Biomarkers for sepsis: more than just fever and leukocytosis-a narrative review

Identification of lethality-related m7G methylation modification patterns and the regulatory features of immune microenvironment in sepsis

Objectives

N7-methylguanosine (m7G) modification is closely related to the occurrence of human diseases, but its roles in sepsis remain unclear. This study aimed to explore the patterns of lethality-related m7G regulatory factor-mediated RNA methylation modification and immune microenvironment regulatory features in sepsis.

Methods

Three sepsis-related datasets (E-MTAB-4421 and E-MTAB-4451 as training sets and GSE185263 as a validation set) were collected, and differentially expressed m7G-related genes were analyzed between survivors and non-survivors. Lethality-related m7G signature genes were then screened using machine learning methods, followed by the construction of a survival recognition model. Additionally, differences in immune cell distribution were determined and differentially expressed genes (DEGs) between different subtypes were analyzed. Weighted gene co-expression network analysis (WGCNA) was used to select important modules and related hub genes.

Results

In total, 10 differentially expressed m7G-related genes were identified between the survivors and non-survivors, and after further analysis, EIF4G3, EIF4E3, NSUN2, NUDT4, and GEMIN5 were identified as the optimal lethality-related m7G genes. A survival status diagnostic model was then constructed with a combined AUC of 0.678. Fifteen types of immune cells were significantly different between survivors and non-survivors. Sepsis samples were classified into two subtypes, with 22 types of immune cells showing significant differences. Subsequently, 1707 DEGs were identified between the two subtypes, which were significantly enriched in 91 GO terms and 16 KEGG pathways. Finally, the green module with |correlation| > 0.3 was found to be closely related to the subtypes and survival status; further, the top10 hub genes were obtained.

Conclusion

The constructed survival status diagnostic model based on the five lethality-related m7G signature genes may help predict the survival status of patients, and the 10 hub genes obtained may be potential therapeutic targets for sepsis.

Novel applications of metformin in the treatment of septic myocardial injury based on metabolomics and network pharmacology

BACKGROUND

While metformin has shown promise in treating septic myocardial injury (SMI), its underlying mechanisms and impact on metabolic disturbances remain poorly understood.

METHODS

This study employed an integrated approach of metabolomics and network pharmacology to identify key targets and pathways through which metformin may act against SMI. Findings were validated using a lipopolysaccharide (LPS)-induced mouse model.

RESULTS

Metformin was found to counter myocardial metabolic disruptions, indicated by the reversal of 49 metabolites primarily involved in purine metabolism, pantothenate and CoA biosynthesis, and histidine metabolism. In vivo, metformin significantly improved survival rates and cardiac function, reduced cardiomyocyte apoptosis, and inhibited inflammation and oxidative stress in LPS-induced mice. Integrated analyses identified 27 potential targets for metformin in SMI treatment. KEGG pathway analysis revealed significant enrichment in TNF, HIF-1, IL-17, and PI3K/AKT signaling pathways, while protein-protein interaction analysis pinpointed ten core targets, including IL6, IL1B, CCL2, CASP3, MMP9, HIF1A, IGF1, NOS3, MMP2, and LEP. Molecular docking and dynamics simulations demonstrated metformin's high affinity for these core targets. Further, RT-qPCR and Western blot analyses confirmed that metformin modulates core target expression to mitigate SMI. Notably, our data underscore the importance of PI3K/AKT and MMP2/MMP9 signaling pathways in SMI therapy.

CONCLUSION

This study elucidates the metabolic and molecular mechanisms of metformin in SMI treatment, supporting its potential repurposing for SMI.

Affinity-based 3D-printed microfluidic chip for clinical sepsis detection with CD69, CD64, and CD25

Sepsis is a life-threatening immune response to infection in the body, eventually resulting in fatal organ failure. Current methods utilize blood cultures and quick-Sequential-Organ-Failure-Assessment (qSOFA), but there is a need for more accurate and time-sensitive diagnostic methods to improve survival rates. We present a 3D-printed microfluidic chip that bioconjugates antibodies CD69, CD64, and CD25 to channel surfaces to capture sepsis cells in blood samples and validate it with clinical samples (n = 125 septic, n = 10 healthy). Other variables were taken such as healthy volunteer blood samples and patient demographics to validate and confirm our device's diagnostic ability. Statistical differences were found between healthy volunteer and sepsis patient antigen cell counts (CD69 p-value < 0.001, CD64 p-value < 0.004, CD25 p-value < 0.0009), and were confirmed using principal component analysis. Demographics such as length of stay, age, culture results, and need for surgery also factored into sepsis detection on a smaller scale than the antigen cell counts. The receiver operating characteristic (ROC) analysis showed an area under the curve (AUC) of 0.989, 0.988, and 0.992 for CD69, CD64, and CD25, respectively, and a combined biomarker panel of 0.997. Overall, the device performed within a shorter time frame of 4 h compared to standard blood culture tests and was validated for use in detecting sepsis in patients.

Biomarkers Unveiling the Interplay of Mind, Nervous System, and Immunity

The field of psychoneuroimmunology has significantly expanded in the last few decades and so has our understanding of the bidirectional communications between the immune and central nervous systems (CNS). There is a preponderance of evidence supporting the fact that immunological pathways and neuroinflammation are involved in the pathophysiology of multiple neurological and mental health conditions. In this chapter, we have explored various neuroimmunological biomarkers involved in these pathways, responsible for developing and perpetuating different neuropsychiatric disorders. This chapter will examine inflammatory biomarkers and those associated with intestinal homeostasis, blood-brain barrier (BBB) permeability, glial cells, and neuronal injury. A range of tests has been developed to evaluate these markers, and we will also explore the existing methods currently employed for these techniques. Further studies of these inflammatory and neurological markers are needed to support their utility as biomarkers for diagnosis and prognosis and to inform treatment strategies for various neuropsychiatric disorders.

Relationship between serum Midkine and Omentin-1 levels and the severity of sepsis in patients and their prognostic value

To explore the relationship between serum levels of midkine and omentin-1 and the severity of sepsis in patients, and their prognostic value. A retrospective analysis was conducted on the clinical data of 180 sepsis patients. According to the severity of the patient's condition, they were separated into sepsis group (n = 76), severe sepsis group (n = 59), and sepsis shock group (n = 45). Based on the survival within 28 days of admission, they were grouped into survivors group (n = 128) and nonsurvivors group (n = 52). The serum Midkine level and APACHE II score in the sepsis shock group were higher than those in the severe sepsis group and sepsis group, while the Omentin-1 level was lower than that in the severe sepsis group and sepsis group (p < 0.05). The serum Midkine level and APACHE II score in the severe sepsis group were higher than those in the sepsis group, while the Omentin-1 level was lower than that in the sepsis group (p < 0.05). The Midkine and APACHE II score in the nonsurvivors group was higher than those in the survivors group, while the Omentin-1 score was lower than that in the survivors group (p < 0.05). Midkine and APACHE II score were independent risk factors for the prognosis of sepsis patients, while Omentin-1 was a protective factor for the prognosis of sepsis patients (p < 0.05). The AUC of the combined prediction of serum Midkine and Ommentin-1 for the prognosis of sepsis patients was 0.880, with a sensitivity of 90.38% and a specificity of 72.66%. The combined prediction of serum Midkine and Ommentin-1 was better than that of individual prediction of Midkine and Ommentin-1. Serum Midkine is highly expressed and Omentin-1 is lowly expressed in sepsis patients, and the combination of the two has a high predictive power for the prognosis of sepsis patients.

Investigating the potential mechanism of Pioglitazone in Sepsis-Related brain injury through transcriptomics

Sepsis-related brain injury (SRBI) refers to brain dysfunction and structural damage caused by sepsis, which is characterized by inflammation, oxidative stress, and destruction of the blood-brain barrier. Pioglitazone is a PPAR-γ agonist in which PPAR-γ acts as an inflammatory modulator, determining the relationship between PPAR-γ and SRBI and inflammatory state is critical for the disease. This study aimed to construct a drug-target-disease network for SRBI and Pioglitazone based on network pharmacology, and to investigate the therapeutic effect and potential mechanism of Pioglitazone in SRBI induced by lipopolysaccharide (LPS) in rats through transcriptomics. To establish a rat Model of SRBI by intraperitoneal injection of LPS (10 mg/kg): SD rats were divided into Control, Model (LPS), Pioglitazone, (LPS + Pioglitazone) and GW9662 group (LPS+GW9662). The effects and potential mechanisms of Pioglitazone in the treatment of SRBI were studied using biochemical indexes, pathological changes and transcriptome-sequencing (RNA-seq). RNA-seq results showed 620 DEGs between the Model and the Pioglitazone groups. Enrichment analysis involved multiple inflammatory response processes and chemokine receptor binding functions. TLR4 and CXCL10 in the Toll signaling pathway may play an important role in SRBI as important targets. Pioglitazone may ameliorate SRBI through the PPAR-γ/TLR4/CXCL10 pathway.

Can exercise as a complementary technique manage inflammatory markers in women with breast cancer who are overweight and obese? A systematic review and meta-analysis

BACKGROUND

Inflammation can result in the development of breast cancer in women with overweight and obese, and also affects the outcome and prognosis of breast cancer patients, thereby decreasing the cure and survival rates of breast cancer patients. Exercise may benefit breast cancer patients as a supplement to conventional treatments. However, research on the effects of exercise on inflammatory markers in women with breast cancer who are overweight and obese remains incomplete.

OBJECTIVE

A systematic review and meta-analysis were used to study the effects of exercise on inflammatory markers in women with breast cancer who are overweight and obese.

METHOD

Literature up to May 2024 was searched from databases such as Cochrane, Embase, Pubmed, Web of Science, and EBSCO, and English-language randomized controlled trials (RCTs) that met the inclusion criteria were screened. The screening criteria were as follows (A) written in English; (B) RCT; (C) studied in women with overweight obese and breast cancer; (D) outcome measures: inflammatory markers; (E) the duration of the exercise intervention was unlimited.

RESULTS

A total of 14 articles and 1064 participants were included. Exercise significantly reduced C-reactive protein (CRP) (MD: -0.52, 95 % CI: -0.94 to -0.11; p = 0.01; heterogeneity p < 0.1), interleukin-6 (IL-6) (MD: -0.87, 95 % CI: -1.62 to -0.11; p = 0.02; heterogeneity p < 0.1), and leptin (MD: -0.92, 95 % CI: -1.71 to -0.13; p = 0.02; heterogeneity p < 0.1) levels and exercise significantly increased adiponectin levels (MD: 0.89, 95 % CI: 0.03-1.75, p = 0.04; heterogeneity p < 0.1) but had no effect on tumor necrosis factor-α (TNF-α) (MD: -0.26, 95 % CI: -0.82-0.29; p = 0.35; heterogeneity p < 0.1) and IL-10 (MD: 0.14, 95 % CI: -0.17-0.45; p = 0.37; heterogeneity p = 0.45) were not significant. In addition, subgroup analyses suggest that combination training (CE) may be the most recommended type of exercise to decrease pro-inflammatory markers, and increase anti-inflammatory markers in women with overweight obesity, and have breast cancer.

CONCLUSION

Exercise significantly reduced CRP, IL-6, and leptin levels and overall increased adiponectin levels in women with overweight obese, and breast cancer. However, the effects on TNF-α and IL-10 levels were not significant. CE may be the most recommended type of exercise for reducing pro-inflammatory factors and increasing anti-inflammatory factors. Therefore, this study considers exercise as an effective complementary approach to managing inflammatory markers in women with breast cancer who are overweight and obese. Future researchers may consider exploring the combined effects of exercise and dietary control, weight loss, and other factors, and formulate a comprehensive treatment plan accordingly.

Predicting Surgical Site Infections in Spine Surgery: Association of Postoperative Lymphocyte Reduction

OBJECTIVE

Postoperative lymphopenia is reported as an excellent indicator to predict surgical-site infection (SSI) after spine surgery. However, there is still controversy concerning which serological markers can predict spinal SSI. This study aims to evaluate excellent and early indicators for detecting SSI, focusing on spine instrumented surgery.

MATERIALS AND METHODS

This study included 268 patients who underwent spinal instrumented surgery from January 2022 to December 2023 (159 female and 109 male, average 62.9 years). The SSI group included 20 patients, and the non-SSI group comprised 248 patients. Surgical time, intraoperative blood loss, and glycemic levels were measured in both groups. The complete blood cell counts, differential counts, albumin, and C-reactive protein (CRP) levels were measured pre-surgery and postoperative on Days 1, 3, and 7. In comparing the groups, the Mann-Whitney U test analysis was used for continuous variables, while the chi-squared test and Fisher's exact test were used for dichotomous variables.

RESULTS

The incidence of SSI after spinal instrumentation was 7.46% and was relatively higher in scoliosis surgery. The SSI group had significantly longer surgical times (248 min vs. 180 min, p = 0.0004) and a higher intraoperative blood loss (772 mL vs. 372 mL, p < 0.0001) than the non-SSI group. In the SSI group, the Day 3 (10.5 ± 6.2% vs. 13.8 ± 6.0%, p = 0.012) and Day 7 (14.4 ± 4.8% vs. 18.8 ± 7.1%, p = 0.012) lymphocyte ratios were lower than the non-SSI group. Albumin levels on Day 1 in the SSI group were lower than in the non-SSI group (2.94 ± 0.30 mg/dL vs. 3.09 ± 0.38 mg/dL, p = 0.045). There is no difference in CRP and lymphocyte count between the two groups.

CONCLUSIONS

SSI patients had lower lymphocyte percentages than non-SSI patients, which was a risk factor for SSI, with constant high inflammation. The Day 3 lymphocyte percentage may predict SSI after spinal instrumented surgery.

Interleukin-6 as a critical inflammatory marker for early diagnosis of surgical site infection after spine surgery

PURPOSE

Early diagnosis of surgical site infections (SSIs) could prevent surgical revision. Inflammatory markers (IMs), such as procalcitonin (PCT), interleukin-6 (IL-6), and tumor necrosis factor α (TNF-α), seem more accurate in diagnosing SSI than C-reactive protein (CRP) and white blood cell (WBC) count. The aim was to compare the predictive values of CRP, WBC count, PCT, IL-6, and TNF-α in SSI detection.

METHODS

A total of 130 patients undergoing dorsal spondylodesis from 2019 to 2024 were enrolled in a prospective diagnostic study at a maximum care spine center. IMs were measured preoperatively and on the postoperative days (PODs) 1, 2, 3, 5, and 7. Patients with high suspicion of SSI underwent revision surgery. SSI was diagnosed when the microbiological evidence was positive. Patients were divided a posteriori into the non-infection and infection groups.

RESULTS

IMs of 118 patients (66.9 ± 13.0 years, 61.0% females) were measured. Fifteen of the 118 patients (12.7%) developed an SSI. The groups differed with respect to existing hypertension, number of instrumented segments, region of surgery, CRPPOD1,7, PCTPOD7, and IL-6POD3,5,7. Binary logistic regression for SSI detection including these parameters showed an area under the curve (AUC) of 0.88 (95% CI 0.79-0.98; P < 0.001). The main effect for SSI detection was maintained by IL-6POD7 (odds ratio = 1.13; 95% CI 1.05-1.23; P = 0.001), which itself showed an AUC of 0.86 (95% CI 0.75-0.97).

CONCLUSION

Compared to CRP, WBC count, PCT, and TNF-α, IL-6 seems to be the critical IM for the early detection of an SSI.

TRIAL REGISTRATION

drks.de: DRKS00033773, date of registration: 29.02.2024, retrospectively registered; Postoperative Markers of Inflammation in Spine Surgery (POMIS) Trial.

Study of the Role of C-reactive Protein/Procalcitonin Ratio as a Prognostic Tool in ICU Patients with Sepsis: A Prospective Observational Study

Background

Prediction of prognosis in sepsis is an essential research area aiming to improve disease outcomes. In this study, we investigated the role of the C-reactive protein (CRP)/procalcitonin (PCT) ratio as a prognostic tool in sepsis patients.

Materials and methods

This prospective observational study was conducted at the intensive care unit (ICU) of Alexandria Main University Hospital in the period from January to June 2024. One hundred and seventy patients with a diagnosis of sepsis were enrolled. Sequential organ failure assessment (SOFA) score, acute physiology and chronic health evaluation (APACHEII) score and CRP/PCT ratio were calculated on admission (day 1), and as a follow-up on day 3. Patients were subsequently divided into survivor and non-survivor groups, and the data were compared.

Results

The CRP/PCT ratio was significantly lower, on admission and on follow-up, in non-survivor patients than in survivor patients. The ratio median (minimum-maximum) in non-survivors was 4.82 (1.51-23.28) vs 11.23 (1.85-136.7) in survivors on admission, and it was 7.37 (2.27-26.36) in non-survivors vs 11.37 (2.78-110.9) in survivors on day 3. The ratio was significantly lower in patients with septic shock than in non-septic shock patients. The ratio had a significant negative correlation with both SOFA and APACHEII scores. The receiver operating characteristic (ROC) curve showed high accuracy of the day 1 CRP/PCT ratio to predict mortality [area under curve (AUC = 0.835)], which is comparable to the day 1 SOFA score (AUC = 0.878) and higher than the day 1 PCT and day 1 APACHE scores.

Conclusion

Our results suggest a potential role for the CRP/PCT ratio, on admission and on follow-up, as a marker for predicting prognosis in sepsis patients, where low ratio values can predict poor disease outcome.

How to cite this article

Abdellatif EM, Hamouda EH. Study of the Role of C-reactive Protein/Procalcitonin Ratio as a Prognostic Tool in ICU Patients with Sepsis: A Prospective Observational Study. Indian J Crit Care Med 2024;28(12):1130-1138.

Machine learning interpretability methods to characterize the importance of hematologic biomarkers in prognosticating patients with suspected infection

OBJECTIVE

To evaluate the effectiveness of Monocyte Distribution Width (MDW) in predicting sepsis outcomes in emergency department (ED) patients compared to other hematologic parameters and vital signs, and to determine whether routine parameters could substitute MDW in machine learning models.

METHODS

We conducted a retrospective analysis of data from 10,229 ED patients admitted to a large regional safety-net hospital in Cleveland, Ohio who had suspected infections and developed sepsis-associated poor outcomes. We developed a new analytical framework consisting of seven data models and an ensemble of high accuracy machine learning (ML) algorithms (accuracy values ranging from 0.83 to 0.90) to predict sepsis-associated poor outcomes (3-day intensive care unit stay or death). Local Interpretable Model-Agnostic Explanation (LIME) and Shapley Additive Value (SHAP) interpretability methods were utilized to assess the contributions of individual hematologic parameters.

RESULTS

The ML interpretability analysis indicated that the predictive value of MDW is significantly reduced when other hematological parameters and vital signs are considered. The results suggest that complete blood count with differential (CBD-DIFF) alongside vital signs can effectively replace MDW in high accuracy machine learning algorithms for screening poor outcome associated with sepsis.

CONCLUSION

MDW, although a newly approved biomarker for sepsis, does not significantly enhance prediction models when combined with routinely available parameters and vital signs. Hospitals, especially those with resource constraints, can rely on existing parameters with high accuracy machine learning models to predict sepsis outcomes effectively, thereby reducing the need for specialized tests like MDW.

Exosomes as novel biomarkers in sepsis and sepsis related organ failure

Sepsis, a severe and life-threatening condition arising from a dysfunctional host response to infection, presents considerable challenges to the health care system and is characterized by high mortality rates and substantial economic costs. Exosomes have garnered attention as potential diagnostic markers because of their capacity to mirror the pathophysiological milieu of sepsis. This discourse reviews the progression of sepsis classification from Sepsis 1.0 to Sepsis 3.0, highlighting the imperative for sensitive and specific biomarkers to facilitate timely diagnosis and optimize patient outcomes. Existing biomarkers, such as procalcitonin (PCT) and C-reactive protein (CRP), exhibit certain limitations, thereby prompting the quest for more dependable diagnostic indicators. Exosomal cargoes, which encompass proteins and miRNAs, present a trove of biomarker candidates, attributable to their stability, pervasive presence, and indicative nature of the disease status. The potential of exosomal biomarkers in the identification of sepsis-induced organ damage, including cardiomyopathy, acute kidney injury, and acute lung injury, is emphasized, as they provide real-time insights into cardiac and renal impairments. Despite promising prospects, hurdles persist in the standardization of exosome extraction and the need for extensive clinical trials to validate their efficacy. The combination of biomarker development and sophisticated exosome detection techniques represents a pioneering strategy in the realm of sepsis diagnosis and management, underscoring the significance of further research and clinical validation.

Synthetic plasma pool cohort correction for affinity-based proteomics datasets allows multiple study comparison

Proteomics stands as the crucial link between genomics and human diseases. Quantitative proteomics provides detailed insights into protein levels, enabling differentiation between distinct phenotypes. OLINK, a biotechnology company from Uppsala, Sweden, offers a targeted, affinity-based protein measurement method called Target 96, which has become prominent in the field of proteomics. The SCALLOP consortium, for instance, contains data from over 70.000 individuals across 45 independent cohort studies, all sampled by OLINK. However, when independent cohorts want to collaborate and quantitatively compare their target 96 protein values, it is currently advised to include 'identical biological bridging' samples in each sampling run to perform a reference sample normalization, correcting technical variations across measurements. Such a 'biological bridging sample' approach requires each of the involved cohorts to resend their biological bridging samples to OLINK to run them all together, which is logistically challenging, costly and time-consuming. Hence alternatives are searched and an evaluation of the current state of the art exposes the need for a more robust method that allows all OLINK Target 96 studies to compare proteomics data accurately and cost-efficiently. To meet these goals we developed the Synthetic Plasma Pool Cohort Correction, the 'SPOC correction' approach, based on the use of an OLINK-composed synthetic plasma sample. The method can easily be implemented in a federated data-sharing context which is illustrated on a sepsis use case.

Advances in diagnosis and prognosis of bacteraemia, bloodstream infection, and sepsis using machine learning: A comprehensive living literature review

BACKGROUND

Blood-related infections are a significant concern in healthcare. They can lead to serious medical complications and even death if not promptly diagnosed and treated. Throughout time, medical research has sought to identify clinical factors and strategies to improve the management of these conditions. The increasing adoption of electronic health records has led to a wealth of electronically available medical information and predictive models have emerged as invaluable tools. This manuscript offers a detailed survey of machine-learning techniques used for the diagnosis and prognosis of bacteraemia, bloodstream infections, and sepsis shedding light on their efficacy, potential limitations, and the intricacies of their integration into clinical practice.

METHODS

This study presents a comprehensive analysis derived from a thorough search across prominent databases, namely EMBASE, Google Scholar, PubMed, Scopus, and Web of Science, spanning from their inception dates to October 25, 2023. Eligibility assessment was conducted independently by investigators, with inclusion criteria encompassing peer-reviewed articles and pertinent non-peer-reviewed literature. Clinical and technical data were meticulously extracted and integrated into a registry, facilitating a holistic examination of the subject matter. To maintain currency and comprehensiveness, readers are encouraged to contribute manuscript suggestions and/or reports for integration into this living registry.

RESULTS

While machine learning (ML) models exhibit promise in advanced disease stages such as sepsis, early stages remain underexplored due to data limitations. Biochemical markers emerge as pivotal predictors during early stages such as bacteraemia, or bloodstream infections, while vital signs assume significance in sepsis prognosis. Integrating temporal trend information into conventional machine learning models appears to enhance performance. Unfortunately, sequential deep learning models face challenges, showing minimal performance improvements and significant drops in external datasets, potentially due to learning missing patterns within the scarce data available rather than understanding disease dynamics. Real-life implementation receives limited attention, as meeting design requirements proves challenging within existing healthcare infrastructure. The data collected in an event-based fashion during clinical practice is insufficient to fully harness the potential of these data-hungry models. Despite limitations, opportunities abound in leveraging flexible models and exploiting real-time non-invasive data collection technologies such as wearable devices or microneedles. Addressing research gaps in early disease stages, harnessing patient history data often underused, and embracing continual diagnostics beyond treatment initiation are crucial for improving healthcare decision-making support and adoption across the entire management pathway.

CONCLUSIONS

This comprehensive survey illuminates the landscape of ML applications in blood-related infection management, offering insights for future research and clinical practice. Implementing clinical ML-based clinical decision support systems requires balancing research with practical considerations. Current methodologies often lead to complex models lacking transparency and practical validation. Integration into healthcare systems faces regulatory, privacy, and trust challenges. Clear presentations and adherence to standards are essential to boost confidence in machine learning models for real-world healthcare applications.

Single-cell RNA sequencing and transcriptomic analysis reveal key genes and regulatory mechanisms in sepsis

The pathogenesis of sepsis, with a high mortality rate and often poor prognosis, has not been fully elucidated. Therefore, an in-depth study on the pathogenesis of sepsis at the molecular level is essential to identify key sepsis-related genes. The aim of this study was to explore the key genes and potential molecular mechanisms of sepsis using a bioinformatics approach. In addition, key genes with miRNA network correlation analysis and immune infiltration correlation analysis were investigated. The scRNA dataset (GSE167363) and RNA-seq dataset (GSE65682, GSE134347) from GEO database were used for screening out differentially expressed genes using single-cell sequencing and transcriptome sequencing. The analysis of immune infiltration was evaluated by the CIBERSORT method. Key genes and possible mechanisms were identified by WGCNA analysis, GSVA analysis, GSEA enrichment analysis and regulatory network analysis, and miRNA networks associated with key genes were constructed. Nine key genes associated with the development of sepsis, namely IL7R, CD3D, IL32, GPR183, HLA-DPB1, CD81, PEBP1, NCL, and ETS1 were screened, and the specific signaling mechanisms associated with the key genes causing sepsis were predicted. Immune profiling showed immune heterogeneity between control and sepsis samples. A regulatory network of 82 miRNAs, 266 pairs of mRNA-miRNA relationship pairs was also constructed. These nine key genes have the potential to become biomarkers for the diagnosis of sepsis and provide new targets and research directions for the treatment of sepsis.

Mortality prediction model from combined serial lactate, procalcitonin and calprotectin levels in critically ill patients with sepsis: A retrospective study according to Sepsis-3 definition

OBJECTIVE

1) To evaluate the ability of baseline and on 24 h serum calprotectin, in comparison to canonical biomarkers (lactate and procalcitonin), for prognosis of 28-day mortality in critically ill septic patients; and 2) To develop a predictive model combining the three biomarkers.

DESIGN

A single-center, retrospective study.

SETTING

Intensive Care Unit of a university hospital.

PATIENTS OR PARTICIPANTS

One hundred and seventy three septic pacientes were included.

INTERVENTIONS

Measurement of baseline lactate, procalcitonin and calprotectin level and procalcitonin and calprotectin levels on 24 h.

MAIN VARIABLES OF INTEREST

Demographics and comorbidities, SOFA score on ICU admission, baseline lactate, procalcitonin and calprotectin on admission and on 24 h and 28-day mortality.

RESULTS

1) On ICU admission, lactate was the only biomarker achieving a significant accuracy (AUC: 0.698); 2) On 24 h, no differences were found on procalcitonin and calprotectin levels. Procalcitonin and calprotectin clearances were significantly lower in non-survivors and both achieved a moderate performance (AUCs: 0.668 and 0.664, respectively); 3) A biomarker based-model achieved a significant accuracy (AUC: 0.766), trending to increase (AUC: 0.829) to SOFA score alone; y 4) Baseline lactate levels and procalcitonin and calprotectin clearance were independent predictors for the outcome.

CONCLUSIONS

1) Baseline and on 24 h calprotectina and procalcitonin levels lacked ability in predicting 28-day mortality; 2) Accuracy of clearance of both biomarkers was moderate; and 3) Combination of SOFA score and the predictive biomarker based-model showed a high prognostic accuracy.

The dysfunction of complement and coagulation in diseases: the implications for the therapeutic interventions

The complement system, comprising over 30 proteins, is integral to the immune system, and the coagulation system is critical for vascular homeostasis. The activation of the complement and coagulation systems involves an organized proteolytic cascade, and the overactivation of these systems is a central pathogenic mechanism in several diseases. This review describes the role of complement and coagulation system activation in critical illness, particularly sepsis. The complexities of sepsis reveal significant knowledge gaps that can be compared to a profound abyss, highlighting the urgent need for further investigation and exploration. It is well recognized that the inflammatory network, coagulation, and complement systems are integral mechanisms through which multiple factors contribute to increased susceptibility to infection and may result in a disordered immune response during septic events in patients. Given the overlapping pathogenic mechanisms in sepsis, immunomodulatory therapies currently under development may be particularly beneficial for patients with sepsis who have concurrent infections. Herein, we present recent findings regarding the molecular relationships between the coagulation and complement pathways in the advancement of sepsis, and propose potential intervention targets related to the crosstalk between coagulation and complement, aiming to provide more valuable treatment of sepsis.

Immunoregulatory protein B7-H3 upregulated in bacterial and viral infection and its diagnostic potential in clinical settings

Bacterial and viral infections cause a huge burden to healthcare settings worldwide, and mortality rates associated with infectious microorganisms have remained high in recent decades. Despite tremendous efforts and resources worldwide to explore diagnostic biomarkers, rapid and easily assayed indicators for the diagnosis of bacterial and viral infections remain a challenge. B7 homolog 3 (B7-H3), a member of the B7 family of immunoregulatory proteins, is overexpressed in patients with septicemia, meningitis, pneumonia, and hepatitis. Therefore, B7-H3 could be used as a potential clinical indicator and therapeutic target for bacterial and viral infections caused by H. pylori, S. pneumoniae, M. pneumoniae, hepatitis B virus (HBV), viral hemorrhagic septicemia virus (VHSV), respiratory syncytial virus (RSV), and human immunodeficiency virus (HIV). Moreover, the interplay between infectious microorganisms and B7-H3 and exploration of the functional roles of the B7-H3 molecule could aid in the development of novel strategies for disease diagnosis and immunotherapy.

Predictive Value of Combined Detection of Serum LGALS3BP and GDF-15 for the Prognosis of ICU Sepsis Patients

Objective

This study aims to investigate the effectiveness of combining serum lectin galactoside-binding soluble 3 binding protein (LGALS3BP) with growth differentiation factor 15 (GDF-15) for predicting outcomes in sepsis patients in an intensive care unit (ICU) setting.

Methods

The study involved 208 sepsis patients from the ICU of our hospital. These patients were categorized based on their 28-day survival outcomes into two groups: 166 in the survival group and 42 in the mortality group. The serum levels of LGALS3BP and GDF-15 were measured using the ELISA technique. Pearson and Spearman methods were utilized for correlation analysis. Factors affecting mortality in ICU sepsis patients were evaluated through multivariate logistic regression analysis. The efficacy of these biomarkers in prognosis prediction was assessed using receiver operating characteristic (ROC) curve analysis.

Results

The proportion of septic shock, APACHE II score, SOFA score, and serum LGALS3BP and GDF-15 levels in ICU sepsis patients in the death group were obviously higher than those in the survival group (P<0.05). The severity of ICU sepsis patients, APACHE II score, and SOFA score were obviously positively correlated with serum LGALS3BP and GDF-15 levels (P<0.05). LGALS3BP (OR: 95% CI=2.745:1.583~4.761) and GDF-15 (OR: 95% CI=2.639:1.423~4.893) were independent risk factors for death in ICU sepsis patients (P<0.05). The AUC of serum LGALS3BP and GDF-15 levels alone in predicting death in ICU sepsis patients was 0.859 and 0.854, obviously lower than the AUC of the combination, 0.943 (Z=2.704, 2.287, P<0.05). The AUC for predicting mortality in ICU sepsis patients using the APACHE II and SOFA scores were 0.832 and 0.842, respectively. The differences in comparison to the AUCs of LGALS3BP and GDF-15 were not statistically significant (P > 0.05).

Conclusion

Serum levels of LGALS3BP and GDF-15 can both be used as predictive indicators for death in ICU sepsis patients, and their combined predictive efficacy is better.

Damage-associated molecular patterns in bacteraemic infection, including a comparative analysis with bacterial DNA, a pathogen-associated molecular pattern

Damage-associated molecular patterns (DAMPs) and pathogen-associated molecular patterns (PAMPs) are key triggers of inflammation in sepsis. However, they have rarely been studied simultaneously. Thus, in the present study of patients with bacteraemic infection, we aimed to study how DAMP dynamics are linked to disease severity and outcome and to compare diagnostic and prognostic properties of a DAMP and a previously analysed PAMP (16S rDNA). In a prospective study of adult patients hospitalized with culture-proven community-onset bacteraemic infection, caused by Streptococcus pneumonia (n = 30), Staphylococcus aureus (n = 27), or Escherichia coli (n = 26), dynamics of a PAMP, i.e. 16S rDNA, have previously been presented. For the present study, blood samples obtained on hospital days 1-2 (when blood culture was positive), 3-4, 7 ± 1, 14 ± 2, and 28 ± 4 were analysed for four different DAMPs, i.e., nuclear DNA (nDNA), mitochondrial DNA (mtDNA), heat shock protein 90 alpha (HSP90α), and extracellular high mobility group box 1 (HMGB1). Sepsis was defined according to the Sepsis-3 criteria. The study outcomes were sepsis at admission and negative outcome, defined as intensive care unit (ICU) admission and/or death within 60 days. Of 83 study patients, sepsis was noted in 41 patients (49%) and a negative outcome was noted in 17 patients (20%). nDNA had areas under the receiver operating characteristic (ROC) curves of 0.78 for sepsis and 0.76 for negative outcome, which were higher than those of the other DAMPs and additional biomarkers (CRP, IL-6, IL-8, and IL-10). The nDNA and positive 16S rDNA results on day 1-2 were correlated with each other (r = 0.68, p < 0.001). Multivariate analyses showed that high day 1-2 concentrations of both nDNA and 16S rDNA were independently associated with sepsis. In addition, high day 1-2 concentration of nDNA was independently associated with negative outcomes. While 16S rDNA dissipated from the circulation within days, nDNA concentrations remained elevated throughout the follow-up period in patients with negative outcome. In conclusion, nDNA outperformed the other DAMPs regarding sepsis detection and outcome prediction. Both nDNA (a DAMP) and 16S rDNA (a PAMP) were independently linked to sepsis; nDNA was also associated with negative outcomes and persisted elevated in such cases. This highlights nDNA as an interesting marker within sepsis pathogenesis and as a promising clinical biomarker, warranting further studies.

Identification of key biomarkers and therapeutic targets in sepsis through coagulation-related gene expression and immune pathway analysis

Sepsis, characterized by a widespread and dysregulated immune response to infection leading to organ dysfunction, presents significant challenges in diagnosis and treatment. In this study, we investigated 203 coagulation-related genes in sepsis patients to explore their roles in the disease. Through differential gene expression analysis, we identified 20 genes with altered expression patterns. Subsequent correlation analysis, visualized through circos plots and heatmaps, revealed significant relationships among these genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses indicated that these genes are involved in immune response activation, coagulation, and immune receptor activity. Disease Ontology (DO) enrichment analysis further linked these genes to autoimmune hemolytic anemia and tumor-related signaling pathways. Additionally, the CIBERSORT analysis highlighted differences in immune cell composition in sepsis patients, revealing an increase in neutrophils and monocytes and a decrease in inactive NK cells, CD8 T cells, and B cells. We employed machine learning techniques, including random forest and SVM, to construct a diagnostic model, identifying FCER1G and FYN as key biomarkers. These biomarkers were validated through their expression levels and ROC curve analysis in an independent validation cohort, demonstrating strong diagnostic potential. Single-cell analysis from the GSE167363 dataset further confirmed the distinct expression profiles of these genes across various cell types, with FCER1G predominantly expressed in monocytes, NK cells, and platelets, and FYN in CD4+ T cells and NK cells. Enrichment analysis via GSEA and ssGSEA revealed that these genes are involved in critical pathways, including intestinal immune networks, fatty acid synthesis, and antigen processing. In conclusion, our comprehensive analysis identifies FCER1G and FYN as promising biomarkers for sepsis, providing valuable insights into the molecular mechanisms of this complex condition. These findings offer new avenues for the development of targeted diagnostic and therapeutic strategies in sepsis management.

Early Mortality Stratification with Serum Albumin and the Sequential Organ Failure Assessment Score at Emergency Department Admission in Septic Shock Patients

Background: Early risk stratification is crucial due to septic patients' heterogeneity. Serum albumin level may reflect the severity of sepsis and host status. This study aimed to evaluate the prognostic ability of the initial sequential organ failure assessment (SOFA) score alone and combined with serum albumin levels for predicting 28-day mortality in patients with septic shock. Methods: We conducted an observational study using a prospective, multicenter registry of septic shock patients between October 2015 and May 2022 from 12 emergency departments in the Korean Shock Society and the results were validated by examining those from the septic shock cohort in Asan Medical Center. The primary outcome was 28-day mortality. The area under the receiver operating characteristic (ROC) curve was used to compare the predictive values of SOFA score alone and SOFA score combined with serum albumin level. Results: Among 5805 septic shock patients, 1529 (26.3%) died within 28 days. Mortality increased stepwise with decreasing serum albumin levels (13.6% in albumin ≥3.5, 20.7% in 3.5-3.0, 29.7% in 3.0-2.5, 44.0% in 2.5-2.0, 56.4% in <2.0). The albumin SOFA score was calculated by adding the initial SOFA score to the 4 points assigned for albumin levels. ROC analysis for predicting 28-day mortality showed that the area under the curve for the albumin SOFA score was 0.71 (95% CI 0.70-0.73), which was significantly higher than that of the initial SOFA score alone (0.68, 95% CI: 0.67-0.69). Conclusions: The combination of the initial SOFA score with albumin can improve prognostic accuracy for patients with septic shock, suggesting the albumin SOFA score may be used as an early mortality stratification tool.

CARD8 polymorphisms among bacterial meningitis patients in North-West Ethiopia

BACKGROUND

The severity of infectious disease outcomes is dependent on the virulence factors of the pathogen and the host immune response. CARD8 is a major regulator of the innate immune proinflammatory response and has been suggested to modulate the host response to common inflammatory diseases. In the present study, the C10X genetic polymorphism in the CARD8 gene was investigated in relation to bacterial meningitis.

METHODS

A total of 400 clinically suspected meningitis patients hospitalized at the University of Gondar Hospital were enrolled in the study. Cerebrospinal fluid (CSF) and blood samples were collected for laboratory investigations. The collected CSF was cultured, and all the results obtained from the culture were confirmed using direct RT‒PCR. Genotyping of whole-blood samples was performed using a TaqMan assay. The results were compared with apparently healthy controls and with PCR-negative meningitis suspected patients.

RESULTS

Of the included patients, 57% were men and the most common clinical signs and symptoms were fever (81%), headache (80%), neck stiffness (76%), nausea (68%), and vomiting (67%). Microbiology culture identified 7 patients with bacterial meningitis caused by Neisseria meningitidis (n = 4) and Streptococcus pneumoniae (n = 3). The RT-PCR revealed 39 positive samples for N. meningitidis (n = 10) and S. pneumoniae (n = 29). A total of 332 whole-blood samples were genotyped with the following results: 151 (45.5%) C10X heterozygotes, 59 (17.7%) C10X homozygotes and 122 (36.7%) wild genotypes. The polymorphic gene carriers among laboratory confirmed, clinically diagnosed meningitis and healthy controls were 23(46%), 246(40%), and 1526(39%), respectively with OR = 1.27 (0.7-2.3) and OR = 1.34 (0.76-2.4). The presence of the C10X polymorphism in the CARD8 gene was more prevalent in suspected meningitis patients than in healthy controls (OR 1.2; 1.00-1.5). Homozygote C10X polymorphic gene carriers were more susceptible to infectious disease. The presence of viable or active bacterial infection was found to be associated with the presence of heterozygous C10X carriers.

CONCLUSIONS

A greater proportion of C10X in the CARD8 gene in confirmed bacterial meningitis patients and clinically diagnosed meningitis patients than in healthy controls. Homozygote C10X polymorphic gene carriers were more susceptible to infectious disease than heterozygote gene carriers and healthy controls.

Sepsis phenotypes, subphenotypes, and endotypes: are they ready for bedside care?

PURPOSE OF REVIEW

Sepsis remains a leading global cause of morbidity and mortality, and despite decades of research, no effective therapies have emerged. The lack of progress in sepsis outcomes is related in part to the significant heterogeneity of sepsis populations. This review seeks to highlight recent literature regarding sepsis phenotypes and the potential for further research and therapeutic intervention.

RECENT FINDINGS

Numerous recent studies have elucidated various phenotypes, subphenotypes, and endotypes in sepsis. Clinical parameters including vital sign trajectories and microbial factors, biomarker investigation, and genomic, transcriptomic, proteomic, and metabolomic studies have illustrated numerous differences in sepsis populations with implications for prediction, diagnosis, treatment, and prognosis of sepsis.

SUMMARY

Sepsis therapies including care bundles, fluid resuscitation, and source control procedures may be better guided by validated phenotypes than universal application. Novel biomarkers may improve upon the sensitivity and specificity of existing markers and identify complications and sequelae of sepsis. Multiomics have demonstrated significant differences in sepsis populations, most notably expanding our understanding of immunosuppressed sepsis phenotypes. Despite progress, these findings may be limited by modest reproducibility and logistical barriers to clinical implementation. Further studies may translate recent findings into bedside care.

The Combination of Systemic Immune-Inflammation Index and Serum Procalcitonin has High Auxiliary Predictive Value for Short-Term Adverse Prognosis in Septic Shock Patients

BACKGROUND

Septic shock is the most serious complication of sepsis, with more secure and efficient biomarkers urgently needed. Systemic immune-inflammation index (SII) and serum procalcitonin (PCT) show involvement in predicting septic shock prognosis.

OBJECTIVE

Herein, we explored the clinical value of the SII-PCT combination in the short-term prognosis of septic shock patients.

METHODS

Totally 200 septic shock patients were analyzed retrospectively and allocated into the survival and death groups upon 28-day in-hospital outcomes. Correlations of SII, PCT, acute physiology and chronic health evaluation II (APACHE II)/sepsis-related organ failure assessment (SOFA) scores, C-reactive protein (CRP), and serum creatinine (Scr) were analyzed using Spearman. The influencing factors of SII and serum PCT for short-term poor prognosis were analyzed using logistic multivariate regression model. The auxiliary predictive value of SII, PCT, and their combination for short-term adverse septic shock prognosis was evaluated by the receiver operating characteristic curve. Differences in the area under the curve (AUC) were compared using MedCalc.

RESULTS

The death group had higher APACHE II/SOFA scores, LYM, CRP, Scr, SII, and PCT levels than the survival group. SII and PCT were positively correlated with APACHE II and SOFA scores, LYM, CRP, and Scr, and were independent risk factors influencing the adverse septic shock prognosis. The AUC of the SII-PCT combination in predicting short-term adverse septic shock prognosis was 0.893 (0.841-0.932), with 76.12% sensitivity and 87.97% specificity, with the combination showing a higher AUC than SII/PCT alone.

CONCLUSIONS

The SII-PCT combination helps predict the adverse prognosis of septic shock patients.

Elevations in presepsin, PCT, hs-CRP, and IL-6 levels predict mortality among septic patients in the ICU

This study aimed to investigate whether changes in presepsin, procalcitonin, high-sensitivity C-reactive protein, and interleukin 6 levels predict mortality in septic patients in the intensive care unit. This study enrolled septic patients between November 2020 and December 2021. Levels of presepsin, procalcitonin, high-sensitivity C-reactive protein, and interleukin 6 were measured on the first (PSEP_0, PCT_0, hsCRP_0, IL-6_0) and third days (PSEP_3, PCT_3, hsCRP_3, IL-6_3). Follow-up was performed on days 3, 7, 14, 21, and 28 after enrollment. The outcome was all-cause death. The study included 119 participants, and the mortality was 18.5%. In univariable Cox proportional hazards regression analysis, ΔPSEP (= PSEP_3 - PSEP_0) > 211.49 pg/mL (hazard ratio, 2.70; 95% confidence interval, 1.17-6.22), ΔPCT (= PCT_3 - PCT_0) > -0.13 ng/mL (hazard ratio, 7.31; 95% confidence interval, 2.68-19.80), ΔhsCRP (= hsCRP_3 - hsCRP_0) > -19.29 mg/L (hazard ratio, 6.89; 95% confidence interval, 1.61-29.40), and ΔIL-6 (= IL-6_3 - IL-6_0) > 1.00 pg/mL (hazard ratio, 3.13; 95% confidence interval, 1.35-7.24) indicated an increased risk of mortality. The composite concordance index for alterations in all 4 distinct biomarkers was highest (concordance index, 0.83; 95% confidence interval, 0.76-0.91), suggesting the optimal performance of this panel in mortality prediction. In decision curve analysis, compared with the Acute Physiology and Chronic Health Evaluation II and Sequential (sepsis-related) Organ Failure Assessment scores, the combination of the 4 biomarkers had a larger net benefit. Interestingly, interleukin 6 was predominantly produced by monocytes upon lipopolysaccharide stimulation in peripheral blood mononuclear cells. ΔPSEP, ΔPCT, ΔhsCRP, and ΔIL-6 are reliable biomarkers for predicting mortality in septic patients in the intensive care unit, and their combination has the best performance.

Immunological alterations in the endothelial barrier: a new predictive and therapeutic paradigm for sepsis

INTRODUCTION

Despite the fact incidence and mortality vary widely among regions, sepsis remains a major cause of morbidity and cost worldwide. The importance of the endothelial barrier in sepsis and infectious diseases is increasingly recognized; however, the underlying pathophysiology of the endothelial barrier in sepsis remains poorly understood.

AREAS COVERED

Here we review the advances in basic and clinical research for relevant papers in PubMed database. We attempt to provide an updated overview of immunological alterations in endothelial dysfunction, discussing the central role of endothelial barrier involved in sepsis to provide new predictive and therapeutic paradigm for sepsis.

EXPERT OPINION

Given its physiological and immunological functions in infectious diseases, the endothelial barrier has been dramatically altered in sepsis, suggesting that endothelial dysfunction may play a critical role in the pathogenesis of sepsis. Although many reliable biomarkers have been investigated to monitor endothelial activation and injury in an attempt to find diagnostic and therapeutic tools, there are no specific therapies to treat sepsis due to its complex pathophysiology. Since sepsis is initiated by both hyperinflammation and immunoparalysis occurring simultaneously, a 'one-treatment-fits-all' strategy for sepsis-induced immune injury and immunoparalysis is bound to fail, and an individualized 'precision medicine' approach is required.

Identification of Immune-Related Genes as Potential Biomarkers in Early Septic Shock

INTRODUCTION

Septic shock, a severe manifestation of infection-induced systemic immune response, poses a critical threat resulting in life-threatening multi-organ failure. Early diagnosis and intervention are imperative due to the potential for irreversible organ damage. However, specific and sensitive detection tools for the diagnosis of septic shock are still lacking.

METHODS

Gene expression files of early septic shock were obtained from the Gene Expression Omnibus (GEO) database. CIBERSORT analysis was used to evaluate immune cell infiltration. Genes related to immunity and disease progression were identified using weighted gene co-expression network analysis (WGCNA), followed by enrichment analysis. CytoHubba was then employed to identify hub genes, and their relationships with immune cells were explored through correlation analysis. Blood samples from healthy controls and patients with early septic shock were collected to validate the expression of hub genes, and an external dataset was used to validate their diagnostic efficacy.

RESULTS

Twelve immune cells showed significant infiltration differences in early septic shock compared to control, such as neutrophils, M0 macrophages, and natural killer cells. The identified immune and disease-related genes were mainly enriched in immune, cell signaling, and metabolism pathways. In addition, six hub genes were identified (PECAM1, F11R, ITGAL, ICAM3, HK3, and MCEMP1), all significantly associated with M0 macrophages and exhibiting an area under curve of over 0.7. These genes exhibited abnormal expression in patients with early septic shock. External datasets and real-time qPCR validation supported the robustness of these findings.

CONCLUSION

Six immune-related hub genes may be potential biomarkers for early septic shock.

Elevated serum albumin-to-creatinine ratio as a protective factor on clinical outcomes among critically ill patients with sepsis: a retrospective study

Background

The aim of this study was to examine the prognostic significance of serum albumin-to-creatinine ratio (ACR) in critically ill patients with sepsis.

Methods

This retrospective study analyzed sepsis cases admitted to the Affiliated Hospital of Jiangsu University between January 2015 and November 2023. The patients were divided into four groups based on their ACR upon admission to the intensive care unit (ICU). Laboratory data were collected at the time of ICU admission, and the primary outcome measure was in-hospital all-cause mortality. Kaplan-Meier survival curves were generated to illustrate the differences in 30-/60-day mortality among the various groups. Multivariate Cox regression models and restricted cubic splines (RCS) were utilized to explore the association between ACR and all-cause mortality in sepsis patients. Subgroup analyses were conducted to examine the impact of other covariates on the relationship between ACR and all-cause mortality.

Results

A total of 1,123 eligible patients were included in the study, with a median ACR of 0.169. The in-hospital mortality rate was 33.7%, the ICU mortality rate was 31.9%, and the 30-day mortality rate was 28.1%. Kaplan-Meier survival analysis demonstrated that patients with higher ACR had a significantly lower risk of 30-/60-day mortality (log-rank p < 0.001). Multivariable Cox proportional hazards analyses revealed that ACR was an independent predictor of in-hospital death (HR: 0.454, 95% CI 0.271-0.761, p = 0.003), ICU death (HR: 0.498, 95% CI 0.293-0.847, p = 0.010), and 30-day death (HR: 0.399, 95% CI 0.218-0.730, p = 0.003). For each 1-unit increase in ACR, there was a 1.203-fold decrease in the risk of death during the hospital stay. The RCS curve illustrated a non-linear negative correlation between ACR and in-hospital mortality (p for non-linear =0.018), ICU mortality (p for non-linear =0.005), and 30-day mortality (p for non-linear =0.006). Sensitivity analysis indicated consistent effect sizes and directions in different subgroups, confirming the stability of the results.

Conclusion

Low ACR levels were identified as independent risk factors associated with increased in-hospital, ICU, and 30-day mortality in sepsis patients. ACR can serve as a significant predictor of the clinical outcome of sepsis.

Diagnostic and Prognostic Utilities of Pancreatic Stone Protein in Patients with Suspected Sepsis

Background/Objectives: Pancreatic stone protein (PSP) is an emerging biomarker of sepsis that is secreted from pancreas sensing remote organ damages. We explored the diagnostic and prognostic utilities of PSP in patients with suspected sepsis. Methods: In a total of 285 patients (suspected sepsis, n = 148; sepsis, n = 137), we compared PSP with procalcitonin (PCT) and sequential organ failure assessment (SOFA) score. Sepsis diagnoses were explored using receiver operating characteristic curve analyses with area under the curves (AUCs). Clinical outcomes (in-hospital mortality, 30-day mortality, and kidney replacement therapy [KRT]) were explored using the Kaplan-Meier method and a multivariate analysis with hazard ratio (HR). Results: PCT and PSP were comparable for sepsis diagnosis (AUC = 0.71-0.72, p < 0.001). The sepsis proportion was significantly higher when both biomarkers increased than when either one or both biomarkers did not increase (89.0% vs. 21.3-47.7%, p < 0.001). Each biomarker quartile (Q1-Q4) differed significantly according to their SOFA score (all p < 0.001). Compared with Q1, the Q2-Q4 groups showed worse clinical outcomes (p = 0.002-0.041). Both biomarkers added to the SOFA score showed higher HRs than the SOFA score alone (3.3-9.6 vs. 2.8-4.2, p < 0.001-0.011), with nearly 2.5-fold higher HR (9.6 vs. 4.2) for predicting KRT. Conclusions: Although PCT and PSP did not independently predict clinical outcomes in the multivariate analysis, PSP demonstrated diagnostic and prognostic utilities in patients with suspected sepsis, especially for predicting kidney dysfunction. PSP, alone or in combination with PCT, would be a valuable tool that can be added to clinical assessments.

Association between red blood cell distribution width and 30-day mortality in critically ill septic patients: a propensity score-matched study

BACKGROUND

Sepsis is the leading cause of death worldwide, and a number of biomarkers have been developed for early mortality risk stratification. Red blood cell distribution width (RDW) is a routinely available hematological data and has been found to be associated with mortality in a number of diseases; therefore, we aim to address the association between RDW and mortality in critically ill patients with sepsis.

METHODS

We analyzed data of critically ill adult patients with sepsis on the TriNetX platform, excluding those with hematologic malignancies, thalassemia, and iron deficiency anemia. Propensity score-matching (PSM) (1:1) was used to mitigate confounding effects, and hazard ratio (HR) with 95% confidence (CI) was calculated to determine the association between RDW and 30-day mortality. We further conducted sensitivity analyses through using distinct cut-points of RDW and severities of sepsis.

RESULTS

A total of 256,387 critically ill septic patients were included in the analysis, and 40.0% of them had RDW equal to or higher than 16%. After PSM, we found that high RDW was associated with an increased 30-day mortality rate (HR: 1.887, 95% CI 1.847-1.928). The associations were consistent using distinct cut-points of RDW, with the strength of association using cut-points of 12%, 14%, 16%, 18% and 20% were 2.098, 2.204, 1.887, 1.809 and 1.932, respectively. Furthermore, we found consistent associations among critically ill septic patients with distinct severities, with the association among those with shock, receiving mechanical ventilation, bacteremia and requirement of hemodialysis being 1.731, 1.735, 2.380 and 1.979, respectively.

CONCLUSION

We found that RDW was associated with 30-day mortality in critically ill septic patients, underscoring the potential as a prognostic marker in sepsis. More studies are needed to explore the underlying mechanisms.

Elevated total bile acid levels as an independent predictor of mortality in pediatric sepsis

BACKGROUND

The close relationship between bile acid (BA) metabolism and sepsis has been investigated in recent years, as knowledge of the role of the gut microbiome and metabolomics in sepsis has grown and become more comprehensive.

METHODS

Patients with sepsis who were admitted to the PICU of the Children's Hospital, Zhejiang University School of Medicine from January 2016 to December 2021 were enrolled in this study. Preoperative non-infectious pediatric patients undergoing elective surgeries in our hospital's department of surgery were recruited as controls during the same period. Clinical data were collected and analyzed.

RESULTS

702 children were enrolled, comprising 538 sepsis survivors, 164 sepsis fatalities, and 269 non-infected controls. Statistical analysis revealed that total BA (TBA) increased in both the early and severe stages of pediatric sepsis. In the severe stage, TBA (OR = 2.898, 95% CI 1.946-4.315, p < 0.05) was identified as a risk factor for sepsis. A clinical model identified TBA (the cut-off value is >17.95 µmol/L) as an independent predictor of sepsis mortality with an AUC of 0.842 (95% CI 0.800-0.883), sensitivity of 54.9%, specificity of 96.6%, and HR = 7.658 (95% CI 5.575-10.520).

CONCLUSIONS

The study showed that elevated TBA was associated with a heightened risk of mortality in pediatric sepsis.

IMPACT

Many clinical indicators show differences between children with sepsis and the control group, among which the difference in serum total bile acid levels is the most significant. During the hospitalization of the patients, the overall bile acid levels in the sepsis death group were higher and exhibited greater fluctuations compared to the survival group, with significant differences. Serum total bile acid levels can serve as effective biomarker for predicting the prognosis of children with sepsis.

Suppression of overactivated immunity in the early stage is the key to improve the prognosis in severe burns

Background

Severe burns can lead to systemic inflammatory response syndrome (SIRS) and multiple organ dysfunction syndrome (MODS) due to inflammation-immunity dysregulation. This study aimed to identify key immune-related molecules and potential drugs for immune regulation in severe burn treatment.

Method

Microarray datasets GSE77791 and GSE37069 were analyzed to identify immune-related differentially expressed genes (DEGs), enriched pathways and prognosis-related genes. The DGIdb database was used to identify potentially clinically relevant small molecular drugs for hub DEGs. Hub DEGs were validated by total RNA from clinical blood samples through qPCR. The efficacy of drug candidates was tested in a severe burn mouse model. Pathologic staining was used to observe organ damage. Enzyme Linked Immunosorbent Assay (ELISA) was used to detect the serum IL-1b, IL-6, TNF-a and MCP-1 contents. Activation of the NF-κB inflammatory pathway was detected by western blotting. Transcriptome sequencing was used to observe inflammatory-immune responses in the lung.

Results

A total of 113 immune-related DEGs were identified, and the presence of immune overactivation was confirmed in severe burns. S100A8 was not only significantly upregulated and identified to be prognosis-related among the hub DEGs but also exhibited an increasing trend in clinical blood samples. Methotrexate, which targets S100A8, as predicted by the DGIdb, significantly reduces transcription level of S100A8 and inflammatory cytokine content in blood, organ damage (lungs, liver, spleen, and kidneys) and mortality in severely burned mice when combined with fluid resuscitation. The inflammatory-immune response was suppressed in the lungs.

Conclusion

S100A8 with high transcription level in blood is a potential biomarker for poor severe burn prognosis. It suggested that methotrexate has a potential application in severe burn immunotherapy. Besides, it should be emphasized that fluid resuscitation is necessary for the function of methotrexate.

Hyperoxia in Sepsis and Septic Shock: A Comprehensive Review of Clinical Evidence and Therapeutic Implications

Sepsis and septic shock are leading causes of mortality in intensive care units, characterized by a dysregulated immune response to infection, leading to severe organ dysfunction. Oxygen therapy is a cornerstone of supportive care in sepsis management, aimed at correcting hypoxemia and improving tissue oxygenation. However, the administration of supplemental oxygen must be carefully managed to avoid hyperoxia, which can lead to oxidative stress and additional tissue damage. This review aims to comprehensively analyze the clinical evidence regarding hyperoxia in the context of sepsis and septic shock, evaluating its potential therapeutic benefits and risks and discussing the implications for clinical practice. A thorough literature review included observational studies, randomized controlled trials (RCTs), meta-analyses, and clinical guidelines. The review focuses on the pathophysiology of sepsis, the mechanisms of hyperoxia-induced injury, and the clinical outcomes associated with different oxygenation strategies. The evidence suggests that while oxygen is crucial in managing sepsis, the risk of hyperoxia-related complications is significant. Hyperoxia has been associated with increased mortality and adverse outcomes in septic patients due to mechanisms such as oxidative stress, impaired microcirculation, and potential worsening of organ dysfunction. RCTs and meta-analyses indicate that conservative oxygen therapy may be beneficial in reducing these risks, though optimal oxygenation targets remain under investigation. This review highlights the importance of careful oxygen management in sepsis and septic shock, emphasizing the need for individualized oxygen therapy to avoid the dangers of hyperoxia. Further research is required to refine oxygenation strategies, establish clear clinical guidelines, and optimize outcomes for sepsis and septic shock patients. Balancing adequate oxygenation with the prevention of hyperoxia-induced injury is crucial in improving the prognosis of these critically ill patients.

Synergistic impact of innate immunity hyper-activation and endothelial dysfunction on the magnitude of organ failure in the infection-sepsis continuum

OBJECTIVES

Identifying host response biomarkers implicated in the emergence of organ failure during infection is key to improving the early detection of this complication.

METHODS

Twenty biomarkers of innate immunity, T-cell response, endothelial dysfunction, coagulation, and immunosuppression were profiled in 180 surgical patients with infections of diverse severity (IDS) and 53 with no infection (nIDS). Those better differentiating IDS/nIDS in the area under the curve were combined to test their association with the sequential organ failure assessment score by linear regression analysis in IDS. Results were validated in another IDS cohort of 174 patients.

RESULTS

C-reactive protein, procalcitonin, pentraxin-3, lipocalin-2 (LCN2), tumoral necrosis factor-α, angiopoietin-2, triggering receptor expressed on myeloid cells-1 (TREM-1) and interleukin (IL)-15 yielded an area under the curve ≥0.75 to differentiate IDS from nIDS. The combination of LCN2, IL-15, TREM-1, angiopoietin-2 (Dys-4) showed the strongest association with sequential organ failure assessment score in IDS (adjusted regression coefficient; standard error; P): Dys-4 (3.55;0.44; <0.001), LCN2 (2.24; 0.28; <0.001), angiopoietin-2 (1.92; 0.33; <0.001), IL-15 (1.78; 0.40; <0.001), TREM-1(1.74; 0.46; <0.001), tumoral necrosis factor-α (1.60; 0.31; <0.001), pentraxin-3 (1.12; 0.18; <0.001), procalcitonin (0.85; 0.12; <0.001). Dys-4 provided similar results in the validation cohort.

CONCLUSIONS

There is a synergistic impact of innate immunity hyper-activation (LCN2, IL-15, TREM-1) and endothelial dysfunction (angiopoietin-2) on the magnitude of organ failure during infection.

Development of a biomarker prediction model for post-trauma multiple organ failure/dysfunction syndrome based on the blood transcriptome

BACKGROUND

Multiple organ failure/dysfunction syndrome (MOF/MODS) is a major cause of mortality and morbidity among severe trauma patients. Current clinical practices entail monitoring physiological measurements and applying clinical score systems to diagnose its onset. Instead, we aimed to develop an early prediction model for MOF outcome evaluated soon after traumatic injury by performing machine learning analysis of genome-wide transcriptome data from blood samples drawn within 24 h of traumatic injury. We then compared its performance to baseline injury severity scores and detection of infections.

METHODS

Buffy coat transcriptome and linked clinical datasets from blunt trauma patients from the Inflammation and the Host Response to Injury Study ("Glue Grant") multi-center cohort were used. According to the inclusion/exclusion criteria, 141 adult (age ≥ 16 years old) blunt trauma patients (excluding penetrating) with early buffy coat (≤ 24 h since trauma injury) samples were analyzed, with 58 MOF-cases and 83 non-cases. We applied the Least Absolute Shrinkage and Selection Operator (LASSO) and eXtreme Gradient Boosting (XGBoost) algorithms to select features and develop models for MOF early outcome prediction.

RESULTS

The LASSO model included 18 transcripts (AUROC [95% CI]: 0.938 [0.890-0.987] (training) and 0.833 [0.699-0.967] (test)), and the XGBoost model included 41 transcripts (0.999 [0.997-1.000] (training) and 0.907 [0.816-0.998] (test)). There were 16 overlapping transcripts comparing the two panels (0.935 [0.884-0.985] (training) and 0.836 [0.703-0.968] (test)). The biomarker models notably outperformed models based on injury severity scores and sex, which we found to be significantly associated with MOF (APACHEII + sex-0.649 [0.537-0.762] (training) and 0.493 [0.301-0.685] (test); ISS + sex-0.630 [0.516-0.744] (training) and 0.482 [0.293-0.670] (test); NISS + sex-0.651 [0.540-0.763] (training) and 0.525 [0.335-0.714] (test)).

CONCLUSIONS

The accurate assessment of MOF from blood samples immediately after trauma is expected to aid in improving clinical decision-making and may contribute to reduced morbidity, mortality and healthcare costs. Moreover, understanding the molecular mechanisms involving the transcripts identified as important for MOF prediction may eventually aid in developing novel interventions.

Sepsis Biomarkers: Advancements and Clinical Applications-A Narrative Review

Sepsis is now defined as a life-threatening syndrome of organ dysfunction triggered by a dysregulated host response to infection, posing significant challenges in critical care. The main objective of this review is to evaluate the potential of emerging biomarkers for early diagnosis and accurate prognosis in sepsis management, which are pivotal for enhancing patient outcomes. Despite advances in supportive care, traditional biomarkers like C-reactive protein and procalcitonin have limitations, and recent studies have identified novel biomarkers with increased sensitivity and specificity, including circular RNAs, HOXA distal transcript antisense RNA, microRNA-486-5p, protein C, triiodothyronine, and prokineticin 2. These emerging biomarkers hold promising potential for the early detection and prognostication of sepsis. They play a crucial role not only in diagnosis but also in guiding antibiotic therapy and evaluating treatment effectiveness. The introduction of point-of-care testing technologies has brought about a paradigm shift in biomarker application, enabling swift and real-time patient evaluation. Despite these advancements, challenges persist, notably concerning biomarker variability and the lack of standardized thresholds. This review summarizes the latest advancements in sepsis biomarker research, spotlighting the progress and clinical implications. It emphasizes the significance of multi-biomarker strategies and the feasibility of personalized medicine in sepsis management. Further verification of biomarkers on a large scale and their integration into clinical practice are advocated to maximize their efficacy in future sepsis treatment.

Clostridioides difficile Infection: Use of Inflammatory Biomarkers and Hemogram-Derived Ratios to Predict Mortality Risk in Hospitalized Patients

BACKGROUND

Clostridioides difficile infection (CDI) is a significant cause of mortality, especially in healthcare environments. Reliable biomarkers that can accurately predict mortality in CDI patients are yet to be evaluated. Our study aims to evaluate the accuracy of several inflammatory biomarkers and hemogram-derived ratios in predicting mortality in CDI patients, such as the neutrophil-to-lymphocyte ratio (NLR), the systemic immune-inflammation index (SII), the platelet-to-neutrophil ratio (PNR), the derived neutrophil-to-lymphocyte ratio (dNLR), C-reactive protein (CRP), the platelet-to-lymphocyte ratio (PLR), and procalcitonin (PCT).

RESULTS

NLR showed a sensitivity of 72.5% and a specificity of 58.42% with an area under curve (AUC) = 0.652. SII had a sensitivity of 77.5%, a specificity of 54.74%, and an AUC = 0.64. PNR, neutrophils, dNLR, and lymphocytes had lower AUCs which ranged from 0.595 to 0.616, with varied sensitivity and specificity. CRP, leukocytes, and platelets showed modest predictive values with AUCs below 0.6. PCT had a sensitivity of 100%, a low specificity of 7.41%, and an AUC = 0.528.

METHODS

We conducted a retrospective analysis of CDI patients from two different hospital settings in Italy and Romania during the COVID-19 pandemic, from 1 January 2020 to 5 May 2023. Statistical analyses included t-tests, Wilcoxon rank-sum tests, χ2 tests, and multivariate logistic regression to identify predictors of mortality. ROC analysis assessed the accuracy of biomarkers and hemogram-derived ratios. A p value < 0.05 was considered significant.

CONCLUSIONS

Neutrophils, dNLR, NLR, SII, and PNR are valuable biomarkers for predicting mortality in CDI patients. Understanding these predictors can improve risk stratification and clinical outcomes for CDI patients.

Biomarkers in sepsis

Sepsis is a life-threatening condition characterized by dysregulated host response to infection leading to organ dysfunction. Despite advances in understanding its pathology, sepsis remains a global health concern and remains a major contributor to mortality. Timely identification is crucial for improving clinical outcomes, as delayed treatment significantly impacts survival. Accordingly, biomarkers play a pivotal role in diagnosis, risk stratification, and management. This review comprehensively discusses various biomarkers in sepsis and their potential application in antimicrobial stewardship and risk assessment. Biomarkers such as white blood cell count, neutrophil to lymphocyte ratio, erythrocyte sedimentation rate, C-reactive protein, interleukin-6, presepsin, and procalcitonin have been extensively studied for their diagnostic and prognostic value as well as in guiding antimicrobial therapy. Furthermore, this review explores the role of biomarkers in risk stratification, emphasizing the importance of identifying high-risk patients who may benefit from specific therapeutic interventions. Moreover, the review discusses the emerging field of transcriptional diagnostics and metagenomic sequencing. Advances in sequencing have enabled the identification of host response signatures and microbial genomes, offering insight into disease pathology and aiding species identification. In conclusion, this review provides a comprehensive overview of the current understanding and future directions of biomarker-based approaches in sepsis diagnosis, management, and personalized therapy.

Circulating inflammatory cytokines and the risk of sepsis: a bidirectional mendelian randomization analysis

BACKGROUND

Sepsis is a life-threatening condition that is characterized by multiorgan dysfunction and caused by dysregulated cytokine networks, which are closely associated with sepsis progression and outcomes. However, currently available treatment strategies that target cytokines have failed. Thus, this study aimed to investigate the interplay between genetically predicted circulating concentrations of cytokines and the outcomes of sepsis and to identify potential targets for sepsis treatment.

METHODS

Data related to 35 circulating cytokines in 31,112 individuals (including 11,643 patients with sepsis) were included in genome-wide association studies (GWASs) from the UK Biobank and FinnGen consortia. A bidirectional two-sample Mendelian randomization (MR) analysis was performed using single nucleotide polymorphisms (SNPs) to evaluate the causal effects of circulating cytokines on sepsis outcomes and other cytokines.

RESULTS

A total of 35 inflammatory cytokine genes were identified in the GWASs, and 11 cytokines, including Interleukin-1 receptor antagonist (IL-1ra), macrophage inflammatory protein 1 (MIP1α), IL-16, et al., were associated with sepsis outcome pairs according to the selection criteria of the cis-pQTL instrument. Multiple MR methods verified that genetically predicted high circulating levels of IL-1ra or MIP1α were negatively correlated with genetic susceptibility to risk of sepsis, including sepsis (28-day mortality), septicaemia, streptococcal and pneumonia-derived septicaemia (P ≤ 0.01). Furthermore, genetic susceptibility of sepsis outcomes except sepsis (28-day mortality) markedly associated with the circulating levels of five cytokines, including active plasminogen activator inhibitor (PAI), interleukin 7 (IL-7), tumour necrosis factor alpha (TNF-α), beta nerve growth factor (NGF-β), hepatic growth factor (HGF) (P < 0.05). Finally, we observed that the causal interaction network between MIP1α or IL-1ra and other cytokines (P < 0.05).

CONCLUSIONS

This comprehensive MR analysis provides insights into the potential causal mechanisms that link key cytokines, particularly MIP1α, with risk of sepsis, and the findings suggest that targeting MIP1α may be a potential strategy for preventing sepsis.

Knockdown of SDC-1 Gene Alleviates the Metabolic Pathway for the Development of MODS

This study aims to reveal the metabolic differences between SDC-1 knockout mice and wild-type mice and the metabolic differences caused by shock in SDC-1 knockout mice by integrating transcriptomics and metabolomics. A total of 1009 differential metabolites were differentially expressed based on untargeted metabolomics and high-resolution mass spectrometry detection techniques. According to Kyoto Encyclopedia of Genes and Genomes enrichment, SDC-1 knockout significantly altered fat digestion and absorption, GnRH signaling pathway, fructose and mannose metabolism, and some other amino-related metabolic pathways and significantly modulated positively regulated longevity regulatory pathways, longevity regulatory pathways-worm, nicotinamide and niacinamide metabolism, and vitamin digestion and absorption pathways after its shock. Our findings indicate that SDC-1 knockout may have potential therapeutic effects in hemorrhagic shock by increasing nicotinamide metabolism.

Machine Learning Screening and Validation of PANoptosis-Related Gene Signatures in Sepsis

Background

Sepsis is a syndrome marked by life-threatening organ dysfunction and a disrupted host immune response to infection. PANoptosis is a recent conceptual development, which emphasises the interconnectedness among multiple programmed cell deaths in various diseases. Nevertheless, the role of PANoptosis in sepsis is still unclear.

Methods

We utilized the GSE65682 dataset to identify PANoptosis-related genes (PRGs) and associated immune characteristics in sepsis, classified sepsis samples based on PRGs using the ConsensusClusterPlus method and applied the Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm to identify cluster-specific hub genes. Based on PANoptosis -specific DEGs, we compared results from machine learning models and the best-performing model was selected. Predictive efficiency was validated through external dataset, nomogram, survival analysis, quantitative real-time PCR, and western blot.

Results

The expression levels of PRGs were generally dysregulated in sepsis patients compared with normal samples, and higher PRGs expression correlated with increased immune cell infiltration. In addition, two distinct PANoptosis-related clusters were defined, and functional analysis indicated that DEGs associated with these clusters were primarily linked to immune-related pathways. The SVM model was selected as best-performing model, with lower residuals and the highest area under the curve (AUC = 0.967), which was then validated in an external dataset (AUC = 0.989) and through in vivo experiments. Additional validation through nomogram and survival analysis further confirmed its substantial predictive efficacy.

Conclusion

Our findings exposed the intricate association between PANoptosis and sepsis, offering important insights on sepsis diagnosis and potential therapeutic targets.

Navigating the Modern Landscape of Sepsis: Advances in Diagnosis and Treatment

Sepsis poses a significant threat to human health due to its high morbidity and mortality rates worldwide. Traditional diagnostic methods for identifying sepsis or its causative organisms are time-consuming and contribute to a high mortality rate. Biomarkers have been developed to overcome these limitations and are currently used for sepsis diagnosis, prognosis prediction, and treatment response assessment. Over the past few decades, more than 250 biomarkers have been identified, a few of which have been used in clinical decision-making. Consistent with the limitations of diagnosing sepsis, there is currently no specific treatment for sepsis. Currently, the general treatment for sepsis is conservative and includes timely antibiotic use and hemodynamic support. When planning sepsis-specific treatment, it is important to select the most suitable patient, considering the heterogeneous nature of sepsis. This comprehensive review summarizes current and evolving biomarkers and therapeutic approaches for sepsis.

Association between admission pan-immune-inflammation value and short-term mortality in septic patients: a retrospective cohort study

Pan-Immune-Inflammation Value (PIV) has recently received more attention as a novel indicator of inflammation. We aimed to evaluate the association between PIV and prognosis in septic patients. Data were extracted from the Medical Information Mart for Intensive Care IV database. The primary and secondary outcomes were 28-day and 90-day mortality. The association between PIV and outcomes was assessed by Kaplan-Meier curves, Cox regression analysis, restricted cubic spline curves and subgroup analysis. A total of 11,331 septic patients were included. Kaplan-Meier curves showed that septic patients with higher PIV had lower 28-day survival rate. In multivariable Cox regression analysis, log2-PIV was positively associated with the risk of 28-day mortality [HR (95% CI) 1.06 (1.03, 1.09), P < 0.001]. The relationship between log2-PIV and 28-day mortality was non-linear with a predicted inflection point at 8. To the right of the inflection point, high log2-PIV was associated with an increased 28-day mortality risk [HR (95% CI) 1.13 (1.09, 1.18), P < 0.001]. However, to the left of this point, this association was non-significant [HR (95% CI) 1.01 (0.94, 1.08), P = 0.791]. Similar results were found for 90-day mortality. Our study showed a non-linear relationship between PIV and 28-day and 90-day mortality risk in septic patients.

Protracted fibrinolysis resistance following cardiac surgery with cardiopulmonary bypass: A prospective observational study of clinical associations and patient outcomes

BACKGROUND

Surgery on cardiopulmonary bypass (CPB) elicits a pleiomorphic systemic host response which, when severe, requires prolonged intensive care support. Given the substantial cross-talk between inflammation, coagulation, and fibrinolysis, the aim of this hypothesis-generating observational study was to document the kinetics of fibrinolysis recovery post-CPB using ClotPro® point-of-care viscoelastometry. Tissue plasminogen activator-induced clot lysis time (TPA LT, s) was correlated with surgical risk, disease severity, organ dysfunction and intensive care length of stay (ICU LOS).

RESULTS

In 52 patients following CPB, TPA LT measured on the first post-operative day (D1) correlated with surgical risk (EuroScore II, Spearman's rho .39, p < .01), time on CPB (rho = .35, p = .04), disease severity (APACHE II, rho = .52, p < .001) and organ dysfunction (SOFA, rho = .51, p < .001) scores, duration of invasive ventilation (rho = .46, p < .01), and renal function (eGFR, rho = -.65, p < .001). In a generalized linear regression model containing TPA LT, CPB run time and markers of organ function, only TPA LT was independently associated with the ICU LOS (odds ratio 1.03 [95% CI 1.01-1.05], p = .01). In a latent variables analysis, the association between TPA LT and the ICU LOS was not mediated by renal function and thus, by inference, variation in the clearance of intraoperative tranexamic acid.

CONCLUSIONS

This observational hypothesis-generating study in patients undergoing cardiac surgery with cardiopulmonary bypass demonstrated an association between the severity of fibrinolysis resistance, measured on the first post-operative day, and the need for extended postoperative ICU level support. Further examination of the role of persistent fibrinolysis resistance on the clinical outcomes in this patient cohort is warranted through large-scale, well-designed clinical studies.

Beyond the Horizon: A Comprehensive Review of Contemporary Strategies in Sepsis Management Encompassing Predictors, Diagnostic Tools, and Therapeutic Advances

This comprehensive review offers a detailed exposition of contemporary strategies in sepsis management, encompassing predictors, diagnostic tools, and therapeutic advances. The analysis elucidates the dynamic nature of sepsis, emphasizing the crucial role of early detection and intervention. The multifaceted strategies advocate for a holistic and personalized approach to sepsis care from traditional clinical methodologies to cutting-edge technologies. The implications for clinical practice underscore clinicians' need to adapt to evolving definitions, integrate advanced diagnostic tools, and embrace precision medicine. Integrating artificial intelligence and telemedicine necessitates a commitment to training and optimization. Judicious antibiotic use and recognition of global health disparities emphasize the importance of a collaborative, global effort in sepsis care. Looking ahead, recommendations for future research underscore priorities such as longitudinal studies on biomarkers, precision medicine trials, implementation science in technology, global health interventions, and innovative antibiotic stewardship strategies. These research priorities aim to contribute to transformative advancements in sepsis management, ultimately enhancing patient outcomes and reducing the global impact of this critical syndrome.

Oral Treatment with the Pectin Fibre Obtained from Yellow Passion Fruit Peels Worsens Sepsis Outcome in Mice by Affecting the Intestinal Barrier

The biological activities of plant-derived soluble dietary fibres (SDFs) have been widely investigated. Pectin from yellow passion fruit (YPF-peSDF) peels was suggested as a protective macromolecule in ulcers and colitis due to its antioxidant and anti-inflammatory properties. Sepsis has high mortality and morbidity and is characterised by inflammatory and oxidative stress imbalances. Evidence suggests that pectins may aid sepsis treatment; however, the effects of YPF-peSDF on sepsis remain unclear. Herein, polymicrobial sepsis was induced by cecal-ligation and puncture in mice treated with YPF-peSDF (1 and 10 mg/kg; gavage). YPF-peSDF accelerated mortality, reaching 100% in 24 h. Inflammation was present in the colons and small intestines (SI) of both vehicle- and fibre-treated mice. Although crypt depth and width, and villus height were preserved in the SI of septic mice administered YPF-peSDF, they exhibited exacerbated muscle layer atrophy and mucosa and submucosa hypertrophy, along with shortened enterocytes. Larger crypts and shorter enterocytes were noted in their colons in comparison with vehicle-controls. YPF-peSDF also reduced inflammatory cell numbers and exacerbated IL-6 levels in peritoneal lavage fluid (PELF) samples. YPF-peSDF modulated SI but not colon cytokines. Lipoperoxidation and antioxidant capacity levels were attenuated in PELF samples. Overall, in contrast to previous evidence, YPF-peSDF worsened polymicrobial sepsis outcomes in mice.

Combination of Creatinine with Inflammatory Biomarkers (PCT, CRP, hsCRP) for Predicting Postoperative ICU Admissions for Elderly Patients

INTRODUCTION

The number of elderly patients who require surgery as their primary treatment has increased rapidly in recent years. Among 300 million people globally who underwent surgery every year, patients aged 65 years and over accounted for more than 30% of cases. Despite medical advances, older patients remain at higher risk of postoperative complications. Early diagnosis and effective prediction are essential requirements for preventing serious postoperative complications. In this study, we aim to provide new biomarker combinations to predict the incidence of postoperative intensive care unit (ICU) admissions > 24 h in elderly patients.

METHODS

This investigation was conducted as a nested case-control study, incorporating 413 participants aged ≥ 65 years who underwent non-cardiac, non-urological elective surgeries. These individuals underwent a 30-day postoperative follow-up. Before surgery, peripheral venous blood was collected for analyzing serum creatinine (Scr), procalcitonin (PCT), C-reactive protein (CRP), and high-sensitivity CRP (hsCRP). The efficacy of these biomarkers in predicting postoperative complications was evaluated using receiver operating characteristic (ROC) curve analysis and area under the curve (AUC) values.

RESULTS

Postoperatively, 10 patients (2.42%) required ICU admission. Regarding ICU admissions, the AUCs with 95% confidence intervals (CIs) for the biomarker combinations of Scr × PCT and Scr × CRP were 0.750 (0.655-0.845, P = 0.007) and 0.724 (0.567-0.882, P = 0.015), respectively. Furthermore, cardiovascular events were observed in 14 patients (3.39%). The AUC with a 95% CI for the combination of Scr × CRP in predicting cardiovascular events was 0.688 (0.560-0.817, P = 0.017).

CONCLUSION

The innovative combinations of biomarkers (Scr × PCT and Scr × CRP) demonstrated efficacy as predictors for postoperative ICU admissions in elderly patients. Additionally, the Scr × CRP also had a moderate predictive value for postoperative cardiovascular events.

TRIAL REGISTRATION

China Clinical Trial Registry, ChiCTR1900026223.