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Background Polymyxin B hemadsorption (PMX-HA) reduces blood endotoxin levels, but characteristics of patients with sepsis likely to benefit from PMX-HA are not well known. We sought to identify patient subgroups likely to benefit from PMX-HA. Methods We retrospectively identified 1911 patients with sepsis from a retrospective observational study in Japan (the JSEPTIC-DIC study) and 286 patients with endotoxemic septic shock from a randomized controlled trial in North America that restricted patients to those with high endotoxin activity (the EUPHRATES trial). We applied the machine learning-based causal forest model to the JSEPTIC-DIC cohort to investigate heterogeneity in treatment effects of PMX-HA on 28-day survival after adjusting for potential confounders and ascertain the best criteria for PMX-HA use. The derived criteria for targeted therapy by PMX-HA were validated using the EUPHRATES trial cohort. Results The causal forest model revealed heterogeneity in treatment effects of PMX-HA. Since patients having higher treatment effects were more likely to have severe coagulopathy and hyperlactatemia, we identified the potential treatment targets of PMX-HA as patients with PT-INR > 1.4 or lactate > 3 mmol/L. In the EUPHRATES trial cohort, PMX-HA use on the targeted subpopulation (75% of all patients) was significantly associated with higher 28-day survival (PMX-HA vs. control, 68% vs. 52%; treatment effect of PMX-HA, + 16% [95% CI + 2.2% to + 30%], p  = 0.02). Conclusions Abnormal coagulation and hyperlactatemia in septic patients with high endotoxin activity appear to be helpful to identify patients who may benefit most from PMX-HA. Our findings will inform enrollment criteria for future interventional trials targeting patients with coagulopathy and hyperlactatemia.

Endotoxin, also referred to as lipopolysaccharide (LPS), is a potent stimulator of the inflammatory cascade which may progress to sepsis and septic shock. The term endotoxic septic shock has been used for patients who have a clinical phenotype that is characterized by high endotoxin activity in addition to a high burden of organ failure; especially a pattern of organ failure including hepatic dysfunction, acute kidney injury, and various forms of endothelial dysfunction. Endotoxic septic shock has been a target for drug therapy for decades with no success. A likely barrier to their success was the inability to quantify endotoxin in the bloodstream. The Endotoxin Activity Assay (EAA) is positioned to change this landscape. In addition, medical devices using adsorptive technology in an extra-corporeal circulation has been shown to remove large quantities of endotoxin from the bloodstream. Focusing on the use of EAA to determine high concentrations of endotoxin will allow patients with endotoxic septic shock to be identified quickly and these patients may benefit most from removal of endotoxin using extracorporeal methods.

Background The Endotoxin Activity Assay™ (EAA) is a commercially available diagnostic test that quantifies endotoxin activity in human whole blood. Despite its promising features, the clinical utility of the EAA in the management of sepsis remains incompletely understood. This study aims to comprehensively review the published literature on the EAA and explore its usage trends and clinical applications in sepsis management. Methods We conducted a scoping review focused on EAA measurement in human sepsis subjects across four major databases: Embase, Web of Science, MEDLINE, and Cochrane Library. All the studies published from the inception of the databases to the search date in May 2025 were screened. Reviews, editorials, conference abstracts, grey literature, and non-human studies were excluded. We extracted and analyzed cohort characteristics, timing and frequency of EAA measurement, and the reported EAA results. Results Our systematic search and screening identified 95 articles that applied EAA on human patients, 54 of which focused on sepsis. These studies were published between 2002 and 2025 and reported EAA results in adult and pediatric patients. Most studies were conducted in Europe (51.9%), Asia (22.2%), and North America (11.1%). The most common study scenario involved using EAA as an inclusion criterion for blood purification therapy for sepsis, primarily polymyxin-B hemoadsorption. Of the 54 studies, three were randomized controlled trials conducted in North America, Thailand, and Switzerland. These trials investigated the effect of endotoxin adsorption therapy and continuous renal replacement therapy with adsorption filters for septic shock, using EAA ≥ 0.6 as part of the inclusion criteria. Nearly half of the studies (48.1%) measured EAA levels more than twice per patient, suggesting that serial endotoxin monitoring is of clinical interest. Conclusions Our results highlight the clinical application of EAA measurement in sepsis patient populations worldwide, particularly its potential role in the application of blood purification therapy. Together with other biomarkers and further validation studies to establish relevant timing, frequency, and cut-off values for sepsis patients, the EAA has the potential to become a component of precision medicine in the ICU by identifying patient subgroups most likely to benefit from targeted interventions, such as blood purification.

BACKGROUNDSepsis encompasses considerable biological and clinical heterogeneity. Previously, 2 phenotypes (\"hyperinflammatory\" and \"hypoinflammatory\") have been consistently identified within sepsis via latent class analysis. These phenotypes differ in their biological features, clinical outcomes, and therapeutic responses to interventions. Prior studies of sepsis heterogeneity have focused primarily on the host response. Here, we investigate the potential influence of the causative pathogen on sepsis heterogeneity and pathobiology.METHODSWe performed a retrospective observational analysis of 8,280 critically ill patients with sepsis to identify associations between pathogen characteristics and the hyperinflammatory and hypoinflammatory patient phenotypes. We also performed controlled murine and swine modeling of sepsis and lung injury and a secondary analysis of 449 patients enrolled in the EUPHRATES randomized controlled trial.RESULTSPathogen characteristics (pathogen identity, burden, virulence, and anatomic site of infection) were strongly and independently associated with the previously reported phenotypes. In a cohort of critically ill patients with sepsis, infection with gram-negative pathogens, primarily Enterobacterales spp. (e.g., Escherichia coli, Klebsiella pneumoniae), was strongly associated with the hyperinflammatory phenotype. The hyperinflammatory phenotype was also independently associated with increased pathogen burden, virulence, and initial anatomic site of infection. In controlled murine and swine modeling, both the identity and burden of the pathogen provoked key biological features of the hyperinflammatory phenotype. Among patients with sepsis, the prognostic value of lactate clearance varied substantially by phenotype. In a secondary analysis of a randomized trial of polymyxin B hemoadsorption (which removes circulating endotoxin), hypoinflammatory patients experienced worse survival.CONCLUSIONSOur results demonstrate the central importance of pathogen features in the clinical and biological heterogeneity of sepsis. Future studies of sepsis pathobiology and heterogeneity should expand their scope beyond the host response, as understanding pathogen-host interactions will be crucial in the development of precision therapeutic strategies to improve patient outcomes.TRIAL REGISTRATIONEUPHRATES trial NCT01046669.FUNDING5P30AG024824, IK2CX002766, R01HL144599, K24HL159247, R01HL158626, R01HL173531, R35GM142992, R35GM145330, R35GM136312, K23HL166880, R35HL140026.

Background Given the success of recent platform trials for COVID-19, Bayesian statistical methods have become an option for complex, heterogenous syndromes like sepsis. However, study design will require careful consideration of how statistical power varies using Bayesian methods across different choices for how historical data are incorporated through a prior distribution and how the analysis is ultimately conducted. Our objective with the current analysis is to assess how different uses of historical data through a prior distribution, and type of analysis influence results of a proposed trial that will be analyzed using Bayesian statistical methods. Methods We conducted a simulation study incorporating historical data from a published multicenter, randomized clinical trial in the US and Canada of polymyxin B hemadsorption for treatment of endotoxemic septic shock. Historical data come from a 179-patient subgroup of the previous trial of adult critically ill patients with septic shock, multiple organ failure and an endotoxin activity of 0.60–0.89. The trial intervention consisted of two polymyxin B hemoadsorption treatments (2 h each) completed within 24 h of enrollment. Results In our simulations for a new trial of 150 patients, a range of hypothetical results were observed. Across a range of baseline risks and treatment effects and four ways of including historical data, we demonstrate an increase in power with the use of clinically defensible incorporation of historical data. In one possible trial result, for example, with an observed reduction in risk of mortality from 44 to 37%, the probability of benefit is 96% with a fixed weight of 75% on prior data and 90% with a commensurate (adaptive-weighting) prior; the same data give an 80% probability of benefit if historical data are ignored. Conclusions Using Bayesian methods and a biologically justifiable use of historical data in a prior distribution yields a study design with higher power than a conventional design that ignores relevant historical data. Bayesian methods may be a viable option for trials in critical care medicine where beneficial treatments have been elusive. Graphical abstract

Background While allied health plays a central role in healthcare, workforce challenges are straining the sector. Challenges are shaped by population changes, emerging models of care, and educational limitations, and were exacerbated by COVID-19. This study aimed to identify drivers of recruitment and retention for allied health clinicians in an Australian metropolitan setting. Identifying and addressing these factors is essential to the design and implementation of tailored, evidence-informed workforce strategy and policy. Methods This cross-sectional, online survey explored workplace attraction, job seeking behaviours, and workplace perceptions. 29 Likert-scale statements informed by the existing literature examined factors influencing allied health retention. Allied health employees from a single Australian metropolitan health network were invited to participate. Descriptive statistics, logistic regression, and deductive content analysis were undertaken. Results 42.6% ( n  = 593) of those invited participated in the survey, with 45.7% ( n  = 271) of participants having been with the organisation for six or more years. 35% ( n  = 197) of respondents to a question about intention to leave agreed that they aimed to leave their current role within six months. Variables associated with intention to leave were not feeling a sense of satisfaction with their role (odds ratio [OR] 1.51, 95% CI 1.22–1.85), not being recognised and rewarded by the team manager (OR 1.37, 95% CI 1.12–1.67), not working in the preferred clinical area (OR 1.56; 95% CI 1.25–1.95), and feeling burned out by the job (OR 1.44; 95% CI 1.16–1.78). Qualitative findings support the centrality of aspects of the job (job characteristics), the organisational context (rewards offered; climate; organisational support) and person-context interface (peer/group relations; work-life conflict) to attraction, retention, and attrition in roles. Conclusion This study identifies factors affecting recruitment, retention, and attrition of allied health professionals in a metropolitan setting. Findings are impacted by the personal and professional effects of the COVID-19 pandemic response. Results provide a baseline upon which the impact of interventions can be measured, while informing the prioritisation and design of tailored workforce strategies. Further, findings may inform local policy responses to improve the allied health workforce and ensure excellent care for the community.

The purpose of this study was to assess impact of different volumes of exercise as well as cumulative moderate to vigorous physical activity (MVPA) on energy intake (EI) and diet quality, as assessed by the Healthy Eating Index-2010(HEI-2010), across a 12-month weight maintenance intervention. Participants were asked to attend group behavioural sessions, eat a diet designed for weight maintenance and exercise either 150, 225 or 300 min/week. Dietary intake was assessed by 3-d food records, and MVPA was assessed by accelerometry. Two hundred and twenty-four participants (42·5 years of age, 82 % female) provided valid dietary data for at least one time point. There was no evidence of group differences in EI, total HEI-2010 score or any of the HEI-2010 component scores (all P > 0·05). After adjusting for age, sex, time, group and group-by-time interactions, there was an effect of cumulative MVPA on EI (1·08, P = 0·04), total HEI-2010 scores (–0·02, P = 0·003), Na (–0·006, P = 0·002) and empty energy scores (–0·007, P = 0·004. There was evidence of a small relationship between cumulative daily EI and weight (β: 0·00187, 95 % CI 0·001, P = 0·003). However, there was no evidence for a relationship between HEI total score (β: −0·006, 95 % CI 0·07, 0·06) or component scores (all P > 0·05) and change in weight across time. The results of this study suggest that increased cumulative MVPA is associated with clinically insignificant increases in EI and decreases in HEI.

Background Daily rhythms are observed in humans and almost all other organisms. Most of these observed rhythms reflect both underlying endogenous circadian rhythms and evoked responses from behaviours such as sleep/wake, eating/fasting, rest/activity, posture changes and exercise. For many research and clinical purposes, it is important to understand the contribution of the endogenous circadian component to these observed rhythms. Content The goal of this manuscript is to provide guidance on best practices in measuring metrics of endogenous circadian rhythms in humans and promote the inclusion of circadian rhythms assessments in studies of health and disease. Circadian rhythms affect all aspects of physiology. By specifying minimal experimental conditions for studies, we aim to improve the quality, reliability and interpretability of research into circadian and daily (i.e., time‐of‐day) rhythms and facilitate the interpretation of clinical and translational findings within the context of human circadian rhythms. We describe protocols, variables and analyses commonly used for studying human daily rhythms, including how to assess the relative contributions of the endogenous circadian system and other daily patterns in behaviours or the environment. We conclude with recommendations for protocols, variables, analyses, definitions and examples of circadian terminology. Conclusion Although circadian rhythms and daily effects on health outcomes can be challenging to distinguish in practice, this distinction may be important in many clinical settings. Identifying and targeting the appropriate underlying (patho)physiology is a medical goal. This review provides methods for identifying circadian effects to aid in the interpretation of published work and the inclusion of circadian factors in clinical research and practice. Understanding the contribution of the endogenous circadian system to observed time‐of‐day rhythms can yield insights that further health‐related research and optimize clinical treatments and increase life expectancy. This manuscript provides guidance on best practices in measuring and distinguishing endogenous circadian rhythms from time‐of‐day rhythms in a variety of settings.

Understanding the functional consequences of genetic variation, and how it affects complex human disease and quantitative traits, remains a critical challenge for biomedicine. We present an analysis of RNA sequencing data from 1641 samples across 43 tissues from 175 individuals, generated as part of the pilot phase of the Genotype-Tissue Expression (GTEx) project. We describe the landscape of gene expression across tissues, catalog thousands of tissue-specific and shared regulatory expression quantitative trait loci (eQTL) variants, describe complex network relationships, and identify signals from genome-wide association studies explained by eQTLs. These findings provide a systematic understanding of the cellular and biological consequences of human genetic variation and of the heterogeneity of such effects among a diverse set of human tissues.