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This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2020. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2020 . Further information about the Annual Update in Intensive Care and Emergency Medicine is available from http://www.springer.com/series/8901 .

PurposeUsing latent class analysis (LCA), we have consistently identified two distinct subphenotypes in four randomized controlled trial cohorts of ARDS. One subphenotype has hyper-inflammatory characteristics and is associated with worse clinical outcomes. Further, within three negative clinical trials, we observed differential treatment response by subphenotype to randomly assigned interventions. The main purpose of this study was to identify ARDS subphenotypes in a contemporary NHLBI Network trial of infection-associated ARDS (SAILS) using LCA and to test for differential treatment response to rosuvastatin therapy in the subphenotypes.MethodsLCA models were constructed using a combination of biomarker and clinical data at baseline in the SAILS study (n = 745). LCA modeling was then repeated using an expanded set of clinical class-defining variables. Subphenotypes were tested for differential treatment response to rosuvastatin.ResultsThe two-class LCA model best fit the population. Forty percent of the patients were classified as the “hyper-inflammatory” subphenotype. Including additional clinical variables in the LCA models did not identify new classes. Mortality at day 60 and day 90 was higher in the hyper-inflammatory subphenotype. No differences in outcome were observed between hyper-inflammatory patients randomized to rosuvastatin therapy versus placebo.ConclusionsLCA using a two-subphenotype model best described the SAILS population. The subphenotypes have features consistent with those previously reported in four other cohorts. Addition of new class-defining variables in the LCA model did not yield additional subphenotypes. No treatment effect was observed with rosuvastatin. These findings further validate the presence of two subphenotypes and demonstrate their utility for patient stratification in ARDS.

Pulmonary dead space fraction (Vd/Vt) is an independent predictor of mortality in acute respiratory distress syndrome (ARDS). Yet, it is seldom used in practice. The ventilatory ratio is a simple bedside index that can be calculated using routinely measured respiratory variables and is a measure of impaired ventilation. Ventilatory ratio is defined as [minute ventilation (ml/min) × Pa (mm Hg)]/(predicted body weight × 100 × 37.5). To determine the relation of ventilatory ratio with Vd/Vt in ARDS. First, in a single-center, prospective observational study of ARDS, we tested the association of Vd/Vt with ventilatory ratio. With in-hospital mortality as the primary outcome and ventilator-free days as the secondary outcome, we tested the role of ventilatory ratio as an outcome predictor. The findings from this study were further verified in secondary analyses of two NHLBI ARDS Network randomized controlled trials. Ventilatory ratio positively correlated with Vd/Vt. Ordinal groups of ventilatory ratio had significantly higher Vd/Vt. Ventilatory ratio was independently associated with increased risk of mortality after adjusting for Pa /Fi , and positive end-expiratory pressure (odds ratio, 1.51; P = 0.024) and after adjusting for Acute Physiologic Assessment and Chronic Health Evaluation II score (odds ratio, 1.59; P = 0.04). These findings were further replicated in secondary analyses of two separate NHLBI randomized controlled trials. Ventilatory ratio correlates well with Vd/Vt in ARDS, and higher values at baseline are associated with increased risk of adverse outcomes. These results are promising for the use of ventilatory ratio as a simple bedside index of impaired ventilation in ARDS.

Both quality improvement and clinical research efforts over the past few decades have focused on consensus definition of sepsis and acute respiratory distress syndrome (ARDS). Although clinical definitions based on readily available clinical data have advanced recognition and timely use of broad supportive treatments, they likely hinder the identification of more targeted therapies that manipulate select biological mechanisms underlying critical illness. Sepsis and ARDS are by definition heterogeneous, and patients vary in both their underlying biology and their severity of illness. We have long been able to identify subtypes of sepsis and ARDS that confer different prognoses. The key is that we are now on the verge of identifying subtypes that may confer different response to therapy. In this perspective, inspired by a 2015 American Thoracic Society International Conference Symposium entitled \"Lumpers and Splitters: Phenotyping in Critical Illness,\" we highlight promising approaches to uncovering patient subtypes that may predict treatment responsiveness and not just differences in prognosis. We then discuss how this information can be leveraged to improve the success and translatability of clinical trials by using predictive enrichment and other design strategies. Last, we discuss the challenges and limitations to identifying biomarkers and endotypes and incorporating them into routine clinical practice.

Cigarette smoking is associated with increased risk of acute respiratory distress syndrome (ARDS) in patients after severe trauma; however, the mechanisms underlying this association are unknown. To determine whether cigarette smoking contributes to ARDS development after trauma by altering community composition of the lung microbiota. We studied the lung microbiota of mechanically ventilated patients admitted to the ICU after severe blunt trauma. To do so, we used 16S ribosomal RNA gene amplicon sequencing of endotracheal aspirate samples obtained on ICU admission (n = 74) and at 48 hours after admission (n = 30). Cigarette smoke exposure (quantified using plasma cotinine), ARDS development, and other clinical parameters were correlated with lung microbiota composition. Smoking status was significantly associated with lung bacterial community composition at ICU admission (P = 0.007 by permutational multivariate ANOVA [PERMANOVA]) and at 48 hours (P = 0.03 by PERMANOVA), as well as with significant enrichment of potential pathogens, including Streptococcus, Fusobacterium, Prevotella, Haemophilus, and Treponema. ARDS development was associated with lung community composition at 48 hours (P = 0.04 by PERMANOVA) and was characterized by relative enrichment of Enterobacteriaceae and of specific taxa enriched at baseline in smokers, including Prevotella and Fusobacterium. After severe blunt trauma, a history of smoking is related to lung microbiota composition, both at the time of ICU admission and at 48 hours. ARDS development is also correlated with respiratory microbial community structure at 48 hours and with taxa that are relatively enriched in smokers at ICU admission. The data derived from this pilot study suggest that smoking-related changes in the lung microbiota could be related to ARDS development after severe trauma.

Electronic-cigarette, or vaping, product use-associated lung injury (EVALI) is a syndrome of acute respiratory failure characterized by monocytic and neutrophilic alveolar inflammation. Epidemiological and clinical evidence suggests a role of vitamin E acetate (VEA) in the development of EVALI, yet it remains unclear whether VEA has direct pulmonary toxicity. To test the hypotheses that aerosolized VEA causes lung injury in mice and directly injures human alveolar epithelial cells, we exposed adult mice and primary human alveolar epithelial type II (AT II) cells to an aerosol of VEA generated by a device designed for vaping oils. Outcome measures in mice included lung edema, BAL analysis, histology, and inflammatory cytokines; outcomes included cell death, cytokine release, cellular uptake of VEA, and gene-expression analysis. Comparison exposures in both models included the popular nicotine-containing JUUL aerosol. We discovered that VEA caused dose-dependent increases in lung water and BAL protein compared with control and JUUL-exposed mice in association with increased BAL neutrophils, oil-laden macrophages, multinucleated giant cells, and inflammatory cytokines. VEA aerosol was also toxic to AT II cells, causing increased cell death and the release of monocyte and neutrophil chemokines. VEA was directly absorbed by AT II cells, resulting in the differential gene expression of several inflammatory biological pathways. Given the epidemiological and clinical characteristics of the EVALI outbreak, these results suggest that VEA plays an important causal role.

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2023. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2023 . Further information about the Annual Update in Intensive Care and Emergency Medicine is available from https://link.springer.com/bookseries/8901 .

IntroductionHeated tobacco products are being touted as novel reduced-harm tobacco products by tobacco companies. In the USA, Philip Morris International submitted a modified risk tobacco product (MRTP) application to the US Food and Drug Administration in 2016 in which it purports that its heated tobacco product, I-Quit-Ordinary-Smoking (IQOS), is associated with reduced harm compared with conventional cigarettes.MethodsWe reviewed Philip Morris International’s MRTP application to assess the pulmonary and immune toxicities associated with IQOS use in both animal and human studies.ResultsAmong rats exposed to IQOS, there was evidence of pulmonary inflammation and immunomodulation. In human users, there was no evidence of improvement in pulmonary inflammation or pulmonary function in cigarette smokers who were switched to IQOS.ConclusionIQOS is associated with significant pulmonary and immunomodulatory toxicities with no detectable differences between conventional cigarette smokers and those who were switched to IQOS in Philip Morris International’s studies. Philip Morris International also failed to consider how dual use and secondhand aerosol exposure may further impact, and likely increase, the harms associated with these products.

Identifying new effective treatments for the acute respiratory distress syndrome (ARDS), including COVID-19 ARDS, remains a challenge. The field of ARDS investigation is moving increasingly toward innovative approaches such as the personalization of therapy to biological and clinical sub-phenotypes. Additionally, there is growing recognition of the importance of the global context to identify effective ARDS treatments. This review highlights emerging opportunities and continued challenges for personalizing therapy for ARDS, from identifying treatable traits to innovative clinical trial design and recognition of patient-level factors as the field of critical care investigation moves forward into the twenty-first century.

Background Antimicrobial resistance (AMR) is rising at an alarming rate and complicating the management of infectious diseases including lower respiratory tract infections (LRTI). Metagenomic next-generation sequencing (mNGS) is a recently established method for culture-independent LRTI diagnosis, but its utility for predicting AMR has remained unclear. We aimed to assess the performance of mNGS for AMR prediction in bacterial LRTI and demonstrate proof of concept for epidemiological AMR surveillance and rapid AMR gene detection using Cas9 enrichment and nanopore sequencing. Methods We studied 88 patients with acute respiratory failure between 07/2013 and 9/2018, enrolled through a previous observational study of LRTI. Inclusion criteria were age ≥ 18, need for mechanical ventilation, and respiratory specimen collection within 72 h of intubation. Exclusion criteria were decline of study participation, unclear LRTI status, or no matched RNA and DNA mNGS data from a respiratory specimen. Patients with LRTI were identified by clinical adjudication. mNGS was performed on lower respiratory tract specimens. The primary outcome was mNGS performance for predicting phenotypic antimicrobial susceptibility and was assessed in patients with LRTI from culture-confirmed bacterial pathogens with clinical antimicrobial susceptibility testing ( n  = 27 patients, n  = 32 pathogens). Secondary outcomes included the association between hospital exposure and AMR gene burden in the respiratory microbiome ( n  = 88 patients), and AMR gene detection using Cas9 targeted enrichment and nanopore sequencing ( n  = 10 patients). Results Compared to clinical antimicrobial susceptibility testing, the performance of respiratory mNGS for predicting AMR varied by pathogen, antimicrobial, and nucleic acid type sequenced. For gram-positive bacteria, a combination of RNA + DNA mNGS achieved a sensitivity of 70% (95% confidence interval (CI) 47–87%) and specificity of 95% (CI 85–99%). For gram-negative bacteria, sensitivity was 100% (CI 87–100%) and specificity 64% (CI 48–78%). Patients with hospital-onset LRTI had a greater AMR gene burden in their respiratory microbiome versus those with community-onset LRTI ( p  = 0.00030), or those without LRTI ( p  = 0.0024). We found that Cas9 targeted sequencing could enrich for low abundance AMR genes by > 2500-fold and enabled their rapid detection using a nanopore platform. Conclusions mNGS has utility for the detection and surveillance of resistant bacterial LRTI pathogens.