Mechanism of electro-acupuncture in alleviating intestinal injury in septic mice via polyamine-related M2-macrophage polarization.

Objective: The objective of this study was to investigate the impact of electro-acupuncture (EA) on sepsis-related intestinal injury and its relationship with macrophage polarization. Methods: A sepsis model was established using cecal ligation and puncture (CLP) to assess the effectiveness of EA. The extent of pathological injury was evaluated using Chiu's score, the expression of ZO-1 and Ocludin, and the impact on macrophage polarization was examined through flow cytometry and immunofluorescence staining. The expression of spermidine, one type of polyamine, and ornithine decarboxylase (ODC) was measured using ELISA and PCR. Once the efficacy was determined, a polyamine depletion model was created, and the role of polyamines was reassessed by evaluating efficacy and observing macrophage polarization. Results: EA treatment reduced the Chiu's score and increased the expression of ZO-1 and Ocludin in the intestinal tissue of septic mice. It inhibited the secretion of IL-1ß and TNF-α, promoted the polarization of M2-type macrophages, increased the secretion of IL-10, and upregulated the expression of Arg-1, spermidine, and ODC. However, after depleting polyamines, the beneficial effects of EA on alleviating intestinal tissue damage and modulating macrophage polarization disappeared. Conclusion: The mechanism underlying the alleviation of intestinal injury associated with CLP-induced sepsis by EA involves with the promotion of M2-type macrophage polarization mediated by spermidine expression.

Associations Between Volume of Early Intravenous Fluid and Hospital Outcomes in Septic Patients With and Without Heart Failure: A Retrospective Cohort Study.

OBJECTIVES: To evaluate the relationship between early IV fluid volume and hospital outcomes, including death in-hospital or discharge to hospice, in septic patients with and without heart failure (HF). DESIGN: A retrospective cohort study using logistic regression with restricted cubic splines to assess for nonlinear relationships between fluid volume and outcomes, stratified by HF status and adjusted for propensity to receive a given fluid volume in the first 6 hours. An ICU subgroup analysis was performed. Secondary outcomes of vasopressor use, mechanical ventilation, and length of stay in survivors were assessed. SETTING: An urban university-based hospital. PATIENTS: A total of 9613 adult patients were admitted from the emergency department from 2012 to 2021 that met electronic health record-based Sepsis-3 criteria. Preexisting HF diagnosis was identified by the International Classification of Diseases codes. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: There were 1449 admissions from patients with HF. The relationship between fluid volume and death or discharge to hospice was nonlinear in patients without HF, and approximately linear in patients with HF. Receiving 0-15 mL/kg in the first 6 hours was associated with lower likelihood of death or discharge to hospice compared with 30-45 mL/kg (odds ratio = 0.61; 95% CI, 0.41-0.90; p = 0.01) in HF patients, but no significant difference for non-HF patients. A similar pattern was identified in ICU admissions and some secondary outcomes. Volumes larger than 15-30 mL/kg for non-HF patients and 30-45 mL/kg for ICU-admitted non-HF patients were not associated with improved outcomes. CONCLUSIONS: Early fluid resuscitation showed distinct patterns of potential harm and benefit between patients with and without HF who met Sepsis-3 criteria. Restricted cubic splines analysis highlighted the importance of considering nonlinear fluid outcomes relationships and identified potential points of diminishing returns (15-30 mL/kg across all patients without HF and 30-45 mL/kg when admitted to the ICU). Receiving less than 15 mL/kg was associated with better outcomes in HF patients, suggesting small volumes may be appropriate in select patients. Future studies may benefit from investigating nonlinear fluid-outcome associations and a focus on other conditions like HF.

Can Machine Learning Personalize Cardiovascular Therapy in Sepsis?

Large randomized trials in sepsis have generally failed to find effective novel treatments. This is increasingly attributed to patient heterogeneity, including heterogeneous cardiovascular changes in septic shock. We discuss the potential for machine learning systems to personalize cardiovascular resuscitation in sepsis. While the literature is replete with proofs of concept, the technological readiness of current systems is low, with a paucity of clinical trials and proven patient benefit. Systems may be vulnerable to confounding and poor generalization to new patient populations or contemporary patterns of care. Typical electronic health records do not capture rich enough data, at sufficient temporal resolution, to produce systems that make actionable treatment suggestions. To resolve these issues, we recommend a simultaneous focus on technical challenges and removing barriers to translation. This will involve improving data quality, adopting causally grounded models, prioritizing safety assessment and integration into healthcare workflows, conducting randomized clinical trials and aligning with regulatory requirements.

Preexisting Diabetes Mellitus and All-Cause Mortality in Adult Patients With Sepsis: A Population-Based Cohort Study.

OBJECTIVES: We assessed the association of preexisting diabetes mellitus with all-cause mortality and organ support receipt in adult patients with sepsis. DESIGN: Population-based cohort study. SETTING: Ontario, Canada (2008-2019). POPULATION: Adult patients (18 yr old or older) with a first sepsis-related hospitalization episode. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The main exposure of interest was preexisting diabetes (either type 1 or 2). The primary outcome was all-cause mortality by 90 days; secondary outcomes included receipt of invasive mechanical ventilation and new renal replacement therapy. We report adjusted (for baseline characteristics using standardization) risk ratios (RRs) alongside 95% CIs. A main secondary analysis evaluated the potential mediation by prior metformin use of the association between preexisting diabetes and all-cause mortality following sepsis. Overall, 503,455 adults with a first sepsis-related hospitalization episode were included; 36% had preexisting diabetes. Mean age was 73 years, and 54% of the cohort were females. Preexisting diabetes was associated with a lower adjusted risk of all-cause mortality at 90 days (RR, 0.81; 95% CI, 0.80-0.82). Preexisting diabetes was associated with an increased risk of new renal replacement therapy (RR, 1.53; 95% CI, 1.46-1.60) but not invasive mechanical ventilation (RR, 1.03; 95% CI, 1.00-1.05). Overall, 21% (95% CI, 19-28) of the association between preexisting diabetes and reduced risk of all-cause mortality was mediated by prior metformin use. CONCLUSIONS: Preexisting diabetes is associated with a lower risk of all-cause mortality and higher risk of new renal replacement therapy among adult patients with sepsis. Future studies should evaluate the underlying mechanisms of these associations.

A scoping review of machine learning for sepsis prediction- feature engineering strategies and model performance: a step towards explainability.

BACKGROUND: Sepsis, an acute and potentially fatal systemic response to infection, significantly impacts global health by affecting millions annually. Prompt identification of sepsis is vital, as treatment delays lead to increased fatalities through progressive organ dysfunction. While recent studies have delved into leveraging Machine Learning (ML) for predicting sepsis, focusing on aspects such as prognosis, diagnosis, and clinical application, there remains a notable deficiency in the discourse regarding feature engineering. Specifically, the role of feature selection and extraction in enhancing model accuracy has been underexplored. OBJECTIVES: This scoping review aims to fulfill two primary objectives: To identify pivotal features for predicting sepsis across a variety of ML models, providing valuable insights for future model development, and To assess model efficacy through performance metrics including AUROC, sensitivity, and specificity. RESULTS: The analysis included 29 studies across diverse clinical settings such as Intensive Care Units (ICU), Emergency Departments, and others, encompassing 1,147,202 patients. The review highlighted the diversity in prediction strategies and timeframes. It was found that feature extraction techniques notably outperformed others in terms of sensitivity and AUROC values, thus indicating their critical role in improving sepsis prediction models. CONCLUSION: Key dynamic indicators, including vital signs and critical laboratory values, are instrumental in the early detection of sepsis. Applying feature selection methods significantly boosts model precision, with models like Random Forest and XG Boost showing promising results. Furthermore, Deep Learning models (DL) reveal unique insights, spotlighting the pivotal role of feature engineering in sepsis prediction, which could greatly benefit clinical practice.

[Tissue perfusion monitoring in children with acute circulatory dysfunction: narrative review]. / Monitorización de la perfusión tisular en el niño con disfunción circulatoria aguda: revisión narrativa.

Sepsis is one of the main causes of admission to Intensive Care Units (ICU). The hemodynamic objectives usually sought during the resuscitation of the patient in septic shock correspond to macrohemodynamic parameters (heart rate, blood pressure, central venous pressure). However, persistent alterations in microcirculation, despite the restoration of macrohemodynamic parameters, can cause organ failure. This dissociation between the macrocirculation and microcirculation originates the need to evaluate organ tissue perfusion, the most commonly used being urinary output, lactatemia, central venous oxygen saturation (ScvO2), and veno-arterial pCO2 gap. Because peripheral tissues, such as the skin, are sensitive to disturbances in perfusion, noninvasive monitoring of peripheral circulation, such as skin temperature gradient, capillary refill time, mottling score, and peripheral perfusion index may be helpful as early markers of the existence of systemic hemodynamic alterations. Peripheral circulation monitoring techniques are relatively easy to interpret and can be used directly at the patient's bedside. This approach can be quickly applied in the intra- or extra-ICU setting. The objective of this narrative review is to analyze the various existing tissue perfusion markers and to update the evidence that allows guiding hemodynamic support in a more individualized therapy for each patient.

Towards personalized medicine: a scoping review of immunotherapy in sepsis.

Despite significant progress in our understanding of the pathophysiology of sepsis and extensive clinical research, there are few proven therapies addressing the underlying immune dysregulation of this life-threatening condition. The aim of this scoping review is to describe the literature evaluating immunotherapy in adult patients with sepsis, emphasizing on methods providing a "personalized immunotherapy" approach, which was defined as the classification of patients into a distinct subgroup or subphenotype, in which a patient's immune profile is used to guide treatment. Subgroups are subsets of sepsis patients, based on any cut-off in a variable. Subphenotypes are subgroups that can be reliably discriminated from other subgroup based on data-driven assessments. Included studies were randomized controlled trials and cohort studies investigating immunomodulatory therapies in adults with sepsis. Studies were identified by searching PubMed, Embase, Cochrane CENTRAL and ClinicalTrials.gov, from the first paper available until January 29th, 2024. The search resulted in 15,853 studies. Title and abstract screening resulted in 1409 studies (9%), assessed for eligibility; 771 studies were included, of which 282 (37%) were observational and 489 (63%) interventional. Treatment groups included were treatments targeting the innate immune response, the complement system, coagulation and endothelial dysfunction, non-pharmalogical treatment, pleiotropic drugs, immunonutrition, concomitant treatments, Traditional Chinese Medicine, immunostimulatory cytokines and growth factors, intravenous immunoglobulins, mesenchymal stem cells and immune-checkpoint inhibitors. A personalized approach was incorporated in 70 studies (9%). Enrichment was applied using cut-offs in temperature, laboratory, biomarker or genetic variables. Trials often showed conflicting results, possibly due to the lack of patient stratification or the potential influence of severity and timing on immunomodulatory therapy results. When a personalized approach was applied, trends of clinical benefit for several interventions emerged, which hold promise for future clinical trials using personalized immunotherapy.

Prediction of Readmission Following Sepsis Using Social Determinants of Health.

OBJECTIVES: To determine the predictive value of social determinants of health (SDoH) variables on 30-day readmission following a sepsis hospitalization as compared with traditional clinical variables. DESIGN: Multicenter retrospective cohort study using patient-level data, including demographic, clinical, and survey data. SETTINGS: Thirty-five hospitals across the United States from 2017 to 2021. PATIENTS: Two hundred seventy-one thousand four hundred twenty-eight individuals in the AllofUs initiative, of which 8909 had an index sepsis hospitalization. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Unplanned 30-day readmission to the hospital. Multinomial logistic regression models were constructed to account for survival in determination of variables associate with 30-day readmission and are presented as adjusted odds rations (aORs). Of the 8909 sepsis patients in our cohort, 21% had an unplanned hospital readmission within 30 days. Median age (interquartile range) was 54 years (41-65 yr), 4762 (53.4%) were female, and there were self-reported 1612 (18.09%) Black, 2271 (25.49%) Hispanic, and 4642 (52.1%) White individuals. In multinomial logistic regression models accounting for survival, we identified that change to nonphysician provider type due to economic reasons (aOR, 2.55 [2.35-2.74]), delay of receiving medical care due to lack of transportation (aOR, 1.68 [1.62-1.74]), and inability to afford flow-up care (aOR, 1.59 [1.52-1.66]) were strongly and independently associated with a 30-day readmission when adjusting for survival. Patients who lived in a ZIP code with a high percentage of patients in poverty and without health insurance were also more likely to be readmitted within 30 days (aOR, 1.26 [1.22-1.29] and aOR, 1.28 [1.26-1.29], respectively). Finally, we found that having a primary care provider and health insurance were associated with low odds of an unplanned 30-day readmission. CONCLUSIONS: In this multicenter retrospective cohort, several SDoH variables were strongly associated with unplanned 30-day readmission. Models predicting readmission following sepsis hospitalization may benefit from the addition of SDoH factors to traditional clinical variables.

Clinical implications of septic cardiomyopathy: A narrative review.

Sepsis is caused by the body's dysregulated response to infection, which can lead to multiorgan injury and death. Patients with sepsis may develop acute cardiac dysfunction, termed septic cardiomyopathy, which is a global but reversible dysfunction of both sides of the heart. This narrative review discusses the mechanistic changes in the heart during septic cardiomyopathy, its diagnosis, existing treatment options regarding severity and course, and emerging treatment approaches. Although no standardized definition for septic cardiomyopathy exists, it is described as a reversible myocardial dysfunction that typically resolves within 7 to 10 days. Septic cardiomyopathy is often diagnosed based on electrocardiography, cardiac magnetic resonance imaging, biomarkers, and direct invasive and noninvasive measures of cardiac output. Presently, the treatment of septic cardiomyopathy is similar to that of sepsis, primarily focusing on acute interventions. Treatments for cardiomyopathy often include angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, and diuretics. However, because of profound hypotension in sepsis, many cardiomyopathy treatments are contraindicated in patients with septic cardiomyopathy. Substantial efforts have been made to study the pathophysiological mechanisms and diagnostic options; however, the lack of a uniform definition for septic cardiomyopathy is challenging for physicians when considering treatments. Another challenge for physicians is that the treatment for septic cardiomyopathy has only focused on acute intervention, whereas the treatment for other cardiomyopathies has been provided on a long-term basis. A better understanding of the underlying mechanisms of septic cardiomyopathy may contribute to the development of a unified definition of the condition and novel treatment options.

Adaptive platform trials rather than randomised controlled trials for paediatric sepsis.

Adaptive platform trials (APTs) offer a promising alternative to traditional randomised controlled trials for evaluating treatments for paediatric sepsis. Randomised controlled trials, despite being the gold standard for establishing causality between interventions and outcomes, make many assumptions about disease prevalence, severity and intervention effects, which are often incorrect. As a result, the evidence for most treatments for paediatric sepsis are based on low-quality evidence. APTs use accrued data rather than assumptions to power trial adaptations. They can assess multiple treatments simultaneously with shared research infrastructure. As such, APTs offer a more efficient, flexible and more effective way to identify optimal treatments. The proposed Paediatric Adaptive Sepsis Platform Trial, leveraging the Paediatric Research in Emergency Departments International Collaborative network's infrastructure, will evaluate resuscitation fluids, vasoactive medications, corticosteroids and antimicrobials. This trial has the potential to substantially impact clinical practice and reduce global sepsis mortality in children.

Sepsis, Management & Advances in Metabolomics.

Though there have been developments in clinical care and management, early and accurate diagnosis and risk stratification are still bottlenecks in septic shock patients. Since septic shock is multifactorial with patient-specific underlying co-morbid conditions, early assessment of sepsis becomes challenging due to variable symptoms and clinical manifestations. Moreover, the treatment strategies are traditionally based on their progression and corresponding clinical symptoms, not personalized. The complex pathophysiology assures that a single biomarker cannot identify, stratify, and describe patients affected by septic shock. Traditional biomarkers like CRP, PCT, and cytokines are not sensitive and specific enough to be used entirely for a patient's diagnosis and prognosis. Thus, the need of the hour is a sensitive and specific biomarker after comprehensive analysis that may facilitate an early diagnosis, prognosis, and drug development. Integration of clinical data with metabolomics would provide means to understand the patient's condition, stratify patients better, and predict the clinical outcome.

Cardiac Function Before Sepsis and Clinical Outcomes.

This cohort study characterizes heterogeneity in cardiac function prior to sepsis and describes associations with hospitalization outcomes and mortality.

Critical care management of acute liver failure.

The management of acute liver failure (ALF) in modern hepatology intensive care units (ICU) has improved patient outcomes. Critical care management of hepatic encephalopathy, cerebral edema, fluid and electrolytes; prevention of infections and organ support are central to improved outcomes of ALF. In particular, the pathogenesis of encephalopathy is multifactorial, with ammonia, elevated intra-cranial pressure and systemic inflammation playing a central role. Although ALF remains associated with high mortality, the availability of supportive care, including organ failure support such as plasma exchange, timely mechanical ventilation or continuous renal replacement therapy, either conservatively manages patients with ALF or offers bridging therapy until liver transplantation. Thus, appropriate critical care management has improved the likelihood of patient recovery in ALF. ICU care interventions such as monitoring of cerebral edema, fluid status assessment and interventions for sepsis prevention, nutritional support and management of electrolytes can salvage a substantial proportion of patients. In this review, we discuss the key aspects of critical care management of ALF.

[Emergencies in infectious diseases]. / Infektiologische Notfälle.

This article aims to provide an overview of common and high-impact medical emergencies that require prompt and effective infectious diseases management. In the described clinical scenarios of malaria, sepsis, necrotizing fasciitis, and meningitis the authors have emphasized the crucial importance of rapid and accurate diagnosis, as well as appropriate treatment from the perspective of infectious diseases. All of these emergencies demand a high degree of clinical suspicion for accurate diagnosis. Some of them also necessitate the involvement of other medical disciplines, such as neurology in the case of meningitis or surgery for necrotizing fasciitis. Additionally, implementing the right empiric antibiotic regimen or, in the case of malaria, antiparasitic treatment is crucial for improving patient outcomes. As patients with these diagnoses may present at any outpatient department, and efficient and quick management is essential, a deep understanding of diagnostic algorithms and potential pitfalls is of the utmost importance.

EARLY FLUID PLUS NOREPINEPHRINE RESUSCITATION DIMINISHES KIDNEY HYPOPERFUSION AND INFLAMMATION IN SEPTIC NEWBORN PIGS.

ABSTRACT: Sepsis is the most frequent risk factor for acute kidney injury (AKI) in critically ill infants. Sepsis-induced dysregulation of kidney microcirculation in newborns is unresolved. The objective of this study was to use the translational swine model to evaluate changes in kidney function during the early phase of sepsis in newborns and the impact of fluid plus norepinephrine resuscitation. Newborn pigs (3-7-day-old) were allocated randomly to three groups: 1) sham, 2) sepsis (cecal ligation and puncture) without subsequent resuscitation, and 3) sepsis with lactated Ringer plus norepinephrine resuscitation. All animals underwent standard anesthesia and mechanical ventilation. Cardiac output and glomerular filtration rate were measured noninvasively. Mean arterial pressure, total renal blood flow, cortical perfusion, medullary perfusion, and medullary tissue oxygen tension (mtPO 2 ) were determined for 12 h. Cecal ligation and puncture decreased mean arterial pressure and cardiac output by more than 50%, with a proportional increase in renal vascular resistance and a 60-80% reduction in renal blood flow, cortical perfusion, medullary perfusion, and mtPO 2 compared to sham. Cecal ligation and puncture also decreased glomerular filtration rate by ~79% and increased AKI biomarkers. Isolated foci of tubular necrosis were observed in the septic piglets. Except for mtPO 2 , changes in all these parameters were ameliorated in resuscitated piglets. Resuscitation also attenuated sepsis-induced increases in the levels of plasma C-reactive protein, proinflammatory cytokines, lactate dehydrogenase, alanine transaminase, aspartate aminotransferase, and renal NLRP3 inflammasome. These data suggest that newborn pigs subjected to cecal ligation and puncture develop hypodynamic septic AKI. Early implementation of resuscitation lessens the degree of inflammation, AKI, and liver injury.

The role of TIM-3 in sepsis: a promising target for immunotherapy?

Sepsis remains a significant cause of mortality and morbidity worldwide, with limited effective treatment options. The T-cell immunoglobulin and mucin domain-containing molecule 3 (TIM-3) has emerged as a potential therapeutic target in various immune-related disorders. This narrative review aims to explore the role of TIM-3 in sepsis and evaluate its potential as a promising target for immunotherapy. We discuss the dynamic expression patterns of TIM-3 during sepsis and its involvement in regulating immune responses. Furthermore, we examine the preclinical studies investigating the regulation of TIM-3 signaling pathways in septic models, highlighting the potential therapeutic benefits and challenges associated with targeting TIM-3. Overall, this review emphasizes the importance of TIM-3 in sepsis pathogenesis and underscores the promising prospects of TIM-3-based immunotherapy as a potential strategy to combat this life-threatening condition.

Predictors of clinical outcomes in patients with sepsis: A retrospective study from a tertiary care hospital in Pakistan.

OBJECTIVE: To assess associations between various clinic-demographic factors and clinical outcomes among patients treated for sepsis. METHODS: The retrospective study was conducted at the Aga Khan University Hospital, Karachi, and comprised data of all patients aged >18 years diagnosed with sepsis from January to December 2019. Multivariable logistic regression was used to evaluate independent associations between predictors and outcomes. Data was analysed using R packages. RESULTS: Of the 1,136 patients, 621(54.6%) were male and 515(45.3%) were female. The overall mean age was 59.05±16.91 years. Female gender (odds ratio: 1.029; 95% confidence interval: 1.03-1.64) was found to be an independent predictor of septic shock, while hypertension (odds ratio0.75; 95% confidence interval: 0.59-0.95) emerged as a protective factor. Chronic kidney disease (odds ratio: 1.539; 95% confidence interval: 1.14-2.07) was an independent predictor of prolonged length of stay, while older age appeared to be protective (odds ratio: 0.98; 95% confidence interval: 0.98-0.99). Mortality was associated with a significantly lower odds of Escherichia coli on culture (odds ratio: 0.26; 95% confidence interval: 0.12-0.54). CONCLUSIONS: Independent associations were found between specific patient characteristics and adverse clinical outcomes.

Th17/Treg balance: the bloom and wane in the pathophysiology of sepsis.

Sepsis is a multi-organ dysfunction characterized by an unregulated host response to infection. It is associated with high morbidity, rapid disease progression, and high mortality. Current therapies mainly focus on symptomatic treatment, such as blood volume supplementation and antibiotic use, but their effectiveness is limited. Th17/Treg balance, based on its inflammatory property, plays a crucial role in determining the direction of the inflammatory response and the regression of organ damage in sepsis patients. This review provides a summary of the changes in T-helper (Th) 17 cell and regulatory T (Treg) cell differentiation and function during sepsis, the heterogeneity of Th17/Treg balance in the inflammatory response, and the relationship between Th17/Treg balance and organ damage. Th17/Treg balance exerts significant control over the bloom and wanes in host inflammatory response throughout sepsis.