Background In acute respiratory distress syndrome (ARDS) unrelated to COVID-19, two phenotypes, based on the severity of systemic inflammation (hyperinflammatory and hypoinflammatory), have been described. The hyperinflammatory phenotype is known to be associated with increased multiorgan failure and mortality. In this study, we aimed to identify these phenotypes in COVID-19-related ARDS. Methods In this prospective observational study done at two UK intensive care units, we recruited patients with ARDS due to COVID-19. Demographic, clinical, and laboratory data were collected at baseline. Plasma samples were analysed for interleukin-6 (IL-6) and soluble tumour necrosis factor receptor superfamily member 1A (TNFR1) using a novel point-of-care assay. A parsimonious regression classifier model was used to calculate the probability for the hyperinflammatory phenotype in COVID-19 using IL-6, soluble TNFR1, and bicarbonate levels. Data from this cohort was compared with patients with ARDS due to causes other than COVID-19 recruited to a previous UK multicentre, randomised controlled trial of simvastatin (HARP-2). Findings Between March 17 and April 25, 2020, 39 patients were recruited to the study. Median ratio of partial pressure of arterial oxygen to fractional concentration of oxygen in inspired air (PaO 2 /FiO 2 ) was 18 kpa (IQR 15–21) and acute physiology and chronic health evaluation II score was 12 (10–16). 17 (44%) of 39 patients had died by day 28 of the study. Compared with survivors, patients who died were older and had lower PaO 2 /FiO 2 . The median probability for the hyperinflammatory phenotype was 0·03 (IQR 0·01–0·2). Depending on the probability cutoff used to assign class, the prevalence of the hyperinflammatory phenotype was between four (10%) and eight (21%) of 39, which is lower than the proportion of patients with the hyperinflammatory phenotype in HARP-2 (186 [35%] of 539). Using the Youden index cutoff (0·274) to classify phenotype, five (63%) of eight patients with the hyperinflammatory phenotype and 12 (39%) of 31 with the hypoinflammatory phenotype died. Compared with matched patients recruited to HARP-2, levels of IL-6 were similar in our cohort, whereas soluble TNFR1 was significantly lower in patients with COVID-19-associated ARDS. Interpretation In this exploratory analysis of 39 patients, ARDS due to COVID-19 was not associated with higher systemic inflammation and was associated with a lower prevalence of the hyperinflammatory phenotype than that observed in historical ARDS data. This finding suggests that the excess mortality observed in COVID-19-related ARDS is unlikely to be due to the upregulation of inflammatory pathways described by the parsimonious model. Funding US National Institutes of Health, Innovate UK, and Randox.

Research and practice in critical care medicine have long been defined by syndromes, which, despite being clinically recognizable entities, are, in fact, loose amalgams of heterogeneous states that may respond differently to therapy. Mounting translational evidence-supported by research on respiratory failure due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection-suggests that the current syndrome-based framework of critical illness should be reconsidered. Here we discuss recent findings from basic science and clinical research in critical care and explore how these might inform a new conceptual model of critical illness. De-emphasizing syndromes, we focus on the underlying biological changes that underpin critical illness states and that may be amenable to treatment. We hypothesize that such an approach will accelerate critical care research, leading to a richer understanding of the pathobiology of critical illness and of the key determinants of patient outcomes. This, in turn, will support the design of more effective clinical trials and inform a more precise and more effective practice at the bedside.

Despite the progression of supportive care in intensive care medicine, advancements in disease-modifying therapeutic options have been slow. Many trials conducted in intensive care medicine have failed to identify treatment benefit. One of the reasons implicated is the underlying heterogeneity of critical care syndromes. There are numerous approaches proposed to dividing these populations into more meaningful subgroups (subphenotypes), though some may be more useful than others. Clinical and biomarker-driven subclassification systems have been proposed for acute respiratory distress syndrome, sepsis, acute kidney injury, and pancreatitis. Identifying those systems that are most useful and biologically-meaningful will lead to further understanding of the pathophysiology of critical care syndromes while also allowing us to focus recruitment in future therapeutic trials to predicted responders. This review discusses recently proposed subphenotypes of critical illness syndromes and highlights the issues that will need to be addressed in order to translate them into clinical practice. Key messages• A variety of subgroups (subphenotypes) of sepsis, acute kidney injury, and acute respiratory distress syndrome patients have been identified that differ in prevalence and mortality.• In retrospective analyses, some subphenotypes have shown differential treatment response to randomised interventions which showed no effect in the overall population.• Mechanistic studies in subphenotypes of critical illness syndromes may allow us to better understand their pathophysiological basis and develop novel targeted therapies.• In order to translate subphenotypes to the bedside, we will need to develop rapid realtime assays for subphenotype assignment, compare disparate subphenotyping strategies prospectively in heterogeneous cohorts, and freely share data.

Psychometric Evaluation of a Measure of Factors Influencing Hand Hygiene Behaviour to Inform Intervention Background. Although the hand hygiene (HH) procedure is simple, the related behaviour is complex and is not readily understood, explained, or changed. There is a need for practical tools to provide data that can guide healthcare managers and practitioners not only on the 'what' (the standards that must be met), but also the 'how' (guidance on how to achieve the standards). Aim. To develop a valid questionnaire to evaluate attitudes to the factors that influence engagement in HH behaviour that can be readily completed, administered, and analysed by healthcare professionals to identify appropriate intervention strategies. Construct validity was assessed using confirmatory factor analysis, predictive validity through comparison with selfreported HH behaviour, and convergent validity through direct unit-level observation of HH behaviour. Methods. The Capability, Opportunity, Motivation-Behaviour (COM-B) model was used to design a 25-item questionnaire that was distributed to Intensive Care Unit (ICU) personnel in Ireland. Direct observation of HH behaviour was carried out at two ICUs. Findings. A total of 292 responses to the survey (response rate 41.0%) were included in the analysis. Confirmatory factor analysis resulted in a 17-item questionnaire. Multiple regression revealed that a model including Capability, Opportunity, and Motivation, was a significant predictor of self-reported Behavioural intention (F(3,209) =22.58, p<0.001). However, the Opportunity factor was not found to make a significant contribution to the regression model. Conclusion. The COMB HH questionnaire is reliable and valid and provides data to support the development, and evaluation, of HH interventions that meet the needs of specific healthcare units.