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Abstract Sepsis represents a critical medical condition stemming from an imbalanced host immune response to infections, which is linked to a significant burden of disease. Despite substantial efforts in laboratory and clinical research, sepsis remains a prominent contributor to mortality worldwide. Nanotechnology presents innovative opportunities for the advancement of sepsis diagnosis and treatment. Due to their unique properties, including diversity, ease of synthesis, biocompatibility, high specificity, and excellent pharmacological efficacy, peptides hold great potential as part of nanotechnology approaches against sepsis. Herein, we present a comprehensive and up-to-date review of the applications of peptides in nanosystems for combating sepsis, with the potential to expedite diagnosis and enhance management outcomes. Firstly, sepsis pathophysiology, antisepsis drug targets, current modalities in management and diagnosis with their limitations, and the potential of peptides to advance the diagnosis and management of sepsis have been adequately addressed. The applications have been organized into diagnostic or managing applications, with the last one being further sub-organized into nano-delivered bioactive peptides with antimicrobial or anti-inflammatory activity, peptides as targeting moieties on the surface of nanosystems against sepsis, and peptides as nanocarriers for antisepsis agents. The studies have been grouped thematically and discussed, emphasizing the constructed nanosystem, physicochemical properties, and peptide-imparted enhancement in diagnostic and therapeutic efficacy. The strengths, limitations, and research gaps in each section have been elaborated. Finally, current challenges and potential future paths to enhance the use of peptides in nanosystems for combating sepsis have been deliberately spotlighted. This review reaffirms peptides' potential as promising biomaterials within nanotechnology strategies aimed at improving sepsis diagnosis and management. Graphical Abstract

Sepsis represents a critical medical condition stemming from an imbalanced host immune response to infections, which is linked to a significant burden of disease. Despite substantial efforts in laboratory and clinical research, sepsis remains a prominent contributor to mortality worldwide. Nanotechnology presents innovative opportunities for the advancement of sepsis diagnosis and treatment. Due to their unique properties, including diversity, ease of synthesis, biocompatibility, high specificity, and excellent pharmacological efficacy, peptides hold great potential as part of nanotechnology approaches against sepsis. Herein, we present a comprehensive and up-to-date review of the applications of peptides in nanosystems for combating sepsis, with the potential to expedite diagnosis and enhance management outcomes. Firstly, sepsis pathophysiology, antisepsis drug targets, current modalities in management and diagnosis with their limitations, and the potential of peptides to advance the diagnosis and management of sepsis have been adequately addressed. The applications have been organized into diagnostic or managing applications, with the last one being further sub-organized into nano-delivered bioactive peptides with antimicrobial or anti-inflammatory activity, peptides as targeting moieties on the surface of nanosystems against sepsis, and peptides as nanocarriers for antisepsis agents. The studies have been grouped thematically and discussed, emphasizing the constructed nanosystem, physicochemical properties, and peptide-imparted enhancement in diagnostic and therapeutic efficacy. The strengths, limitations, and research gaps in each section have been elaborated. Finally, current challenges and potential future paths to enhance the use of peptides in nanosystems for combating sepsis have been deliberately spotlighted. This review reaffirms peptides' potential as promising biomaterials within nanotechnology strategies aimed at improving sepsis diagnosis and management. Highlights: • Due to their unique characteristics, Peptides hold significant promise as part of nanotechnology approaches for diagnosing and treating sepsis, a current leading global killer. • Various diagnostic nanotools utilizing peptides as pathogen recognition moieties can improve the pathogen capturing efficiency for sepsis diagnosis. • Nano-delivery can overcome the limitations of bioactive peptides and enhance their antibacterial and anti-inflammatory efficacy in sepsis management. • Peptides offer significant capabilities as targeting moieties and nanocarriers to augment the effectiveness of antisepsis agents. • Future research identified can potentiate the applications of peptides for the diagnosis and treatment of sepsis. [ABSTRACT FROM AUTHOR]

Sepsis is an immune response to a microbial invasion that causes organ injury and dysfunction due to a systemic inflammatory response. Sepsis is a serious, life-threatening condition and a widely recognized global health challenge. Given its high death rate, it is critical to diagnose sepsis and start treatment as early as possible. There is an urgent need for a sensitive and rapid screening method for detecting sepsis. In this study, we investigated the use of MMP-9 as a biomarker for sepsis. A colorimetric paper-based biosensor was used for the detection of MMP-9 utilizing peptide-magnetic nanoparticle conjugates. The method is based on the cleavage of the MMP-9-specific peptide by the protease leading to the detaching of the magnetic beads from the sensor surface and changing of color. A fecal intraperitoneal (FIP) challenge was used to induce sepsis in mice, and an MMP-9 secretion was measured by taking blood and Bronchoalveolar Lavage (BAL) fluid samples at 1 h, 2 h, 4 h, and 20 h (early sepsis) post-challenge intervals. The results of the paper-based sensor for the detection of MMP-9 levels in blood samples and BAL samples were compared with ELISA and Western Blot. We found that both blood and BAL levels of MMP-9 increased immediately and could be detected as early as 1 h in FIP mice post-challenge. Our work adds evidence to the assertion that MMP-9 is a reliable biomarker for the detection of sepsis at early stages. [ABSTRACT FROM AUTHOR]

Sepsis is an immune response to a microbial invasion that causes organ injury and dysfunction due to a systemic inflammatory response. Sepsis is a serious, life-threatening condition and a widely recognized global health challenge. Given its high death rate, it is critical to diagnose sepsis and start treatment as early as possible. There is an urgent need for a sensitive and rapid screening method for detecting sepsis. In this study, we investigated the use of MMP-9 as a biomarker for sepsis. A colorimetric paper-based biosensor was used for the detection of MMP-9 utilizing peptide-magnetic nanoparticle conjugates. The method is based on the cleavage of the MMP-9-specific peptide by the protease leading to the detaching of the magnetic beads from the sensor surface and changing of color. A fecal intraperitoneal (FIP) challenge was used to induce sepsis in mice, and an MMP-9 secretion was measured by taking blood and Bronchoalveolar Lavage (BAL) fluid samples at 1 h, 2 h, 4 h, and 20 h (early sepsis) post-challenge intervals. The results of the paper-based sensor for the detection of MMP-9 levels in blood samples and BAL samples were compared with ELISA and Western Blot. We found that both blood and BAL levels of MMP-9 increased immediately and could be detected as early as 1 h in FIP mice post-challenge. Our work adds evidence to the assertion that MMP-9 is a reliable biomarker for the detection of sepsis at early stages.

Blood stream infections (BSIs) cause high mortality, and their rapid detection remains a significant diagnostic challenge. Timely and informed administration of antibiotics can significantly improve patient outcomes. However, blood culture, which takes up to 5 d for a negative result, followed by PCR remains the gold standard in diagnosing BSI. Here, we introduce a new approach to blood-based diagnostics where large blood volumes can be rapidly dried, resulting in inactivation of the inhibitory components in blood. Further thermal treatments then generate a physical microscale and nanoscale fluidic network inside the dried matrix to allow access to target nucleic acid. The amplification enzymes and primers initiate the reaction within the dried blood matrix through these networks, precluding any need for conventional nucleic acid purification. High heme background is confined to the solid phase, while amplicons are enriched in the clear supernatant (liquid phase), giving fluorescence change comparable to purified DNA reactions. We demonstrate single-molecule sensitivity using a loop-mediated isothermal amplification reaction in our platform and detect a broad spectrum of pathogens, including gram-positive methicillin-resistant and methicillin-susceptible Staphylococcus aureus bacteria, gram-negative Escherichia coli bacteria, and Candida albicans (fungus) from whole blood with a limit of detection (LOD) of 1.2 colony-forming units (CFU)/mL from 0.8 to 1 mL of starting blood volume. We validated our assay using 63 clinical samples (100% sensitivity and specificity) and significantly reduced sample-to-result time from over 20 h to <2.5 h. The reduction in instrumentation complexity and costs compared to blood culture and alternate molecular diagnostic platforms can have broad applications in healthcare systems in developed world and resource-limited settings. [ABSTRACT FROM AUTHOR]

Abstract Background This study aimed to assess the predictive power of three different Sepsis Scoring Systems (SSSs), namely maternity Systematic Inflammatory Response Syndrome (mSIRS), quick Sepsis-related Organ Failure Assessment (qSOFA) and Modified Early Warning System (MEWS) in identifying sepsis by comparing them with positive culture. This study also sought to evaluate compliance with using the Sepsis Six Care Bundle (SSCB) operated in an individual health board. Methods A retrospective cohort study was conducted in 3 maternity hospitals of a single Scottish health board that admitted 2690 pregnancies in a 12 weeks period in 2016. Data for study was obtained from medical notes, handheld and electronic health records for women who were prescribed antibiotics with a confirmed or suspected diagnosis of sepsis. Data on clinical parameters was used to classify women according to mSIRS, qSOFA and MEWS as having sepsis or not and this was compared to results of positive culture to obtain sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and area under Receiver Operating Characteristic curve (AUROC) along with their 95% confidence intervals. Data was also obtained on SSCB compliance. Results A total of 89 women were diagnosed with sepsis, of which 14 had missing data, leaving 75 for final analysis. Sensitivity, specificity, PPV, NPV and AUROC of mSIRS and MEWS were almost similar with AUROC of both being around 50%. Only 33 (37.1%) had identifiable sepsis six sticker displayed on medical notes and only 2 (2.2%) had all elements of SSCB delivered within the recommended one-hour post-diagnosis period. Blood culture and full blood count with other lab tests had been performed for most women (97%) followed by intravenous antibiotics and fluids (93.9%). Conclusions mSIRS and MEWS were quite similar in detecting sepsis when compared to positive culture, with their ability to detect sepsis being close to chance. This underlines the need for creating a valid SSS with high sensitivity and specificity for clinical use in obstetric settings. Clinical use of SSCB was limited despite it being a health board policy, although there is considerable possibility of improvement following detailed audits and removal of barriers for implementing SSCB.

Background: Sepsis is a disease characterized by infection-induced multiorgan dysfunction, which can progress to septic shock if not promptly treated. Early identification of sepsis is crucial for its treatment. However, there are currently limited specific biomarkers for sepsis or septic shock. This study aims to identify potential biomarkers for sepsis and septic shock., Methods: We analyzed single-cell transcriptomic data of peripheral blood mononuclear cells (PBMCs) from healthy individuals, sepsis and septic shock patients, identified differences in gene expression and cell-cell communication between different cell types during disease progression. Moreover, our analyses were further validated with flow cytometry and bulk RNA-seq data., Results: Our study elucidates the alterations in cellular proportions and cell-cell communication among healthy controls, sepsis, and septic shock patients. We identified a specific augmentation in the Resistin signaling within sepsis monocytes, mediated via RETN-CAP1 ligand-receptor pairs. Additionally, we observed enhanced IL16 signaling within monocytes from septic shock patients, mediated through IL16-CD4 ligand-receptor pairs. Subsequently, we confirmed our findings by validating the increase in CAP-1 + monocytes in sepsis and IL16 + monocytes in septic shock in mouse models. And a significant upregulation of CAP-1 and IL16 was also observed in the bulk RNA-seq data from patients with sepsis and septic shock. Furthermore, we identified four distinct clusters of CD14 + monocytes, highlighting the heterogeneity of monocytes in the progress of sepsis., Conclusions: In summary, our work demonstrates changes in cell-cell communication of healthy controls, sepsis and septic shock, confirming that the molecules CAP-1 and IL16 on monocytes may serve as potential diagnostic markers for sepsis and septic shock, respectively. These findings provide new insights for early diagnosis and stratified treatment of the disease., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The objective of this study was to investigate the value of the lactate to albumin ratio (L:A) as a prognostic marker for mortality in septic dogs. A single-center retrospective case-control study based on clinical record review was conducted at an academic teaching hospital. All records were extracted for diagnoses of bacterial sepsis, septic peritonitis, septic shock, or septicemia between February 2012 and October 2021. The study included 143 dogs. The most commonly identified sepsis diagnoses in dogs were septic peritonitis (55%; 78/143), unclassified sepsis (20%), and sepsis secondary to wounds or dermatological conditions (10%; 15/143). Median lactate and albumin for all dogs at presentation were 2.80 mmol/L and 2.6 g/dL, respectively; the median L:A ratio was 1.22. No clinically or statistically significant differences in lactate (P = 0.631), albumin (P = 0.695), or L:A (P = 0.908) were found between survivors and nonsurvivors., (© 2024 by American Animal Hospital Association.)

Abstract: Purpose : The objective of this study is to establish a nomogram that correlates optimized Acute Physiology and Chronic Health Evaluation II (APACHE II) score with sepsis-related indicators, aiming to provide a robust model for early prediction of sepsis prognosis in clinical practice and serve as a valuable reference for improved diagnosis and treatment strategies. Methods : This retrospective study extracted sepsis patients meeting the inclusion criteria from the MIMIC-IV database to form the training group. An optimized APACHE II score integrated with relevant indicators was developed using a nomogram for predicting the prognosis of sepsis patients. External validation was conducted using data from the intensive care unit at Lanzhou University Second Hospital. Results : The study enrolled 1805 patients in the training cohort and 203 patients in the validation cohort. A multifactor analysis was conducted to identify factors affecting patient mortality within 28 days, resulting in the development of an optimized score by simplifying evaluation indicators from APACHE II score. The results showed that the optimized score (area under the ROC curve [AUC] = 0.715) had a higher area under receiver operating characteristic curve than Sequential Organ Failure Assessment score (AUC = 0.637) but slightly lower than APACHE II score (AUC = 0.720). Significant indicators identified through multifactor analysis included platelet count, total bilirubin level, albumin level, prothrombin time, activated partial thromboplastin time, mechanical ventilation use and renal replacement therapy use. These seven indicators were combined with optimized score to construct a nomogram based on these seven indicators. The nomogram demonstrated good clinical predictive value in both training cohort (AUC = 0.803) and validation cohort (AUC = 0.750). Calibration curves and decision curve analyses also confirmed its good predictive ability, surpassing the APACHE II score and Sequential Organ Failure Assessment score in identifying high-risk patients. Conclusions : The nomogram was established in this study using the MIMIC-IV database and validated with external data, demonstrating its robust discriminability, calibration, and clinical practicability for predicting 28-day mortality in sepsis patients. These findings aim to provide substantial support for clinicians' decision making., Competing Interests: The authors report no conflicts of interest., (Copyright © 2024 by the Shock Society.)

Background: Sepsis is defined as dysregulated host response to infection that leads to life-threatening organ dysfunction. Biomarkers characterising the dysregulated host response in sepsis are lacking. We aimed to develop host gene expression signatures to predict organ dysfunction in children with bacterial or viral infection., Methods: This cohort study was done in emergency departments and intensive care units of four hospitals in Queensland, Australia, and recruited children aged 1 month to 17 years who, upon admission, underwent a diagnostic test, including blood cultures, for suspected sepsis. Whole-blood RNA sequencing of blood was performed with Illumina NovaSeq (San Diego, CA, USA). Samples with completed phenotyping, monitoring, and RNA extraction by March 31, 2020, were included in the discovery cohort; samples collected or completed thereafter and by Oct 27, 2021, constituted the Rapid Paediatric Infection Diagnosis in Sepsis (RAPIDS) internal validation cohort. An external validation cohort was assembled from RNA sequencing gene expression count data from the observational European Childhood Life-threatening Infectious Disease Study (EUCLIDS), which recruited children with severe infection in nine European countries between 2012 and 2016. Feature selection approaches were applied to derive novel gene signatures for disease class (bacterial vs viral infection) and disease severity (presence vs absence of organ dysfunction 24 h post-sampling). The primary endpoint was the presence of organ dysfunction 24 h after blood sampling in the presence of confirmed bacterial versus viral infection. Gene signature performance is reported as area under the receiver operating characteristic curves (AUCs) and 95% CI., Findings: Between Sept 25, 2017, and Oct 27, 2021, 907 patients were enrolled. Blood samples from 595 patients were included in the discovery cohort, and samples from 312 children were included in the RAPIDS validation cohort. We derived a ten-gene disease class signature that achieved an AUC of 94·1% (95% CI 90·6-97·7) in distinguishing bacterial from viral infections in the RAPIDS validation cohort. A ten-gene disease severity signature achieved an AUC of 82·2% (95% CI 76·3-88·1) in predicting organ dysfunction within 24 h of sampling in the RAPIDS validation cohort. Used in tandem, the disease class and disease severity signatures predicted organ dysfunction within 24 h of sampling with an AUC of 90·5% (95% CI 83·3-97·6) for patients with predicted bacterial infection and 94·7% (87·8-100·0) for patients with predicted viral infection. In the external EUCLIDS validation dataset (n=362), the disease class and disease severity predicted organ dysfunction at time of sampling with an AUC of 70·1% (95% CI 44·1-96·2) for patients with predicted bacterial infection and 69·6% (53·1-86·0) for patients with predicted viral infection., Interpretation: In children evaluated for sepsis, novel host transcriptomic signatures specific for bacterial and viral infection can identify dysregulated host response leading to organ dysfunction., Funding: Australian Government Medical Research Future Fund Genomic Health Futures Mission, Children's Hospital Foundation Queensland, Brisbane Diamantina Health Partners, Emergency Medicine Foundation, Gold Coast Hospital Foundation, Far North Queensland Foundation, Townsville Hospital and Health Services SERTA Grant, and Australian Infectious Diseases Research Centre., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Objectives: We evaluated the diagnostic accuracy of cerebrospinal fluid (CSF) inflammatory markers for diagnosing bacterial meningitis in neonates with sepsis and/or meningitis., Methods: Cases were identified from a prospective multicenter study including patients aged 0-3 months with Group B Streptococcal (GBS) or Escherichia coli culture positive sepsis/meningitis. CSF CXCL10, MDC, IL-6, IL-8, IL-10, TNF- α, MIF, IL-1RA, CXCL13, IL-1β, CRP and procalcitonin concentrations were measured with Luminex technology., Results: In 61/373 patients (17%) residual CSF from the lumbar puncture was available, of whom 16 (26%) had definitive meningitis, 15 (25%) probable meningitis and 30 (49%) had sepsis. All biomarkers were detectable in CSF and showed significantly higher concentrations in definitive meningitis versus sepsis patients and six biomarkers in probable meningitis versus sepsis patients. Discrimination between definitive meningitis and sepsis was excellent for IL-1RA (area under the receiver operating characteristic curve [AUC] 0.93), TNF-α (AUC 0.92), CXCL10 (AUC 0.90), IL-1β (AUC 0.92), IL-6 (AUC 0.94), IL-10 (AUC 0.93) and a combination of IL-1RA, TNF-α, CXCL-10 and CSF leukocyte count (AUC 0.95). CSF leukocyte count remained the predictor with the highest diagnostic accuracy (AUC 0.96)., Conclusion: CSF inflammatory markers can be used to differentiate between neonatal sepsis and meningitis., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Fast and accurate diagnosis of bloodstream infection is necessary to inform treatment decisions for septic patients, who face hourly increases in mortality risk. Blood culture remains the gold standard test but typically requires approximately 15 hours to detect the presence of a pathogen. We, therefore, assessed the potential for universal digital high-resolution melt (U-dHRM) analysis to accomplish faster broad-based bacterial detection, load quantification, and species-level identification directly from whole blood. Analytical validation studies demonstrated strong agreement between U-dHRM load measurement and quantitative blood culture, indicating that U-dHRM detection is highly specific to intact organisms. In a pilot clinical study of 17 whole blood samples from pediatric patients undergoing simultaneous blood culture testing, U-dHRM achieved 100% concordance when compared with blood culture and 88% concordance when compared with clinical adjudication. Moreover, U-dHRM identified the causative pathogen to the species level in all cases where the organism was represented in the melt curve database. These results were achieved with a 1-mL sample input and sample-to-answer time of 6 hours. Overall, this pilot study suggests that U-dHRM may be a promising method to address the challenges of quickly and accurately diagnosing a bloodstream infection., (Copyright © 2024 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

Aim: The diagnosis of early-onset neonatal sepsis (EOS) remains difficult. The main aim was to study the effect of a new algorithm for EOS, which includes the level of procalcitonin in umbilical cord blood, on the exposure to antibiotic therapy of premature newborn infants., Methods: This was a monocentric, observational and retrospective study with before-and-after design. The duration and dose of antibiotic therapy provided as well as the morbidity and mortality were compared in two groups, one included 01 May 2015-30 November 2015 when procalcitonin was not used, and one after the change 01 November 2016-30 May 2017 when procalcitonin was used in a hospital setting in Nice, France., Results: Sixty newborn infants were included in the before group and 54 in the after group. Antibiotic therapy was stopped after 24 h for 18 newborn infants in the after group and four in the before group, and after 48 h for 26 newborn infants in the after group and 10 in the before group., Conclusion: The implementation of a new decision-making algorithm including early procalcitonin assay of premature newborn infants significantly reduced exposure to antibiotics without modifying mortality or morbidity., (© 2024 The Authors. Acta Paediatrica published by John Wiley & Sons Ltd on behalf of Foundation Acta Paediatrica.)

Aim: This retrospective cohort study aimed to assess the utility of maternal C-reactive protein (CRP) and leukocyte levels in predicting neonatal sepsis after preterm premature rupture of membranes (pPROM)., Methods: We conducted a retrospective cohort study (2009-2021), encompassing preterm infants born ≤29 + 6 weeks of gestation following pPROM. The primary outcome was early-onset neonatal sepsis within the initial 72 h of life., Results: We analysed data from 706 patients with a median gestational age at pPROM of 25.1 weeks and a median gestational age at birth of 26.4 weeks. Overall survival rate was 86.1%, with 65.7% survival without severe morbidities. These rates were significantly worse in preterm infants with sepsis. Maternal CRP and leukocyte levels correlated significantly with neonatal infection markers and sepsis. However, their predictive values, correlation coefficients, and area under the curve values were generally low. Using maternal CRP ≥2 mg/dL to predict neonatal sepsis yielded a positive predictive value of 18.5%, negative predictive value of 91.5%, AUC of 0.589, 45.5% sensitivity, and 74.5% specificity., Conclusion: Maternal CRP and leukocyte levels were ineffective as a tool for predicting early-onset neonatal sepsis following early pPROM. Consequently, these biomarkers lack the reliability required for clinical decision-making in this context., (© 2024 The Authors. Acta Paediatrica published by John Wiley & Sons Ltd on behalf of Foundation Acta Paediatrica.)

Purpose: To describe a case of endogenous endophthalmitis as a complication from hair transplantation., Methods: Case report of a 53-year-old man with a history of recent hair transplantation., Results: The patient presented with a febrile illness and blurry vision 1 week after hair transplantation. Infectious workup included blood cultures positive for methicillin-resistant Staphylococcus aureus, and he was treated with IV antibiotics. Initial ocular examination demonstrated 20/30 and hand motions in the right and left eyes, respectively, with significant vitritis. He underwent vitreous tap and injections of vancomycin and dexamethasone in both eyes and removal of purulent staple from the site of recently transplanted hair. His ocular and systemic symptoms improved. Approximately 3 months after initial clearing of the initial infection he had recurrence of bacteremia that prompted repeat intravitreal and systemic antibiotics. His vision returned to baseline with mild residual optic nerve pallor and atrophic retinal changes in the left eye., Conclusion: Hair transplantation is associated with minimal systemic complications, but in rare cases, sepsis is possible and can result in intraocular seeding causing endophthalmitis. MRSA endogenous endophthalmitis frequently results in negative vitreous taps and treatment outcomes in the literature have been shown to vary widely including a return to baseline vision as in the described case.

Background:  Septic-associated disseminated intravascular coagulation (DIC) is heterogeneous regarding prognosis and responsiveness to anticoagulant therapy., Objectives:  To investigate the relationship between the timing of development and recovery of DIC, its prognosis, and the difference in response to anticoagulant therapy in sepsis-associated DIC patients., Methods:  This study was performed with a dataset from a multicenter nationwide retrospective cohort study (J-Septic DIC registry) in Japan between 2011 and 2013 to reveal the subgroup "high risk of death in DIC" and investigate the relationship between anticoagulant use and mortality. Patients were assigned to four groups based on the International Society on Thrombosis and Haemostasis-overt DIC status at days 1 and 3: non-DIC (-/-), early-recovered DIC (+/-), late-onset DIC (-/+), and persistent DIC (+/+)., Results:  A total of 1,922 patients were included. In-hospital mortality in persistent and late-onset DIC patients was significantly higher than in patients with non-DIC and early-recovered DIC. This finding indicates that persistent DIC and late-onset DIC were a poor-prognosis subgroup, "high-risk" DIC. Meanwhile, patients with high-risk DIC treated with anticoagulants had significantly better outcomes than those without anticoagulants after adjusting for confounding factors., Conclusion:  This study showed that individuals with a high risk of death, persistent DIC, and late-onset DIC were a poor-prognostic subgroup in septic DIC; however, high-risk DIC is also a subgroup that can obtain more benefits from anticoagulant therapy., Competing Interests: K.Y. has received research grants from Asahi Kasei Pharma and Japan Blood Products Organization. T.I has received a research grant from JIMRO and has participated in advisory boards of Japan Blood Products Organization and Toray Medical., (Thieme. All rights reserved.)

Background and Purpose: Acute kidney injury (AKI) is a common complication in patients with sepsis, and early detection and timely treatment are crucial. This article aims to explore the clinical role of microRNA-155 (miR-155) in early diagnosis and prognosis evaluation of septic patients with acute kidney injury., Methods: We collected the blood samples of septic patients and measured the relative expression of serum miR-155 by RT-qPCR, and drew the receiver operating characteristic (ROC) curves to evaluate its early diagnosis for septic AKI., Results: The relative expression of miR-155 in the septic AKI was significantly higher than that in the septic non-AKI, and increased with the aggravation of renal function damage. The ROC curve of miR-155 for the diagnosis of septic AKI was 1.91 (95% CI: 1.61-2.19). When the optimal cut-off value of miR-155 expression was 2.37, its sensitivity for diagnosing septic AKI was 91.12% (95% CI: 80.41-95.07%), and its specificity was 84.52% (95% CI: 71.74-89.36%). Furthermore, the severity of kidney injury, SOFA score, APACHE II score and miR-155 were the risk factors affecting the prognosis of septic patients with AKI., Conclusion: Serum miR-155 can be used as a novel biomarker for the early diagnosis of septic AKI, and also has important clinical value in the prognosis evaluation of septic patients with AKI., (© 2023. The Author(s), under exclusive licence to Springer Nature B.V.)

Sepsis syndromes have been recognized since antiquity yet still pose significant challenges to modern medicine. One of the biggest challenges lies in the heterogeneity of triggers and its protean clinical manifestations, as well as its rapidly progressive and lethal nature. Thus, there is a critical need for biomarkers that can quickly and accurately detect sepsis onset and predict treatment response. In this review, we will briefly describe the current consensus definitions of sepsis and the ideal features of a biomarker. We will then delve into currently available and in-development markers of pathogens, hosts, and their interactions that together comprise the sepsis syndrome., Competing Interests: Declaration of Conflicting InterestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Introduction: It is important to predict adverse outcomes in febrile children with hematology/oncology diseases. Procalcitonin (PCT) is a promising biomarker for the prediction of infection severity, but further studies have revealed its performance in excluding adverse outcomes of infection. IL-6 and IL-10 were reported to have a close association with those infection outcomes. The aim of the study was to investigate the performance of IL-6 and IL-10 in febrile pediatric hematology/oncology patients with normal PCT., Methods: This was a retrospective study conducted in a tertiary children's hospital in China over the past ten years. Inflammatory biomarkers, including IL-6, IL-10, PCT and C-reactive protein (CRP), were detected at the onset of infection. Separate analyses were conducted in patients with neutropenia and without neutropenia., Results: In total, 5987 febrile cases were enrolled. For patients with neutropenia, IL-6, IL-10 and PCT were significantly increased in patients with bloodstream infection (BSI), gram-negative bacteremia (GNB) and severe sepsis (SS), but only IL-6 and IL-10 were predictive of GNB and SS. For patients without neutropenia, IL-6, IL-10 and PCT were significantly increased in patients with BSI, GNB and SS, but no biomarkers were predictive of adverse outcomes. All biomarkers failed to exclude patients with fever of unknown origin or upper respiratory infection/bronchitis in patients with neutropenia., Conclusions: IL-6 and IL-10 could be predictors for GNB and SS in febrile patients with neutropenia and had some association with unfavorable outcomes in febrile patients without neutropenia. All biomarkers failed to exclude patients with fever of unknown origin or upper respiratory infection/bronchitis., Competing Interests: Declaration of competing interest The authors have no relevant financial or non-financial interests to disclose., (Copyright © 2023 Japanese Society of Chemotherapy, Japanese Association for Infectious Diseases, and Japanese Society for Infection Prevention and Control. Published by Elsevier Ltd. All rights reserved.)

Sepsis is caused by the body's dysregulated response to infection, which can lead to multiorgan injury and death. Patients with sepsis may develop acute cardiac dysfunction, termed septic cardiomyopathy, which is a global but reversible dysfunction of both sides of the heart. This narrative review discusses the mechanistic changes in the heart during septic cardiomyopathy, its diagnosis, existing treatment options regarding severity and course, and emerging treatment approaches. Although no standardized definition for septic cardiomyopathy exists, it is described as a reversible myocardial dysfunction that typically resolves within 7 to 10 days. Septic cardiomyopathy is often diagnosed based on electrocardiography, cardiac magnetic resonance imaging, biomarkers, and direct invasive and noninvasive measures of cardiac output. Presently, the treatment of septic cardiomyopathy is similar to that of sepsis, primarily focusing on acute interventions. Treatments for cardiomyopathy often include angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, and diuretics. However, because of profound hypotension in sepsis, many cardiomyopathy treatments are contraindicated in patients with septic cardiomyopathy. Substantial efforts have been made to study the pathophysiological mechanisms and diagnostic options; however, the lack of a uniform definition for septic cardiomyopathy is challenging for physicians when considering treatments. Another challenge for physicians is that the treatment for septic cardiomyopathy has only focused on acute intervention, whereas the treatment for other cardiomyopathies has been provided on a long-term basis. A better understanding of the underlying mechanisms of septic cardiomyopathy may contribute to the development of a unified definition of the condition and novel treatment options., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

Introduction: Brain dysfunction in sepsis is known as Sepsis-associated encephalopathy (SAE), which often results in severe cognitive and neurological sequelae and increases the risk of death. Neuron specific enolase (NSE) may serve as an important neurocritical biomarker for detection and longitudinal monitoring in SAE patients. Our Meta-analysis aimed to explore the diagnostic and prognostic value of serum NSE in SAE patients. Currently, no systematic Review and Meta-analysis have been assessed that NSE as a biomarker of SAE., Methods: The study protocol was registered in the PROSPERO database (CRD42023398736) and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We conducted a systematic review and Meta-analysis to evaluate the serum NSE's diagnostic accuracy for SAE and prognostic strength for probability of death of septic patients. We systematic searched electronic bibliographic databases from PubMed, MEDLINE, Web of Science, Embase, Cochrane databases, CNKI, CQVIP, and WFSD. QUADAS-2 assessment tool was used to evaluate quality and risk of bias of the selected studies. Subgroup analyses, funnel plots, sensitivity analyses were also carried out. Review Manager version 5.4 and Stata16.0. was used for statistical analysis., Results: This Meta-analysis included 22 studies with 1361 serum samples from SAE patients and 1580 serum samples from no-encephalopathy septic (NE) patients. The Meta-analysis showed that individuals with SAE had higher serum NSE level than NE controls (SMD 1.93 (95 % CI 1.51-2.35), P < 0.00001). In addition, there are 948 serum samples from survival septic patients and 446 serum samples from non-survival septic patients, septic patients with survival outcomes had lower serum NSE levels than those with death outcomes (SMD -1.87 (95 % CI -2.43 to -1.32), P < 0.00001)., Conclusion: Our Meta-analysis reveals a significant association between elevated NSE concentrations and the increased likelihood of concomitant SAE and mortality during septic patients. This comprehensive analysis will equip ICU physicians with up-to-date insights to accurately identify patients at risk of SAE and implement appropriate intervention strategies to mitigate morbidity and improve neurological outcomes. However, it is important to note that the presence of substantial heterogeneity among studies poses challenges in determining the most effective discrimination cutoff values and optimal sampling collection time., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Chromobacterium is a genus of fourteen species with validly published names, most often found in soil and waters in tropical and subtropical regions around the world. The most well-known species of the genus, C. violaceum, occasionally causes clinically relevant infections; cases of soft tissue infections with septicemia and fatal outcomes have been described., Case Presentation: Here, we present a clinical case report of a 79-year-old man from Sweden with a soft-tissue infection and septicemia. The pathogen was identified as a strain of Chromobacterium species, but not C. violaceum. The patient was treated with clindamycin and ciprofloxacin and recovered well., Conclusions: This case report demonstrates the potential of Chromobacterium species as infectious agents in immunocompetent patients. It also indicates the existence of a novel species., (© 2024. The Author(s).)

This case reviews the clinical course of an elderly woman on chronic total parenteral nutrition who developed sepsis secondary to a rare, newly described gram-negative rod known as Phytobacter ursingii The patient noticed a leak in her Hickman catheter when infusing her nutrition. 24 hours after a new catheter was replaced, the patient developed fevers, chills and weakness. She presented to the hospital with hypotension and tachycardia, meeting shock criteria. Blood cultures grew P. ursingii, and the diagnosis of septic shock was confirmed. Susceptibilities informed antibiotic coverage, and she ultimately improved within the next 48 hours., Competing Interests: Competing interests: None declared., (© BMJ Publishing Group Limited 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Immunosuppression is a leading cause of septic death. Therefore, it is necessary to search for biomarkers that can evaluate the immune status of patients with sepsis. We assessed the diagnostic and prognostic value of low-density neutrophils (LDNs) and myeloid-derived suppressor cells (MDSCs) subsets in the peripheral blood mononuclear cells (PBMCs) of patients with sepsis., Methods: LDNs and MDSC subsets were compared among 52 inpatients with sepsis, 33 inpatients with infection, and 32 healthy controls to investigate their potential as immune indicators of sepsis. The percentages of LDNs, monocytic MDSCs (M-MDSCs), and polymorphonuclear MDSCs (PMN-MDSCs) in PBMCs were analyzed. Sequential organ failure assessment (SOFA) scores, C-reactive protein (CRP), and procalcitonin (PCT) levels were measured concurrently., Results: The percentages of LDNs and MDSC subsets were significantly increased in infection and sepsis as compared to control. MDSCs performed similarly to CRP and PCT in diagnosing infection or sepsis. LDNs and MDSC subsets positively correlated with PCT and CRP levels and showed an upward trend with the number of dysfunctional organs and SOFA score. Non-survivors had elevated M-MDSCs compared with that of patients who survived sepsis within 28 days after enrollment., Conclusions: MDSCs show potential as a diagnostic biomarker comparable to CRP and PCT, in infection and sepsis, even in distinguishing sepsis from infection. M-MDSCs show potential as a prognostic biomarker of sepsis and may be useful to predict 28-day hospital mortality in patients with sepsis., (© 2024. The Author(s).)

This prospective observational study explored the predictive value of CD86 in the early diagnosis of sepsis in the emergency department. The primary endpoint was the factors associated with a diagnosis of sepsis. The secondary endpoint was the factors associated with mortality among patients with sepsis. It enrolled inpatients with infection or high clinical suspicion of infection in the emergency department of a tertiary Hospital between September 2019 and June 2021. The patients were divided into the sepsis and non-sepsis groups according to the Sepsis-3 standard. The non-sepsis group included 56 patients, and the sepsis group included 65 patients (19 of whom ultimately died). The multivariable analysis showed that CD86% (odds ratio [OR] = 1.22, 95% confidence interval [CI]: 1.04-1.44, P = 0.015), platelet count (OR = 0.99, 95%CI: 0.986-0.997, P = 0.001), interleukin-10 (OR = 1.01, 95%CI: 1.004-1.025, P = 0.009), and procalcitonin (OR = 1.17, 95%CI: 1.01-1.37, P = 0.043) were independent risk factors for sepsis, while human leukocyte antigen (HLA%) (OR = 0.96, 05%CI: 0.935-0.995, P = 0.022), respiratory rate (OR = 1.16, 95%CI: 1.03-1.30, P = 0.014), and platelet count (OR = 1.01, 95%CI: 1.002-1.016, P = 0.016) were independent risk factors for death in patients with sepsis. The model for sepsis (CD86%, platelets, interleukin-10, and procalcitonin) and the model for death (HLA%, respiratory rate, and platelets) had an area under the curve (AUC) of 0.870 and 0.843, respectively. CD86% in the first 24 h after admission for acute infection was independently associated with the occurrence of sepsis in the emergency department., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 lv et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background and Objective: Acute Kidney Injury (AKI) is a common and severe complication in patients diagnosed with sepsis. It is associated with higher mortality rates, prolonged hospital stays, increased utilization of medical resources, and financial burden on patients' families. This study aimed to establish and validate predictive models using machine learning algorithms to accurately predict the occurrence of AKI in patients diagnosed with sepsis., Methods: This retrospective study utilized real observational data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. It included patients aged 18 to 90 years diagnosed with sepsis who were admitted to the ICU for the first time and had hospital stays exceeding 48 hours. Predictive models, employing various machine learning algorithms including Light Gradient Boosting Machine (LightGBM), EXtreme Gradient Boosting (XGBoost), Random Forest (RF), Decision Tree (DT), Artificial Neural Network (ANN), Support Vector Machine (SVM), and Logistic Regression (LR), were developed. The dataset was randomly divided into training and test sets at a ratio of 4:1., Results: A total of 10,575 sepsis patients were included in the analysis, of whom 8,575 (81.1%) developed AKI during hospitalization. A selection of 47 variables was utilized for model construction. The models derived from LightGBM, XGBoost, RF, DT, ANN, SVM, and LR achieved AUCs of 0.801, 0.773, 0.772, 0.737, 0.720, 0.765, and 0.776, respectively. Among these models, LightGBM demonstrated the most superior predictive performance., Conclusions: These machine learning models offer valuable predictive capabilities for identifying AKI in patients diagnosed with sepsis. The LightGBM model, with its superior predictive capability, could aid clinicians in early identification of high-risk patients., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright: © 2024 Shi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Manual microscopy of Gram stains from positive blood cultures (PBCs) is crucial for diagnosing bloodstream infections but remains labor intensive, time consuming, and subjective. This study aimed to evaluate a scan and analysis system that combines fully automated digital microscopy with deep convolutional neural networks (CNNs) to assist the interpretation of Gram stains from PBCs for routine laboratory use. The CNN was trained to classify images of Gram stains based on staining and morphology into seven different classes: background/false-positive, Gram-positive cocci in clusters (GPCCL), Gram-positive cocci in pairs (GPCP), Gram-positive cocci in chains (GPCC), rod-shaped bacilli (RSB), yeasts, and polymicrobial specimens. A total of 1,555 Gram-stained slides of PBCs were scanned, pre-classified, and reviewed by medical professionals. The results of assisted Gram stain interpretation were compared to those of manual microscopy and cultural species identification by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). The comparison of assisted Gram stain interpretation and manual microscopy yielded positive/negative percent agreement values of 95.8%/98.0% (GPCCL), 87.6%/99.3% (GPCP/GPCC), 97.4%/97.8% (RSB), 83.3%/99.3% (yeasts), and 87.0%/98.5% (negative/false positive). The assisted Gram stain interpretation, when compared to MALDI-TOF MS species identification, also yielded similar results. During the analytical performance study, assisted interpretation showed excellent reproducibility and repeatability. Any microorganism in PBCs should be detectable at the determined limit of detection of 10 5 CFU/mL. Although the CNN-based interpretation of Gram stains from PBCs is not yet ready for clinical implementation, it has potential for future integration and advancement., Competing Interests: E.G., H.M., S.H., and W.B. are employees of MetaSystems Hard & Software GmbH. Metafer is provided to University Hospital Heidelberg and its employees, C. Walter, S.Z., and I.B., as part of a cooperation agreement free of charge.

Delayed diagnosis of patients with sepsis or septic shock is associated with increased mortality and morbidity. UPLC-MS and NMR spectroscopy were used to measure panels of lipoproteins, lipids, biogenic amines, amino acids, and tryptophan pathway metabolites in blood plasma samples collected from 152 patients within 48 h of admission into the Intensive Care Unit (ICU) where 62 patients had no sepsis, 71 patients had sepsis, and 19 patients had septic shock. Patients with sepsis or septic shock had higher concentrations of neopterin and lower levels of HDL cholesterol and phospholipid particles in comparison to nonsepsis patients. Septic shock could be differentiated from sepsis patients based on different concentrations of 10 lipids, including significantly lower concentrations of five phosphatidylcholine species, three cholesterol esters, one dihydroceramide, and one phosphatidylethanolamine. The Supramolecular Phospholipid Composite (SPC) was reduced in all ICU patients, while the composite markers of acute phase glycoproteins were increased in the sepsis and septic shock patients within 48 h admission into ICU. We show that the plasma metabolic phenotype obtained within 48 h of ICU admission is diagnostic for the presence of sepsis and that septic shock can be differentiated from sepsis based on the lipid profile.

Background: Sepsis syndromes are a major burden in the ICU with very high mortality. Vasopressin and copeptin are released in response to hypovolemia and have shown potential significance in diagnosing sepsis., Objective: To investigate the levels of copeptin in patients with sepsis syndromes and evaluate its relation with patient prognosis and mortality., Methods: Four databases were searched for literature published from inception to the 8th of November 2022. Original research articles where copeptin was measured in sepsis patients and compared with controls were included. Data extraction and synthesis: study characteristics, levels of copeptin in the participants, and copeptin assay description were extracted. Levels of copeptin in patients were pooled and compared with controls in terms of the standard mean difference (SMD) generated using a random-effects model., Results: Fifteen studies met the selection criteria. Copeptin levels were significantly higher in patients with sepsis, severe sepsis, and septic shock as compared to controls [(SMD: 1.49, 95% CI: 0.81-2.16, P<0.0001), (SMD: 1.94, 95% CI: 0.34-3.54, P=0.02), and (SMD: 2.17, 95% CI: 0.68-3.66, P=0.004), respectively]. The highest copeptin levels were noted in septic shock patients. The admission copeptin levels were significantly lower in survivors as compared to nonsurvivors (SMD: -1.73; 95% CI: -2.41 to -1.06, P<0.001)., Conclusion and Relevance: Copeptin was significantly elevated in sepsis, severe sepsis, and septic shock. Survivors had a significantly lower copeptin during admission. Copeptin offered an excellent predictability to predict 1-month mortality. Measuring the copeptin in sepsis patients can aid treating physicians to foresee patients' prognosis., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

Importance: Recent sepsis trials suggest that fluid-liberal vs fluid-restrictive resuscitation has similar outcomes. These trials used generalized approaches to resuscitation, and little is known about how clinicians personalize fluid and vasopressor administration in practice., Objective: To understand how clinicians personalize decisions about resuscitation in practice., Design, Setting, and Participants: This survey study of US clinicians in the Society of Critical Care Medicine membership roster was conducted from November 2022 to January 2023. Surveys contained 10 vignettes of patients with sepsis where pertinent clinical factors (eg, fluid received and volume status) were randomized. Respondents selected the next steps in management. Data analysis was conducted from February to September 2023., Exposure: Online Qualtrics clinical vignette survey., Main Outcomes and Measures: Using multivariable logistic regression, the associations of clinical factors with decisions about fluid administration, vasopressor initiation, and vasopressor route were tested. Results are presented as adjusted proportions with 95% CIs., Results: Among 11 203 invited clinicians, 550 (4.9%; 261 men [47.5%] and 192 women [34.9%]; 173 with >15 years of practice [31.5%]) completed at least 1 vignette and were included. A majority were physicians (337 respondents [61.3%]) and critical care trained (369 respondents [67.1%]). Fluid volume already received by a patient was associated with resuscitation decisions. After 1 L of fluid, an adjusted 82.5% (95% CI, 80.2%-84.8%) of respondents prescribed additional fluid and an adjusted 55.0% (95% CI, 51.9%-58.1%) initiated vasopressors. After 5 L of fluid, an adjusted 17.5% (95% CI, 15.1%-19.9%) of respondents prescribed more fluid while an adjusted 92.7% (95% CI, 91.1%-94.3%) initiated vasopressors. More respondents prescribed fluid when the patient examination found dry vs wet (ie, overloaded) volume status (adjusted proportion, 66.9% [95% CI, 62.5%-71.2%] vs adjusted proportion, 26.5% [95% CI, 22.3%-30.6%]). Medical history, respiratory status, lactate trend, and acute kidney injury had small associations with fluid and vasopressor decisions. In 1023 of 1127 vignettes (90.8%) where the patient did not have central access, respondents were willing to start vasopressors through a peripheral intravenous catheter. In cases where patients were already receiving peripheral norepinephrine, respondents were more likely to place a central line at higher norepinephrine doses of 0.5 µg/kg/min (adjusted proportion, 78.0%; 95% CI, 74.7%-81.2%) vs 0.08 µg/kg/min (adjusted proportion, 25.2%; 95% CI, 21.8%-28.5%) and after 24 hours (adjusted proportion, 59.5%; 95% CI, 56.6%-62.5%) vs 8 hours (adjusted proportion, 47.1%; 95% CI, 44.0%-50.1%)., Conclusions and Relevance: These findings suggest that fluid volume received is the predominant factor associated with ongoing fluid and vasopressor decisions, outweighing many other clinical factors. Peripheral vasopressor use is common. Future studies aimed at personalizing resuscitation must account for fluid volumes and should incorporate specific tools to help clinicians personalize resuscitation.

Objectives: To develop and validate a risk model for 1-year mortality based on variables available from early prehospital emergency attendance of patients with infection., Material and Methods: Prospective, observational, noninterventional multicenter study in adults with suspected infection transferred to 4 Spanish hospitals by advanced life-support ambulances from June 1, 2020, through June 30, 2022. We collected demographic, physiological, clinical, and analytical data. Cox regression analysis was used to develop and validate a risk model for 1-year mortality., Results: Four hundred ten patients were enrolled (development cohort, 287; validation cohort, 123). Cumulative mortality was 49% overall. Sepsis (infection plus a Sepsis-related Organ Failure Assessment score of 2 or higher) was diagnosed in 29.2% of survivors vs 56.7% of nonsurvivors. The risk model achieved an area under the receiver operating characteristic curve of 0.89 for 1-year mortality. The following predictors were included in the model: age; institutionalization; age-adjusted Charlson comorbidity index; PaCO2; potassium, lactate, urea nitrogen, and creatinine levels; fraction of inspired oxygen; and diagnosed sepsis., Conclusion: The model showed excellent ability to predict 1-year mortality based on epidemiological, analytical, and clinical variables, identifying patients at high risk of death soon after their first contact with the health care system.

Sepsis is the third leading cause of death worldwide. Antibiotics are an important component in the treatment of sepsis. The use of antibiotics is currently facing the challenge of increasing antibiotic resistance (Evans et al., 2021). Sepsis medication prediction can be modeled as a Markov decision process, but existing methods fail to integrate with medical knowledge, making the decision process potentially deviate from medical common sense and leading to underperformance. (Wang et al., 2021). In this paper, we use Deep Q-Network (DQN) to construct a Sepsis Anti-infection DQN (SAI-DQN) model to address the challenge of determining the optimal combination and duration of antibiotics in sepsis treatment. By setting sepsis clinical knowledge as reward functions to guide DQN complying with medical guidelines, we formed personalized treatment recommendations for antibiotic combinations. The results showed that our model had a higher average value for decision-making than clinical decisions. For the test set of patients, our model predicts that 79.07% of patients will achieve a favorable prognosis with the recommended combination of antibiotics. By statistically analyzing decision trajectories and drug action selection, our model was able to provide reasonable medication recommendations that comply with clinical practices. Our model was able to improve patient outcomes by recommending appropriate antibiotic combinations in line with certain clinical knowledge., Competing Interests: Declaration of competing interest All authors declare no conflicts of interest in this research., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Purpose: Evaluate the effectiveness of the clinical decision support tools (CDSTs), POC Advisor (POCA), and Modified Early Warning System (MEWS) in identifying sepsis risk and influencing time to treatment for inpatients, comparing their respective alert mechanisms., Methods: This study was conducted at two academic university medical center hospitals. Data from adult inpatients in medical-surgical and telemetry units were analyzed from January 1, 2020, to December 31, 2020. Criteria included sepsis-related ICD-10 codes, antibiotic administration, and ordered sepsis labs. Subsequent statistical analyses utilized Fisher's exact test and Wilcoxon Rank Sum test, focusing on mortality differences by age, sex, and race/ethnicity., Results: Among 744 patients, 143 sepsis events were identified, with 83% already receiving treatment upon CDST alert. Group 1 (POCA alert) showed reduced response time compared with MEWS, while Group 3 (MEWS) experienced longer time to treatment. Group 4 included sepsis events missed by both systems. Mortality differences were not significant among the groups., Conclusion: While CDSTs play a role, nursing assessment and clinical judgment are crucial. This study recognized the potential for alarm fatigue due to a high number of CDST-driven alerts, while emphasizing the importance of a collaborative approach for prompt sepsis treatment and potential reduction in sepsis-related mortality., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Competing Interests: The author declares no conflict of interest.

Objective: Sepsis is one of the most serious hospital conditions associated with high mortality. Sepsis is the result of a dysregulated immune response to infection that can lead to multiple organ dysfunction and death. Due to the wide variability in the causes of sepsis, clinical presentation, and the recovery trajectories, identifying sepsis sub-phenotypes is crucial to advance our understanding of sepsis characterization, to choose targeted treatments and optimal timing of interventions, and to improve prognostication. Prior studies have described different sub-phenotypes of sepsis using organ-specific characteristics. These studies applied clustering algorithms to electronic health records (EHRs) to identify disease sub-phenotypes. However, prior approaches did not capture temporal information and made uncertain assumptions about the relationships among the sub-phenotypes for clustering procedures., Methods: We developed a time-aware soft clustering algorithm guided by clinical variables to identify sepsis sub-phenotypes using data available in the EHR., Results: We identified six novel sepsis hybrid sub-phenotypes and evaluated them for medical plausibility. In addition, we built an early-warning sepsis prediction model using logistic regression., Conclusion: Our results suggest that these novel sepsis hybrid sub-phenotypes are promising to provide more accurate information on sepsis-related organ dysfunction and sepsis recovery trajectories which can be important to inform management decisions and sepsis prognosis., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Anru Zhang reports financial support and administrative support were provided by Duke University. Anru Zhang reports a relationship with Duke University that includes: employment. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The authors declare no conflicts of interest., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Accurate identification of delirium in sepsis patients is crucial for guiding clinical diagnosis and treatment. However, there are no accurate biomarkers and indicators at present. We aimed to identify which combinations of cognitive impairment-related biomarkers and other easily accessible assessments best predict delirium in sepsis patients., Methods: One hundred and one sepsis patients were enrolled in a prospective study cohort. S100B, NSE, and BNIP3 L biomarkers were detected in plasma and cerebrospinal fluid and patients' optic nerve sheath diameter (ONSD). The optimal biomarkers identified by Logistic regression are combined with other factors such as ONSD to filter out the perfect model to predict delirium in sepsis patients through Logistic regression, Naïve Bayes, decision tree, and neural network models., Main Results: Among all biomarkers, compared with BNIP3 L (AUC = .706, 95% CI = .597-.815) and NSE (AUC = .711, 95% CI = .609-.813) in cerebrospinal fluid, plasma S100B (AUC = .729, 95% CI = .626-.832) had the best discrimination performance for delirium in sepsis patients. Logistic regression analysis showed that the combination of cerebrospinal fluid BNIP3 L with plasma S100B, ONSD, neutrophils, and age provided the best discrimination to cognitive impairment in sepsis patients (accuracy = .901, specificity = .923, sensitivity = .911), which was better than Naïve Bayes, decision tree, and neural network models. Neutrophils, ONSD, and cerebrospinal fluid BNIP3 L were consistently the major contributors in a few models., Conclusions: The logistic regression showed that the combination model was strongly correlated with cognitive dysfunction in sepsis patients.

Objective: Sepsis is a life-threatening condition in the ICU and requires treatment in time. Despite the accuracy of existing sepsis prediction models, insufficient focus on reducing alarms could worsen alarm fatigue and desensitisation in ICUs, potentially compromising patient safety. In this retrospective study, we aim to develop an accurate, robust, and readily deployable method in ICUs, only based on the vital signs and laboratory tests., Methods: Our method consists of a customised down-sampling process and a specific dynamic sliding window and XGBoost to offer sepsis prediction. The down-sampling process was applied to the retrospective data for training the XGBoost model. During the testing stage, the dynamic sliding window and the trained XGBoost were used to predict sepsis on the retrospective datasets, PhysioNet and FHC., Results: With the filtered data from PhysioNet, our method achieved 80.74% accuracy (77.90% sensitivity and 84.42% specificity) and 83.95% (84.82% sensitivity and 82.00% specificity) on the test set of PhysioNet-A and PhysioNet-B, respectively. The AUC score was 0.89 for both datasets. On the FHC dataset, our method achieved 92.38% accuracy (88.37% sensitivity and 95.16% specificity) and 0.98 AUC score on the test set of FHC., Conclusion: Our results indicate that the down-sampling process and the dynamic sliding window with XGBoost brought robust and accurate performance to give sepsis prediction under various hospital settings. The localisation and robustness of our method can assist in sepsis diagnosis in different ICU settings., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Qinhao Wu has patent #202310548236.8 pending to Qinhao Wu., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Neonatal sepsis is responsible for significant morbidity and mortality worldwide. Its accurate and timely diagnosis is hindered by vague symptoms and the urgent necessity for early antibiotic intervention. The gold standard for diagnosing the condition is the identification of a pathogenic organism from normally sterile sites via laboratory testing. However, this method is resource-intensive and cannot be conducted continuously., Objective: This study aimed to predict the onset of late-onset sepsis (LOS) with good diagnostic value as early as possible using non-invasive biosignal measurements from neonatal intensive care unit (NICU) monitors., Methods: In this prospective multicenter study, we developed a multimodal machine learning algorithm based on a convolutional neural network (CNN) structure that uses the power spectral density (PSD) of recorded biosignals to predict the onset of LOS. This approach aimed to discern LOS-related pathogenic spectral signatures without labor-intensive manual artifact removal., Results: The model achieved an area under the receiver operating characteristic score of 0.810 (95 % CI 0.698-0.922) on the validation dataset. With an optimal operating point, LOS detection had 83 % sensitivity and 73 % specificity. The median early detection was 44 h before clinical suspicion. The results highlighted the additive importance of electrocardiogram and respiratory impedance (RESP) signals in improving predictive accuracy. According to a more detailed analysis, the predictive power arose from the morphology of the electrocardiogram's R-wave and sudden changes in the RESP signal., Conclusion: Raw biosignals from NICU monitors, in conjunction with PSD transformation, as input to the CNN, can provide state-of-the-art prediction performance for LOS without the need for artifact removal. To the knowledge of the authors, this is the first study to highlight the independent and additive predictive potential of electrocardiogram R-wave morphology and concurrent, sudden changes in the RESP waveform in predicting the onset of LOS using non-invasive biosignals., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Antti Kallonen has patents pending on the methodology (EP21801580, US2023-0290511 and FI20205993). Other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Physiological hemostasis is a balance between pro- and anticoagulant pathways, and in sepsis, this equilibrium is disturbed, resulting in systemic thrombin generation, impaired anticoagulant activity, and suppression of fibrinolysis, a condition termed sepsis-induced coagulopathy (SIC). SIC is a common complication, being present in 24% of patients with sepsis and 66% of patients with septic shock, and is often associated with poor clinical outcomes and high mortality. 1 , 2 Recent preclinical and clinical studies have generated new insights into the molecular pathogenesis of SIC. In this article, we analyze the complex pathophysiology of SIC with a focus on the role of procoagulant innate immune signaling in hemostatic activation--tissue factor production, thrombin generation, endotheliopathy, and impaired antithrombotic functions. We also review clinical presentations of SIC, the diagnostic scoring system and laboratory tests, the current standard of care, and clinical trials evaluating the efficacies of anticoagulant therapies., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the International Anesthesia Research Society.)

Background: Serum and radiological parameters used to predict prognosis in COVID patients are not feasible in the Emergency Department. Due to its damaging effect on multiple organs and lungs, scores used to assess multiorgan damage and pneumonia such as Pandemic Medical Early Warning Score (PMEWS), National Early Warning Score 2 (NEWS2), WHO score, quick Sequential Organ Failure Assessment (qSOFA), and DS-CRB 65 can be used to triage patients in the Emergency Department. They can be used to predict patients with the highest risk of seven-day mortality and need for intensive respiratory or vasopressor support (IRVS)., Purpose: The primary purpose was to find the score with the highest AUC in predicting IRVS and mortality at seven days. Additional objective was to find out any independent factors associated with IRVS and mortality., Methods: The data of adult patients who presented to the Emergency Department (ED) between April 1, 2021 and June 30, 2021 were collected. The WHO score, CRB-65, DS-CRB 65, PMEWS, NEWS2, and qSOFA score were calculated for all patients. Statistical analysis was done and an ROC curve was calculated for all the tools for mortality and need for IRVS at seven days., Findings: 677 patients presented to the Emergency Department with COVID-19 during the period above. Presence of Diabetes Mellitus (p = 0.001), Hypertension (p = 0.001), and chronic kidney disease(CKD) (p = 0.04) was significantly associated with need for IRVS. Age, duration of symptoms, pulse rate, respiratory rate, room air saturation, mental status at admission, and time to IRVS need were identified as independent predictors of in-hospital mortality. The longer the time to IRVS need from ED arrival, the higher the likelihood of mortality. PMEWS (0.830) had the highest AUC, followed by NEWS2 (0.805). A PMEWS cut-off of 6.5 was 74.2% sensitive and 78.3% specific in predicting the need for IRVS. ROC analysis to predict 7-day mortality showed that PMEWS had an AUC of 0.802 (0.766-0.839). QSOFA performed poorly in predicting IRVS (AUC 0.645) and 7-day mortality (AUC 0.677)., Conclusion: PMEWS may be used for triaging patients presenting to the Emergency Department with COVID-19 and accurately predicts the need for IRVS and seven day mortality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Introduction: Identifying patients with at a high risk of progressing to septic shock is essential. Due to systemic vasodilation in the pathophysiology of septic shock, the use of diastolic blood pressure (DBP) has emerged. We hypothesized that the initial shock index (SI) and diastolic SI (DSI) at the emergency department (ED) triage can predict septic shock., Method: This observational study used the prospectively collected sepsis registry. The primary outcome was progression to septic shock. Secondary outcomes were the time to vasopressor requirement, vasopressor dose, and severity according to SI and DSI. Patients were classified by tertiles according to the first principal component of shock index and diastolic shock index., Results: A total of 1267 patients were included in the analysis. The area under the receiver operating characteristic curve (AUC) for predicting progression to septic shock for DSI was 0.717, while that for SI was 0.707. The AUC for predicting progression to septic shock for DSI and SI were significantly higher than those for conventional early warning scores. Middle tertile showed adjusted Odd ratio (aOR) of 1.448 (95% CI 1.074-1.953), and that of upper tertile showed 3.704 (95% CI 2.299-4.111)., Conclusion: The SI and DSI were significant predictors of progression to septic shock. Our findings suggest an association between DSI and vasopressor requirement. We propose stratifying lower tertile as being at low risk, middle tertile as being at intermediate risk, and upper tertile as being at high risk of progression to septic shock. This system can be applied simply at the ED triage., Competing Interests: Declaration of competing interest None., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Purpose: This study aimed to compare non-invasive oscillometric blood pressure (NIBP) measurement with invasive arterial blood pressure (IBP) measurement in patients with sepsis., Methods: We conducted a retrospective study to evaluate the agreement between IBP and NIBP using the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Paired blood pressure measurements of mean arterial pressure (MAP), systolic blood pressure (SBP), and diastolic blood pressure (DBP) were compared using Bland-Altman analysis and paired Student's t test. We also focus on the effect of norepinephrine (NE) on the agreement between the two methods and the association between blood pressure and mortality during intensive care unit (ICU) stay., Results: A total of 96,673 paired blood pressure measurements from 6060 unique patients were analyzed in the study. In Bland-Altman analysis, the bias (± SD, 95% limits of agreement) was 6.21 mmHg (± 12.05 mmHg, - 17.41 to 29.83 mmHg) for MAP, 0.39 mmHg (± 19.25 mmHg, - 37.34 to 38.12 mmHg) for SBP, and 0.80 mmHg (± 12.92 mmHg, - 24.52 to 26.12 mmHg) for DBP between the two techniques. Similarly, large limits of agreement were shown in different groups of NE doses. NE doses significantly affected the agreement between IBP and NIBP. SBP between the two methods gave an inconsistent assessment of patients' risk of ICU mortality., Conclusion: IBP and NIBP were not interchangeable in septic patients. Clinicians should be aware that non-invasive MAP was clinically and significantly underestimated invasive MAP., (© 2024. The Author(s) under exclusive licence to Japanese Society of Anesthesiologists.)

Objectives: To describe mortality associated with different clinical phenotypes of sepsis in children., Design: Retrospective study., Setting: PICU of a tertiary care center in India from 2017 to 2022., Patients: Six hundred twelve children (from 2 mo to 17 yr old) with a retrospectively applied diagnosis of sepsis using 2020 guidance., Methods: The main outcome was mortality associated with sepsis subtypes. Other analyses included assessment of risk factors, requirement for organ support, and PICU resources used by sepsis phenotype. Clinical data were recorded on a predesigned proforma., Interventions: None., Measurements and Results: Of the 612 children identified, there were 382 (62%) with sepsis but no multiple organ failure (NoMOF), 48 (8%) with thrombocytopenia-associated MOF (TAMOF), 140 (23%) with MOF without thrombocytopenia, and 40 (6.5%) with sequential MOF (SMOF). Mortality was higher in the SMOF (20/40 [50%]), MOF (62/140 [44%]) and TAMOF (20/48 [42%]) groups, compared with NoMOF group (82/382 [21%] [ p < 0.001]). The requirement for organ support and PICU resources was higher in all phenotypes with MOF as compared with those without MOF. On multivariable analysis elevated lactate and having MOF were associated with greater odds of mortality., Conclusions: In this single-center experience of sepsis in India, we found that sepsis phenotypes having MOF were associated with mortality and the requirement of PICU resources. Prospective studies in different regions of the world will help identify a classification of pediatric sepsis that is more widely applicable., Competing Interests: The authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2024 by the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies.)

Purpose: To prospectively validate, in an ICU setting, the prognostic accuracy of the sepsis prediction algorithm NAVOY® Sepsis which uses 4 h of input for routinely collected vital parameters, blood gas values, and lab values., Materials and Methods: Patients 18 years or older admitted to the ICU at Skåne University Hospital Malmö from December 2020 to September 2021 were recruited in the study. A total of 304 patients were randomized into one of two groups: Algorithm group with active sepsis alerts, or Standard of care. NAVOY® Sepsis made silent predictions in the Standard of care group, in order to evaluate its performance without disturbing the outcome. The study was blinded, i.e., study personnel did not know to which group patients were randomized. The healthcare provider followed standard practices in assessing possible development of sepsis and intervening accordingly. The patients were followed-up in the study until ICU discharge., Results: NAVOY® Sepsis could predict the development of sepsis, according to the Sepsis-3 criteria, three hours before sepsis onset with high performance: accuracy 0.79; sensitivity 0.80; and specificity 0.78., Conclusions: The accuracy, sensitivity, and specificity were all high, validating the prognostic accuracy of NAVOY® Sepsis in an ICU setting, including Covid-19 patients., Competing Interests: Declaration of Competing Interest David Becedas and Inger Persson are shareholders of AlgoDx AB, and Andreas Macura has received stock options from AlgoDx AB., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Aim: The aim of this review was to summarise the most recent evidence about the use of omics-based techniques as an instrument for a more rapid and accurate characterisation of respiratory tract infections, neurological infections and sepsis in paediatrics., Methods: We performed a narrative review using PubMed and a set of inclusion criteria: English language articles, clinical trials, meta-analysis and reviews including only paediatric population inherited to this topic in the last 15 years., Results: The examined studies suggest that host gene expression signatures are an effective method to characterise the different types of infections, to distinguish infection from colonisation and, in some cases, to assess the severity of the disease in children., Conclusions: 'Omics-based techniques' may help to define the aetiology of infections in paediatrics, representing a useful tool to choose the most appropriate therapies and limit antibiotic resistance., (© 2024 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.)

We have evaluated the performance of FilmArray BCID2 in reactive blood cultures in a small acute care hospital compared to conventional diagnostics at a regional microbiological laboratory. This is a retrospective observational study of BactAlert reactive blood cultures (n = 160) from Helgeland Hospital, July-December 2021, analysed by BCID2 locally and conventional culture at a regional laboratory. The overall clinical and analytic sensitivity with BCID2 were 87.2% and 97.8%, respectively. The false-negative BCID2 rate was low (n = 4; 2.9%). No false-positive BCID2 results were observed. The BCID2 data were available on average 1.88 days earlier than culture-based results, due to long transport time to the regional laboratory. The BCID2 provided results to support a significantly earlier optimized targeted antibiotic treatment in 27% of the cases according to national guidelines for empirical treatment of BSI. The high clinical and analytical sensitivity, and specificity support the use of BCID2 as a robust supplement to traditional cultivation of positive blood cultures. The significant time gain to microbial identification and detection of resistance determinants suggests a great clinical importance of BCID2 in small acute care hospitals with long transport time to conventional clinical microbiology services., (© 2024 The Authors. APMIS published by John Wiley & Sons Ltd on behalf of Scandinavian Societies for Pathology, Medical Microbiology and Immunology.)