinetics allow for an early diagnosis of VAP. METHODS: The BioVAP study was a prospective observational study designed to evaluate the role of biomarker dynamics in the diagnosis of VAP. To determine the association between repeatedly measured PSP and the risk of VAP, we used joint models for longitudinal and time-to-event data. RESULTS: Of 209 patients, 43 (20.6%) patients developed VAP, with a median time of 4 days. Multivariate joint models with PSP, CRP, and PCT did not show an association between biomarkers and VAP for the daily absolute value, with a hazard ratio (HR) for PSP of 1.01 (95% credible interval: 0.97 to 1.05), for CRP of 1.00 (0.83 to 1.22), and for PCT of 0.95 (0.82 to 1.08). The daily change of biomarkers provided similar results, with an HR for PSP of 1.15 (0.94 to 1.41), for CRP of 0.76 (0.35 to 1.58), and for PCT of 0.77 (0.40 to 1.45). CONCLUSION: Neither absolute PSP values nor PSP kinetics alone nor in combination with other biomarkers were useful in improving the prediction diagnosis accuracy in patients with VAP. Clinical Trial Registration: Registered retrospectively on August 3rd, 2012. NCT02078999.publishersversionpublishe

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 &gt; 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 &gt; 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.</p

Biomarker patterns in patients with cardiogenic shock versus septic shock

Background: In cardiogenic shock (CS), contractile failure is often accompanied by a systemic inflammatory response syndrome. In contrast, many patients with septic shock (SS) develop cardiac dysfunction. A similar hemodynamic support strategy is often deployed in both syndromes but it is unclear whether this is justified based on profiles of biomarkers expressing neurohormonal activation and cardiovascular stress. Methods: In this prospective, multicenter cohort, 111 patients with acute myocardial infarction related CS were identified, and matched to patients with SS. Clinical parameters were collected and blood samples were obtained on day 1–3 of Intensive Care admission. Results: In this shock cohort comprising 222 patients, with a mean age of 61 (±13.5) years and of whom 161 (37 %) were male, we found that despite obvious clinical disparities on admission, mortality at 30-days did not differ (CS: 40.5 % vs. SS 43.1 %, p = 0.56). Overall, plasma concentrations of all biomarkers were higher in SS patients, with the largest difference on the first day. However, only in CS patients the biomarker concentrations were associated with mortality. Conclusion: In this prospective, multicenter cohort SS and CS patients showed similarities in baseline conditions and had similar mortality. However, several biomarkers only showed prognostic value in CS

Continuous exhaled breath analysis on the ICU

During admittance to the ICU, critically ill patients frequently develop secondary infections and/or multiple organ failure. Continuous monitoring of biological markers is very much needed. This study describes a new method to continuously monitor biomarkers in exhaled breath with an electronic nose

Phenotypes

Little progress has been made in the identification of novel pharmacological therapies for critically ill patients with sepsis, acute kidney injury, and acute respiratory distress syndrome. This lack of progress can likely be explained in part by inherent heterogeneity in the critically ill population, including but not limited to the dynamic state of the host response. Homogeneity can be improved by grouping patients with similar characteristics. Currently, multiple subphenotypes have been identified in which the markers of dysregulated host response are central to patient classification. In this chapter, we elaborate on this biologic heterogeneity in the critically ill, introduce the principles of phenotyping and precision medicine, and discuss the identified data-driven subphenotypes and the role of the dysregulated immune response in it. The role of the immune response as a common thread is apparent in and between all subphenotypes. Targeting a more generalizable component in the immune response identified in a subphenotype might be beneficial not only for that specific subphenotype, but also for other identified subphenotypes with the same characteristics. This approach may open up new therapeutic opportunities, but it also highlights the complexity in performing clinical trials in the critically ill

Latent class analysis of imaging and clinical respiratory parameters from patients with COVID-19-related ARDS identifies recruitment subphenotypes

Background: Patients with COVID-19-related acute respiratory distress syndrome (ARDS) require respiratory support with invasive mechanical ventilation and show varying responses to recruitment manoeuvres. In patients with ARDS not related to COVID-19, two pulmonary subphenotypes that differed in recruitability were identified using latent class analysis (LCA) of imaging and clinical respiratory parameters. We aimed to evaluate if similar subphenotypes are present in patients with COVID-19-related ARDS. Methods: This is the retrospective analysis of mechanically ventilated patients with COVID-19-related ARDS who underwent CT scans at positive end-expiratory pressure of 10 cmH2O and after a recruitment manoeuvre at 20 cmH2O. LCA was applied to quantitative CT-derived parameters, clinical respiratory parameters, blood gas analysis and routine laboratory values before recruitment to identify subphenotypes. Results: 99 patients were included. Using 12 variables, a two-class LCA model was identified as best fitting. Subphenotype 2 (recruitable) was characterized by a lower PaO2/FiO2, lower normally aerated lung volume and lower compliance as opposed to a higher non-aerated lung mass and higher mechanical power when compared to subphenotype 1 (non-recruitable). Patients with subphenotype 2 had more decrease in non-aerated lung mass in response to a standardized recruitment manoeuvre (p = 0.024) and were mechanically ventilated longer until successful extubation (adjusted SHR 0.46, 95% CI 0.23–0.91, p = 0.026), while no difference in survival was found (p = 0.814). Conclusions: A recruitable and non-recruitable subphenotype were identified in patients with COVID-19-related ARDS. These findings are in line with previous studies in non-COVID-19-related ARDS and suggest that a combination of imaging and clinical respiratory parameters could facilitate the identification of recruitable lungs before the manoeuvre