The End of “One Size Fits All” Sepsis Therapies: Toward an Individualized Approach

Clinical subtypes in critically ill patients with sepsis: validation and parsimonious classifier model development

BACKGROUND

The application of sepsis subtypes to enhance personalized medicine in critically ill patients is hindered by the lack of validation across diverse cohorts and the absence of a simple classification model. We aimed to validate the previously identified SENECA clinical sepsis subtypes in multiple large ICU cohorts, and to develop parsimonious classifier models for δ-type adjudication in clinical practice.

METHODS

Data from four cohorts between 2008 and 2023 were used to assign α, β, γ and δ-type in patients fulfilling the Sepsis-3 criteria using clinical variables: (I) The Molecular diAgnosis and Risk stratification of Sepsis (MARS, n = 2449), (II) a contemporary continuation of the MARS study (MARS2, n = 2445) (III) the Dutch National Intensive Care Evaluation registry (NICE, n = 28,621) and (IV) the Medical Information Mart for Intensive Care including (MIMIC-IV, n = 18,661). K-means clustering using clinical variables was conducted to assess the optimal number of classes and compared to the SENECA subtypes. Parsimonious models were built in the SENECA derivation cohort to predict subtype membership using logistic regression, and validated in MARS and MIMIC-IV.

RESULTS

Among 52.226 patients with sepsis, the subtype distribution in MARS, MARS2 and NICE was 2-6% for the α-type, 1-5% for the β-type, 49-65% for the γ-type and 26-48% for the δ-type compared to 33%, 27%, 27% and 13% in the original SENECA derivation cohort, whereas subtype distribution in MIMIC-IV was more similar at 25%, 24%, 27% and 25%, respectively. In-hospital mortality rates were significantly different between the four cohorts for α, γ and δ-type (p < 0.001). Method-based validation showed moderate overlap with the original subtypes in both MARS and MIMIC-IV. A parsimonious model for all four subtypes had moderate to low accuracy (accuracy 62.2%), while a parsimonious classifier model with 3 variables (aspartate aminotransferase, serum lactate, and bicarbonate) had excellent accuracy in predicting the δ-type patients from all other types in the derivation cohort and moderate accuracy in the validation cohorts (MARS: area under the receiver operator characteristic curve (AUC) 0.93, 95% CI [0.92-0.94], accuracy 85.5% [84.0-86.8%]; MIMIC-IV: AUC 0.86 [0.85-0.87], accuracy 82.9% [82.4-83.4%]).

CONCLUSIONS

The distribution and mortality rates of clinical sepsis subtypes varied between US and European cohorts. A three-variable model could accurately identify the δ-type sepsis patients.

Recent Progress in PDMS-Based Microfluidics Toward Integrated Organ-on-a-Chip Biosensors and Personalized Medicine

The organ-on-a-chip (OoC) technology holds significant promise for biosensors and personalized medicine by enabling the creation of miniature, patient-specific models of human organs. This review studies the recent advancements in the application of polydimethylsiloxane (PDMS) microfluidics for OoC purposes. It underscores the main fabrication technologies of PDMS microfluidic systems, such as photolithography, injection molding, hot embossing, and 3D printing. The review also highlights the crucial role of integrated biosensors within OoC platforms. These electrochemical, electrical, and optical sensors, integrated within the microfluidic environment, provide valuable insights into cellular behavior and drug response. Furthermore, the review explores the exciting potential of PDMS-based OoC technology for personalized medicine. OoC devices can forecast drug effectiveness and tailor therapeutic strategies for patients by incorporating patient-derived cells and replicating individual physiological variations, helping the healing process and accelerating recovery. This personalized approach can revolutionize healthcare by offering more precise and efficient treatment options. Understanding OoC fabrication and its applications in biosensors and personalized medicine can play a pivotal role in future implementations of multifunctional OoC biosensors.

Whole blood ratio of CDK1/CX3CR1 mRNA expression combined to lactate refines the prediction of ICU mortality in septic patients in the Sepsis-3 era: a proof-of-concept study

Background

Transcriptomics biomarkers have been widely used to predict mortality in patients with sepsis. However, the association between mRNA levels and outcomes shows substantial variability over the course of sepsis, limiting their predictive performance. We aimed to: (a) identify and validate an mRNA biomarker signature whose association with all-cause intensive care unit (ICU) mortality is consistent at several timepoints; and (b) evaluate how this mRNA signature could be used in association with lactate levels for predictive and prognostic enrichment in sepsis.

Methods

We conducted a gene expression analysis study at two timepoints (day 1 and day 2-3 following ICU admission) using microarray data from adult septic patients to identify candidate biomarkers predictive of all-cause ICU mortality. We validated mRNA biomarkers using reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) on an external validation cohort. The predictive performance of the mRNA biomarkers combination was assessed in association with lactate level to refine ICU mortality prediction.

Main results

Among 180 chips from 100 septic patients, we identified 39 upregulated and 2 downregulated differentially expressed genes (DEGs) in survivors vs. non-survivors, both at day 1 and days 2-3 following ICU admission. We combined CDK1, the hub gene of upregulated DEGs, and CX3CR1 and IL1b to compute expression ratios. The CDK1/CX3CR1 ratio had the best performance to predict all-cause ICU mortality, with an area under the ROC curve (AUROC) of 0.77 (95% confidence interval [CI] 0.88-0.66) at day 1 and of 0.82 (95% CI 0.91-0.72) at days 2-3 after ICU admission. This performance was better than that of each individual mRNA biomarker. In the external validation cohort, the predictive performance of the CDK1/CX3CR1 ratio, measured using RT-qPCR, was similar to that of lactate when measure at day 1, and higher when measured at days 2-3. Combining lactate levels and the CDK1/CX3CR1 ratio, we identify 3 groups of patients with an increasing risk of ICU-mortality, ranging from 9 to 60% with an intermediate-risk group mortality rate of 28%.

Conclusion

With stable predictive performance over the first 3 days following ICU admission, the CDK1/CX3CR1 ratio identifies three groups of septic patients with increasing ICU mortality risk. In combination with lactate, this novel biomarker strategy may be useful for sepsis patient stratification for personalized medicine trials and ICU management.

Use of extracorporeal blood purification therapies in sepsis: the current paradigm, available evidence, and future perspectives

BACKGROUND

Sepsis is the result of a dysregulated immune response to infection and is associated with acute organ dysfunction. The syndrome's complexity is contingent upon the underlying pathology and individual patient characteristics, including their immune response. The involvement of multiple organs and physiological functions adds complexity, with "organ cross-talk" emerging as a pivotal pathophysiological and clinical aspect. This narrative review to evaluate the rationale and available clinical evidence supporting the use of extracorporeal blood purification therapies as adjunctive therapy in patients with sepsis and septic shock.

MAIN BODY

A search of the PubMed, Embase, Web of Science and Scopus databases for relevant literature from August 2002 to May 2024 has been conducted. The search was performed using the terms: 1) "blood purification" or "hemadsorption" or "plasma exchange" AND 2) "sepsis" or "septic shock". Therefore the authors have focused our discussion on several key areas such as conducting well-designed trials, developing more personalized protocols, ensuring optimal management and monitoring.

CONCLUSIONS

Given the heterogeneity of patients with sepsis, conducting traditional randomized clinical trials in this domain can be a daunting task. However, statistical techniques such as Bayesian methods, propensity score analysis, and emulated clinical trials using clinical databases hold promise for enhancing comparability between the study groups. Indeed, to comprehend the clinical efficacy of extracorporeal blood purification techniques in patients with sepsis, it is imperative to assemble homogeneous groups of patients receiving uniform treatments. Clinical strategies should be individualized, signaling the end of the "one size fits all" approach in sepsis therapy and the need for personalized treatments.

Crossing Age Boundaries: The Unifying Potential of Presepsin in Sepsis Diagnosis Across Diverse Age Groups

Sepsis is a pervasive condition that affects individuals of all ages, with significant social and economic consequences. The early diagnosis of sepsis is fundamental for establishing appropriate treatment and is based on warning scores and clinical characteristics, with positive microbiological cultures being the gold standard. Research has yet to identify a single biomarker to meet this diagnostic demand. Presepsin is a molecule that has the potential as a biomarker for diagnosing sepsis. In this paper, we present a narrative review of the diagnostic and prognostic performance of presepsin in different age groups. Given its particularities, it is identified that presepsin is a potential biomarker for sepsis at all stages of life.

Shadows and lights in sepsis immunotherapy

INTRODUCTION

Sepsis remains a major global public health challenge. The host's response in sepsis involves both an exaggerated inflammatory reaction and immunosuppressive mechanisms. A better understanding of this response has shed light on the failure of anti-inflammatory therapies administered under the 'one size fits all' approach during the last decades.

AREAS COVERED

To date, patients' management has moved toward a comprehensive precision medicine approach that aims to personalize immunotherapy, whether anti-inflammatory or immunostimulatory. Large Prospective interventional randomized controlled trials validating this approach are about to start. A crucial prerequisite for these studies is to stratify patients based on biomarkers that will help defining the patients' immuno-inflammatory trajectory.

EXPERT OPINION

Some biomarkers are already available in routine clinical care, while improvements are anticipated through the standardized use of transcriptomics and other multi-omics technologies in this field. With these precautions in mind, it is reasonable to anticipate improvement in outcomes in sepsis.

Machine learning reveals the rules governing the efficacy of mesenchymal stromal cells in septic preclinical models

BACKGROUND

Mesenchymal Stromal Cells (MSCs) are the preferred candidates for therapeutics as they possess multi-directional differentiation potential, exhibit potent immunomodulatory activity, are anti-inflammatory, and can function like antimicrobials. These capabilities have therefore encouraged scientists to undertake numerous preclinical as well as a few clinical trials to access the translational potential of MSCs in disease therapeutics. In spite of these efforts, the efficacy of MSCs has not been consistent-as is reflected in the large variation in the values of outcome measures like survival rates. Survival rate is a resultant of complex cascading interactions that not only depends upon upstream experimental factors like dosage, time of infusion, type of transplant, etc.; but is also dictated, post-infusion, by intrinsic host specific attributes like inflammatory microniche including proinflammatory cytokines and alarmins released by the damaged host cells. These complex interdependencies make a researcher's task of designing MSC transfusion experiments challenging.

METHODS

In order to identify the rules and associated attributes that influence the final outcome (survival rates) of MSC transfusion experiments, we decided to apply machine learning techniques on manually curated data collected from available literature. As sepsis is a multi-faceted condition that involves highly dysregulated immune response, inflammatory environment and microbial invasion, sepsis can be an efficient model to verify the therapeutic effects of MSCs. We therefore decided to implement rule-based classification models on data obtained from studies involving interventions of MSCs in sepsis preclinical models.

RESULTS

The rules from the generated graph models indicated that survival rates, post-MSC-infusion, are influenced by factors like source, dosage, time of infusion, pre-Interleukin-6 (IL-6)/ Tumour Necrosis Factor- alpha (TNF-α levels, etc. CONCLUSION: This approach provides important information for optimization of MSCs based treatment strategies that may help the researchers design their experiments.

From immune dysregulation to organ dysfunction: understanding the enigma of Sepsis

Sepsis is a syndrome precipitated by immune dysregulation in response to infection, and represents a pivotal factor in global mortality attributed to diseases. The recent consensus delineates sepsis as a perilous state of organ dysfunction arising from the host's maladaptive reaction to infection. It masks the complexity and breadth of the immune mechanisms involved in sepsis, which is characterized by simultaneous hyperinflammation and immunosuppression. Sepsis is highly correlated with the dysregulation of immune response, which is mainly mediated by various immune cells and their interactions. This syndrome can lead to a plethora of complications, encompassing systemic inflammatory response, metabolic disturbances, infectious shock, MODS, and DIC. Furthermore, more research studies have been conducted on sepsis in the past few years. The pathological characteristics of sepsis have been improved or treated by targeting signaling pathways like NF-B, JAK-STAT, PI3K-Akt, and p38-MAPK. Combined drug therapy is better than single drug therapy for sepsis. This article will review the latest progress in the pathogenesis and treatment of sepsis.

Immunomodulatory drugs in sepsis: a systematic review and meta-analysis

Dysregulation of the host immune response has a central role in the pathophysiology of sepsis. There has been much interest in immunomodulatory drugs as potential therapeutic adjuncts in sepsis. We conducted a systematic review and meta-analysis of randomised controlled trials evaluating the safety and clinical effectiveness of immunomodulatory drugs as adjuncts to standard care in the treatment of adults with sepsis. Our primary outcomes were serious adverse events and all-cause mortality. Fifty-six unique, eligible randomised controlled trials were identified, assessing a range of interventions including cytokine inhibitors; anti-inflammatories; immune cell stimulators; platelet pathway inhibitors; and complement inhibitors. At 1-month follow-up, the use of cytokine inhibitors was associated with a decreased risk of serious adverse events, based on 11 studies involving 7138 patients (RR (95%CI) 0.95 (0.90-1.00), I2 = 0%). The only immunomodulatory drugs associated with an increased risk of serious adverse events were toll-like receptor 4 antagonists (RR (95%CI) 1.18 (1.04-1.34), I2 = 0% (two trials, 567 patients)). Based on 18 randomised controlled trials, involving 11,075 patients, cytokine inhibitors reduced 1-month mortality (RR (95%CI) 0.88 (0.78-0.98), I2 = 57%). Mortality reduction was also shown in the subgroup of 13 randomised controlled trials that evaluated anti-tumour necrosis factor α interventions (RR (95%CI) 0.93 (0.87-0.99), I2 = 0%). Anti-inflammatory drugs had the largest apparent effect on mortality at 2 months at any dose (two trials, 228 patients, RR (95%CI) 0.64 (0.51-0.80), I2 = 0%) and at 3 months at any dose (three trials involving 277 patients, RR (95%CI) 0.67 (0.55-0.81), I2 = 0%). These data indicate that, except for toll-like receptor 4 antagonists, there is no evidence of safety concerns for the use of immunomodulatory drugs in sepsis, and they may show some short-term mortality benefit for selected drugs.

Enhancing sepsis biomarker development: key considerations from public and private perspectives

Implementation of biomarkers in sepsis and septic shock in emergency situations, remains highly challenging. This viewpoint arose from a public-private 3-day workshop aiming to facilitate the transition of sepsis biomarkers into clinical practice. The authors consist of international academic researchers and clinician-scientists and industry experts who gathered (i) to identify current obstacles impeding biomarker research in sepsis, (ii) to outline the important milestones of the critical path of biomarker development and (iii) to discuss novel avenues in biomarker discovery and implementation. To define more appropriately the potential place of biomarkers in sepsis, a better understanding of sepsis pathophysiology is mandatory, in particular the sepsis patient's trajectory from the early inflammatory onset to the late persisting immunosuppression phase. This time-varying host response urges to develop time-resolved test to characterize persistence of immunological dysfunctions. Furthermore, age-related difference has to be considered between adult and paediatric septic patients. In this context, numerous barriers to biomarker adoption in practice, such as lack of consensus about diagnostic performances, the absence of strict recommendations for sepsis biomarker development, cost and resources implications, methodological validation challenges or limited awareness and education have been identified. Biomarker-guided interventions for sepsis to identify patients that would benefit more from therapy, such as sTREM-1-guided Nangibotide treatment or Adrenomedullin-guided Enibarcimab treatment, appear promising but require further evaluation. Artificial intelligence also has great potential in the sepsis biomarker discovery field through capability to analyse high volume complex data and identify complex multiparametric patient endotypes or trajectories. To conclude, biomarker development in sepsis requires (i) a comprehensive and multidisciplinary approach employing the most advanced analytical tools, (ii) the creation of a platform that collaboratively merges scientific and commercial needs and (iii) the support of an expedited regulatory approval process.

eQTLs identify regulatory networks and drivers of variation in the individual response to sepsis

Sepsis is a clinical syndrome of life-threatening organ dysfunction caused by a dysregulated response to infection, for which disease heterogeneity is a major obstacle to developing targeted treatments. We have previously identified gene-expression-based patient subgroups (sepsis response signatures [SRS]) informative for outcome and underlying pathophysiology. Here, we aimed to investigate the role of genetic variation in determining the host transcriptomic response and to delineate regulatory networks underlying SRS. Using genotyping and RNA-sequencing data on 638 adult sepsis patients, we report 16,049 independent expression (eQTLs) and 32 co-expression module (modQTLs) quantitative trait loci in this disease context. We identified significant interactions between SRS and genotype for 1,578 SNP-gene pairs and combined transcription factor (TF) binding site information (SNP2TFBS) and predicted regulon activity (DoRothEA) to identify candidate upstream regulators. Overall, these approaches identified putative mechanistic links between host genetic variation, cell subtypes, and the individual transcriptomic response to infection.

Joint modeling of monocyte HLA-DR expression trajectories predicts 28-day mortality in severe SARS-CoV-2 patients

The recent SarsCov2 pandemic has disrupted healthcare system notably impacting intensive care units (ICU). In severe cases, the immune system is dysregulated, associating signs of hyperinflammation and immunosuppression. In the present work, we investigated, using a joint modeling approach, whether the trajectories of cellular immunological parameters were associated with survival of COVID-19 ICU patients. This study is based on the REA-IMMUNO-COVID cohort including 538 COVID-19 patients admitted to ICU between March 2020 and May 2022. Measurements of monocyte HLA-DR expression (mHLA-DR), counts of neutrophils, of total lymphocytes, and of CD4+ and CD8+ subsets were performed five times during the first month after ICU admission. Univariate joint models combining survival at day 28 (D28), hospital discharge and longitudinal analysis of those biomarkers' kinetics with mixed-effects models were performed prior to the building of a multivariate joint model. We showed that a higher mHLA-DR value was associated with a lower risk of death. Predicted mHLA-DR nadir cutoff value that maximized the Youden index was 5414 Ab/C and led to an AUC = 0.70 confidence interval (95%CI) = [0.65; 0.75] regarding association with D28 mortality while dynamic predictions using mHLA-DR kinetics until D7, D12 and D20 showed AUCs of 0.82 [0.77; 0.87], 0.81 [0.75; 0.87] and 0.84 [0.75; 0.93]. Therefore, the final joint model provided adequate discrimination performances at D28 after collection of biomarker samples until D7, which improved as more samples were collected. After severe COVID-19, decreased mHLA-DR expression is associated with a greater risk of death at D28 independently of usual clinical confounders.

Monitoring monocyte HLA-DR expression and CD4 + T lymphocyte count in dexamethasone-treated severe COVID-19 patients

BACKGROUND

A 10-day dexamethasone regimen has emerged as the internationally adopted standard-of-care for severe COVID-19 patients. However, the immune response triggered by SARS-CoV-2 infection remains a complex and dynamic phenomenon, leading to various immune profiles and trajectories. The immune status of severe COVID-19 patients following complete dexamethasone treatment has yet to be thoroughly documented.

RESULTS

To analyze monocyte HLA-DR expression (mHLA-DR) and CD4 + T lymphocyte count (CD4) in critically ill COVID-19 patients after a dexamethasone course and evaluate their association with 28-day ICU mortality, adult COVID-19 patients (n = 176) with an ICU length of stay of at least 10 days and under dexamethasone treatment were included. Associations between each biomarker value (or in combination) measured at day 10 after ICU admission and 28-day mortality in ICU were evaluated. At day 10, the majority of patients presented decreased values of both parameters. A significant association between low mHLA-DR and 28-day mortality was observed. This association remained significant in a multivariate analysis including age, comorbidities or pre-existing immunosuppression (adjusted Hazard ratio (aHR) = 2.86 [1.30-6.32], p = 0.009). Similar results were obtained with decreased CD4 + T cell count (aHR = 2.10 [1.09-4.04], p = 0.027). When combining these biomarkers, patients with both decreased mHLA-DR and low CD4 presented with an independent and significant elevated risk of 28-day mortality (i.e., 60%, aHR = 4.83 (1.72-13.57), p = 0.001).

CONCLUSIONS

By using standardized immunomonitoring tools available in clinical practice, it is possible to identify a subgroup of patients at high risk of mortality at the end of a 10-day dexamethasone treatment. This emphasizes the significance of integrating immune monitoring into the surveillance of intensive care patients in order to guide further immumodulation approaches.

Efficacy and Safety of Umbilical Cord-Derived Mesenchymal Stromal Cell Therapy in Preclinical Models of Sepsis: A Systematic Review and Meta-analysis

BACKGROUND

In preclinical studies, mesenchymal stromal cells (MSCs), including umbilical cord-derived MSCs (UC-MSCs), demonstrate the ability to modulate numerous pathophysiological processes related to sepsis; however, a systematic synthesis of the literature is needed to assess the efficacy of UC-MSCs for treating sepsis.

OBJECTIVE

To examine the effects of UC-MSCs on overall mortality (primary outcome) as well as on organ dysfunction, coagulopathy, endothelial permeability, pathogen clearance, and systemic inflammation (secondary outcomes) at prespecified time intervals in preclinical models of sepsis.

METHODS

A systematic search was conducted on Embase, Ovid MEDLINE, and Web of Science up to June 20, 2023. Preclinical controlled studies using in vivo sepsis models with systemic UC-MSC administration were included. Meta-analyses were conducted and expressed as odds ratios (OR) and ratios of the weighted means with 95% CI for categorical and continuous data, respectively. Risk of bias was assessed with the SYRCLE tool.

RESULTS

Twenty-six studies (34 experiments, n = 1258 animals) were included in this review. Overall mortality was significantly reduced with UC-MSC treatment as compared to controls (OR: 0.26, 95% CI: 0.18-0.36). At various prespecified time intervals, UC-MSCs reduced surrogate measures of organ dysfunction related to the kidney, liver, and lung; reduced coagulopathy and endothelial permeability; and enhanced pathogen clearance from multiple sites. UC-MSCs also modulated systemic inflammatory mediators. No studies were rated as low risk across all SYCLE domains.

CONCLUSIONS

These results demonstrate the efficacy of UC-MSC treatment in preclinical sepsis models and highlight their potential as a therapeutic intervention for septic shock.

DIFFERENTIAL SIGNALING EFFECTS OF ESCHERICHIA COLI AND STAPHYLOCOCCUS AUREUS IN HUMAN WHOLE BLOOD INDICATE DISTINCT REGULATION OF THE NRF2 PATHWAY

ABSTRACT

Escherichia coli and Staphylococcus aureus are two of the most common bacterial species responsible for sepsis. While it is observed that they have disparate clinical phenotypes, the signaling differences elicited by each bacteria that drive this variance remain unclear. Therefore, we used human whole blood exposed to heat-killed E. coli or S. aureus and measured the transcriptomic signatures. Relative to unstimulated control blood, heat-killed bacteria exposure led to significant dysregulation (upregulated and downregulated) of >5,000 genes for each experimental condition, with a slight increase in gene alterations by S. aureus. While there was significant overlap regarding proinflammatory pathways, Gene Ontology overrepresentation analysis of the most altered genes suggested biological processes like macrophage differentiation and ubiquinone biosynthesis were more unique to heat-killed S. aureus, compared with heat-killed E. coli exposure. Using Ingenuity Pathway Analysis, it was demonstrated that nuclear factor erythroid 2-related factor 2 signaling, a main transcription factor in antioxidant responses, was predominately upregulated in S. aureus exposed blood relative to E. coli. Furthermore, the use of pharmacologics that preferentially targeted the nuclear factor erythroid 2-related factor 2 pathway led to differential cytokine profiles depending on the type of bacterial exposure. These findings reveal significant inflammatory dysregulation between E. coli and S. aureus and provide insight into the targeting of unique pathways to curb bacteria-specific responses.

Decrease in Mortality after the Implementation of a Hospital Model to Improve Performance in Sepsis Care: Princess Sepsis Code

Sepsis is a time-dependent disease whose prognosis is influenced by early diagnosis and therapeutic measures. Mortality from sepsis remains high, and for this reason, the guidelines of the Surviving Sepsis Campaign recommend establishing specific care programs aimed at patients with sepsis. We present the results of the application of a hospital model to improve performance in sepsis care, called Princess Sepsis Code, with the aim of reducing mortality. A retrospective study was conducted using clinical, epidemiological, and outcome variables in patients diagnosed with sepsis from 2015 to 2022. A total of 2676 patients were included, 32% of whom required admission to the intensive care unit, with the most frequent focus of the sepsis being abdominal. Mortality in 2015, at the beginning of the sepsis code program, was 24%, with a declining rate noted over the study period, with mortality reaching 17% in 2022. In the multivariate analysis, age > 70 years, respiratory rate > 22 rpm, deterioration in the level of consciousness, serum lactate > 2 mmol/L, creatinine > 1.6 mg/dL, and the focus of the sepsis were identified as variables independently related to mortality. The implementation of the Princess Sepsis Code care model reduces the mortality of patients exhibiting sepsis and septic shock.

Continuous renal replacement therapy with oXiris® in patients with hematologically malignant septic shock: A retrospective study

BACKGROUND

The mortality rate from septic shock in patients with hematological malignancies (HMs) remains significantly higher than that in patients without HMs. A longer resuscitation time would definitely be harmful because of the irreversibly immunocompromised status of the patients. Shortening the resuscitation time through continuous renal replacement therapy (CRRT) with oXiris® would be an attractive strategy in managing such patients.

AIM

To explore the effects of CRRT and oXiris® in shortening the resuscitation time and modifying the host response by reducing inflammation mediator levels.

METHODS

Forty-five patients with HM were diagnosed with septic shock and underwent CRRT between 2018 and 2022. Patients were divided into two groups based on the hemofilter used for CRRT (oXiris® group, n = 26; M150 group, n = 19). We compared the number of days of negative and total fluid balance after 7 d of CRRT between the groups. The heart rate, norepinephrine dose, Sequential Organ Failure Assessment (SOFA) score, and blood lactic acid levels at different time points in the two groups were also compared. Blood levels of inflammatory mediators in the 26 patients in the oXiris® group were measured to further infer the possible mechanism.

RESULTS

The average total fluid balance after 7 d of CRRT in the oXiris® group was significantly lower than that of patients in the M150 hemofilter group. The SOFA scores of patients after CRRT with oXiris® therapy were significantly lower than those before treatment on day 1 (d1), d3 and d7 after CRRT; these parameters were also significantly lower than those of the control group on d7. The lac level after oXiris® therapy was significantly lower than that before treatment on d3 and d7 after CRRT. There were no significant differences in the above parameters between the two groups at the other time points. In the oXiris® group, procalcitonin levels decreased on d7, whereas interleukin-6 and tumor necrosis factor levels decreased significantly on d3 and d7 after treatment.

CONCLUSION

CRRT with oXiris® hemofilter may improve hemodynamics by reducing inflammatory mediators and playing a role in shortening the resuscitation period and decreasing total fluid balance in the resuscitation phases.

Inflammatory phenotypes may be more important than age and comorbidities in predicting clinical outcomes in hospitalised patients with COVID-19

Objectives

In critically ill patients with COVID-19, distinct hyperinflammatory and hypoinflammatory phenotypes have been described, with different outcomes and responses to therapy. We investigated if similar phenotypes exist in non-severe illness.

Methods

Consecutive patients with polymerase chain reaction (PCR) confirmed SARS-CoV-2 were examined. Baseline demographics and laboratory investigations were tabulated, including serum C-reactive protein. Patients were divided into those who were hyperinflammatory (defined as C-reactive protein >17 mg/l) or hypoinflammatory. Adverse outcomes, defined as requiring oxygenation, intensive care, or death, were recorded during the hospital stay. Clinical characteristics and outcomes were compared.

Results

Of the 1781 patients examined, 276 (15.5%) had a hyperinflammatory phenotype. They were older (51.8 ± 17.2 vs 40.3 ± 13.8 years, P <0.001), had a lower PCR cycle threshold (PCR cycle threshold value 19.3 ± 6.3 vs 22.7 ± 15.4, P = 0.025) at presentation, and more medical comorbidities. The hyperinflammatory phenotype was independently associated with adverse clinical outcomes, even after adjusting for age, medical history and viral load on multivariable analyses (adjusted odds ratio 5.78, 95% confidence interval 2.86-11.63).

Conclusion

Even in non-severe COVID-19, there are distinct hyper- and hypoinflammatory phenotypes, with the hyperinflammatory phenotype strongly associated with adverse clinical outcomes, that could be distinguished with a simple biomarker.

Clinical Sepsis Phenotypes in Critically Ill Patients

Sepsis, defined as the life-threatening dysregulated host response to an infection leading to organ dysfunction, is considered as one of the leading causes of mortality worldwide, especially in intensive care units (ICU). Moreover, sepsis remains an enigmatic clinical syndrome, with complex pathophysiology incompletely understood and a great heterogeneity both in terms of clinical expression, patient response to currently available therapeutic interventions and outcomes. This heterogeneity proves to be a major obstacle in our quest to deliver improved treatment in septic critical care patients; thus, identification of clinical phenotypes is absolutely necessary. Although this might be seen as an extremely difficult task, nowadays, artificial intelligence and machine learning techniques can be recruited to quantify similarities between individuals within sepsis population and differentiate them into distinct phenotypes regarding not only temperature, hemodynamics or type of organ dysfunction, but also fluid status/responsiveness, trajectories in ICU and outcome. Hopefully, we will eventually manage to determine both the subgroup of septic patients that will benefit from a therapeutic intervention and the correct timing of applying the intervention during the disease process.

Defining critical illness using immunological endotypes in patients with and without sepsis: a cohort study

BACKGROUND

Sepsis is a heterogenous syndrome with limited therapeutic options. Identifying immunological endotypes through gene expression patterns in septic patients may lead to targeted interventions. We investigated whether patients admitted to a surgical intensive care unit (ICU) with sepsis and with high risk of mortality express similar endotypes to non-septic, but still critically ill patients using two multiplex transcriptomic metrics obtained both on admission to a surgical ICU and at set intervals.

METHODS

We analyzed transcriptomic data from 522 patients in two single-site, prospective, observational cohorts admitted to surgical ICUs over a 5-year period ending in July 2020. Using an FDA-cleared analytical platform (nCounter FLEX^®, NanoString, Inc.), we assessed a previously validated 29-messenger RNA transcriptomic classifier for likelihood of 30-day mortality (IMX-SEV-3) and a 33-messenger RNA transcriptomic endotype classifier. Clinical outcomes included all-cause mortality, development of chronic critical illness, and secondary infections. Univariate and multivariate analyses were performed to assess for true effect and confounding.

RESULTS

Sepsis was associated with a significantly higher predicted and actual hospital mortality. At enrollment, the predominant endotype for both septic and non-septic patients was adaptive, though with significantly different distributions. Inflammopathic and coagulopathic septic patients, as well as inflammopathic non-septic patients, showed significantly higher frequencies of secondary infections compared to those with adaptive endotypes (p < 0.01). Endotypes changed during ICU hospitalization in 57.5% of patients. Patients who remained adaptive had overall better prognosis, while those who remained inflammopathic or coagulopathic had worse overall outcomes. For severity metrics, patients admitted with sepsis and a high predicted likelihood of mortality showed an inflammopathic (49.6%) endotype and had higher rates of cumulative adverse outcomes (67.4%). Patients at low mortality risk, whether septic or non-septic, almost uniformly presented with an adaptive endotype (100% and 93.4%, respectively).

CONCLUSION

Critically ill surgical patients express different and evolving immunological endotypes depending upon both their sepsis status and severity of their clinical course. Future studies will elucidate whether endotyping critically ill, septic patients can identify individuals for targeted therapeutic interventions to improve patient management and outcomes.

Defining critical illness using immunological endotypes in patients with and without of sepsis: A cohort study

Background: Sepsis is a heterogenous syndrome with limited therapeutic options. Identifying characteristic gene expression patterns, or endotypes, in septic patients may lead to targeted interventions. We investigated whether patients admitted to a surgical ICU with sepsis and with high risk of mortality express similar endotypes to non-septic, but still critically ill patients using two multiplex transcriptomic metrics obtained both on admission to a surgical intensive care unit (ICU) and at set intervals. Methods: We analyzed transcriptomic data from 522 patients in two single-site, prospective, observational cohorts admitted to surgical ICUs over a 5-year period ending in July 2020 . Using an FDA-cleared analytical platform (nCounter FLEX ^® , NanoString, Inc.), we assessed a previously validated 29-messenger RNA transcriptomic classifier for likelihood of 30-day mortality (IMX-SEV-3) and a 33-messenger RNA transcriptomic endotype classifier. Clinical outcomes included all-cause (in-hospital, 30-, 90-day) mortality, development of chronic critical illness (CCI), and secondary infections. Univariate and multivariate analyses were performed to assess for true effect and confounding. Results: Sepsis was associated with a significantly higher predicted and actual hospital mortality. At enrollment, the predominant endotype for both septic and non-septic patients was adaptive , though with significantly different distributions. Inflammopathic and coagulopathic septic patients, as well as inflammopathic non-septic patients, showed significantly higher frequencies of secondary infections compared to those with adaptive endotypes (p<0.01). Endotypes changed during ICU hospitalization in 57.5% of patients. Patients who remained adaptive had overall better prognosis, while those who remained inflammopathic or coagulopathic had worse overall outcomes. For severity metrics, patients admitted with sepsis and a high predicted likelihood of mortality showed an inflammopathic (49.6%) endotype and had higher rates of cumulative adverse outcomes (67.4%). Patients at low mortality risk, whether septic or non-septic, almost uniformly presented with an adaptive endotype (100% and 93.4%, respectively). Conclusion : Critically ill surgical patients express different and evolving immunological endotypes depending upon both their sepsis status and severity of their clinical course. Future studies will elucidate whether endotyping critically ill, septic patients can identify individuals for targeted therapeutic interventions to improve patient management and outcomes.

Treatment Advances in Sepsis and Septic Shock: Modulating Pro- and Anti-Inflammatory Mechanisms

Sepsis is currently defined as a life-threatening organ dysfunction caused by a dysregulated host response to infection, and it affects over 25 million people every year. Even more severe, septic shock is a subset of sepsis defined by persistent hypotension, and hospital mortality rates are higher than 40%. Although early sepsis mortality has greatly improved in the past few years, sepsis patients who survive the hyperinflammation and subsequent organ damage often die from long-term complications, such as secondary infection, and despite decades of clinical trials targeting this stage of the disease, currently, no sepsis-specific therapies exist. As new pathophysiological mechanisms have been uncovered, immunostimulatory therapy has emerged as a promising path forward. Highly investigated treatment strategies include cytokines and growth factors, immune checkpoint inhibitors, and even cellular therapies. There is much to be learned from related illnesses, and immunotherapy trials in oncology, as well as the recent COVID-19 pandemic, have greatly informed sepsis research. Although the journey ahead is a long one, the stratification of patients according to their immune status and the employment of combination therapies represent a hopeful way forward.

How I personalize fluid therapy in septic shock?

During septic shock, fluid therapy is aimed at increasing cardiac output and improving tissue oxygenation, but it poses two problems: it has inconsistent and transient efficacy, and it has many well-documented deleterious effects. We suggest that there is a place for its personalization according to the patient characteristics and the clinical situation, at all stages of circulatory failure. Regarding the choice of fluid for volume expansion, isotonic saline induces hyperchloremic acidosis, but only for very large volumes administered. We suggest that balanced solutions should be reserved for patients who have already received large volumes and in whom the chloremia is rising. The initial volume expansion, intended to compensate for the constant hypovolaemia in the initial phase of septic shock, cannot be adapted to the patient's weight only, as suggested by the Surviving Sepsis Campaign, but should also consider potential absolute hypovolemia induced by fluid losses. After the initial fluid infusion, preload responsiveness may rapidly disappear, and it should be assessed. The choice between tests used for this purpose depends on the presence or absence of mechanical ventilation, the monitoring in place and the risk of fluid accumulation. In non-intubated patients, the passive leg raising test and the mini-fluid challenge are suitable. In patients without cardiac output monitoring, tests like the tidal volume challenge, the passive leg raising test and the mini-fluid challenge can be used as they can be performed by measuring changes in pulse pressure variation, assessed through an arterial line. The mini-fluid challenge should not be repeated in patients who already received large volumes of fluids. The variables to assess fluid accumulation depend on the clinical condition. In acute respiratory distress syndrome, pulmonary arterial occlusion pressure, extravascular lung water and pulmonary vascular permeability index assess the risk of worsening alveolar oedema better than arterial oxygenation. In case of abdominal problems, the intra-abdominal pressure should be taken into account. Finally, fluid depletion in the de-escalation phase is considered in patients with significant fluid accumulation. Fluid removal can be guided by preload responsiveness testing, since haemodynamic deterioration is likely to occur in patients with a preload dependent state.

The double sides of NLRP3 inflammasome activation in sepsis

Sepsis is defined as a life-threatening organ dysfunction induced by a dysregulated host immune response to infection. Immune response induced by sepsis is complex and dynamic. It is schematically described as an early dysregulated systemic inflammatory response leading to organ failures and early deaths, followed by the development of persistent immune alterations affecting both the innate and adaptive immune responses associated with increased risk of secondary infections, viral reactivations, and late mortality. In this review, we will focus on the role of NACHT, leucin-rich repeat and pyrin-containing protein 3 (NLRP3) inflammasome in the pathophysiology of sepsis. NLRP3 inflammasome is a multiproteic intracellular complex activated by infectious pathogens through a two-step process resulting in the release of the pro-inflammatory cytokines IL-1β and IL-18 and the formation of membrane pores by gasdermin D, inducing a pro-inflammatory form of cell death called pyroptosis. The role of NLRP3 inflammasome in the pathophysiology of sepsis can be ambivalent. Indeed, although it might protect against sepsis when moderately activated after initial infection, excessive NLRP3 inflammasome activation can induce dysregulated inflammation leading to multiple organ failure and death during the acute phase of the disease. Moreover, this activation might become exhausted and contribute to post-septic immunosuppression, driving impaired functions of innate and adaptive immune cells. Targeting the NLRP3 inflammasome could thus be an attractive option in sepsis either through IL-1β and IL-18 antagonists or through inhibition of NLRP3 inflammasome pathway downstream components. Available treatments and results of first clinical trials will be discussed.

Sepsis and infection: Two words that should not be confused

The underlying cause of sepsis is a dysregulated host response to infection, leading to multiple organ failure. Identifying sepsis is crucial because of the associated pathophysiological, practical, and therapeutic implications, which will determine where and how the patient should be managed. In the absence of an end-of-life decision to limit therapies, the patient should be admitted to the intensive care unit immediately. Importantly, not all patients with sepsis are the same and being able to better characterize them is important. The future will focus on phenotypes to characterize critically ill patients, with or without infection, to enable more appropriate targeting of therapeutic interventions.

Antithrombin as Therapeutic Intervention against Sepsis-Induced Coagulopathy and Disseminated Intravascular Coagulation: Lessons Learned from COVID-19-Associated Coagulopathy

Recent research has contributed significantly to our understanding of the pathogenesis of acute disseminated intravascular coagulation. COVID-19 can be considered as a new underlying condition of disseminated intravascular coagulation. In this narrative review, current evidence is presented regarding biomarker differences between sepsis-induced and COVID-19-associated coagulopathies, supporting the importance of acquired antithrombin deficiency in the early differential diagnosis of septic coagulopathy and its potential impact on treatment with endogenous anticoagulants. Establishing new scoring systems for septic coagulopathy in combination with endogenous anticoagulant biomarker activities may allow for the identification of those in the heterogeneous population of sepsis patients who are more likely to benefit from targeted specific treatment interventions.