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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 ([alpha], [beta], [gamma], and [delta]), (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 [gamma] (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., Author(s): Rombout B. E. van Amstel [sup.1] [sup.2], Jason N. Kennedy [sup.3], Brendon P. Scicluna [sup.4] [sup.5], Lieuwe D. J. Bos [sup.1] [sup.2], Hessel Peters-Sengers [sup.6] [sup.7], Joe M. Butler [...]

Purpose Severe community-acquired pneumonia (sCAP) is associated with high morbidity and mortality, and whilst European and non-European guidelines are available for community-acquired pneumonia, there are no specific guidelines for sCAP. Methods The European Respiratory Society (ERS), European Society of Intensive Care Medicine (ESICM), European Society of Clinical Microbiology and Infectious Diseases (ESCMID), and Latin American Thoracic Association (ALAT) launched a task force to develop the first international guidelines for sCAP. The panel comprised a total of 18 European and four non-European experts, as well as two methodologists. Eight clinical questions for sCAP diagnosis and treatment were chosen to be addressed. Systematic literature searches were performed in several databases. Meta-analyses were performed for evidence synthesis, whenever possible. The quality of evidence was assessed with GRADE (Grading of Recommendations, Assessment, Development and Evaluation). Evidence to Decision frameworks were used to decide on the direction and strength of recommendations. Results Recommendations issued were related to diagnosis, antibiotics, organ support, biomarkers and co-adjuvant therapy. After considering the confidence in effect estimates, the importance of outcomes studied, desirable and undesirable consequences of treatment, cost, feasibility, acceptability of the intervention and implications to health equity, recommendations were made for or against specific treatment interventions. Conclusions In these international guidelines, ERS, ESICM, ESCMID, and ALAT provide evidence-based clinical practice recommendations for diagnosis, empirical treatment, and antibiotic therapy for sCAP, following the GRADE approach. Furthermore, current knowledge gaps have been highlighted and recommendations for future research have been made., Author(s): Ignacio Martin-Loeches [sup.1] [sup.2] [sup.3] [sup.4], Antoni Torres [sup.3] [sup.4], Blin Nagavci [sup.5], Stefano Aliberti [sup.6] [sup.7], Massimo Antonelli [sup.8], Matteo Bassetti [sup.9], Lieuwe D. Bos [sup.10], James D. [...]

Author(s): Malou Janssen [sup.1] [sup.2], Henrik Endeman [sup.2], Lieuwe D. J. Bos [sup.3] [sup.4] Author Affiliations: (1) grid.415868.6, 0000 0004 0624 5690, Internal Medicine, Reinier de Graaf Gasthuis, , Delft, [...]

Author(s): Andrew Conway Morris [sup.1] [sup.2] [sup.3], Lieuwe D. J. Bos [sup.4], Saad Nseir [sup.5] [sup.6] Author Affiliations: (1) grid.5335.0, 0000000121885934, Division of Immunology, Department of Pathology, University of Cambridge, [...]

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. To impact clinical care, identification of subpopulations must do more than differentiate prognosis. It 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. [ABSTRACT FROM AUTHOR]

Although the acute respiratory distress syndrome (ARDS) is well defined by the development of acute hypoxemia, bilateral infiltrates and non-cardiogenic pulmonary edema, ARDS is heterogeneous in terms of clinical risk factors, physiology of lung injury, microbiology, and biology, potentially explaining why pharmacologic therapies have been mostly unsuccessful in treating ARDS. Identifying phenotypes of ARDS and integrating this information into patient selection for clinical trials may increase the chance for efficacy with new treatments. In this review, we focus on classifying ARDS by the associated clinical disorders, physiological data, and radiographic imaging. We consider biologic phenotypes, including plasma protein biomarkers, gene expression, and common causative microbiologic pathogens. We will also discuss the issue of focusing clinical trials on the patient's phase of lung injury, including prevention, administration of therapy during early acute lung injury, and treatment of established ARDS. A more in depth understanding of the interplay of these variables in ARDS should provide more success in designing and conducting clinical trials and achieving the goal of personalized medicine., Author(s): Michael A. Matthay [sup.1] [sup.2] [sup.3], Yaseen M. Arabi [sup.4], Emily R. Siegel [sup.2], Lorraine B. Ware [sup.5], Lieuwe D. J. Bos [sup.6], Pratik Sinha [sup.7], Jeremy R. Beitler [...]

Author(s): Ignacio Martin-Loeches [sup.1] [sup.2] [sup.3] [sup.4], Antoni Torres [sup.3] [sup.4], Blin Nagavci [sup.5], Stefano Aliberti [sup.6] [sup.7], Massimo Antonelli [sup.8], Matteo Bassetti [sup.9], Lieuwe D. Bos [sup.10], James D. [...]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Impaired intestinal barrier function can enable passage of enteric microorganisms into the bloodstream and lead to nosocomial bloodstream infections during critical illness. We aimed to determine the relative importance of gut translocation as a source for ICU-acquired enterococcal bacteremia of unknown origin. Methods: We conducted a nested case–control study in two mixed medical-surgical tertiary ICUs in the Netherlands among patients enrolled between 2011 and 2018. We selected 72 cases with ICU-acquired bacteremia due to enterococci (which are known gastrointestinal tract commensals) and 137 matched controls with bacteremia due to coagulase-negative staphylococci (CoNS) (which are of non-intestinal origin). We measured intestinal fatty acid-binding protein, trefoil factor-3, and citrulline 48 h before bacteremia onset. A composite measure for Gut Barrier Injury (GBI) was calculated as the sum of standardized z-scores for each biomarker plus a clinical gastrointestinal failure score. Results: No single biomarker yielded statistically significant differences between cases and controls. Median composite GBI was higher in cases than in controls (0.58, IQR − 0.36–1.69 vs. 0.32, IQR − 0.53–1.57, p = 0.33) and higher composite measures of GBI correlated with higher disease severity and ICU mortality (p < 0.001). In multivariable analysis, higher composite GBI was not significantly associated with increased occurrence of enterococcal bacteremia relative to CoNS bacteremia (adjusted OR 1.12 95% CI 0.93–1.34, p = 0.22). Conclusions: We could not demonstrate an association between biomarkers of gastrointestinal barrier dysfunction and an increased occurrence of bacteremia due to gut compared to skin flora during critical illness, suggesting against bacterial translocation as a major vector for acquisition of nosocomial bloodstream infections in the ICU. [ABSTRACT FROM AUTHOR]

The article discusses the success of the ESICM datathons, which bring together data scientists and intensive care professionals to analyze large intensive care databases and provide new insights for the intensive care community. The field of data science is particularly relevant for intensive care medicine, as it generates vast amounts of diverse data that can be difficult for humans to fully comprehend. The article highlights the importance of artificial intelligence models based on previous patient data to support decision-making in intensive care. The ESICM Data Science Section has approved a strategy that prioritizes a "bytes-to-bedside" approach, integrating data science and artificial intelligence into intensive care medicine. The strategy includes pillars such as data science education, research promotion, responsible data sharing, benchmarking, and collaboration. The article also mentions the challenges and barriers to implementing machine learning models in clinical practice. The ESICM datathons have resulted in peer-reviewed publications and have continued to be successful, even in an online format. The article concludes by encouraging data scientists and intensive care professionals to unite and work together to improve intensive care. [Extracted from the article]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Mucormycosis is a severe complication in critically ill COVID-19 patients. Throughout the pandemic, a notable prevalence of mucormycosis has been observed in the Indian population, whereas lower occurrences have been reported in Europe. However, limited data exist regarding its prevalence in Europe, which is potentially underestimated due to the low sensitivity of bronchoalveolar lavage (BAL) cultures. We aimed to evaluate the prevalence of mucormycosis in a high-risk critically ill COVID-19 population in the Netherlands, and to evaluate the potential benefit of adding Mucor PCR to BAL as part of routine follow-up. In this study, we included 1035 critically ill COVID-19 patients admitted to either one of the two ICUs at AmsterdamUMC between March 2020 and May 2022; of these, 374 had undergone at least one bronchoscopy. Following the AmsterdamUMC protocols, bronchoscopies were conducted weekly until clinical improvement was achieved. We cultured BAL fluid for fungi and used PCR and galactomannan testing to detect Aspergillus spp. Additionally, we retrospectively performed qPCR targeting Mucorales DNA in the BAL of 89 deceased patients. All cultures were negative for Mucorales, whereas 42 (11%) cultures were positive for Aspergillus. Furthermore, qPCR targeting Mucorales was negative in all 89 deceased patients. This study showed that pulmonary mucormycosis was not present in critically ill COVID-19 patients in two tertiary care ICUs. These results indicate routine Mucorales qPCR screening is not clinically necessary in a high-standard-of-care tertiary ICU in a low-endemic area. [ABSTRACT FROM AUTHOR]

Purpose Mechanical power (MP) may unify variables known to be related to development of ventilator-induced lung injury. The aim of this study is to examine the association between MP and mortality in critically ill patients receiving invasive ventilation for at least 48 h. Methods This is an analysis of data stored in the databases of the MIMIC-III and eICU. Critically ill patients receiving invasive ventilation for at least 48 h were included. The exposure of interest was MP. The primary outcome was in-hospital mortality. Results Data from 8207 patients were analyzed. Median MP during the second 24 h was 21.4 (16.2-28.1) J/min in MIMIC-III and 16.0 (11.7-22.1) J/min in eICU. MP was independently associated with in-hospital mortality [odds ratio per 5 J/min increase (OR) 1.06 (95% confidence interval (CI) 1.01-1.11); p = 0.021 in MIMIC-III, and 1.10 (1.02-1.18); p = 0.010 in eICU]. MP was also associated with ICU mortality, 30-day mortality, and with ventilator-free days, ICU and hospital length of stay. Even at low tidal volume, high MP was associated with in-hospital mortality [OR 1.70 (1.32-2.18); p < 0.001] and other secondary outcomes. Finally, there is a consistent increase in the risk of death with MP higher than 17.0 J/min. Conclusion High MP of ventilation is independently associated with higher in-hospital mortality and several other outcomes in ICU patients receiving invasive ventilation for at least 48 h., Author(s): Ary Serpa Neto [sup.1] [sup.2] [sup.3], Rodrigo Octavio Deliberato [sup.2] [sup.3] [sup.4], Alistair E. W. Johnson [sup.5], Lieuwe D. Bos [sup.1], Pedro Amorim [sup.6], Silvio Moreto Pereira [sup.6], Denise [...]

Purpose To evaluate patients with resolved versus confirmed ARDS, identify subgroups with substantial mortality risk, and to determine the utility of day 2 ARDS reclassification. Methods Our primary objective, in this secondary LUNG SAFE analysis, was to compare outcome in patients with resolved versus confirmed ARDS after 24 h. Secondary objectives included identifying factors associated with ARDS persistence and mortality, and the utility of day 2 ARDS reclassification. Results Of 2377 patients fulfilling the ARDS definition on the first day of ARDS (day 1) and receiving invasive mechanical ventilation, 503 (24%) no longer fulfilled the ARDS definition the next day, 52% of whom initially had moderate or severe ARDS. Higher tidal volume on day 1 of ARDS was associated with confirmed ARDS [OR 1.07 (CI 1.01-1.13), P = 0.035]. Hospital mortality was 38% overall, ranging from 31% in resolved ARDS to 41% in confirmed ARDS, and 57% in confirmed severe ARDS at day 2. In both resolved and confirmed ARDS, age, non-respiratory SOFA score, lower PEEP and P/F ratio, higher peak pressure and respiratory rate were each associated with mortality. In confirmed ARDS, pH and the presence of immunosuppression or neoplasm were also associated with mortality. The increase in area under the receiver operating curve for ARDS reclassification on day 2 was marginal. Conclusions ARDS, whether resolved or confirmed at day 2, has a high mortality rate. ARDS reclassification at day 2 has limited predictive value for mortality. The substantial mortality risk in severe confirmed ARDS suggests that complex interventions might best be tested in this population. Trial Registration ClinicalTrials.gov NCT02010073., Author(s): Fabiana Madotto [sup.1] [sup.2], Tài Pham [sup.2] [sup.3] [sup.4], Giacomo Bellani [sup.5] [sup.6], Lieuwe D. Bos [sup.7], Fabienne D. Simonis [sup.7], Eddy Fan [sup.8] [sup.9], Antonio Artigas [sup.10], Laurent [...]

Author(s): Bastiaan V. C. Kraaijenbrink [sup.1], Amne Mousa [sup.1] [sup.2], Lieuwe D. Bos [sup.3], Frederique Paulus [sup.3], Pieter R. Tuinman [sup.1] [sup.2] Author Affiliations: (1) grid.509540.d, 0000 0004 6880 3010, [...]

Author(s): Lieuwe D. J. Bos [sup.1] [sup.2], Andre C. Kalil [sup.3] Author Affiliations: (1) Intensive Care, Infection and Immunity, Amsterdam UMC -Location AMC, , Amsterdam, The Netherlands (2) Department of [...]

Author(s): Lieuwe D. J. Bos [sup.1], Elie Azoulay [sup.2], Ignacio Martin-Loeches [sup.3] [sup.4] Author Affiliations: (1) 0000 0004 0617 8280, grid.416409.e, St James's Hospital, , James's St N, Ushers, D03 [...]