Parsimonious Waveform-derived Features consisting of Pulse Arrival Time and Heart Rate Variability Predicts the Onset of Septic Shock.

Sepsis is a major public health emergency and one of the leading causes of morbidity and mortality in critically ill patients. For each hour treatment is delayed, shock-related mortality increases, so early diagnosis and intervention is of utmost importance. However, earlier recognition of shock requires active monitoring, which may be delayed due to subclinical manifestations of the disease at the early phase of onset. Machine learning systems can increase timely detection of shock onset by exploiting complex interactions among continuous physiological waveforms. We use a dataset consisting of high-resolution physiological waveforms from intensive care unit (ICU) of a tertiary hospital system. We investigate the use of mean arterial blood pressure (MAP), pulse arrival time (PAT), heart rate variability (HRV), and heart rate (HR) for the early prediction of shock onset. Using only five minutes of the aforementioned vital signals from 239 ICU patients, our developed models can accurately predict septic shock onset 6 to 36 hours prior to clinical recognition with area under the receiver operating characteristic (AUROC) of 0.84 and 0.8 respectively. This work lays foundations for a robust, efficient, accurate and early prediction of septic shock onset which may help clinicians in their decision-making processes. This study introduces machine learning models that provide fast and accurate predictions of septic shock onset times up to 36 hours in advance. BP, PAT and HR dynamics can independently predict septic shock onset with a look-back period of only 5 mins.

CD8+ T cells are necessary for improved sepsis survival induced by CD28 agonism in immunologically experienced mice.

Introduction: A hallmark of T cell dysregulation during sepsis is the downregulation of costimulatory molecules. CD28 is one of T cell costimulatory molecules significantly altered on memory T cells during sepsis. We recently showed that treatment with a αCD28 agonist in septic immunologically experienced mice led to improved survival. Therefore, here we aimed to identify the cell subset(s) necessary for the survival benefit observed in the context of CD28 agonism, and to further investigate the mechanism by which CD28 agonism improves sepsis survival in immunologically experienced mice. Methods: Mice received specific pathogen inoculation to generate memory T cell populations similar in frequency to that of adult humans. Once these infections were cleared and the T cell response had transitioned to the memory phase, animals were rendered septic via cecal ligation and puncture in the presence or absence of an agonistic anti-CD28 mAb. Results: Results demonstrated that CD8+ T cells, and not bulk CD4+ T cells or CD25+ regulatory T cells, were necessary for the survival benefit observed in CD28 agonist-treated septic immunologically experienced mice. Upon examination of these CD8+ T cells, we found that CD28 agonism in septic immunologically experienced mice was associated with an increase in Foxp3+ CD8+ T cells as compared to vehicle-treated controls. When CD8+ T cells were depleted in septic immunologically experienced mice in the setting of CD28 agonism, a significant increase in levels of inflammatory cytokines in the blood was observed. Discussion: Taken together, these results indicate that CD28 agonism in immunologically experienced mice effectively suppresses inflammation via a CD8+-dependent mechanism to decrease mortality during sepsis.

OXIDATIVE study: A pilot prospective observational cohort study protocol examining the influence of peri-reperfusion hyperoxemia and immune dysregulation on early allograft dysfunction after orthotopic liver transplantation.

Early allograft dysfunction (EAD) is a functional hepatic insufficiency within a week of orthotopic liver transplantation (OLT) and is associated with morbidity and mortality. The etiology of EAD is multifactorial and largely driven by ischemia reperfusion injury (IRI), a phenomenon characterized by oxygen scarcity followed by paradoxical oxidative stress and inflammation. With the expanded use of marginal allografts more susceptible to IRI, the incidence of EAD may be increasing. This necessitates an in-depth understanding of the innate molecular mechanisms underlying EAD and interventions to mitigate its impact. Our central hypothesis is peri-reperfusion hyperoxemia and immune dysregulation exacerbate IRI and increase the risk of EAD. We will perform a pilot prospective single-center observational cohort study of 40 patients. The aims are to determine (1) the association between peri-reperfusion hyperoxemia and EAD and (2) whether peri-reperfusion perturbed cytokine, protein, and hypoxia inducible factor-1 alpha (HIF-1α) levels correlate with EAD after OLT. Inclusion criteria include age ≥ 18 years, liver failure, and donation after brain or circulatory death. Exclusion criteria include living donor donation, repeat OLT within a week of transplantation, multiple organ transplantation, and pregnancy. Partial pressure of arterial oxygen (PaO2) as the study measure allows for the examination of oxygen exposure within the confines of existing variability in anesthesiologist-administered fraction of inspired oxygen (FiO2) and the inclusion of patients with intrapulmonary shunting. The Olthoff et al. definition of EAD is the primary outcome. Secondary outcomes include postoperative acute kidney injury, pulmonary and biliary complications, surgical wound dehiscence and infection, and mortality. The goal of this study protocol is to identify EAD contributors that could be targeted to attenuate its impact and improve OLT outcomes. If validated, peri-reperfusion hyperoxemia and immune perturbations could be targeted via FiO2 titration to a goal PaO2 and/or administration of an immunomodulatory agent by the anesthesiologist intraoperatively.

Claudin-2 upregulation enhances intestinal permeability, immune activation, dysbiosis, and mortality in sepsis.

Intestinal epithelial expression of the tight junction protein claudin-2, which forms paracellular cation and water channels, is precisely regulated during development and in disease. Here, we show that small intestinal epithelial claudin-2 expression is selectively upregulated in septic patients. Similar changes occurred in septic mice, where claudin-2 upregulation coincided with increased flux across the paracellular pore pathway. In order to define the significance of these changes, sepsis was induced in claudin-2 knockout (KO) and wild-type (WT) mice. Sepsis-induced increases in pore pathway permeability were prevented by claudin-2 KO. Moreover, claudin-2 deletion reduced interleukin-17 production and T cell activation and limited intestinal damage. These effects were associated with reduced numbers of neutrophils, macrophages, dendritic cells, and bacteria within the peritoneal fluid of septic claudin-2 KO mice. Most strikingly, claudin-2 deletion dramatically enhanced survival in sepsis. Finally, the microbial changes induced by sepsis were less pathogenic in claudin-2 KO mice as survival of healthy WT mice injected with cecal slurry collected from WT mice 24 h after sepsis was far worse than that of healthy WT mice injected with cecal slurry collected from claudin-2 KO mice 24 h after sepsis. Claudin-2 upregulation and increased pore pathway permeability are, therefore, key intermediates that contribute to development of dysbiosis, intestinal damage, inflammation, ineffective pathogen control, and increased mortality in sepsis. The striking impact of claudin-2 deletion on progression of the lethal cascade activated during sepsis suggests that claudin-2 may be an attractive therapeutic target in septic patients.

CTLA-4 Checkpoint Inhibition Improves Sepsis Survival in Alcohol-Exposed Mice.

Chronic alcohol use increases morbidity and mortality in the setting of sepsis. Both chronic alcohol use and sepsis are characterized by immune dysregulation, including overexpression of T cell coinhibitory molecules. We sought to characterize the role of CTLA-4 during sepsis in the setting of chronic alcohol exposure using a murine model of chronic alcohol ingestion followed by cecal ligation and puncture. Results indicated that CTLA-4 expression is increased on CD4+ T cells isolated from alcohol-drinking septic mice as compared with either alcohol-drinking sham controls or water-drinking septic mice. Moreover, checkpoint inhibition of CTLA-4 improved sepsis survival in alcohol-drinking septic mice, but not water-drinking septic mice. Interrogation of the T cell compartments in these animals following pharmacologic CTLA-4 blockade, as well as following conditional Ctla4 deletion in CD4+ T cells, revealed that CTLA-4 deficiency promoted the activation and proliferation of effector regulatory T cells and the generation of conventional effector memory CD4+ T cells. These data highlight an important role for CTLA-4 in mediating mortality during sepsis in the setting of chronic alcohol exposure and may inform future approaches to develop targeted therapies for this patient population.

Surviving Sepsis Campaign Research Priorities 2023.

OBJECTIVES: To identify research priorities in the management, epidemiology, outcome, and pathophysiology of sepsis and septic shock. DESIGN: Shortly after publication of the most recent Surviving Sepsis Campaign Guidelines, the Surviving Sepsis Research Committee, a multiprofessional group of 16 international experts representing the European Society of Intensive Care Medicine and the Society of Critical Care Medicine, convened virtually and iteratively developed the article and recommendations, which represents an update from the 2018 Surviving Sepsis Campaign Research Priorities. METHODS: Each task force member submitted five research questions on any sepsis-related subject. Committee members then independently ranked their top three priorities from the list generated. The highest rated clinical and basic science questions were developed into the current article. RESULTS: A total of 81 questions were submitted. After merging similar questions, there were 34 clinical and ten basic science research questions submitted for voting. The five top clinical priorities were as follows: 1) what is the best strategy for screening and identification of patients with sepsis, and can predictive modeling assist in real-time recognition of sepsis? 2) what causes organ injury and dysfunction in sepsis, how should it be defined, and how can it be detected? 3) how should fluid resuscitation be individualized initially and beyond? 4) what is the best vasopressor approach for treating the different phases of septic shock? and 5) can a personalized/precision medicine approach identify optimal therapies to improve patient outcomes? The five top basic science priorities were as follows: 1) How can we improve animal models so that they more closely resemble sepsis in humans? 2) What outcome variables maximize correlations between human sepsis and animal models and are therefore most appropriate to use in both? 3) How does sepsis affect the brain, and how do sepsis-induced brain alterations contribute to organ dysfunction? How does sepsis affect interactions between neural, endocrine, and immune systems? 4) How does the microbiome affect sepsis pathobiology? 5) How do genetics and epigenetics influence the development of sepsis, the course of sepsis and the response to treatments for sepsis? CONCLUSIONS: Knowledge advances in multiple clinical domains have been incorporated in progressive iterations of the Surviving Sepsis Campaign guidelines, allowing for evidence-based recommendations for short- and long-term management of sepsis. However, the strength of existing evidence is modest with significant knowledge gaps and mortality from sepsis remains high. The priorities identified represent a roadmap for research in sepsis and septic shock.

Transforming the Future of Surgeon-Scientists.

OBJECTIVE: To create a blueprint for surgical department leaders, academic institutions, and funding agencies to optimally support surgeon-scientists. BACKGROUND: Scientific contributions by surgeons have been transformative across many medical disciplines. Surgeon-scientists provide a distinct approach and mindset toward key scientific questions. However, lack of institutional support, pressure for increased clinical productivity, and growing administrative burden are major challenges for the surgeon-scientist, as is the time-consuming nature of surgical training and practice. METHODS: An American Surgical Association Research Sustainability Task Force was created to outline a blueprint for sustainable science in surgery. Leaders from top NIH-sponsored departments of surgery engaged in video and in-person meetings between January and April 2023. A strength, weakness, opportunities, threats analysis was performed, and workgroups focused on the roles of surgeons, the department and institutions, and funding agencies. RESULTS: Taskforce recommendations: (1) SURGEONS: Growth mindset : identifying research focus, long-term planning, patience/tenacity, team science, collaborations with disparate experts; Skill set : align skills and research, fill critical skill gaps, develop team leadership skills; DEPARTMENT OF SURGERY (DOS): (2) MENTORSHIP: Chair : mentor-mentee matching/regular meetings/accountability, review of junior faculty progress, mentorship training requirement, recognition of mentorship (eg, relative value unit equivalent, awards; Mentor: dedicated time, relevant scientific expertise, extramural funding, experience and/or trained as mentor, trusted advisor; Mentee : enthusiastic/eager, proactive, open to feedback, clear about goals; (3) FINANCIAL SUSTAINABILITY: diversification of research portfolio, identification of matching funding sources, departmental resource awards (eg, T-/P-grants), leveraging of institutional resources, negotiation of formalized/formulaic funds flow investment from academic medical center toward science, philanthropy; (4) STRUCTURAL/STRATEGIC SUPPORT: Structural: grants administrative support, biostats/bioinformatics support, clinical trial and research support, regulatory support, shared departmental laboratory space/equipment; Strategic: hiring diverse surgeon-scientist/scientists faculty across DOS, strategic faculty retention/ recruitment, philanthropy, career development support, progress tracking, grant writing support, DOS-wide research meetings, regular DOS strategic research planning; (5) COMMUNITY AND CULTURE: Community: right mix of faculty, connection surgeon with broad scientific community; Culture: building research infrastructure, financial support for research, projecting importance of research (awards, grand rounds, shoutouts); (6) THE ROLE OF INSTITUTIONS: Foundation: research space co-location, flexible start-up packages, courses/mock study section, awards, diverse institutional mentorship teams; Nurture: institutional infrastructure, funding (eg, endowed chairs), promotion friendly toward surgeon-scientists, surgeon-scientists in institutional leadership positions; Expectations: RVU target relief, salary gap funding, competitive starting salaries, longitudinal salary strategy; (7) THE ROLE OF FUNDING AGENCIES: change surgeon research training paradigm, offer alternate awards to K-awards, increasing salary cap to reflect market reality, time extension for surgeon early-stage investigator status, surgeon representation on study section, focused award strategies for professional societies/foundations. CONCLUSIONS: Authentic recommitment from surgeon leaders with intentional and ambitious actions from institutions, corporations, funders, and society is essential in order to reap the essential benefits of surgeon-scientists toward advancements of science.

TiME OUT: Time-specific machine-learning evaluation to optimize ultramassive transfusion.

BACKGROUND: Ultramassive transfusion (UMT) is a resource-demanding intervention for trauma patients in hemorrhagic shock, and associated mortality rates remains high. Current research has been unable to identify a transfusion ceiling or point where UMT transitions from lifesaving to futility. Furthermore, little consideration has been given to how time-specific patient data points impact decisions with ongoing high-volume resuscitation. Therefore, this study sought to use time-specific machine learning modeling to predict mortality and identify parameters associated with survivability in trauma patients undergoing UMT. METHODS: A retrospective review was conducted at a Level I trauma (2018-2021) and included trauma patients meeting criteria for UMT, defined as ≥20 red blood cell products within 24 hours of admission. Cross-sectional data were obtained from the blood bank and trauma registries, and time-specific data were obtained from the electronic medical record. Time-specific decision-tree models predicating mortality were generated and evaluated using area under the curve. RESULTS: In the 180 patients included, mortality rate was 40.5% at 48 hours and 52.2% overall. The deceased received significantly more blood products with a median of 71.5 total units compared with 55.5 in the survivors ( p < 0.001) and significantly greater rates of packed red blood cells and fresh frozen plasma at each time interval. Time-specific decision-tree models predicted mortality with an accuracy as high as 81%. In the early time intervals, hemodynamic stability, undergoing an emergency department thoracotomy, and injury severity were most predictive of survival, while, in the later intervals, markers of adequate resuscitation such as arterial pH and lactate level became more prominent. CONCLUSION: This study supports that the decision of "when to stop" in UMT resuscitation is not based exclusively on the number of units transfused but rather the complex integration of patient and time-specific data. Machine learning is an effective tool to investigate this concept, and further research is needed to refine and validate these time-specific decision-tree models. LEVEL OF EVIDENCE: Prognostic and Epidemiological; Level IV.

Using Trajectories of Bedside Vital Signs to Identify COVID-19 Subphenotypes.

BACKGROUND: Trajectories of bedside vital signs have been used to identify sepsis subphenotypes with distinct outcomes and treatment responses. The objective of this study was to validate the vitals trajectory model in a multicenter cohort of patients hospitalized with COVID-19 and to evaluate the clinical characteristics and outcomes of the resulting subphenotypes. RESEARCH QUESTION: Can the trajectory of routine bedside vital signs identify COVID-19 subphenotypes with distinct clinical characteristics and outcomes? STUDY DESIGN AND METHODS: The study included adult patients admitted with COVID-19 to four academic hospitals in the Emory Healthcare system between March 1, 2020, and May 31, 2022. Using a validated group-based trajectory model, we classified patients into previously defined vital sign trajectories using oral temperature, heart rate, respiratory rate, and systolic and diastolic BP measured in the first 8 h of hospitalization. Clinical characteristics, biomarkers, and outcomes were compared between subphenotypes. Heterogeneity of treatment effect to tocilizumab was evaluated. RESULTS: The 7,065 patients with hospitalized COVID-19 were classified into four subphenotypes: group A (n = 1,429, 20%)-high temperature, heart rate, respiratory rate, and hypotensive; group B (1,454, 21%)-high temperature, heart rate, respiratory rate, and hypertensive; group C (2,996, 42%)-low temperature, heart rate, respiratory rate, and normotensive; and group D (1,186, 17%)-low temperature, heart rate, respiratory rate, and hypotensive. Groups A and D had higher ORs of mechanical ventilation, vasopressors, and 30-day inpatient mortality (P < .001). On comparing patients receiving tocilizumab (n = 55) with those who met criteria for tocilizumab but were admitted before its use (n = 461), there was significant heterogeneity of treatment effect across subphenotypes in the association of tocilizumab with 30-day mortality (P = .001). INTERPRETATION: By using bedside vital signs available in even low-resource settings, we found novel subphenotypes associated with distinct manifestations of COVID-19, which could lead to preemptive and targeted treatments.

Uncertainty-Aware Convolutional Neural Network for Identifying Bilateral Opacities on Chest X-rays: A Tool to Aid Diagnosis of Acute Respiratory Distress Syndrome.

Acute Respiratory Distress Syndrome (ARDS) is a severe lung injury with high mortality, primarily characterized by bilateral pulmonary opacities on chest radiographs and hypoxemia. In this work, we trained a convolutional neural network (CNN) model that can reliably identify bilateral opacities on routine chest X-ray images of critically ill patients. We propose this model as a tool to generate predictive alerts for possible ARDS cases, enabling early diagnosis. Our team created a unique dataset of 7800 single-view chest-X-ray images labeled for the presence of bilateral or unilateral pulmonary opacities, or 'equivocal' images, by three blinded clinicians. We used a novel training technique that enables the CNN to explicitly predict the 'equivocal' class using an uncertainty-aware label smoothing loss. We achieved an Area under the Receiver Operating Characteristic Curve (AUROC) of 0.82 (95% CI: 0.80, 0.85), a precision of 0.75 (95% CI: 0.73, 0.78), and a sensitivity of 0.76 (95% CI: 0.73, 0.78) on the internal test set while achieving an (AUROC) of 0.84 (95% CI: 0.81, 0.86), a precision of 0.73 (95% CI: 0.63, 0.69), and a sensitivity of 0.73 (95% CI: 0.70, 0.75) on an external validation set. Further, our results show that this approach improves the model calibration and diagnostic odds ratio of the hypothesized alert tool, making it ideal for clinical decision support systems.

Intravenous vitamin C therapy in adult patients with sepsis: A rapid practice guideline.

BACKGROUND: This Rapid Practice Guideline provides an evidence-based recommendation to address the question: in adults with sepsis or septic shock, should we recommend using or not using intravenous vitamin C therapy? METHODS: The panel included 21 experts from 16 countries and used a strict policy for potential financial and intellectual conflicts of interest. Methodological support was provided by the Guidelines in Intensive Care, Development, and Evaluation (GUIDE) group. Based on an updated systematic review, and the grading of recommendations, assessment, development, and evaluation approach, we evaluated the certainty of evidence and developed recommendations using the evidence-to-decision framework. We conducted an electronic vote, requiring >80% agreement among the panel for a recommendation to be adopted. RESULTS: At longest follow-up, 90 days, intravenous vitamin C probably does not substantially impact (relative risk 1.05, 95% confidence interval [CI] 0.94 to 1.17; absolute risk difference 1.8%, 95% CI -2.2 to 6.2; 6 trials, n = 2148, moderate certainty). Effects of vitamin C on mortality at earlier timepoints was of low or very low certainty due to risk of bias of the included studies and significant heterogeneity between study results. Few adverse events were reported with the use of vitamin C. The panel did not identify any major differences in other outcomes, including duration of mechanical ventilation, ventilator free days, hospital or intensive care unit length of stay, acute kidney injury, need for renal replacement therapy. Vitamin C may result in a slight reduction in duration of vasopressor support (MD -18.9 h, 95% CI -26.5 to -11.4; 21 trials, n = 2661, low certainty); but may not reduce sequential organ failure assessment scores (MD -0.69, 95% CI -1.55 to 0.71; 24 trials, n = 4002, low certainty). The panel judged the undesirable consequences of using IV vitamin C to probably outweigh the desirable consequences, and therefore issued a conditional recommendation against using IV vitamin C therapy in sepsis. CONCLUSIONS: The panel suggests against use of intravenous vitamin C in adult patients with sepsis, beyond that of standard nutritional supplementation. Small and single center trials on this topic should be discouraged.

CHRONIC ETHANOL USE WORSENS GUT PERMEABILITY AND ALTERS TIGHT JUNCTION EXPRESSION IN A MURINE SEPSIS MODEL.

ABSTRACT: Alcohol use disorder is associated with increased mortality in septic patients. Murine studies demonstrate that ethanol/sepsis is associated with changes in gut integrity. This study examined intestinal permeability after ethanol/sepsis and investigated mechanisms responsible for alterations in barrier function. Mice were randomized to drink either 20% ethanol or water for 12 weeks and then were subjected to either sham laparotomy or cecal ligation and puncture (CLP). Intestinal permeability was disproportionately increased in ethanol/septic mice via the pore, leak, and unrestricted pathways. Consistent with increased permeability in the leak pathway, jejunal myosin light chain (MLC) kinase (MLCK) expression and the ratio of phospho-MLC to total MLC were both increased in ethanol/CLP. Gut permeability was altered in MLCK -/- mice in water/CLP; however, permeability was not different between WT and MLCK -/- mice in ethanol/CLP. Similarly, jejunal IL-1ß levels were decreased while systemic IL-6 levels were increased in MLCK -/- mice in water/CLP but no differences were identified in ethanol/CLP. While we have previously shown that mortality is improved in MLCK -/- mice after water/CLP, mortality was significantly worse in MLCK -/- mice after ethanol/CLP. Consistent with an increase in the pore pathway, claudin 4 levels were also selectively decreased in ethanol/CLP WT mice. Furthermore, mRNA expression of jejunal TNF and IFN-γ were both significantly increased in ethanol/CLP. The frequency of CD4 + cells expressing TNF and IL-17A and the frequency of CD8 + cells expressing IFN-γ in Peyer's Patches were also increased in ethanol/CLP. Thus, there is an ethanol-specific worsening of gut barrier function after CLP that impacts all pathways of intestinal permeability, mediated, in part, via changes to the tight junction. Differences in the host response in the setting of chronic alcohol use may play a role in future precision medicine approaches toward the treatment of sepsis.

Flow-Sizing Critical Care Resources.

OBJECTIVES: To describe the factors affecting critical care capacity and how critical care organizations (CCOs) within academic centers in the U.S. flow-size critical care resources under normal operations, strain, and surge conditions. DATA SOURCES: PubMed, federal agency and American Hospital Association reports, and previous CCO survey results were reviewed. STUDY SELECTION: Studies and reports of critical care bed capacity and utilization within CCOs and in the United States were selected. DATA EXTRACTION: The Academic Leaders in the Critical Care Medicine Task Force established regular conference calls to reach a consensus on the approach of CCOs to "flow-sizing" critical care services. DATA SYNTHESIS: The approach of CCOs to "flow-sizing" critical care is outlined. The vertical (relation to institutional resources, e.g., space allocation, equipment, personnel redistribution) and horizontal (interdepartmental, e.g., emergency department, operating room, inpatient floors) integration of critical care delivery (ICUs, rapid response) for healthcare organizations and the methods by which CCOs flow-size critical care during normal operations, strain, and surge conditions are described. The advantages, barriers, and recommendations for the rapid and efficient scaling of critical care operations via a CCO structure are explained. Comprehensive guidance and resources for the development of "flow-sizing" capability by a CCO within a healthcare organization are provided. CONCLUSIONS: We identified and summarized the fundamental principles affecting critical care capacity. The taskforce highlighted the advantages of the CCO governance model to achieve rapid and cost-effective "flow-sizing" of critical care services and provide recommendations and resources to facilitate this capability. The relevance of a comprehensive approach to "flow-sizing" has become particularly relevant in the wake of the latest COVID-19 pandemic. In light of the growing risks of another extreme epidemic, planning for adequate capacity to confront the next critical care crisis is urgent.

Cancer and sepsis.

Sepsis is one of the leading causes of death worldwide. While mortality is high regardless of inciting infection or comorbidities, mortality in patients with cancer and sepsis is significantly higher than mortality in patients with sepsis without cancer. Cancer patients are also significantly more likely to develop sepsis than the general population. The mechanisms underlying increased mortality in cancer and sepsis patients are multifactorial. Cancer treatment alters the host immune response and can increase susceptibility to infection. Preclinical data also suggests that cancer, in and of itself, increases mortality from sepsis with dysregulation of the adaptive immune system playing a key role. Further, preclinical data demonstrate that sepsis can alter subsequent tumor growth while tumoral immunity impacts survival from sepsis. Checkpoint inhibition is a well-accepted treatment for many types of cancer, and there is increasing evidence suggesting this may be a useful strategy in sepsis as well. However, preclinical studies of checkpoint inhibition in cancer and sepsis demonstrate results that could not have been predicted by examining either variable in isolation. As sepsis management transitions from a 'one size fits all' model to a more individualized approach, understanding the mechanistic impact of cancer on outcomes from sepsis represents an important strategy towards delivering on the promise of precision medicine in the intensive care unit.

Gut Microbiome in Sepsis.

Abstract The gut has been hypothesized to be the "motor" of multiple organ dysfunction in sepsis. Although there are multiple ways in which the gut can drive systemic inflammation, increasing evidence suggests that the intestinal microbiome plays a more substantial role than previously appreciated. An English language literature review was performed to summarize the current knowledge of sepsis-induced gut microbiome dysbiosis. Conversion of a normal microbiome to a pathobiome in the setting of sepsis is associated with worsened mortality. Changes in microbiome composition and diversity signal the intestinal epithelium and immune system resulting in increased intestinal permeability and a dysregulated immune response to sepsis. Clinical approaches to return to microbiome homeostasis may be theoretically possible through a variety of methods including probiotics, prebiotics, fecal microbial transplant, and selective decontamination of the digestive tract. However, more research is required to determine the efficacy (if any) of targeting the microbiome for therapeutic gain. The gut microbiome rapidly loses diversity with emergence of virulent bacteria in sepsis. Restoring normal commensal bacterial diversity through various therapies may be an avenue to improve sepsis mortality.

Comparison of time series clustering methods for identifying novel subphenotypes of patients with infection.

OBJECTIVE: Severe infection can lead to organ dysfunction and sepsis. Identifying subphenotypes of infected patients is essential for personalized management. It is unknown how different time series clustering algorithms compare in identifying these subphenotypes. MATERIALS AND METHODS: Patients with suspected infection admitted between 2014 and 2019 to 4 hospitals in Emory healthcare were included, split into separate training and validation cohorts. Dynamic time warping (DTW) was applied to vital signs from the first 8 h of hospitalization, and hierarchical clustering (DTW-HC) and partition around medoids (DTW-PAM) were used to cluster patients into subphenotypes. DTW-HC, DTW-PAM, and a previously published group-based trajectory model (GBTM) were evaluated for agreement in subphenotype clusters, trajectory patterns, and subphenotype associations with clinical outcomes and treatment responses. RESULTS: There were 12 473 patients in training and 8256 patients in validation cohorts. DTW-HC, DTW-PAM, and GBTM models resulted in 4 consistent vitals trajectory patterns with significant agreement in clustering (71-80% agreement, P < .001): group A was hyperthermic, tachycardic, tachypneic, and hypotensive. Group B was hyperthermic, tachycardic, tachypneic, and hypertensive. Groups C and D had lower temperatures, heart rates, and respiratory rates, with group C normotensive and group D hypotensive. Group A had higher odds ratio of 30-day inpatient mortality (P < .01) and group D had significant mortality benefit from balanced crystalloids compared to saline (P < .01) in all 3 models. DISCUSSION: DTW- and GBTM-based clustering algorithms applied to vital signs in infected patients identified consistent subphenotypes with distinct clinical outcomes and treatment responses. CONCLUSION: Time series clustering with distinct computational approaches demonstrate similar performance and significant agreement in the resulting subphenotypes.