Prognostic and predictive enrichment in sepsis

The Lipid Intensive Drug Therapy for Sepsis Phase II Pilot Clinical Trial

OBJECTIVES

Low cholesterol levels in early sepsis patients are associated with mortality. We sought to test if IV lipid emulsion administration to sepsis patients with low cholesterol levels would prevent a decline or increase total cholesterol levels at 48 hours.

DESIGN

Phase II, adaptive, randomized pilot clinical trial powered for 48 patients.

SETTING

Emergency department or ICU of an academic medical center.

PATIENTS

Sepsis patients (first 24 hr) with Sequential Organ Failure Assessment greater than or equal to 4 or shock.

INTERVENTIONS

Patients meeting study criteria, including screening total cholesterol levels less than or equal to 100 mg/dL or high-density lipoprotein cholesterol (HDL-C) + low-density lipoprotein cholesterol (LDL-C) less than or equal to 70 mg/dL, were randomized to receive one of three doses of lipid emulsion administered twice in 48 hours or no drug (controls). The primary endpoint was a change in serum total cholesterol (48 hr - enrollment) between groups.

MEASUREMENTS AND MAIN RESULTS

Forty-nine patients were enrolled and randomized. Two patients randomized to lipid emulsion were withdrawn before drug administration. Data for 24 control patients and 23 lipid emulsion patients were analyzed. The mean change in total cholesterol from enrollment to 48 hours was not different between groups and was 5 mg/dL ( sd 20) for lipid emulsion patients, and 2 mg/dL ( sd 18) for control patients ( p = 0.62). The mean changes in HDL-C and LDL-C were similar between groups. Mean change in triglycerides was elevated in lipid emulsion patients (61 mg/dL, sd 87) compared with controls (20 mg/dL, sd 70, p = 0.086). The 48-hour change in SOFA score was -2 (interquartile range [IQR] -4, -1) for control patients and -2 (IQR -3, 0) for lipid emulsion patients ( p = 0.46).

CONCLUSIONS

Administration of IV lipid emulsion to early sepsis patients with low cholesterol levels did not influence change in cholesterol levels from enrollment to 48 hours.

Identification of severe acute pediatric asthma phenotypes using unsupervised machine learning

RATIONALE

More targeted management of severe acute pediatric asthma could improve clinical outcomes.

OBJECTIVES

To identify distinct clinical phenotypes of severe acute pediatric asthma using variables obtained in the first 12 h of hospitalization.

METHODS

We conducted a retrospective cohort study in a quaternary care children's hospital from 2014 to 2022. Encounters for children ages 2-18 years admitted to the hospital for asthma were included. We used consensus k means clustering with patient demographics, vital signs, diagnostics, and laboratory data obtained in the first 12 h of hospitalization.

MEASUREMENTS AND MAIN RESULTS

The study population included 683 encounters divided into derivation (80%) and validation (20%) sets, and two distinct clusters were identified. Compared to Cluster 1 in the derivation set, Cluster 2 encounters (177 [32%]) were older (11 years [8; 14] vs. 5 years [3; 8]; p < .01) and more commonly males (63% vs. 53%; p = .03) of Black race (51% vs. 40%; p = .03) with non-Hispanic ethnicity (96% vs. 84%; p < .01). Cluster 2 encounters had smaller improvements in vital signs at 12-h including percent change in heart rate (-1.7 [-11.7; 12.7] vs. -7.8 [-18.5; 1.7]; p < .01), and respiratory rate (0.0 [-20.0; 22.2] vs. -11.4 [-27.3; 9.0]; p < .01). Encounters in Cluster 2 had lower percentages of neutrophils (70.0 [55.0; 83.0] vs. 85.0 [77.0; 90.0]; p < .01) and higher percentages of lymphocytes (17.0 [8.0; 32.0] vs. 9.0 [5.3; 14.0]; p < .01). Cluster 2 encounters had higher rates of invasive mechanical ventilation (23% vs. 5%; p < .01), longer hospital length of stay (4.5 [2.6; 8.8] vs. 2.9 [2.0; 4.3]; p < .01), and a higher mortality rate (7.3% vs. 0.0%; p < .01). The predicted cluster assignments in the validation set shared the same ratio (~2:1), and many of the same characteristics.

CONCLUSIONS

We identified two clinical phenotypes of severe acute pediatric asthma which exhibited distinct clinical features and outcomes.

From ICU Syndromes to ICU Subphenotypes: Consensus Report and Recommendations for Developing Precision Medicine in the ICU

Critical care uses syndromic definitions to describe patient groups for clinical practice and research. There is growing recognition that a "precision medicine" approach is required and that integrated biologic and physiologic data identify reproducible subpopulations that may respond differently to treatment. This article reviews the current state of the field and considers how to successfully transition to a precision medicine approach. To impact clinical care, identification of subpopulations must do more than differentiate prognosis. It must differentiate response to treatment, ideally by defining subgroups with distinct functional or pathobiological mechanisms (endotypes). There are now multiple examples of reproducible subpopulations of sepsis, acute respiratory distress syndrome, and acute kidney or brain injury described using clinical, physiological, and/or biological data. Many of these subpopulations have demonstrated the potential to define differential treatment response, largely in retrospective studies, and that the same treatment-responsive subpopulations may cross multiple clinical syndromes (treatable traits). To bring about a change in clinical practice, a precision medicine approach must be evaluated in prospective clinical studies requiring novel adaptive trial designs. Several such studies are underway, but there are multiple challenges to be tackled. Such subpopulations must be readily identifiable and be applicable to all critically ill populations around the world. Subdividing clinical syndromes into subpopulations will require large patient numbers. Global collaboration of investigators, clinicians, industry, and patients over many years will therefore be required to transition to a precision medicine approach and ultimately realize treatment advances seen in other medical fields.

Integrated clustering of multiple immune marker trajectories reveals different immunotypes in severely injured patients

BACKGROUND

The immune response of critically ill patients, such as those with sepsis, severe trauma, or major surgery, is heterogeneous and dynamic, but its characterization and impact on outcomes are poorly understood. Until now, the primary challenge in advancing our understanding of the disease has been to concurrently address both multiparametric and temporal aspects.

METHODS

We used a clustering method to identify distinct groups of patients, based on various immune marker trajectories during the first week after admission to ICU. In 339 severely injured patients, we initially longitudinally clustered common biomarkers (both soluble and cellular parameters), whose variations are well-established during the immunosuppressive phase of sepsis. We then applied this multi-trajectory clustering using markers composed of whole blood immune-related mRNA.

RESULTS

We found that both sets of markers revealed two immunotypes, one of which was associated with worse outcomes, such as increased risk of hospital-acquired infection and mortality, and prolonged hospital stays. This immunotype showed signs of both hyperinflammation and immunosuppression, which persisted over time.

CONCLUSION

Our study suggest that the immune system of critically ill patients can be characterized by two distinct longitudinal immunotypes, one of which included patients with a persistently dysregulated and impaired immune response. This work confirms the relevance of such methodology to stratify patients and pave the way for further studies using markers indicative of potential immunomodulatory drug targets.

Protective effects of DcR3-SUMO on lipopolysaccharide-induced inflammatory cells and septic mice

Despite the high mortality rate associated with sepsis, no specific drugs are available. Decoy receptor 3 (DcR3) is now considered a valuable biomarker and therapeutic target for managing inflammatory conditions. DcR3-SUMO, an analog of DcR3, has a simple production process and high yield. However, its precise underlying mechanisms in sepsis remain unclear. This study investigated the protective effects of DcR3-SUMO on lipopolysaccharide (LPS)-induced inflammatory cells and septic mice. We evaluated the effects of DcR3 intervention and overexpression on intracellular inflammatory cytokine levels in vitro. DcR3-SUMO significantly reduced cytokine levels within inflammatory cells, and notably increased DcR3 protein and mRNA levels in LPS-induced septic mice, confirming its anti-inflammatory efficacy. Our in vitro and in vivo results demonstrated comparable anti-inflammatory effects between DcR3-SUMO and native DcR3. DcR3-SUMO protein administration in septic mice notably enhanced tissue morphology, decreased sepsis scores, and elevated survival rates. Furthermore, DcR3-SUMO treatment effectively lowered inflammatory cytokine levels in the serum, liver, and lung tissues, and mitigated the extent of tissue damage. AlphaFold3 structural predictions indicated that DcR3-SUMO, similar to DcR3, effectively interacts with the three pro-apoptotic ligands, namely TL1A, LIGHT, and FasL. Collectively, DcR3-SUMO and DcR3 exhibit comparable anti-inflammatory effects, making DcR3-SUMO a promising therapeutic agent for sepsis.

The value of right ventricular pulmonary artery coupling in determining the prognosis of patients with sepsis

The outcomes of patients with sepsis are influenced by the contractile function of the right ventricle (RV), but the impact of cardiopulmonary interaction in ICU-mortality of sepsis patients remains unclear. This study aims to investigate the ICU-mortality impact of right ventricular-pulmonary artery (RV-PA) coupling in patients with sepsis. We employed echocardiography to assess patients with sepsis within the initial 24 h of their admission to the ICU. RV-PA coupling was evaluated using the tricuspid annular plane systolic excursion (TAPSE) to pulmonary artery systolic pressure (PASP) ratio. A total of 92 subjects were enrolled, with 55 survivors and 37 non-survivors. TAPSE/PASP ratio assessed mortality with an area under the curve (AUC) of 0.766 (95% CI 0.670-0.862) and the optimal cutoff value was 0.495 mm/mmHg. We constructed a nomogram depicting the TAPSE/PASP in conjunction with IL-6 and Lac for the joint prediction of sepsis prognosis, and demonstrated the highest predictive capability (AUC = 0.878, 95% CI 0.809-0.948). In conclusion, the TAPSE/PASP ratio demonstrated prognostic value for ICU mortality in sepsis patients. The nomogram, which combines the TAPSE/PASP, IL-6, and LAC, demonstrated enhanced predictive efficacy for the prognosis of sepsis patients.

Biomarker-Based Risk Stratification Tool in Pediatric Acute Respiratory Distress Syndrome: Single-Center, Longitudinal Validation in a 2014-2019 Cohort

OBJECTIVES

The Pediatric Acute Respiratory Distress Syndrome Biomarker Risk Model (PARDSEVERE) used age and three plasma biomarkers measured within 24 hours of pediatric acute respiratory distress syndrome (ARDS) onset to predict mortality in a pilot cohort of 152 patients. However, longitudinal performance of PARDSEVERE has not been evaluated, and it is unclear whether the risk model can be used to prognosticate after day 0. We, therefore, sought to determine the test characteristics of PARDSEVERE model and population over the first 7 days after ARDS onset.

DESIGN

Secondary unplanned post hoc analysis of data from a prospective observational cohort study carried out 2014-2019.

SETTING

University-affiliated PICU.

PATIENTS

Mechanically ventilated children with ARDS.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Between July 2014 and December 2019, 279 patients with ARDS had plasma collected at day 0, 266 at day 3 (11 nonsurvivors, two discharged between days 0 and 3), and 207 at day 7 (27 nonsurvivors, 45 discharged between days 3 and 7). The actual prevalence of mortality on days 0, 3, and 7, was 23% (64/279), 14% (38/266), and 13% (27/207), respectively. The PARDSEVERE risk model for mortality on days 0, 3, and 7 had area under the receiver operating characteristic curve (AUROC [95% CI]) of 0.76 (0.69-0.82), 0.68 (0.60-0.76), and 0.74 (0.65-0.83), respectively. The AUROC data translate into prevalence thresholds for the PARDSEVERE model for mortality (i.e., using the sensitivity and specificity values) of 37%, 27%, and 24% on days 0, 3, and 7, respectively. Negative predictive value (NPV) was high throughout (0.87-0.90 for all three-time points).

CONCLUSIONS

In this exploratory analysis of the PARDSEVERE model of mortality risk prediction in a population longitudinal series of data from days 0, 3, and 7 after ARDS diagnosis, the diagnostic performance is in the "acceptable" category. NPV was good. A major limitation is that actual mortality is far below the prevalence threshold for such testing. The model may, therefore, be more useful in cohorts with higher mortality rates (e.g., immunocompromised, other countries), and future enhancements to the model should be explored.

Predicting Organ Dysfunction in Septic and Critically Ill Patients: A Prospective Cohort Study Using Rapid Ex Vivo Immune Profiling

OBJECTIVES

While cytokine response patterns are pivotal in mediating immune responses, they are also often dysregulated in sepsis and critical illness. We hypothesized that these immunological deficits, quantifiable through ex vivo whole blood stimulation assays, may be indicative of subsequent organ dysfunction.

DESIGN

In a prospective observational study, adult septic patients and critically ill but nonseptic controls were identified within 48 hours of critical illness onset. Using a rapid, ex vivo assay based on responses to lipopolysaccharide (LPS), anti-CD3/anti-CD28 antibodies, and phorbol 12-myristate 13-acetate with ionomycin, cytokine responses to immune stimulants were quantified. The primary outcome was the relationship between early cytokine production and subsequent organ dysfunction, as measured by the Sequential Organ Failure Assessment score on day 3 of illness (SOFAd3).

SETTING

Patients were recruited in an academic medical center and data processing and analysis were done in an academic laboratory setting.

PATIENTS

Ninety-six adult septic and critically ill nonseptic patients were enrolled.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Elevated levels of tumor necrosis factor and interleukin-6 post-endotoxin challenge were inversely correlated with SOFAd3. Interferon-gamma production per lymphocyte was inversely related to organ dysfunction at day 3 and differed between septic and nonseptic patients. Clustering analysis revealed two distinct immune phenotypes, represented by differential responses to 18 hours of LPS stimulation and 4 hours of anti-CD3/anti-CD28 stimulation.

CONCLUSIONS

Our rapid immune profiling technique offers a promising tool for early prediction and management of organ dysfunction in critically ill patients. This information could be pivotal for early intervention and for preventing irreversible organ damage during the acute phase of critical illness.

Exosome-shuttled miR-150-5p from LPS-preconditioned mesenchymal stem cells down-regulate PI3K/Akt/mTOR pathway via Irs1 to enhance M2 macrophage polarization and confer protection against sepsis

Rationale

Sepsis is a life-threatening organ dysfunction and lack of effective measures in the current. Exosomes from mesenchymal stem cells (MSCs) reported to alleviate inflammation during sepsis, and the preconditioning of MSCs could enhance their paracrine potential. Therefore, this study investigated whether exosomes secreted by lipopolysaccharide (LPS)-pretreated MSCs exert superior antiseptic effects, and explored the underlying molecular mechanisms.

Methods

Exosomes were isolated and characterized from the supernatants of MSCs. The therapeutic efficacy of normal exosomes (Exo) and LPS-pretreated exosomes (LPS-Exo) were evaluated in terms of survival rates, inflammatory response, and organ damage in an LPS-induced sepsis model. Macrophages were stimulated with LPS and treated with Exo or LPS-Exo to confirm the results of the in vivo studies, and to explain the potential mechanisms.

Results

LPS-Exo were shown to inhibit aberrant pro-inflammatory cytokines, prevent organ damages, and improve survival rates of the septic mice to a greater extent than Exo. In vitro, LPS-Exo significantly promoted the M2 polarization of macrophages exposed to inflammation. miRNA sequencing and qRT-PCR analysis identified the remarkable expression of miR-150-5p in LPS-Exo compared to that in Exo, and exosomal miR-150-5p was transferred into recipient macrophages and mediated macrophage polarization. Further investigation demonstrated that miR-150-5p targets Irs1 in recipient macrophages and subsequently modulates macrophage plasticity by down-regulating the PI3K/Akt/mTOR pathway.

Conclusion

The current findings highly suggest that exosomes derived from LPS pre-conditioned MSCs represent a promising cell-free therapeutic method and highlight miR-150-5p as a novel molecular target for regulating immune hyperactivation during sepsis.

A design specification for Critical Illness Digital Twins (CIDTs) to cure sepsis: responding to the National Academies of Sciences, Engineering and Medicine Report "Foundational Research Gaps and Future Directions for Digital Twins"

On December 15, 2023, The National Academies of Sciences, Engineering and Medicine (NASEM) released a report entitled: "Foundational Research Gaps and Future Directions for Digital Twins." The ostensible purpose of this report was to bring some structure to the burgeoning field of digital twins by providing a working definition and a series of research challenges that need to be addressed to allow this technology to fulfill its full potential. In the work presented herein we focus on five specific findings from the NASEM Report: 1) definition of a Digital Twin, 2) using "fit-for-purpose" guidance, 3) developing novel approaches to Verification, Validation and Uncertainty Quantification (VVUQ) of Digital Twins, 4) incorporating control as an explicit purpose for a Digital Twin and 5) using a Digital Twin to guide data collection and sensor development, and describe how these findings are addressed through the design specifications for a Critical Illness Digital Twin (CIDT) aimed at curing sepsis.

Construction and validation of a nomogram prediction model for the progression to septic shock in elderly patients with urosepsis

Background

Septic shock is a clinical syndrome characterized by the progression of sepsis to a severe stage. Elderly patients with urosepsis in the intensive care unit (ICU) are more likely to progress to septic shock. This study aimed to establish and validate a nomogram model for predicting the risk of progression to septic shock in elderly patients with urosepsis.

Methods

We extracted data from the Medical Information Mart for Intensive Care (MIMIC-IV) and the eICU Collaborative Research Database (eICU-CRD). The MIMIC-IV dataset was split into a training set for model development and an internal validation set to assess model performance. Further external validation was performed using a distinct dataset sourced from the eICU-CRD. Predictors were screened using least absolute shrinkage and selection operator (LASSO) regression and multivariable logistic regression analyses. The evaluation of model performance included discrimination, calibration, and clinical usefulness.

Results

The study demonstrated that the Glasgow Coma Scale (GCS), white blood count (WBC), platelet, blood urea nitrogen (BUN), calcium, albumin, congestive heart failure (CHF), and invasive ventilation were closely associated with septic shock in the training cohort. Nomogram prediction, utilizing eight parameters, demonstrated strong predictive accuracy with area under the curve (AUC) values of 0.809 (95 % CI 0.786-0.834), 0.794 (95 % CI 0.756-0.831), and 0.723 (95 % CI 0.647-0.801) in the training, internal validation, and external validation sets, respectively. Additionally, the nomogram demonstrated a promising calibration performance and significant clinical usefulness in both the training and validation sets.

Conclusion

The constructed nomogram is a reliable and practical tool for predicting the risk of progression to septic shock in elderly patients with urosepsis. Its implementation in clinical practice may enhance the early identification of high-risk patients, facilitate timely and targeted interventions to mitigate the risk of septic shock, and improve patient outcomes.

High-throughput mass spectrometry maps the sepsis plasma proteome and differences in patient response

Sepsis, the dysregulated host response to infection causing life-threatening organ dysfunction, is a global health challenge requiring better understanding of pathophysiology and new therapeutic approaches. Here, we applied high-throughput tandem mass spectrometry to delineate the plasma proteome for sepsis and comparator groups (noninfected critical illness, postoperative inflammation, and healthy volunteers) involving 2612 samples (from 1611 patients) and 4553 liquid chromatography-mass spectrometry analyses acquired through a single batch of continuous measurements, with a throughput of 100 samples per day. We show how this scale of data can delineate proteins, pathways, and coexpression modules in sepsis and be integrated with paired leukocyte transcriptomic data (837 samples from n = 649 patients). We mapped the plasma proteomic landscape of the host response in sepsis, including changes over time, and identified features relating to etiology, clinical phenotypes (including organ failures), and severity. This work reveals subphenotypes informative for sepsis response state, disease processes, and outcome; identifies potential biomarkers; and advances opportunities for a precision medicine approach to sepsis.

HERPES SIMPLEX VIRUS-1 SUSCEPTIBILITY AS A RISK FACTOR FOR SEPSIS, WITH CYTOMEGALOVIRUS SUSCEPTIBILITY ELEVATING SEVERITY: INSIGHTS FROM A BIDIRECTIONAL MENDELIAN RANDOMIZATION STUDY

ABSTRACT

Objective: We conducted a two-sample bidirectional Mendelian randomization (MR) study to investigate the causal relationships between herpes viruses and sepsis. Methods: Publicly available genome-wide association study data were used. Four viruses, HSV-1, HSV-2, EBV, and CMV, were selected, with serum positivity and levels of antibody in serum as the herpes virus data. Results: In forward MR, susceptibility to HSV-1 was a risk factor for sepsis. The susceptibility to CMV showed a severity-dependent effect on sepsis and was a risk factor for the 28-day mortality from sepsis, and was also a risk factor for 28-day sepsis mortality in critical care admission. The EBV EA-D antibody level after EBV infection was a protective factor for 28-day sepsis mortality in critical care admission, and CMV pp28 antibody level was a risk factor for 28-day sepsis mortality in critical care admission. No statistically significant causal relationships between HSV-2 and sepsis were found. No exposures having statistically significant association with sepsis critical care admission as an outcome were found. In reverse MR, the sepsis critical care admission group manifested a decrease in CMV pp52 antibody levels. No causal relationships with statistical significance between sepsis exposure and other herpes virus outcomes were found. Conclusion: Our study identifies HSV-1 susceptibility as a sepsis risk, with CMV susceptibility elevating severity. Varied effects of EBV and CMV antibodies on sepsis severity are noted. Severe sepsis results in a decline in CMV antibody levels. Our results help prognostic and predictive enrichment and offer valuable information for precision sepsis treatment.

Subgroup identification-based model selection to improve the predictive performance of individualized dosing

Currently, model-informed precision dosing uses one population pharmacokinetic model that best fits the target population. We aimed to develop a subgroup identification-based model selection approach to improve the predictive performance of individualized dosing, using vancomycin in neonates/infants as a test case. Data from neonates/infants with at least one vancomycin concentration was randomly divided into training and test dataset. Population predictions from published vancomycin population pharmacokinetic models were calculated. The single best-performing model based on various performance metrics, including median absolute percentage error (APE) and percentage of predictions within 20% (P20) or 60% (P60) of measurement, were determined. Clustering based on median APEs or clinical and demographic characteristics and model selection by genetic algorithm was used to group neonates/infants according to their best-performing model. Subsequently, classification trees to predict the best-performing model using clinical and demographic characteristics were developed. A total of 208 vancomycin treatment episodes in training and 88 in test dataset was included. Of 30 identified models from the literature, the single best-performing model for training dataset had P20 26.2-42.6% in test dataset. The best-performing clustering approach based on median APEs or clinical and demographic characteristics and model selection by genetic algorithm had P20 44.1-45.5% in test dataset, whereas P60 was comparable. Our proof-of-concept study shows that the prediction of the best-performing model for each patient according to the proposed model selection approaches has the potential to improve the predictive performance of model-informed precision dosing compared with the single best-performing model approach.

Biological basis of critical illness subclasses: from the bedside to the bench and back again

Critical illness syndromes including sepsis, acute respiratory distress syndrome, and acute kidney injury (AKI) are associated with high in-hospital mortality and long-term adverse health outcomes among survivors. Despite advancements in care, clinical and biological heterogeneity among patients continues to hamper identification of efficacious therapies. Precision medicine offers hope by identifying patient subclasses based on clinical, laboratory, biomarker and 'omic' data and potentially facilitating better alignment of interventions. Within the previous two decades, numerous studies have made strides in identifying gene-expression based endotypes and clinico-biomarker based phenotypes among critically ill patients associated with differential outcomes and responses to treatment. In this state-of-the-art review, we summarize the biological similarities and differences across the various subclassification schemes among critically ill patients. In addition, we highlight current translational gaps, the need for advanced scientific tools, human-relevant disease models, to gain a comprehensive understanding of the molecular mechanisms underlying critical illness subclasses.

Use of Immune Profiling Panel to assess the immune response of septic patients for prediction of worsening as a composite endpoint

Sepsis induces intense, dynamic and heterogeneous host response modulations. Despite improvement of patient management, the risk of mortality and healthcare-associated infections remains high. Treatments to counterbalance immune response are under evaluation, but effective biomarkers are still lacking to perform patient stratification. The design of the present study was defined to alleviate the limitations of existing literature: we selected patients who survived the initial hyperinflammatory response and are still hospitalized at day 5-7 after ICU admission. Using the Immune Profiling Panel (IPP), a fully automated RT-qPCR multiplex prototype, we optimized a machine learning model combining the IPP gene expression levels for the identification of patients at high risk of worsening, a composite endpoint defined as death or secondary infection, within one week after sampling. This was done on 332 sepsis patients selected from two retrospective studies. The IPP model identified a high-risk group comprising 30% of patients, with a significant increased proportion of worsening events at day 28 compared to the low-risk group (49% vs. 28%, respectively). These preliminary results underline the potential clinical application of IPP for sepsis patient stratification in a personalized medicine perspective, that will be confirmed in a larger prospective multicenter study.

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.

The immune landscape of sepsis and using immune clusters for identifying sepsis endotypes

Background

The dysregulated immune response to sepsis still remains unclear. Stratification of sepsis patients into endotypes based on immune indicators is important for the future development of personalized therapies. We aimed to evaluate the immune landscape of sepsis and the use of immune clusters for identifying sepsis endotypes.

Methods

The indicators involved in innate, cellular, and humoral immune cells, inhibitory immune cells, and cytokines were simultaneously assessed in 90 sepsis patients and 40 healthy controls. Unsupervised k-means cluster analysis of immune indicator data were used to identify patient clusters, and a random forest approach was used to build a prediction model for classifying sepsis endotypes.

Results

We depicted that the impairment of innate and adaptive immunity accompanying increased inflammation was the most prominent feature in patients with sepsis. However, using immune indicators for distinguishing sepsis from bacteremia was difficult, most likely due to the considerable heterogeneity in sepsis patients. Cluster analysis of sepsis patients identified three immune clusters with different survival rates. Cluster 1 (36.7%) could be distinguished from the other clusters as being an "effector-type" cluster, whereas cluster 2 (34.4%) was a "potential-type" cluster, and cluster 3 (28.9%) was a "dysregulation-type" cluster, which showed the lowest survival rate. In addition, we established a prediction model based on immune indicator data, which accurately classified sepsis patients into three immune endotypes.

Conclusion

We depicted the immune landscape of patients with sepsis and identified three distinct immune endotypes with different survival rates. Cluster membership could be predicted with a model based on immune data.

Profiling the dysregulated immune response in sepsis: overcoming challenges to achieve the goal of precision medicine

Sepsis is characterised by a dysregulated host immune response to infection. Despite recognition of its significance, immune status monitoring is not implemented in clinical practice due in part to the current absence of direct therapeutic implications. Technological advances in immunological profiling could enhance our understanding of immune dysregulation and facilitate integration into clinical practice. In this Review, we provide an overview of the current state of immune profiling in sepsis, including its use, current challenges, and opportunities for progress. We highlight the important role of immunological biomarkers in facilitating predictive enrichment in current and future treatment scenarios. We propose that multiple immune and non-immune-related parameters, including clinical and microbiological data, be integrated into diagnostic and predictive combitypes, with the aid of machine learning and artificial intelligence techniques. These combitypes could form the basis of workable algorithms to guide clinical decisions that make precision medicine in sepsis a reality and improve patient outcomes.

Pediatric Sepsis Phenotypes and Outcome: 5-Year Retrospective Cohort Study in a Single Center in India (2017-2022)

OBJECTIVES

To describe mortality associated with different clinical phenotypes of sepsis in children.

DESIGN

Retrospective study.

SETTING

PICU of a tertiary care center in India from 2017 to 2022.

PATIENTS

Six hundred twelve children (from 2 mo to 17 yr old) with a retrospectively applied diagnosis of sepsis using 2020 guidance.

METHODS

The main outcome was mortality associated with sepsis subtypes. Other analyses included assessment of risk factors, requirement for organ support, and PICU resources used by sepsis phenotype. Clinical data were recorded on a predesigned proforma.

INTERVENTIONS

None.

MEASUREMENTS AND RESULTS

Of the 612 children identified, there were 382 (62%) with sepsis but no multiple organ failure (NoMOF), 48 (8%) with thrombocytopenia-associated MOF (TAMOF), 140 (23%) with MOF without thrombocytopenia, and 40 (6.5%) with sequential MOF (SMOF). Mortality was higher in the SMOF (20/40 [50%]), MOF (62/140 [44%]) and TAMOF (20/48 [42%]) groups, compared with NoMOF group (82/382 [21%] [ p < 0.001]). The requirement for organ support and PICU resources was higher in all phenotypes with MOF as compared with those without MOF. On multivariable analysis elevated lactate and having MOF were associated with greater odds of mortality.

CONCLUSIONS

In this single-center experience of sepsis in India, we found that sepsis phenotypes having MOF were associated with mortality and the requirement of PICU resources. Prospective studies in different regions of the world will help identify a classification of pediatric sepsis that is more widely applicable.

Prevalence of frailty and association with patient centered outcomes: A prospective registry-embedded cohort study from India

PURPOSE

We aimed to study the prevalence of frailty, evaluate risk factors, and understand impact on outcomes in India.

METHODS

This was a prospective registry-embedded cohort study across 7 intensive care units (ICUs) and included adult patients anticipated to stay for at least 48 h. Primary exposure was frailty, as defined by a score ≥ 5 on the Clinical Frailty Scale and primary outcome was ICU mortality. Secondary outcomes included in-hospital mortality and resource utilization. We used generalized linear models to evaluate risk factors and model association between frailty and outcomes.

RESULTS

838 patients were included, with median (IQR) age 57 (42,68) yrs.; 64.8% were male. Prevalence of frailty was 19.8%. Charlson comorbidity index (OR:1.73 (95%CI:1.39,2.15)), Subjective Global Assessment categories mild/moderate malnourishment (OR:1.90 (95%CI:1.29, 2.80)) and severe malnourishment (OR:4.76 (95% CI:2.10,10.77)) were associated with frailty. Frailty was associated with higher odds of ICU mortality (adjusted OR:2.04 (95% CI:1.25,3.33)), hospital mortality (adjusted OR:2.36 (95%CI:1.45,3.84)), development of stage2/3 AKI (unadjusted OR:2.35 (95%CI:1.60, 3.43)), receipt of non-invasive ventilation (unadjusted OR:2.68 (95%CI:1.77, 4.03)), receipt of vasopressors (unadjusted OR:1.47 (95%CI:1.04, 2.07)), and receipt of kidney replacement therapy (unadjusted OR:3.15 (95%CI:1.90, 5.17)).

CONCLUSIONS

Frailty is common among critically ill patients in India and is associated with worse outcomes.

STUDY REGISTRATION

CTRI/2021/02/031503.

Sepsis-associated acute kidney injury: recent advances in enrichment strategies, sub-phenotyping and clinical trials

Acute kidney injury (AKI) often complicates sepsis and is associated with high morbidity and mortality. In recent years, several important clinical trials have improved our understanding of sepsis-associated AKI (SA-AKI) and impacted clinical care. Advances in sub-phenotyping of sepsis and AKI and clinical trial design offer unprecedented opportunities to fill gaps in knowledge and generate better evidence for improving the outcome of critically ill patients with SA-AKI. In this manuscript, we review the recent literature of clinical trials in sepsis with focus on studies that explore SA-AKI as a primary or secondary outcome. We discuss lessons learned and potential opportunities to improve the design of clinical trials and generate actionable evidence in future research. We specifically discuss the role of enrichment strategies to target populations that are most likely to derive benefit and the importance of patient-centered clinical trial endpoints and appropriate trial designs with the aim to provide guidance in designing future trials.

Clinical practice of sepsis-induced immunosuppression: Current immunotherapy and future options

Sepsis is a potentially fatal condition characterized by the failure of one or more organs due to a disordered host response to infection. The development of sepsis is closely linked to immune dysfunction. As a result, immunotherapy has gained traction as a promising approach to sepsis treatment, as it holds the potential to reverse immunosuppression and restore immune balance, thereby improving the prognosis of septic patients. However, due to the highly heterogeneous nature of sepsis, it is crucial to carefully select the appropriate patient population for immunotherapy. This review summarizes the current and evolved treatments for sepsis-induced immunosuppression to enhance clinicians' understanding and practical application of immunotherapy in the management of sepsis.

A proposed framework for advancing acute kidney injury risk stratification and diagnosis in children: a report from the 26th Acute Disease Quality Initiative (ADQI) conference

Acute kidney injury (AKI) in children is associated with increased morbidity, reduced health-related quality of life, greater resource utilization, and higher mortality. Improvements in the timeliness and precision of AKI diagnosis in children are needed. In this report, we highlight existing, novel, and on-the-horizon diagnostic and risk-stratification tools for pediatric AKI, and outline opportunities for integration into clinical practice. We also summarize pediatric-specific high-risk diagnoses and exposures for AKI, as well as the potential role of real-time risk stratification and clinical decision support to improve outcomes. Lastly, the key characteristics of important pediatric AKI phenotypes will be outlined. Throughout, we identify key knowledge gaps, which represent prioritized areas of focus for future research that will facilitate a comprehensive, timely and personalized approach to pediatric AKI diagnosis and management.

ICU-acquired infections in immunocompromised patients

Immunocompromised patients account for an increasing proportion of the typical intensive care unit (ICU) case-mix. Because of the increased availability of new drugs for cancer and auto-immune diseases, and improvement in the care of the most severely immunocompromised ICU patients (including those with hematologic malignancies), critically ill immunocompromised patients form a highly heterogeneous patient population. Furthermore, a large number of ICU patients with no apparent immunosuppression also harbor underlying conditions altering their immune response, or develop ICU-acquired immune deficiencies as a result of sepsis, trauma or major surgery. While infections are associated with significant morbidity and mortality in immunocompromised critically ill patients, little specific data are available on the incidence, microbiology, management and outcomes of ICU-acquired infections in this population. As a result, immunocompromised patients are usually excluded from trials and guidelines on the management of ICU-acquired infections. The most common ICU-acquired infections in immunocompromised patients are ventilator-associated lower respiratory tract infections (which include ventilator-associated pneumonia and tracheobronchitis) and bloodstream infections. Recently, several large observational studies have shed light on some of the epidemiological specificities of these infections-as well as on the dynamics of colonization and infection with multidrug-resistant bacteria-in these patients, and these will be discussed in this review. Immunocompromised patients are also at higher risk than non-immunocompromised hosts of fungal and viral infections, and the diagnostic and therapeutic management of these infections will be covered. Finally, we will suggest some important areas of future investigation.

Targeting ferroptosis in the maintenance of mitochondrial homeostasis in the realm of septic cardiomyopathy

Septic cardiomyopathy is one of the predominant culprit factors contributing to the rising mortality in patients with severe sepsis. Among various mechanisms responsible for the etiology of septic heart anomalies, disruption of mitochondrial homeostasis has gained much recent attention, resulting in myocardial inflammation and even cell death. Ferroptosis is a novel category of regulated cell death (RCD) provoked by iron-dependent phospholipid peroxidation through iron-mediated phospholipid (PL) peroxidation, enroute to the rupture of plasma membranes and eventually cell death. This review summarizes the recent progress of ferroptosis in mitochondrial homeostasis during septic cardiomyopathy. We will emphasize the role of mitochondrial iron transport channels and the antioxidant system in ferroptosis. Finally, we will summarize and discuss future research, which should help guide disease treatment.

NMI Functions as Immuno-regulatory Molecule in Sepsis by Regulating Multiple Signaling Pathways

Sepsis-induced tissue and organ damage is caused by an overactive inflammatory response, immune dysfunction, and coagulation dysfunction. Danger-associated molecular pattern (DAMP) molecules play a critical role in the excessive inflammation observed in sepsis. In our previous research, we identified NMI as a new type of DAMP molecule that promotes inflammation in sepsis by binding to toll-like receptor 4 (TLR4) on macrophage surfaces, activating the NF-κB pathway, and releasing pro-inflammatory cytokines. However, it is still unknown whether NMI plays a significant role in other pathways. Our analysis of bulk and single-cell transcriptome data from the GEO database revealed a significant increase in NMI expression in neutrophils and monocytes in sepsis patients. It is likely that NMI functions through multiple receptors in sepsis, including IFNAR1, IFNAR2, TNFR1, TLR3, TLR1, IL9R, IL10RB, and TLR4. Furthermore, the correlation between NMI expression and the activation of NF-κB, MAPK, and JAK pathways, as well as the up-regulation of their downstream pro-inflammatory factors, demonstrates that NMI may exacerbate the inflammatory response through these signaling pathways. Finally, we demonstrated that STAT1 phosphorylation was enhanced in RAW cells upon stimulation with NMI, supporting the activation of JAK signaling pathway by NMI. Collectively, these findings shed new light on the functional mechanism of NMI in sepsis.

Association between serum sodium and 28-day mortality in sepsis patients: A secondary data analysis from three large critical illness cohorts

OBJECTIVE

The present study was designed to explore the association between serum sodium and mortality in patients with sepsis by using a large sample, multicenter MIMIC-IV database.

METHODS

We extracted the data of 34 925 sepsis patients from the retrospective cohort mimicIV database. After adjusting the confounders, we explored the independent effects of serum sodium on 28-day mortality.

RESULTS

A nonlinear relationship existed between serum sodium and 28-day mortality, of which a negative association was found between serum sodium and 28-day mortality (odds ratio: 0.95, 95% CI: 0.94, 0.96, p = 0.0001) when serum sodium was in 102 mmol/L to 138 mmol/L, but a positive correlation appeared when sodium climbed to the range of 140-179 mmol/L (odds ratio: 1.04, 95% CI: 1.03-1.06, p = 0.0001).

CONCLUSIONS

Both lower and higher serum sodium levels are associated with an increased risk of death in sepsis patients.

Highly secreted tryptophanyl tRNA synthetase 1 as a potential theranostic target for hypercytokinemic severe sepsis

Despite intensive clinical and scientific efforts, the mortality rate of sepsis remains high due to the lack of precise biomarkers for patient stratification and therapeutic guidance. Secreted human tryptophanyl-tRNA synthetase 1 (WARS1), an endogenous ligand for Toll-like receptor (TLR) 2 and TLR4 against infection, activates the genes that signify the hyperinflammatory sepsis phenotype. High plasma WARS1 levels stratified the early death of critically ill patients with sepsis, along with elevated levels of cytokines, chemokines, and lactate, as well as increased numbers of absolute neutrophils and monocytes, and higher Sequential Organ Failure Assessment (SOFA) scores. These symptoms were recapitulated in severely ill septic mice with hypercytokinemia. Further, injection of WARS1 into mildly septic mice worsened morbidity and mortality. We created an anti-human WARS1-neutralizing antibody that suppresses proinflammatory cytokine expression in marmosets with endotoxemia. Administration of this antibody into severe septic mice attenuated cytokine storm, organ failure, and early mortality. With antibiotics, the antibody almost completely prevented fatalities. These data imply that blood-circulating WARS1-guided anti-WARS1 therapy may provide a novel theranostic strategy for life-threatening systemic hyperinflammatory sepsis.

Alleviating sepsis: Revealing the protective role of costunolide in a cecal ligation and puncture rat model

Objectives

Sepsis poses a significant threat to human life, rendering it a burdensome medical disease. Despite significant advancements, the current state of medical science still lacks a viable and efficacious cure. Costunolide (COST) is a multifaceted sesquiterpene lactone that exhibits a range of actions, including anti-inflammatory and antioxidant properties. We investigated the potential impacts of COST on a rat sepsis model caused by cecal ligation and puncture (CLP).

Materials and Methods

We created an experimental rat model with the following groups: SHAM, CLP, CLP+low dose COST, and CLP+high dose COST. Blood, kidney, and lung samples were collected. Inflammatory mediators such as interleukin-1beta (IL-1β), IL-6, tumor necrosis factor-alpha (TNF- α), and nuclear factor kappa-B (NF-κB) were investigated. In addition, we assessed oxidative stress by measuring 8-Hydroxydeoxyguanosine (8-OHdG) immunopositivity, MDA levels, glutathione (GSH), and superoxide dismutase (SOD) activity. Histopathological and immunohistochemical examinations backed up our findings.

Results

Compared to the CLP group, the COST group showed a reduction in inflammatory and oxidative stress indicators. The expression of inflammatory mediators was suppressed by COST, and histological examinations revealed improvements in kidney and lung tissues in the treatment groups.

Conclusion

Our study highlights the preventive effects of COST against CLP-induced sepsis-related injury. Considering its beneficial effects against many diseases, COST is worthy as to be evaluated against sepsis.

The pathophysiology of sepsis and precision-medicine-based immunotherapy

Sepsis remains a major cause of morbidity and mortality in both low- and high-income countries. Antibiotic therapy and supportive care have significantly improved survival following sepsis in the twentieth century, but further progress has been challenging. Immunotherapy trials for sepsis, mainly aimed at suppressing the immune response, from the 1990s and 2000s, have largely failed, in part owing to unresolved patient heterogeneity in the underlying immune disbalance. The past decade has brought the promise to break this blockade through technological developments based on omics-based technologies and systems medicine that can provide a much larger data space to describe in greater detail the immune endotypes in sepsis. Patient stratification opens new avenues towards precision medicine approaches that aim to apply immunotherapies to sepsis, on the basis of precise biomarkers and molecular mechanisms defining specific immune endotypes. This approach has the potential to lead to the establishment of immunotherapy as a successful pillar in the treatment of sepsis for future generations.

Research Priorities in Critical Care Cardiology: JACC Expert Panel

Over the last several decades, the cardiac intensive care unit (CICU) has seen a substantial evolution in the patient population, comorbidities, and diagnoses. However, the generation of high-quality evidence to manage these complex and critically ill patients has been slow. Given the scarcity of clinical trials focused on critical care cardiology (CCC), CICU clinicians are often left to extrapolate from studies that either exclude or poorly represent the patient population admitted to CICUs. The lack of high-quality evidence and limited guidance from society guidelines has led to significant variation in practice patterns for many of the most common CICU diagnoses. Several barriers, both common to critical care research and unique to CCC, have impeded progress. In this multinational perspective, we describe key areas of priority for CCC research, current challenges for investigation in the CICU, and essential elements of a path forward for the field.

Classification of patients with COVID-19 by blood RNA endotype: a prospective cohort study

IMPORTANCE

In this study, whole-blood RNAs (prolactin and toll-like receptor 3) involved in the prognosis of patients with COVID-19 were identified. The RNA endotypes classified by these important RNAs highlight the possibility of stratifying the COVID-19 patient population and the need for targeted therapy based on these phenotypes.

Whole blood transcriptomics identifies subclasses of pediatric septic shock

BACKGROUND

Sepsis is a highly heterogeneous syndrome, which has hindered the development of effective therapies. This has prompted investigators to develop a precision medicine approach aimed at identifying biologically homogenous subgroups of patients with septic shock and critical illnesses. Transcriptomic analysis can identify subclasses derived from differences in underlying pathophysiological processes that may provide the basis for new targeted therapies. The goal of this study was to elucidate pathophysiological pathways and identify pediatric septic shock subclasses based on whole blood RNA expression profiles.

METHODS

The subjects were critically ill children with cardiopulmonary failure who were a part of a prospective randomized insulin titration trial to treat hyperglycemia. Genome-wide expression profiling was conducted using RNA sequencing from whole blood samples obtained from 46 children with septic shock and 52 mechanically ventilated noninfected controls without shock. Patients with septic shock were allocated to subclasses based on hierarchical clustering of gene expression profiles, and we then compared clinical characteristics, plasma inflammatory markers, cell compositions using GEDIT, and immune repertoires using Imrep between the two subclasses.

RESULTS

Patients with septic shock depicted alterations in innate and adaptive immune pathways. Among patients with septic shock, we identified two subtypes based on gene expression patterns. Compared with Subclass 2, Subclass 1 was characterized by upregulation of innate immunity pathways and downregulation of adaptive immunity pathways. Subclass 1 had significantly worse clinical outcomes despite the two classes having similar illness severity on initial clinical presentation. Subclass 1 had elevated levels of plasma inflammatory cytokines and endothelial injury biomarkers and demonstrated decreased percentages of CD4 T cells and B cells and less diverse T cell receptor repertoires.

CONCLUSIONS

Two subclasses of pediatric septic shock patients were discovered through genome-wide expression profiling based on whole blood RNA sequencing with major biological and clinical differences. Trial Registration This is a secondary analysis of data generated as part of the observational CAF-PINT ancillary of the HALF-PINT study (NCT01565941). Registered March 29, 2012.

Novel tripeptide RKH derived from Akkermansia muciniphila protects against lethal sepsis

OBJECTIVE

The pathogenesis of sepsis is complex, and the sepsis-induced systemic proinflammatory phase is one of the key drivers of organ failure and consequent mortality. Akkermansia muciniphila (AKK) is recognised as a functional probiotic strain that exerts beneficial effects on the progression of many diseases; however, whether AKK participates in sepsis pathogenesis is still unclear. Here, we evaluated the potential contribution of AKK to lethal sepsis development.

DESIGN

Relative abundance of gut microbial AKK in septic patients was evaluated. Cecal ligation and puncture (CLP) surgery and lipopolysaccharide (LPS) injection were employed to establish sepsis in mice. Non-targeted and targeted metabolomics analysis were used for metabolites analysis.

RESULTS

We first found that the relative abundance of gut microbial AKK in septic patients was significantly reduced compared with that in non-septic controls. Live AKK supplementation, as well as supplementation with its culture supernatant, remarkably reduced sepsis-induced mortality in sepsis models. Metabolomics analysis and germ-free mouse validation experiments revealed that live AKK was able to generate a novel tripeptide Arg-Lys-His (RKH). RKH exerted protective effects against sepsis-induced death and organ damage. Furthermore, RKH markedly reduced sepsis-induced inflammatory cell activation and proinflammatory factor overproduction. A mechanistic study revealed that RKH could directly bind to Toll-like receptor 4 (TLR4) and block TLR4 signal transduction in immune cells. Finally, we validated the preventive effects of RKH against sepsis-induced systemic inflammation and organ damage in a piglet model.

CONCLUSION

We revealed that a novel tripeptide, RKH, derived from live AKK, may act as a novel endogenous antagonist for TLR4. RKH may serve as a novel potential therapeutic approach to combat lethal sepsis after successfully translating its efficacy into clinical practice.

Ex Vivo Endotoxin Stimulation of Blood for Predicting Survival in Patients With Sepsis: A Systematic Review

BACKGROUND

Sepsis is a syndrome characterized by host immune dysfunction, with the extent of immunoparalysis differing among patients. Lipopolysaccharide (LPS) is used commonly to assess the immune function of critically ill patients with sepsis. However, the reliability of this ex vivo diagnostic test in predicting clinical outcomes remains uncertain.

RESEARCH QUESTION

Does LPS-induced tumor necrosis factor (TNF) production from the blood of patients with sepsis predict mortality? Secondary outcomes included ICU and hospital stay durations, nosocomial infection rate, and organ recovery rate.

STUDY DESIGN AND METHODS

Human sepsis studies from various databases through April 2023 were evaluated. Inclusion criteria encompassed LPS-stimulated blood assays, English language, and reported clinical outcomes. Bias risk was evaluated using the Newcastle-Ottawa scale (NOS). Relationships between TNF production and mortality were analyzed at sepsis onset and during established sepsis, alongside secondary outcomes.

RESULTS

Of 11,580 studies, 17 studies (14 adult and three pediatric) were selected for analysis. Although 15 studies were evaluated as moderate to high quality using the NOS, it is important to note that some of these studies also had identifiable biases, such as unclear methods of participant recruitment. Nine studies detailed survival outcomes associated with LPS-induced TNF production at sepsis onset, whereas five studies explored TNF production's relationship with mortality during established sepsis. Trends suggested that lower LPS-induced TNF production correlated with higher mortality. However, heterogeneity in methodologies, especially the LPS assay protocol, hindered definitive conclusions. Publication bias was highlighted using funnel plot analysis. Concerning secondary outcomes, diminished TNF production might signify worsening organ dysfunction, although the link between cytokine production and nosocomial infection varied among studies.

INTERPRETATION

For functional immune profiling in sepsis, streamlined research methodologies are essential. This entails organizing cohorts based on microbial sources of sepsis, establishing standardized definitions of immunoparalysis, using consistent types and dosages of immune stimulants, adhering to uniform blood incubation conditions, and adopting consistent clinical outcomes.

N6-methyladenosine modification: Regulatory mechanisms and therapeutic potential in sepsis

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection and is characterized by multiple biological and clinical features. N6-methyladenosine (m6A) modification is the most common type of RNA modifications in eukaryotes and plays an important regulatory role in various biological processes. Recently, m6A modification has been found to be involved in the regulation of immune responses in sepsis. In addition, several studies have shown that m6A modification is involved in sepsis-induced multiple organ dysfunctions, including cardiovascular dysfunction, acute lung injury (ALI), acute kidney injury (AKI) and etc. Considering the complex pathogenesis of sepsis and the lack of specific therapeutic drugs, m6A modification may be the important bond in the pathophysiological process of sepsis and even therapeutic targets. This review systematically highlights the recent advances regarding the roles of m6A modification in sepsis and sheds light on their use as treatment targets for sepsis.

Inflammatory biomarkers to predict the prognosis of acute bacterial and viral infections

Mortality in acute infections is mostly associated with sepsis, defined as 'life-threatening organ dysfunction caused by a dysregulated host response to infection'. It remains challenging to identify the patients with increased mortality risk due to the high heterogeneity in the dysregulated host immune response and disease progression. Biomarkers reflecting different pathways involved in the inflammatory response might improve prediction of mortality risk (prognostic enrichment) among patients with acute infections by reducing heterogeneity of the host response, as well as suggest novel strategies for patient stratification and treatment (predictive enrichment) through precision medicine approaches. The predictive value of inflammatory biomarkers has been extensively investigated in bacterial infections and the recent COVID-19 pandemic caused an increased interest in inflammatory biomarkers in this viral infection. However, limited research investigated whether the prognostic potential of these biomarkers differs between bacterial and viral infections. In this narrative review, we provide an overview of the value of various inflammatory biomarkers for the prediction of mortality in bacterial and viral infections.

Extending the 'host response' paradigm from sepsis to cardiogenic shock: evidence, limitations and opportunities

Recent clinical and research efforts in cardiogenic shock (CS) have largely focussed on the restoration of the low cardiac output state that is the conditio sine qua non of the clinical syndrome. This approach has failed to translate into improved outcomes, and mortality has remained static at 30-50%. There is an unmet need to better delineate the pathobiology of CS to understand the observed heterogeneity of presentation and treatment effect and to identify novel therapeutic targets. Despite data in other critical illness syndromes, specifically sepsis, the role of dysregulated inflammation and immunity is hitherto poorly described in CS. High-dimensional molecular profiling, particularly through leukocyte transcriptomics, may afford opportunity to better characterise subgroups of patients with shared mechanisms of immune dysregulation. In this state-of-the-art review, we outline the rationale for considering molecular subtypes of CS. We describe how high-dimensional molecular technologies can be used to identify these subtypes, and whether they share biological features with sepsis and other critical illness states. Finally, we propose how the identification of molecular subtypes of patients may enrich future clinical trial design and identification of novel therapies for CS.

Obesity Alters cytokine signaling and gut microbiome in septic mice

Sepsis is a leading cause of mortality. Plasma cytokine levels may identify those at increased risk of mortality from sepsis. Our aim was to understand how obesity alters cytokine levels during early sepsis and its correlation with survival. Six-week-old C57BL/6 male mice were randomized to control (non-obese) or high fat diet (obese) for 5-7 weeks. Sepsis was induced by cecal ligation and perforation (CLP). Cytokine levels were measured from cheek bleeds 8 h after CLP, and mice were monitored for survival. Other cohorts were sacrificed 1 h after CLP for plasma and tissue. Septic obese mice had higher survival. At 8 h after sepsis, obese mice had higher adiponectin, leptin, and resistin but lower TNFα and IL-6 compared to non-obese mice. When stratified by 24-h survival, adipokines were not significantly different in obese and non-obese mice. TNFα and IL-6 were higher in non-obese, compared to obese, mice that died within 24 h of sepsis. Diet and to sepsis significantly impacted the cecal microbiome. IL-6 is a prognostic biomarker during early sepsis in non-obese and obese mice. A plausible mechanism for the survival difference in non-obese and obese mice may be the difference in gut microbiome and its evolution during sepsis.

Single-cell transcriptional gene signature analysis identifies IL-17 signaling pathway as the key pathway in sepsis

Sepsis is a multiple dysregulated systemic inflammatory response with high mortality and leads to public concern. This study was designed to identify possible critical pathways associated with sepsis clinical severity and outcome, which offer potential biomarkers and therapeutic targets for sepsis diagnosis and treatment. Single-cell transcriptome profiles of human peripheral blood mononuclear (PBMC) in the healthy control population and sepsis patients were downloaded from the sepsis database GSE167363 and performed quality control before subsequent analysis. The bulk-RNA sequencing of blood samples in the sepsis-associated databases GSE100159 and GSE133822 was also used to confirm the association between critical pathways and sepsis pathology after processing raw data. We found there was a total of 18 distinct clusters in PBMC of sepsis, which was identified by the t-SNE and UMAP dimension reduction analysis. Meanwhile, the main cell types including B, NK, T, and monocyte cells were identified via the cell maker website and the "Single R" package cell-type annotation analysis. Subsequently, GO and KEGG enrichment analysis of differential expression genes in each cluster found that DEGs between healthy control and sepsis patients were significantly enriched in the IL-17 signaling pathway in monocyte, NK, and T cells. Finally, GSE100159 and GSE133822 confirmed IL-17 signaling pathway-associated genes including IL-17R, TRAF6, RELB, TRAF5, CEBPB, JUNB, CXCL1, CXCL3, CXCL8, CXCR1, and CXCR2 were significantly up-regulated in sepsis blood samples compared with the age-matched healthy control population. Taken together, we concluded that the IL-17 signaling pathway serves as a significant potential mechanism of sepsis and provides a promising therapeutic target for sepsis treatment. This research will further deepen our understanding of sepsis development.

Optimizing Vasopressin Use and Initiation Timing in Septic Shock: A Narrative Review

TOPIC IMPORTANCE

This review discusses the rationale for vasopressin use, summarizes the results of clinical trials evaluating vasopressin, and focuses on the timing of vasopressin initiation to provide clinicians guidance for optimal adjunctive vasopressin initiation in patients with septic shock.

REVIEW FINDINGS

Patients with septic shock require vasoactive agents to restore adequate tissue perfusion. After norepinephrine, vasopressin is the suggested second-line adjunctive agent in patients with persistent inadequate mean arterial pressure. Vasopressin use in practice is heterogeneous likely because of inconsistent clinical trial findings, the lack of specific recommendations for when it should be used, and the high drug acquisition cost. Despite these limitations, vasopressin has demonstrated price inelastic demand, and its use in the United States has continued to increase. However, questions remain regarding optimal vasopressin use in patients with septic shock, particularly regarding patient selection and the timing of vasopressin initiation.

SUMMARY

Experimental studies evaluating the initiation timing of vasopressin in patients with septic shock are limited, and recent observational studies have revealed an association between vasopressin initiation at lower norepinephrine-equivalent doses or lower lactate concentrations and lower mortality.

Uncovering heterogeneity in sepsis: a comparative analysis of subphenotypes

PURPOSE

The heterogeneity in sepsis is held responsible, in part, for the lack of precision treatment. Many attempts to identify subtypes of sepsis patients identify those with shared underlying biology or outcomes. To date, though, there has been limited effort to determine overlap across these previously identified subtypes. We aimed to determine the concordance of critically ill patients with sepsis classified by four previously described subtype strategies.

METHODS

This secondary analysis of a multicenter prospective observational study included 522 critically ill patients with sepsis assigned to four previously established subtype strategies, primarily based on: (i) clinical data in the electronic health record (α, β, γ, and δ), (ii) biomarker data (hyper- and hypoinflammatory), and (iii-iv) transcriptomic data (Mars1-Mars4 and SRS1-SRS2). Concordance was studied between different subtype labels, clinical characteristics, biological host response aberrations, as well as combinations of subtypes by sepsis ensembles.

RESULTS

All four subtype labels could be adjudicated in this cohort, with the distribution of the clinical subtype varying most from the original cohort. The most common subtypes in each of the four strategies were γ (61%), which is higher compared to the original classification, hypoinflammatory (60%), Mars2 (35%), and SRS2 (54%). There was no clear relationship between any of the subtyping approaches (Cramer's V = 0.086-0.456). Mars2 and SRS1 were most alike in terms of host response biomarkers (p = 0.079-0.424), while other subtype strategies showed no clear relationship. Patients enriched for multiple subtypes revealed that characteristics and outcomes differ dependent on the combination of subtypes made.

CONCLUSION

Among critically ill patients with sepsis, subtype strategies using clinical, biomarker, and transcriptomic data do not identify comparable patient populations and are likely to reflect disparate clinical characteristics and underlying biology.

Biomarker Enrichment in Sepsis-Associated Acute Kidney Injury: Finding High-Risk Patients in the Intensive Care Unit

BACKGROUND

Sepsis-associated acute kidney injury (AKI) is a leading comorbidity in admissions to the intensive care unit. While a gold standard definition exists, it remains imperfect and does not allow for the timely identification of patients in the setting of critical illness. This review will discuss the use of biochemical and electronic biomarkers to allow for prognostic and predictive enrichment of patients with sepsis-associated AKI over and above the use of serum creatinine and urine output.

SUMMARY

Current data suggest that several biomarkers are capable of identifying patients with sepsis at risk for the development of severe AKI and other associated morbidity. This review discusses these data and these biomarkers in the setting of sub-phenotyping and endotyping sepsis-associated AKI. While not all these tests are widely available and some require further validation, in the near future we anticipate several new tools to help nephrologists and other providers better care for patients with sepsis-associated AKI.

KEY MESSAGES

Predictive and prognostic enrichment using both traditional biomarkers and novel biomarkers in the setting of sepsis can identify subsets of patients with either similar outcomes or similar pathophysiology, respectively. Novel biomarkers can identify kidney injury in patients without consensus definition AKI (e.g., changes in creatinine or urine output) and can predict other adverse outcomes (e.g., severe consensus definition AKI, inpatient mortality). Finally, emerging artificial intelligence and machine learning-derived risk models are able to predict sepsis-associated AKI in critically ill patients using advanced learning techniques and several laboratory and vital sign measurements.

Mapping the epigenomic landscape of human monocytes following innate immune activation reveals context-specific mechanisms driving endotoxin tolerance

BACKGROUND

Monocytes are key mediators of innate immunity to infection, undergoing profound and dynamic changes in epigenetic state and immune function which are broadly protective but may be dysregulated in disease. Here, we aimed to advance understanding of epigenetic regulation following innate immune activation, acutely and in endotoxin tolerant states.

METHODS

We exposed human primary monocytes from healthy donors (n = 6) to interferon-γ or differing combinations of endotoxin (lipopolysaccharide), including acute response (2 h) and two models of endotoxin tolerance: repeated stimulations (6 + 6 h) and prolonged exposure to endotoxin (24 h). Another subset of monocytes was left untreated (naïve). We identified context-specific regulatory elements based on epigenetic signatures for chromatin accessibility (ATAC-seq) and regulatory non-coding RNAs from total RNA sequencing.

RESULTS

We present an atlas of differential gene expression for endotoxin and interferon response, identifying widespread context specific changes. Across assayed states, only 24-29% of genes showing differential exon usage are also differential at the gene level. Overall, 19.9% (6,884 of 34,616) of repeatedly observed ATAC peaks were differential in at least one condition, the majority upregulated on stimulation and located in distal regions (64.1% vs 45.9% of non-differential peaks) within which sequences were less conserved than non-differential peaks. We identified enhancer-derived RNA signatures specific to different monocyte states that correlated with chromatin accessibility changes. The endotoxin tolerance models showed distinct chromatin accessibility and transcriptomic signatures, with integrated analysis identifying genes and pathways involved in the inflammatory response, detoxification, metabolism and wound healing. We leveraged eQTL mapping for the same monocyte activation states to link potential enhancers with specific genes, identifying 1,946 unique differential ATAC peaks with 1,340 expression associated genes. We further use this to inform understanding of reported GWAS, for example involving FCHO1 and coronary artery disease.

CONCLUSION

This study reports context-specific regulatory elements based on transcriptomic profiling and epigenetic signatures for enhancer-derived RNAs and chromatin accessibility in immune tolerant monocyte states, and demonstrates the informativeness of linking such elements and eQTL to inform future mechanistic studies aimed at defining therapeutic targets of immunosuppression and diseases.

Leveraging Data Science and Novel Technologies to Develop and Implement Precision Medicine Strategies in Critical Care

Precision medicine aims to identify treatments that are most likely to result in favorable outcomes for subgroups of patients with similar clinical and biological characteristics. The gaps for the development and implementation of precision medicine strategies in the critical care setting are many, but the advent of data science and multi-omics approaches, combined with the rich data ecosystem in the intensive care unit, offer unprecedented opportunities to realize the promise of precision critical care. In this article, the authors review the data-driven and technology-based approaches being leveraged to discover and implement precision medicine strategies in the critical care setting.

Acute Disorders of Consciousness in Pediatric Severe Sepsis and Organ Failure: Secondary Analysis of the Multicenter Phenotyping Sepsis-Induced Multiple Organ Failure Study

OBJECTIVES

Acute disorders of consciousness (DoC) in pediatric severe sepsis are associated with increased risk of morbidity and mortality. We sought to examine the frequency of and factors associated with DoC in children with sepsis-induced organ failure.

DESIGN

Secondary analysis of the multicenter Phenotyping Sepsis-Induced Multiple Organ Failure Study (PHENOMS).

SETTING

Nine tertiary care PICUs in the United States.

PATIENTS

Children less than 18 years old admitted to a PICU with severe sepsis and at least one organ failure during a PICU stay.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The primary outcome was frequency of DoC, defined as Glasgow Coma Scale (GCS) less than 12 in the absence of sedatives during an ICU stay, among children with severe sepsis and the following: single organ failure, nonphenotypeable multiple organ failure (MOF), MOF with one of the PHENOMS phenotypes (immunoparalysis-associated MOF [IPMOF], sequential liver failure-associated MOF, thrombocytopenia-associated MOF), or MOF with multiple phenotypes. A multivariable logistic regression analysis was performed to evaluate the association between clinical variables and organ failure groups with DoC. Of 401 children studied, 71 (18%) presented with DoC. Children presenting with DoC were older (median 8 vs 5 yr; p = 0.023), had increased hospital mortality (21% vs 10%; p = 0.011), and more frequently presented with both any MOF (93% vs 71%; p < 0.001) and macrophage activation syndrome (14% vs 4%; p = 0.004). Among children with any MOF, those presenting with DoC most frequently had nonphenotypeable MOF and IPMOF (52% and 34%, respectively). In the multivariable analysis, older age (odds ratio, 1.07; 95% CI, 1.01-1.12) and any MOF (3.22 [1.19-8.70]) were associated with DoC.

CONCLUSIONS

One of every five children with severe sepsis and organ failure experienced acute DoC during their PICU stay. Preliminary findings suggest the need for prospective evaluation of DoC in children with sepsis and MOF.

Sepsis heterogeneity

BACKGROUND

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection, with extremely high mortality. Notably, sepsis is a heterogeneous syndrome characterized by a vast, multidimensional array of clinical and biologic features, which has hindered advances in the therapeutic field beyond the current standards.

DATA SOURCES

We used PubMed to search the subject-related medical literature by searching for the following single and/or combination keywords: sepsis, heterogeneity, personalized treatment, host response, infection, epidemiology, mortality, incidence, age, children, sex, comorbidities, gene susceptibility, infection sites, bacteria, fungi, virus, host response, organ dysfunction and management.

RESULTS

We found that host factors (age, biological sex, comorbidities, and genetics), infection etiology, host response dysregulation and multiple organ dysfunctions can all result in different disease manifestations, progression, and response to treatment, which make it difficult to effectively treat and manage sepsis patients.

CONCLUSIONS

Herein, we have summarized contributing factors to sepsis heterogeneity, including host factors, infection etiology, host response dysregulation, and multiple organ dysfunctions, from the key elements of pathogenesis of sepsis. An in-depth understanding of the factors that contribute to the heterogeneity of sepsis will help clinicians understand the complexity of sepsis and enable researchers to conduct more personalized clinical studies for homogenous patients.

Prognostic biomarkers for sepsis mortality based on the literature and LC-MS-based metabolomics of sepsis patients

OBJECTIVES

The management of sepsis, a potentially lethal overreaction to infection, is limited by the lack of prognostic tools to guide its treatment. Our aim is to identify a novel metabolic biomarker panel for predicting sepsis mortality based on a literature review and liquid chromatography-mass spectrometry (LC-MS)-based metabolomics.

METHODS

In the literature, we found metabolomics biomarkers reported to predict sepsis mortality. We determined the classifications, reported frequency, and KEGG pathway enrichment of these markers. Using serum samples from 20 sepsis survivors and 20 non-survivors within 28 days after admission to the intensive care unit (ICU), we performed LC-MS-based metabolomics. Based on the literature review and metabolomics, a prognostic biomarker panel for sepsis was identified and its area under the curve (AUC) values was assessed.

RESULTS

Kynurenate, caffeine, and lysoPC 22:4 were selected as a prognostic biomarker panel for sepsis. The panel had an area under the curve (AUC) of 0.885 (95% CI, 0.694-1) evaluated by linear support vector machine (SVM) and 0.849 (0.699-1) by random forest (RF), which was higher than that of the Sequential Organ Failure Assessment (SOFA). A combination of kynurenate, caffeine, and lysoPC 22:4 and SOFA provided the best discriminating performance, with AUCs of 0.961 (0.878-1) for SVM and 0.916 (0.774-1) for RF.

CONCLUSIONS

The prognostic biomarker panel consisting of kynurenate, caffeine, and lysoPC 22:4 may aid in the identification of sepsis patients at a high risk of death, leading to personalized therapy in clinical practice that will improve sepsis survival.

A hypoxia- and lactate metabolism-related gene signature to predict prognosis of sepsis: discovery and validation in independent cohorts

BACKGROUND

High throughput gene expression profiling is a valuable tool in providing insight into the molecular mechanism of human diseases. Hypoxia- and lactate metabolism-related genes (HLMRGs) are fundamentally dysregulated in sepsis and have great predictive potential. Therefore, we attempted to build an HLMRG signature to predict the prognosis of patients with sepsis.

METHODS

Three publicly available transcriptomic profiles of peripheral blood mononuclear cells from patients with sepsis (GSE65682, E-MTAB-4421 and E-MTAB-4451, total n = 850) were included in this study. An HLMRG signature was created by employing Cox regression and least absolute shrinkage and selection operator estimation. The CIBERSORT method was used to analyze the abundances of 22 immune cell subtypes based on transcriptomic data. Metascape was used to investigate pathways related to the HLMRG signature.

RESULTS

We developed a prognostic signature based on five HLMRGs (ERO1L, SIAH2, TGFA, TGFBI, and THBS1). This classifier successfully discriminated patients with disparate 28-day mortality in the discovery cohort (GSE65682, n = 479), and consistent results were observed in the validation cohort (E-MTAB-4421 plus E-MTAB-4451, n = 371). Estimation of immune infiltration revealed significant associations between the risk score and a subset of immune cells. Enrichment analysis revealed that pathways related to antimicrobial immune responses, leukocyte activation, and cell adhesion and migration were significantly associated with the HLMRG signature.

CONCLUSIONS

Identification of a prognostic signature suggests the critical role of hypoxia and lactate metabolism in the pathophysiology of sepsis. The HLMRG signature can be used as an efficient tool for the risk stratification of patients with sepsis.