Real-time risk monitoring is critical but challenging in intensive care units (ICUs) due to the lack of real-time updates for most clinical variables. Although real-time predictions have been integrated into various risk monitoring systems, existing systems do not address uncertainties in risk assessments. We developed a novel framework based on commonly used systems like the Sequential Organ Failure Assessment (SOFA) score by incorporating uncertainties to improve the effectiveness of real-time risk monitoring.

This study included 5351 patients admitted to the Cardiothoracic ICU in the National University Hospital in Singapore. We developed machine learning models to predict long lead-time variables and computed real-time SOFA scores using predictions. We calculated intervals to capture uncertainties in risk assessments and validated the association of the estimated real-time scores and intervals with mortality and readmission.

Our model outperforms SOFA score in predicting 24-h mortality: Nagelkerke's R-squared (0.224 vs. 0.185, p < 0.001) and the area under the receiver operating characteristic curve (AUC) (0.870 vs. 0.843, p < 0.001), and significantly outperforms quick SOFA (Nagelkerke's R-squared = 0.125, AUC = 0.778). Our model also performs better in predicting 30-day readmission. We confirmed a positive net reclassification improvement (NRI) of our model over the SOFA score (0.184, p < 0.001). Similarly, we enhanced two additional scoring systems.

Incorporating uncertainties improved existing scores in real-time monitoring, which could be used to trigger on-demand laboratory tests, potentially improving early detection, reducing unnecessary testing, and thereby lowering healthcare expenditures, mortality, and readmission rates in clinical practice.

The online version contains supplementary material available at 10.1007/s13755-024-00331-5.

Sepsis is an uncontrolled systemic response to infection that leads to life-threatening organ dysfunction. The in-hospital mortality rate remains significantly high in septic shock patients with malignancies. This study investigates whether early and high-volume administration of sodium bicarbonate during continuous renal replacement therapy (CRRT) can reduce 28-day mortality, increase shock reversal rates, and shorten the duration of CRRT, mechanical ventilation, and intensive care unit (ICU) stays. The goal is to provide valuable clinical data for the management of cancer patients with sepsis-associated acute kidney injury (SAKI).

A retrospective study was performed on 88 patients who were admitted to the ICU and received continuous renal replacement therapy (CRRT) for acute renal failure secondary to sepsis at the Cancer Center of Sun Yat-sen University from March 2010 to October 2021. Based on the initiation time of CRRT and the volume of sodium bicarbonate infusion, patients were divided into four groups: the early high-volume group, early low-volume group, late high-volume group, and late low-volume group.

The results of this study showed that in the 28-day mortality model, established using the Cox proportional hazards method, early CRRT (HR 0.473; 95% CI 0.245-0.915, p = 0.026) and high-volume sodium bicarbonate infusion (HR 0.173; 95% CI 0.078-0.383, p < 0.001) were identified as two independent protective factors. The 28-day mortality rate in the early high-volume group (15.0%) was significantly lower than that of the other three groups (60.0%, 30.0%, and 75.0%, respectively; χ2 = 23.822, p < 0.001). Additionally, the shock reversal rate in the early high-volume group (80.0%) was significantly higher compared to the other groups (35.0%, 45.0%, and 35.7%; χ2 =13.576, p = 0.004). The duration of CRRT was shorter in the early high-volume group (35.0 ± 4.45 h) than in the other groups (70.0 ± 30.19 h, 48.0 ± 5.22 h, and 72.0 ± 19.84 h; χ2 =11.278, p = 0.01). Furthermore, the duration of mechanical ventilation (7.0 ± 3.33 days) was lower in the early high-volume group compared to the other groups (8.0 ± 1.12 days,10.0 ± 1.11 days, and 8.0 ± 2.65 days; χ2 =8.064, p = 0.045), as was the length of ICU stay (7.0 ± 0.89 days) compared to the other groups (13.0 ± 3.35 days, 10.0 ± 1.49 days, and10.0 ± 3.70 days; χ2 = 9.184, p = 0.027).

Early and high-volume administration of sodium bicarbonate during CRRT may reduce 28-day mortality and improve shock reversal rates in patients with sepsis-associated acute kidney injury complicated by malignancy. Prospective randomized controlled large sample studies are needed to confirm this.

Sepsis is a life-threatening condition characterized by multiple organ dysfunction syndrome resulted from dysregulated host responses to infection. Sepsis-associated encephalopathy (SAE) is one of the most common symptoms of acute-phase sepsis, with nearly 70 % of patients with sepsis ultimately developing SAE. Pyroptosis represents a type of cell death that is initiated by inflammation. This cell death type is associated with various infectious and noninfectious diseases. The gasdermin family proteins are crucial cell death executors and critical components in regulating the canonical pyroptosis pathway in microglia. In this review, we summarize the inhibitory effects of several drugs and genes on the pyroptosis pathway. Our findings suggest that several drugs (puerarin, VX765, HC067047, dexpramipexole, and Danhong injection), erbin gene, and TRIM45 knockdown improve SAE by suppressing the canonical pathway of NLRP3/caspase-1/gasdermin D-mediated pyroptosis. Therefore, they have significant importance in terms of brain protection. Moreover, we review the relevant literature published in recent years and summarize the research status and development prospects in this field to provide a basis for subsequent related research.

Prompt recognition and treatment of patients with sepsis improve survival. Patients transported to hospital with sepsis often do not receive treatment until they are assessed in emergency departments. Initiation of treatments by paramedics at the point of first contact may improve outcomes for these patients.

The study design involves two randomised controlled trials (RCTs) conducted using a 2×2 factorial design comparing use of (1) early intramuscular ceftriaxone versus placebo and (2) an early liberal intravenous fluid strategy (up to 2 L normal saline) versus usual care resuscitation guided by paramedic medical directives. Patients who are ≥18 years of age will be eligible for inclusion if they have sepsis, defined as (1) paramedic suspicion of infection, (2) fever (temperature ≥38.0°C measured by paramedic or history of fever during the previous 24 hours), and (3) hypotension: SBP <100 mm Hg. The primary outcome is mortality prior to hospital discharge or within 90 days of admission. Secondary outcomes are all-cause mortality at 90 days after enrolment; organ dysfunction during first 24 hours (mechanical ventilation, vasopressor therapy, dialysis) and hospitalisation (mechanical ventilation; dialysis); rates and duration of hospital admission; rates of ICU admission during index hospitalisation; discharge destination; proportion of patients with positive blood cultures obtained in hospital (first 24 hours); microbiological profile including distribution of microorganism species and resistant organisms; proportion of patients receiving additional antibiotics within 6 hours and within 24 hours of hospital admission; frequency distribution of first antibiotics (if any) delivered within 24 hours of hospital arrival; mean time to antibiotics delivered within 24 hours of hospital arrival (if any); proportion of patients receiving fluid bolus (>250 mL) within 24 hours of hospital arrival; total amount of crystalloid infused during transport and first 24 hours of hospitalisation; and proportion of enrolled patients not suspected to have sepsis or infection by emergency department physicians. Safety outcomes include the proportion of patients with pulmonary oedema during transport to hospital and on initial chest X-ray and the proportion of patients with anaphylaxis or suspected allergic reactions to study medication.

This study has been approved through Clinical Trials Ontario's streamlined ethics review process (board of record, Sunnybrook Health Sciences Centre). It will be conducted in accordance with the Declaration of Helsinki, Good Clinical Practice guidelines and regulatory requirements. The final results will be disseminated to participating paramedic services through educational materials, presentations and interactive training. We anticipate our trial will achieve wide dissemination through publication in a peer-reviewed medical journal and presentation at international conferences targeting the fields of prehospital and emergency medicine, resuscitation and critical care.

NCT03068741.

Infectious complications following prostate biopsy are costly and potentially deadly. Multiple strategies have been devised to avoid infections, including augmented prophylaxis and transperineal biopsy (TPBx). Their uptake and success in reducing population-level infectious outcomes following biopsy are largely unknown. Here, we evaluate contemporary postbiopsy infections and hospital admissions in a large insurance claims dataset.

The Merative MarketScan Database was queried for prostate biopsies from 2012 to 2021. MarketScan contains inpatient and outpatient data on >40 million individuals annually. Our primary endpoint was overall and sepsis-related hospitalizations within 14-days of prostate biopsy, and postbiopsy infections not requiring admission. Multvariable analysis evaluated temporal trends in endpoints.

We identified 301,733 patients undergoing prostate biopsy between 2012 and 2021 among whom 2,587 developed sepsis. The proportion of patients with sepsis decreased from 1.1% in 2017 to 0.7% in 2021, following an increase from 0.6% in 2012 to 1.1% in 2016. This paralleled trends in hospitalizations within 14-days. Postbiopsy infections not requiring hospitalization remained stable across the study period. These temporal trends persisted even after adjustment for patient age, comorbidities, biopsy history, insurance status, and geographic region. Single-agent fluoroquinolone use decreased alongside an increase in multiagent prophylaxis over the study period.

We identified a decrease in postbiopsy all-cause and sepsis-related hospitalization, synchronous with augmented prophylaxis. Our findings suggest population-level improvement in major postbiopsy complications, reversing a trend from historical series.

The obesity paradox, where higher body mass index (BMI) is associated with improved survival, is observed in sepsis and cancer individually. However, its effect in patients with both conditions is unclear. The objective of this study is to evaluate the obesity paradox in intensive care unit (ICU) patients with sepsis and cancer and examine whether BMI's impact on mortality varies across patient phenotypes.

Data from the Medical Information Mart for Intensive Care IV database were analyzed. Patients were categorized by BMI into underweight (<18.5 kg/m2, n = 173), normal weight (18.5-24.9 kg/m2, n = 1283), overweight (25-29.9 kg/m2, n = 1498), and obesity (≥30 kg/m2, n = 960). The primary outcome was 28-day mortality, with secondary outcomes including 6-month mortality, 1-year mortality, length of ICU stay, continuous renal replacement therapy usage, and invasive ventilation usage. Multivariable logistic regression and restricted cubic splines were used to explore the BMI-mortality relationship, and unsupervised clustering was performed to identify patient phenotypes.

Among 3914 patients, obesity was associated with lower mortality. Clustering revealed four distinct phenotypes, with the protective effect of obesity being more evident in patients with lower Sequential Organ Failure Assessment (SOFA) scores (Cluster1, Cluster2 and Cluster3).

The obesity paradox is evident in both short-term outcome (28-day mortality) and long-term outcomes (6-month and 1-year mortality) among patients with sepsis and cancer, particularly in those presenting with lower disease severity. These findings highlight the need for personalized treatment approaches in this complex patient population.

Patients with intracerebral hemorrhage (ICH) are highly susceptible to sepsis. This study evaluates the efficacy of machine learning (ML) models in predicting sepsis risk in intensive care units (ICUs) patients with ICH. We conducted a retrospective analysis on ICH patients using the MIMIC-IV database, randomly dividing them into training and validation cohorts. We identified sepsis prognostic factors using Least Absolute Shrinkage and Selection Operator (LASSO) and backward stepwise logistic regression. Several machine learning algorithms were developed and assessed for predictive accuracy, with external validation performed using the eICU Collaborative Research Database (eICU-CRD). We analyzed 2,214 patients, including 1,550 in the training set, 664 in the validation set, and 513 for external validation using the eICU-CRD. The Random Forest (RF) model outperformed others, achieving Area Under the Curves (AUCs) of 0.912 in training, 0.832 in internal validation, and 0.798 in external validation. Neural Network and Logistic Regression models recorded training AUCs of 0.840 and 0.804, respectively. ML models, especially the RF model, effectively predict sepsis in ICU patients with ICH, enabling early identification and management of high-risk cases.

Hospital-at-home (HAH) is increasingly recognized as a viable alternative to in-hospital stay across various clinical settings. However, until recently, complex patients, particularly those with bacteremia, were not considered suitable candidates for HAH care. The purpose of this article is to describe a unique series of these high-risk patients and the means for attending them at home, for the first time in scientific literature. A retrospective analysis was conducted on a group of patients with bacteremia who were treated in the setting of a telemedicine-controlled HAH service. Twenty-eight patients with blood stream infections were treated in our HAH service. 60.7% were female, with a patient median age of 77 years. Most patients (64.3%) were admitted from the internal medicine ward; 17.86% (5 patients) were admitted at home, and 17.86% were admitted directly from the emergency department. A significant portion had severe comorbidities: 53.6% presented with malignancies, 21.4% presented with dementia, 42.9% presented with diabetes mellitus, 42.9% had chronic kidney disease, and 7 patients (25%) were on continuous immunosuppressive medication. The mean length of HAH stay was 4.1 ± 2.0 days. The majority (67.9%) were discharged at home, while 28.6% required transfer to in-hospital care. One patient died during the HAH stay, and another died during the 30-day follow-up. Telemedicine-controlled HAH service is a viable alternative to traditional in-hospital care for high-risk patients suffering from bacteremia. This is the first clinical report asserting that careful patient selection and meticulous management during HAH care result in good clinical outcomes.

Hemorrhagic shock (HS) leads to organ dysfunction, which increases the incidence of unfavorable outcomes in patients. However, adjuvant drug therapy for HS has not been widely accepted, and the benefits of vasopressors are generally considered to have insufficient evidence. Energy homeostasis disruption and excessive immune system activation are the main mechanisms underlying HS-induced organ dysfunction. Recent reports on HS animal models and clinical trials have revealed potential drugs that target the immune response, oxidative damage, and energy homeostasis in HS, providing new insights for the treatment of HS-induced organ dysfunction. In this review, we first discuss the pathophysiology of organ dysfunction involved in HS injury and then systematically review potential drugs that regulate immunity, the inflammatory response, oxidative damage, energy homeostasis, and cell death. We also review the available drugs with clinical evidence of HS-induced organ dysfunction efficacy. Treatment strategies combined with an improved understanding of the organ injury mechanisms of HS may help identify and develop targeted therapeutic modalities that mitigate severe organ dysfunction and reduce mortality caused by HS injury.

Acute kidney injury (AKI) is common in hospitalized adults and a risk factor for chronic kidney disease and mortality. The effect of angiotensin-converting enzyme inhibitors (ACEi) or angiotensin receptor blockers (ARBs) post-AKI on mortality and long-term kidney function remains unclear.

Propensity-weighted retrospective observational cohort study.

A total of 3,289 patients with AKI admitted to a tertiary care hospital from November 2015-October 2016, with follow-up until September 2020.

ACEi/ARB use within 180 days post-AKI.

All-cause mortality, and major adverse kidney events (MAKE) as defined by composite of renal replacement therapy post-AKI, sustained estimated glomerular filtration rate (eGFR) decline >30% from baseline, or eGFR ≤15 mL/min/1.73 m2.

We generated propensity weights for ACEi/ARB use post-AKI, using age, sex, comorbid conditions, prior medication, intensive care unit admission, severe sepsis, and index AKI Kidney Disease: Improving Global Outcomes severity. Cox proportional hazard models were used to test associations of post-AKI ACEi/ARB with mortality, MAKE, and joint models for eGFR slopes.

A total of 2,309 (70.2%) participants died or experienced MAKE by end of follow-up. 161 (4.9%) and 406 (12.3%) patients initiated or resumed prior ACEi/ARB use within 180 days post-AKI, respectively. Although the overall cohort had no significant mortality association with post-AKI ACEi/ARB use, a significant association with lower mortality was observed in patients with KDIGO 3 AKI (HR, 0.40; 95% CI, 0.21-0.75; P interaction = 0.003). However, post-AKI ACEi/ARB use was associated with increased MAKE in patients without cardiovascular indications for ACEi/ARB use (HR, 1.52; 95% CI, 1.17-1.98; P interaction = 0.03). Although post-AKI use of ACEi/ARB was associated with acute eGFR decline (initial eGFR change -2.3 mL/min/1.73 m2/year; 95% CI, -3.1 to -1.5; P < 0.001), no association with longer-term eGFR decline was observed.

Retrospective observational study on heterogeneous AKI cohort without data on ACEi/ARB cumulative exposure.

Early ACEi/ARB post-AKI was not associated with better long-term survival or kidney function but was associated with lower mortality in patients with KDIGO 3 AKI.

Rapid and accurate prediction of mortality risk among intensive care unit (ICU) sepsis patients is crucial for timely intervention and improving patient outcomes. However, due to the multimodal and dynamic time-series nature of patient visit information and the limited data samples, it is challenging to obtain discriminative patient representations, leading to suboptimal mortality prediction results. To address this issue, we design a time-aware graph embedding attention model (TGAM) to integrate multimodal data and predict mortality in ICU sepsis patients. Our approach involves modeling and generating patient representations that encompass not only demographic information but also dynamic time-series data reflecting patient health status. Additionally, the graph convolutional network is used to obtain informative concept embeddings from medical ontologies, and an improved transformer is used to capture the temporal information of the patient's health status and handle missing values, overcoming the limitations of small samples. The experimental results on the MIMIC-III and MIMIC-IV datasets demonstrate that TGAM significantly improves prediction accuracy, with AUROC scores of 87.65% and 87.00% on the MIMIC-III and MIMIC-IV datasets, respectively, outperforming baseline models by over 5 percentage points. TGAM also achieves higher sensitivity, specificity, and AUPRC metrics, and lower Brier Score compared with baseline models, highlighting its effectiveness in identifying high-risk patients. These findings suggest that TGAM has the potential to become a valuable tool for identifying high-risk sepsis patients, enabling clinicians to make more informed and timely intervention decisions.

Septic shock is a lethal disease, and identifying high-risk patients through noninvasive and widely available biomarkers can help improve global outcomes. While the clinical impact of chloride levels on critically ill patients remains unclear, this study aims to investigate the association between hypochloremia and mortality following ICU admission among septic shock patients.

This is an analysis of data stored in the databases of Medical Information Mart for Intensive Care IV (MIMIC-IV). The initial chloride levels were classified ashypochloremia, normal chloraemia, and hyperchloraemia. A multivariate logistic regression model was applied, adjusting for age, lactate, pH, PO2, urine volume, RDW, creatinine, and liver disease, to assess the association between the three categories of chloride levels and mortality.

Of 3726 patients included in the study, 470 patients (12.6%) had hypochloremia on ICU admission. During the follow-up period, 1120 (33.5%) patients died. Hypochloremia was significantly associated with increased mortality and the incidence of AKI after adjusting for several variables.

Hypochloremia is independently associated with higher hospital mortality, AKI incidence among septic shock patients. However, further high-quality research is necessary to establish the precise relationship between hypochloremia and septic shock prognosis.

Approximately half of the patients with sepsis require intensive care unit (ICU) management and their mortality rate remains high. The concept of withholding and withdrawal life-sustaining treatment (WWLST) issue was introduced to limit the suffering of critically ill patients. However, little is known about the characteristics and outcomes of WWLST in patients with sepsis. We conducted a nationwide cohort study of adult patients with sepsis prospectively collected from the Korean Sepsis Alliance Database of 20 tertiary referral or university-affiliated hospitals in South Korea between September 2019 and December 2021. Patients were classified according to WWLST issues and characteristics, and their prognoses were compared. Among the 11,981 patients with sepsis included in the study, 4430 (37.0%) had WWLST issues. The WWLST group was older, frailer, and had higher Sequential Organ Failure Assessment (SOFA) scores than the no-WWLST group. The WWLST group had more underlying diseases, including solid tumors (45.2% vs. 30.6%, p < 0.001) and hematologic malignancies (8.0% vs. 5.2%, p < 0.001), than the no-WWLST group. Regarding patient outcomes and interventions in the ICU, the WWLST group used vasopressors (35.4% vs. 32.8%, p = 0.003) more frequently; invasive mechanical ventilation (62.9% vs. 41.9%, p < 0.001) and continuous renal replacement therapy (40.8% vs. 17.6%, p < 0.001) were applied more frequently in the WWLST group than in the no-WWLST group. Logistic regression analysis revealed the factors associated with WWLST group to be old age, low body mass index, higher Charlson comorbidity index, clinical frailty scale, SOFA score, underlying diseases such as solid tumors and hematologic malignancies, invasive mechanical ventilation, and continuous renal replacement therapy. We predicted that the WWLST group would have a fewer ICU admissions and less invasive treatment. However, the admission rate was equivalent, and the percentage of invasive treatment, length of ICU stays, and mortality rate were higher and longer in the WWLST group. In patients with sepsis who have factors related to WWLST, appropriate communication with the patient and their family about WWLST can improve the quality of life and quality of death.

Sepsis is a leading cause of morbidity and mortality in children, requiring early recognition for timely intervention. Traditional biomarkers like C-reactive protein (CRP) are widely used but have limitations in specificity and early detection. Procalcitonin (PCT) has emerged as a promising alternative for differentiating bacterial infections from viral illnesses. This study aims to evaluate the diagnostic performance of PCT and CRP in identifying sepsis among febrile pediatric patients presenting to the emergency department (ED).

We conducted a retrospective, observational study at a tertiary hospital from January 2022 to January 2024. A total of 208 children aged 1 month to 14 years with fever (≥ 38 °C) were included. Patients were categorized into sepsis (n = 84) and non-sepsis (n = 124) groups based on clinical assessment and blood culture results. Biomarker levels, patient demographics, clinical outcomes, and disposition were analyzed.

Elevated PCT and CRP levels were significantly associated with sepsis. PCT demonstrated earlier elevation compared to CRP, correlating with higher rates of PICU admission (34.7% vs. 11.1%, p < 0.001). Blood culture positivity was a strong predictor of severe sepsis (OR: 9.369, p < 0.0003). Logistic regression identified high-grade fever, chronic disease, and viral co-infections as additional risk factors.

PCT is a superior early biomarker for detecting invasive bacterial infections compared to CRP. Incorporating PCT in sepsis protocols can improve early diagnosis, guiding prompt and appropriate management in pediatric ED settings.

Our research aimed to explore the application of pulse pressure (PP) at the bedside of elderly intensive care unit (ICU) patients with sepsis through a large-scale retrospective cohort study.

We obtained data from four heterogeneous datasets, which included information on elderly sepsis patients (≥ 65 years). The data were divided into the inference and validation datasets. Thereby enhancing the generalizability of the study. The primary outcome was mortality at 28 days, and piecewise exponential additive mixed model (PAMM) were employed to estimate the strength of the associations over time.

We included 12,525 elderly patients with sepsis in the initial inference dataset. Based on the PAMM's inference results, we identified a specific low PP phenotype from the time-dependent endpoint dataset. The phenotype indicates an imbalance between the patient's cardiac pumping ability and circulatory resistance, contributing to an increased 28-day mortality (hazard ratio, 2.36; 95% CI, 2.12-2.63). The consistency of these results was validated using data from various sources.

Low PP phenotype (PP < 45 mmHg 72 h after intensive care unit admission and lasting for > 3h) may provide an early dynamic warning of the therapeutic effects of resuscitation interventions in long-hospitalized elderly patients with sepsis.

The results demonstrate acceptable consistency across heterogeneous datasets and hold promise for further development and integration into bedside monitoring systems for elderly sepsis patients.

Despite therapeutic advances, sepsis remains a global burden. Shortcomings within the healthcare system that inflate morbidity and mortality rates are instructive in this regard. This review aims to provide a qualitative synthesis of literature related to healthcare providers' perspectives on sepsis care, emphasizing perceived factors that impact the adequate care of septic patients and sepsis survivors.

In February 2023, we conducted a systematized search approach using the PubMed database.

Of 114 articles found in the PubMed database, 37 were included. A further 13 articles were identified by manual search. Healthcare providers highlighted a variety of dysfunctional and functional processes with an impact on sepsis care. Six domains were identified, related to the underlying disease, the patient, the provider, the guidelines, the healthcare system, and the collaboration among providers. Of note, providers' level of knowledge and a lack of communication between disciplines and/or sectors were reported as shortcomings in each phase of the care pathway (prevention, recognition, treatment, transitions of care, and aftercare).

This review suggests that, without limitation, interventions that provide continuous provider education as well as standard communication channels between interdisciplinary and intersectoral providers have great potential to improve structural deficiencies in sepsis care.

Sepsis is a severe condition associated with high mortality, and hospital performance is variable. The objective of this study was to develop geospatial sepsis clusters, identify sources of variation between clusters, and test the hypothesis that redistributing sepsis patients from low-performing hospitals to higher-performing hospitals within a cluster will improve sepsis outcomes.

We conducted a cohort study of age-qualifying Medicare beneficiaries using administrative claims data from 2013 to 2015. We calculated risk-standardized mortality for hospitals then used a clustering algorithm to define geospatial cluster boundaries based on care-seeking and interhospital transfer patterns. Finally, we used simulation to model the effect of reallocating sepsis patients to higher-performing hospitals within the same cluster.

None.

We included 1,125,308 patients, and they were grouped into 222 regional clusters. High-performing clusters were located largely in the Midwest, and they tended to be in less urban regions with smaller hospitals. In our simulation, the most impactful strategy was reassigning cases from the lowest-performing hospital in a cluster to the highest-performing hospital in the cluster, which was predicted to prevent 1705 deaths per year in the United States. This aggregate benefit was lower than the 5702 deaths predicted from reducing mortality by 1% absolute in hospitals in the lower half of the performance distribution.

Geospatial clusters provide insight into regional approaches to system-based acute care. In a simulation study, targeted sepsis regionalization appears less effective than local performance improvement in reducing preventable sepsis deaths.

Background: Sepsis is a major global health issue and the leading cause of death in critically ill patients, with rising incidence and associated healthcare costs. Early administration of antibiotic therapy is crucial, but increasing antibiotic resistance poses a threat. Beta-lactam antibiotics, commonly used as a first-line therapy option against sepsis, often demonstrate unpredictable concentrations due to pharmacokinetic and pharmacodynamic changes in critically ill patients. Acute kidney injury (AKI) affects a significant portion of septic patients, and continuous renal replacement therapy can further complicate treatment by reducing antibiotic levels and, consequently, increasing antibiotic resistance risk. Objectives: To develop pharmacokinetic/pharmacodynamic models for beta-lactam antibiotics in septic shock patients undergoing continuous renal replacement therapy (CRRT), with the goal of optimizing antibiotic dosing and then improving treatment outcomes. Methods: Septic shock Caucasian adult patients treated with beta-lactams and who have undergone major surgery in AKI failure that requires CRRT will be eligible with previous informed written consent. CRRT will be performed exclusively using Continuous Venovenous Hemodiafiltration (CVVHDF) modality. Antimicrobial determination analyses will be carried out with LC-MS/MS. Further calculation of pharmacokinetic parameters and determination of PK/PD breakpoints will be made using Monte Carlo simulation. Conclusions: The expected results from this study will lead to a better understanding of the pharmacokinetics of beta-lactam antibiotics in critically ill patients with AKI and septic shock undergoing CVVHDF, allowing for improved therapeutic strategies.

Acute cholecystitis in older patients with multimorbidity is associated with a high risk of morbidity and mortality. Debate exists as to whether operative or nonoperative treatment is the most appropriate approach.

To compare the effectiveness of operative and nonoperative treatment in older adults with multimorbidity who are hospitalized emergently with acute cholecystitis.

This was a nationwide retrospective comparative effectiveness research study conducted in the US from 2016 to 2018 that used both an inverse propensity weight analysis and an instrumental variable analysis. The study participants were Medicare beneficiaries with multimorbidity hospitalized emergently with acute cholecystitis. Previously validated qualifying comorbidity sets were used to identify multimorbidity. Data were analyzed from April 1, 2016, to December 31, 2018.

Treatment assignment of operative or nonoperative treatment for acute cholecystitis.

The primary outcome was 30- and 90-day mortality. Secondary outcomes included readmission rates, emergency department (ED) revisit rates, and cost. A preference-based instrumental variable approach was used to isolate circumstances for which the decision to operate is in clinical equipoise. Our hypothesis was that operative treatment would be associated with decreased mortality compared with nonoperative management.

Among the 32 527 included patients, the median age was 78.8 years (IQR, 72.4-85.2 years), and 21 728 patients (66.8%) underwent cholecystectomy. Of the 10 799 patients (33.2%) who received nonoperative treatment, 3462 (32.1%) received a percutaneous cholecystostomy tube. Among all patients, operative treatment was associated with a lower risk of 30-day mortality (risk difference [RD], -0.03; P < .001) and 90-day mortality (RD, -0.04; P < .001) compared with nonoperative treatment. Among patients for whom the treatment decision was in clinical equipoise, mortality was similar for the operative and nonoperative treatment groups; operative treatment was associated with a lower risk of 30-day readmissions (RD, -0.15; P < .001) and 90-day readmissions (RD, -0.23; P < .001) as well as a lower risk of 30-day ED revisits (RD, -0.09; P < .001) and 90-day ED revisits (RD, -0.12; P < .001). The risk-adjusted cost of operative treatment was higher at the index hospitalization (+$2870.84; P < .001) and lower at 90 days (-$5495.38; P < .001) and 180 days (-$9134.66; P < .001) compared with nonoperative treatment.

The findings of this comparative effectiveness research study suggest that risk-adjusted operative treatment of acute cholecystitis in older patients with multimorbidity was associated with lower rates of 30- and 90-day readmissions and ED revisits compared with nonoperative treatment and a lower cost by 90 days. These findings further suggest that when uncertainty exists regarding the most appropriate treatment approach for this challenging population, strong consideration should be given to operative treatment.

To describe mortality predictive factors in patients 80years or older with infection who were visited at the emergency department and were admitted to hospital.

Retrospective observational study. Patients ≥80years old who visited the emergency department (January 1st to December 31st, 2022), whose main diagnosis was infection and required admission, were included. Factors associated with mortality at the end of the episode were determined.

987 patients were included (mean age 87years, 53% women). Mortality at the end of the episode was 13% (n=127). Median survival of the series was 52days (95%CI: 44-60). The independent factors related to mortality were: age (HR: 1.07; 95%CI: 1.03-1.11; P<.001), frailty (Clinical Frailty Scale [CFS]) (HR: 1.51; 95%CI: 1.15-1.97; P=.003), qSOFA (HR: 1.35; 95%CI: 1.07-1.70; P=.01), SOFA (HR: 1.23; 95%CI: 1.15-1.38; P<.001), leukocyte count (HR: 1.04; 95%CI: 1.02-1.06; P<.001) and criteria for sepsis and/or septic shock (HR: 2.52; 95%CI: 1.63-3.87; P<.001). On the contrary, any type of microbiological isolation was associated with lower mortality (HR: 0.44; 95%CI: 0.29-0.64; P<.001).

qSOFA and SOFA scores, the sepsis and septic shock criteria, as well as frailty are predictive factors of poor prognosis in very elderly patients who come to the emergency room due to infection. Knowing frailty would allow us to adapt the treatment and therapeutic effort to the patient's characteristics.

Sepsis-associated encephalopathy (SAE) is a complex condition with variable outcomes. This study investigates the potential of the Triglyceride-glucose (TyG) index as a marker for disease severity and prognosis in SAE patients.

We conducted a retrospective cohort study using data from the Medical Information Mart for Intensive Care (MIMIC-IV) database. Patients with sepsis who were admitted to the intensive care unit (ICU) were categorized into two groups based on the occurrence of SAE. Key clinical outcomes were 90-day survival (primary outcome) and length of ICU and hospital stays, as well as the use of vasoactive medications (secondary outcomes). The TyG index was calculated, and its association with disease severity scores and patient outcomes was analyzed using statistical methods, including survival analysis, Cox regression, and correlation analyses.

The study population's median age was 65.96 years, predominantly male (60.1%). Higher TyG index scores correlated with elevated clinical severity scores (APSIII, LODS, OASIS, SAPSII, and CCI) and increased ICU and hospital stay durations. TyG index categorization revealed significant differences in 90-day survival probabilities, with "high TyG" associated with a 25% increased mortality risk compared to "low TyG." Furthermore, TyG index showed a moderate positive correlation with ICU stay duration and use of norepinephrine and vasopressin, but not with dopamine and epinephrine use.

The TyG index is a significant independent predictor of disease severity and prognosis in SAE patients. High TyG levels correlate with worse clinical outcomes and increased mortality risk, suggesting its potential as a valuable tool in managing SAE.

Sepsis is a common condition associated with significant morbidity and mortality. Emergency physicians play a key role in the diagnosis and management of this condition.

This paper evaluates key evidence-based updates concerning the management of sepsis and septic shock for the emergency clinician.

Sepsis is a life-threatening syndrome, and rapid diagnosis and management are essential. Antimicrobials should be administered as soon as possible, as delays are associated with increased mortality. Resuscitation targets include mean arterial pressure ≥ 65 mmHg, mental status, capillary refill time, lactate, and urine output. Intravenous fluid resuscitation plays an integral role in those who are fluid responsive. Balanced crystalloids and normal saline are both reasonable options for resuscitation. Early vasopressors should be initiated in those who are not fluid-responsive. Norepinephrine is the recommended first-line vasopressor, and if hypotension persists, vasopressin should be considered, followed by epinephrine. Administration of vasopressors through a peripheral 20-gauge or larger intravenous line is safe and effective. Steroids such as hydrocortisone and fludrocortisone should be considered in those with refractory septic shock.

An understanding of the recent updates in the literature concerning sepsis and septic shock can assist emergency clinicians and improve the care of these patients.

Sepsis triggers a harmful immune response due to infection, causing high mortality. Predicting sepsis outcomes early is vital. Despite machine learning's (ML) use in medical research, local validation within the Medical Information Mart for Intensive Care IV (MIMIC-IV) database is lacking. We aimed to devise a prognostic model, leveraging MIMIC-IV data, to predict sepsis mortality and validate it in a Chinese teaching hospital. MIMIC-IV provided patient data, split into training and internal validation sets. Four ML models logistic regression (LR), support vector machine (SVM), deep neural networks (DNN), and extreme gradient boosting (XGBoost) were employed. Shapley additive interpretation offered early and interpretable mortality predictions. Area under the ROC curve (AUROC) gaged predictive performance. Results were cross verified in a Chinese teaching hospital. The study included 27,134 sepsis patients from MIMIC-IV and 487 from China. After comparing, 52 clinical indicators were selected for ML model development. All models exhibited excellent discriminative ability. XGBoost surpassed others, with AUROC of 0.873 internally and 0.844 externally. XGBoost outperformed other ML models (LR: 0.829; SVM: 0.830; DNN: 0.837) and clinical scores (Simplified Acute Physiology Score II: 0.728; Sequential Organ Failure Assessment: 0.728; Oxford Acute Severity of Illness Score: 0.738; Glasgow Coma Scale: 0.691). XGBoost's hospital mortality prediction achieved AUROC 0.873, sensitivity 0.818, accuracy 0.777, specificity 0.768, and F1 score 0.551. We crafted an interpretable model for sepsis death risk prediction. ML algorithms surpassed traditional scores for sepsis mortality forecast. Validation in a Chinese teaching hospital echoed these findings.

Sepsis is an aggressive response to an infection leading to widespread inflammation, and may lead to death. It remains a significant challenge for cancer patients especially for the elderly due to their immunocompromised status and other comorbidities. So, this study aimed to assess the risk of mortality due to sepsis among elderly cancer patients and provide an updated evidence to the literature for better management outcomes.

We used data from the Surveillance, Epidemiology, and End Results (SEER) program. We included cancer patients who died due to sepsis between 2000 and 2021. The Standardized Mortality Ratio (SMR) for elderly cancer patients who died due to sepsis was calculated as observed/expected (O/E). We used 95% confidence intervals (CI) and the excess risk (ER) was per 100 000. Significance was achieved at 0.05.

Out of 5 239 194 elderly cancer patients, 18 311 died from sepsis. Men represented 55% and the majority were Caucasians (82%). Death from sepsis along 10+ years of follow-up had a significant SMR with an O/E of 1.32 (P >0.05, 95% CI: 1.30-1.34, ER = 2.56) especially within the first year after cancer diagnosis (O/E = 3.00, P >0.05). Gastric cancer had an increased risk for sepsis death in the elderly (O/E = 2.55, P < 0.05, 95% CI: 2.28-2.85). Liver and intrahepatic bile cancer had a significant SMR for sepsis (O/E = 5.56, P < 0.05, 95% CI: 5.01-6.36). However, it had an insignificant risk for sepsis deaths along 120+ months of follow-up period (O/E = 1.21, 95% CI: 0.25-3.52, ER = 1.73).

Sepsis is a rapid silent killer targeting a vulnerable population. Although it had a declining mortality rate along 10+ years of follow up as the majority die due to other cancer-related and non-cancer-related causes, it still represents a certain threat to elderly cancer patients due to the immunosuppression of cancer treatment regimen and antibiotic resistance. Further studies are encouraged to focus on elderly cancer patients' health care and to intensify infection control measures.

Sepsis is characterised by dysregulated immune responses to infection, leading to multi-organ dysfunction and high rates of mortality. With increasing survival rates in recent years long-term neurological and psychiatric consequences have become more apparent in survivors. Many patients develop sepsis associated encephalopathy (SAE) which encompasses the profound but usually transient neuropsychiatric syndrome delirium but also new brain injury that emerges in the months and years post-sepsis. It is now clear that systemic inflammatory signals reach the brain during sepsis and that very significant neuroinflammation ensues. The major brain resident immune cell population, the microglia, has been implicated in acute and chronic cognitive dysfunction in animal models of sepsis based on a growing number of studies using bacterial endotoxin and in polymicrobial sepsis models such as cecal ligation and puncture. The current review explores the effects of sepsis on the brain, focussing on how systemic insults translate to microglial activation and neuroinflammation and how this disrupts neuronal function and integrity. We examine what has been demonstrated specifically with respect to microglial activation, revealing robust evidence for a role for neuroinflammation in sepsis-induced brain sequelae but less clear information on the extent of the specific microglial contribution to this, arising from findings using global knockout mice, non-selective drugs and treatments that equally target peripheral and central compartments. There is, nonetheless, clear evidence that microglia do become activated and do contribute to brain consequences of sepsis thus arguing for improved understanding of these neuroinflammatory processes toward the prevention and treatment of sepsis-induced brain dysfunction.

Aim & Background: Delirium frequently occurs in the acute phase of sepsis and is associated with increased ICU and hospital length of stay, duration of mechanical ventilation, and higher mortality rates. We utilized the Near-Infrared Spectroscopy monitor to measure and compare the regional cerebral oxygen saturation in mechanically ventilated patients of sepsis receiving either dexmedetomidine or propofol sedation and assessed the association between delirium and regional cerebral oxygen saturation. Methods: A single center prospective randomized control trial conducted over a period of two years, 54 patients were included, equally divided between propofol and dexmedetomidine groups. Patients received a blinded study drug, propofol (10 mg/mL) or dexmedetomidine (5 mcg/mL) via infusion pump according to randomization. Infusion rates were adjusted every 10 min based on weight-based titration tables, aiming for target sedation (RASS -2 to 0). Management components included pain monitoring using the CPOT score and delirium assessment using CAM-ICU score. Results: Dexmedetomidine group showed higher mean regional cerebral oxygen saturation as compared to propofol group (P = .036). No significant differences were found in mechanical ventilation or ICU stay durations, delirium-free days, or sedation cessation reasons. Delirium occurred in 36 patients, with lower mean regional cerebral oxygen saturation as compared to non-delirious patients. Conclusion: The dexmedetomidine group had higher regional cerebral oxygen saturation compared to the propofol group. Delirious patients showed lower cerebral oxygen saturation than non-delirious patients, suggesting a link between sedation type, cerebral oxygenation, and delirium. CTRI registration: REF/2021/11/048655 N.

Prediction of mortality in intensive care unit (ICU) patients typically relies on black box models (that are unacceptable for use in hospitals) or hand-tuned interpretable models (that might lead to the loss in performance). We aim to bridge the gap between these 2 categories by building on modern interpretable machine learning (ML) techniques to design interpretable mortality risk scores that are as accurate as black boxes.

We developed a new algorithm, GroupFasterRisk, which has several important benefits: it uses both hard and soft direct sparsity regularization, it incorporates group sparsity to allow more cohesive models, it allows for monotonicity constraint to include domain knowledge, and it produces many equally good models, which allows domain experts to choose among them. For evaluation, we leveraged the largest existing public ICU monitoring datasets (MIMIC III and eICU).

Models produced by GroupFasterRisk outperformed OASIS and SAPS II scores and performed similarly to APACHE IV/IVa while using at most a third of the parameters. For patients with sepsis/septicemia, acute myocardial infarction, heart failure, and acute kidney failure, GroupFasterRisk models outperformed OASIS and SOFA. Finally, different mortality prediction ML approaches performed better based on variables selected by GroupFasterRisk as compared to OASIS variables.

GroupFasterRisk's models performed better than risk scores currently used in hospitals, and on par with black box ML models, while being orders of magnitude sparser. Because GroupFasterRisk produces a variety of risk scores, it allows design flexibility-the key enabler of practical model creation.

GroupFasterRisk is a fast, accessible, and flexible procedure that allows learning a diverse set of sparse risk scores for mortality prediction.

Sepsis and septic shock are common conditions evaluated and managed in the emergency department (ED), and these conditions are associated with significant morbidity and mortality. There have been several recent updates in the literature, including guidelines, on the evaluation and diagnosis of sepsis and septic shock.

This is the first paper in a two-part series that provides emergency clinicians with evidence-based updates concerning sepsis and septic shock. This first paper focuses on evaluation and diagnosis of sepsis and septic shock.

The evaluation, diagnosis, and management of sepsis have evolved since the first definition in 1991. Current guidelines emphasize rapid diagnosis to improve patient outcomes. However, scoring systems have conflicting data for diagnosis, and sepsis should be considered in any patient with infection and abnormal vital signs, evidence of systemic inflammation (e.g., elevated white blood cell count or C-reactive protein), or evidence of end-organ dysfunction. The clinician should consider septic shock in any patient with infection and hypotension despite volume resuscitation or who require vasopressors to maintain a mean arterial pressure ≥ 65 mmHg. There are a variety of sources of sepsis but the most common include pulmonary, urinary tract, abdomen, and skin/soft tissue. Examples of other less common etiologies include the central nervous system (e.g., meningitis, encephalitis), spine (e.g., spinal epidural abscess, osteomyelitis), cardiac (e.g., endocarditis), and joints (e.g., septic arthritis). Evaluation may include biomarkers such as procalcitonin, C-reactive protein, and lactate, but these should not be used in isolation to exclude sepsis. Imaging is a key component of evaluation and should be based on the suspected source.

There have been several recent updates in the literature including guidelines concerning sepsis and septic shock; an understanding of these updates can assist emergency clinicians and improve the care of these patients.

Sepsis is a leading cause of in-hospital mortality. However, its prevalence is increasing among the elderly population. Therefore, early identification and prediction of the risk of death in elderly patients with sepsis is crucial. The objective of this study was to create a machine learning model that can predict short-term mortality risk in elderly patients with severe sepsis in a clear and concise manner.

Data was collected from the MIMIC-IV (2.2). It was randomly divided into a training set and a validation set using a 7:3 ratio. Mortality predictors were determined through Recursive Feature Elimination (RFE). A prediction model for 28 days of ICU stay was built using six machine-learning algorithms. To create a comprehensive and nuanced model resolution, Shapley Additive Explanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) were used to systematically interpret the models at both a global and detailed level.

The study involved the analysis of 4,056 elderly patients with sepsis. A feature recursive elimination algorithm was utilized to select eight variables out of 49 for model development. Six machine learning models were assessed, and the Extreme Gradient Boosting (XGBoost) model was found to perform the best. The validation set achieved an AUC of 0.88 (95% CI: 0.86-0.90) and an accuracy of 0.84 (95% CI: 0.81-0.86) for this model. To examine the roles of the eight key variables in the model, SHAP analysis was employed. The global ranking order was made evident, and through the use of LIME analysis, the weights of each feature range in the prediction model were determined.

The study's machine learning prediction model is a dependable tool for forecasting the prognosis of elderly patients with severe sepsis.

Sepsis and septic shock are significant global healthcare challenges with high mortality rates. Effective management requires timely and adequate antimicrobial therapy. Beta-lactam antibiotics, commonly used in patients with sepsis, are crucial for treating these infections. However, standard dosing often leads to insufficient plasma levels due to dynamic physiological changes in critically ill patients. Previous randomized controlled trials highlighted the need for timely dose adjustments to improve clinical outcomes. This is the study protocol for the BULLSEYE trial in which we aim to optimize antibiotic treatment during the initial 48 h of sepsis by comparing standard to double dosing of beta-lactam antibiotics.

This open-label, multicenter, randomized controlled trial will compare standard to double dosing of beta-lactam antibiotics (cefuroxime, ceftazidime, ceftriaxone, cefotaxime, amoxicillin, amoxicillin/clavulanic acid, flucloxacillin, meropenem, and piperacillin/clavulanic acid) in critically ill patients with septic shock. Participants will be randomized into two arms: the control arm receiving standard care, and the intervention arm receiving double antibiotic doses for 48 h, irrespective of renal function. Following this period, all patients will receive standard doses as per local protocol. The primary outcome is all cause 28-day mortality, with secondary outcomes including 90-day, 365-day, hospital and ICU mortality, hospital and ICU length of stay, SOFA scores, time to shock reversal, microbiological eradication, clinical cure, pharmacodynamic target attainment, safety, quality of life, and medical consumption.

The BULLSEYE trial aims to improve sepsis treatment in critically ill patients. Despite anticipated recruitment challenges, its large sample size ensures robust comparability. This pivotal trial could significantly impact sepsis treatment, leading to better clinical outcomes.

EU_CT 2024-512950-13-00. Protocol version 2.3, protocol date 09-12-2024. Prospectively registered on 09-01-2025 at Clinicaltrails.gov nr. NCT06766461.

In observational studies that use administrative data, it is essential to report technical details such as the number of International Classification of Disease (ICD) coding fields extracted. This information is crucial for ensuring comparability between studies and for avoiding truncation bias in estimates, particularly for complex conditions like sepsis. Specific sepsis codes (explicit sepsis) are suggested to be identified by extracting 15 diagnosis fields, while for implicit sepsis, which comprises an infection code combined with acute organ failure, the number of diagnosis field remains unknown.

The objective was to explore the necessary number of diagnosis fields to capture explicit and implicit sepsis.

We conducted a study utilizing The Norwegian Patient Register (NPR), which encompasses all medical ICD-10 codes from specialized health services in Norway. Data were extracted for all adult patients with hospital discharges registered with explicit and implicit sepsis codes from all Norwegian hospitals between 2008 through 2021.

Out of 317,705 sepsis admissions, we identified 105,499 ICD-10 codes for explicit sepsis, while implicit sepsis was identified through 270,346 codes for infection in combination with 240,789 codes for acute organ failure. Through our analysis, we found that 55%, 37%, and 10% of the explicit, infection, and acute organ failure codes, respectively, were documented as the main diagnosis. The proportion of explicit and infection codes peaked in the primary diagnosis field, while for acute organ failure codes, this was true in the third secondary diagnosis field. Notably, the cumulative proportion reached 99% in diagnosis field 10 for explicit codes and in diagnosis field 13 for implicit codes.

Expanding the utilization of multiple diagnosis fields can enhance the comparability of data in epidemiological studies, both internationally and within countries. To make truncation bias visible, reporting guidelines should specify the number of diagnosis fields when extracting ICD-10 codes.

Previous studies have shown an association between depression and increased susceptibility to infection in the general population. However, there has been no prior research specifically examining the relationship between treatment-resistant depression (TRD) and severe bacterial infections (SBI) in adolescents and young adults. This retrospective observational cohort study utilized the Taiwan National Health Insurance Research Database (NHIRD) from 2001 to 2010. It included adolescents (12-19 years of age) and young adults (20-29 years of age) diagnosed with major depressive disorder (MDD), comprising 6958 cases of TRD and 27,832 cases of antidepressant-responsive depression (ARPD). The TRD and ARPD groups were further matched (4:1) by chronological age, age at diagnosis of depression, sex, residence, and family income. The primary outcomes were severe bacterial infections (SBI) and septicemia. Cox regression analysis was conducted to identify the risk of hospitalization due to SBI or septicemia during the follow-up period. Compared with controls, the ARPD group had increased risks of SBI (hazard ratio [HR] with 95% confidence interval [CI]: 3.90, 2.73-5.57) and septicemia (HR, 95% CI: 2.56, 1.34-4.91). Notably, the risks of SBI and septicemia appeared to be further elevated in the TRD group. The TRD group exhibited higher incidences of SBI (HR, 95% CI: 6.99, 4.73-10.34) and septicemia (HR, 95% CI: 2.85, 1.28-6.36) than the control group. Adolescents and young adults with TRD had 6.99-fold and 3.90-fold increased risks of SBI and septicemia compared to individuals without MDD, respectively. Therefore, healthcare providers need to be vigilant when monitoring and implementing preventive measures in this population.

Sepsis is a leading cause of death in hospitalized patients. The underlying pathophysiologic mechanisms of sepsis have not been fully elucidated thus far. The receptor of programmed cell death 1 (PD-1) and its ligand (PD-L1), in combination with the Toll-like receptors (TLRs), seem to contribute considerably in systematic responses during sepsis. Investigating the relationship between them and identifying potential target pathways is important in the future management of sepsis, especially in relation to acute lung injury. This study investigated the interactions between TLR-5, -6, and -9 and PD-1/PD-L1 expression in a septic mouse model. Sixty C57BL/6J mice were included and categorized in six study groups. Three sepsis (S) groups (24 h, 48 h, and 72 h) and three sham (Sh) groups (24 h, 48 h, and 72 h) were created. Cecal ligation and puncture (CLP) was utilized to simulate sepsis in the S groups. Hematological analysis and lung tissue histopathological analysis were performed after 24 h, 48 h, and 72 h. Significant decreases in S groups compared to Sh groups in WBC and lymphocyte counts at 24, 48, and 72 h were observed. Significant increases in S groups compared to Sh groups in RBC and monocyte counts, IL-6 and IL-10 levels, alveolar flooding, and alveolar collapse were demonstrated by histopathological analysis. This study suggested a strong correlation between TLR expression and PD-1/PD-L1 up-regulation in lung tissue during sepsis. These molecules, also, seem to contribute to the histopathological changes in lung tissue during sepsis, leading to acute lung injury.

TLR4/MD-2, a protein complex to recognize LPS, has become an ideal target for the treatment of inflammation-related diseases. Blumeatin (BL), which is isolated from Blumea balsamifera (L.) DC has rarely been reported in the inflammation field. In this article, we targeted the TLR4/MD-2 complex to explore how BL regulates the TLR4/NF-κB inflammatory signaling pathway and inhibits LPS-induced inflammation. BL can target the hydrophobic pocket of TLR4/MD-2, inhibit the binding of LPS to TLR4/MD-2, the dimerization of TLR4 and MD-2, and the TLR4/NF-κB signaling pathway activation and the secretion of downstream inflammatory factors. BL may be used as a molecular target of TLR4/MD-2 for the treatment of inflammation-related diseases.

Objective: To evaluate the difference in proportion of patients receiving antimicrobials within one hour of sepsis recognition at sepsis-related Medical Emergency Team (MET) calls, without or with a sepsis-credentialed pharmacist. Design: Retrospective pre and post-intervention study. Setting: Single centre tertiary referral hospital. Participants: Patients admitted to the General Medicine Unit who had a sepsis-related MET call 24 hrs per day, and all other units from 17:00-08:00 hrs from August 2019 to Jan 2020 in the pre-intervention cohort and Aug 2020 to Jan 2021 for the post-intervention cohort. Interventions: Pharmacists attended MET calls to assist selection of antimicrobials, collaboratively prescribe with the medical officers, ensure supply, provide advice on dosing calculations, reconstitution, and administration. The pre-intervention cohort (Aug 2019-Jan 2020) did not have credentialed pharmacists' involvement at MET calls. Outcome Measures: Proportion of patients who received antimicrobials within one hours of MET call. Results: There were 97 sepsis-related MET calls in the pre-intervention cohort and 110 sepsis-related MET calls in the post-intervention cohort. A significantly higher proportion of patients received antimicrobials within one hour with pharmacist involvement, compared to control (81.3% vs 59.7%, P = .0006). A reduction in median time to antimicrobial administration (43 min vs 54 min, P = .017) was observed. Conclusion: Sepsis-related MET calls with pharmacist involvement experienced a greater proportion of patients receiving antimicrobials within one hour of sepsis recognition, and a reduction in median time to antimicrobial administration. These results provide support for routine pharmacist involvement at MET calls to assist patients receiving medications in a timely and efficient manner.

Repurposing electronic health record (EHR) or electronic medical record (EMR) data holds significant promise for evidence-based epidemic intelligence and research. Key challenges include sepsis recognition by physicians and issues with EHR and EMR data. Recent advances in data-driven techniques, alongside initiatives like the Surviving Sepsis Campaign and the Severe Sepsis and Septic Shock Management Bundle (SEP-1), have improved sepsis definition, early detection, subtype characterization, prognostication and personalized treatment. This includes identifying potential biomarkers or digital signatures to enhance diagnosis, guide therapy and optimize clinical management. Machine learning applications play a crucial role in identifying biomarkers and digital signatures associated with sepsis and its sub-phenotypes. Additionally, electronic phenotyping, leveraging EHR and EMR data, has emerged as a valuable tool for evidence-based sepsis identification and management. This review examines methods for identifying sepsis cohorts, focusing on two main approaches: utilizing health administrative data with standardized diagnostic coding via the International Classification of Diseases and integrating clinical data. This overview provides a comprehensive analysis of current cohort identification and electronic phenotyping strategies for sepsis, highlighting their potential applications and challenges. The accuracy of an electronic phenotype or signature is pivotal for precision medicine, enabling a shift from subjective clinical descriptions to data-driven insights.

Sepsis remains the leading cause of in-hospital death and one of the costliest inpatient conditions in the United States, while treatment delays worsen outcomes. We sought to determine factors and outcomes associated with a missed emergency physician (EP) diagnosis of sepsis.

We conducted a secondary analysis of a prospective single-center observational cohort of undifferentiated, critically ill medical patients (September 2020-May 2022). EP gestalt of suspicion for sepsis was measured using a visual analog scale (VAS; 0%-100%) at 15 and 60 min post-patient arrival. The primary outcome was an explicit hospital discharge diagnosis of sepsis that was present on arrival. We calculated test characteristics for clinically relevant subgroups and examined factors associated with initial and persistent missed diagnoses. Associations with process (antibiotics) and clinical (mortality) outcomes were assessed after adjusting for severity.

Among 2484 eligible patients, 275 (11%) met the primary outcome. A VAS score of ≥50 (more likely than not of being septic) at 15 min demonstrated sensitivity 0.83 (95% confidence interval [CI] 0.78-0.87) and specificity 0.85 (95% CI 0.83-0.86). Older age, hypoxia, hypotension, renal insufficiency, leukocytosis, and both high and low temperature were significantly associated with lower accuracy due to reduced specificity, but maintained sensitivity. Of 48 (17%) and 23 (8%) missed cases at 15 and 60 min, elevated lactate, leukocytosis, bandemia, and positive urinalysis were more common in the missed sepsis compared to nonsepsis cases. Missed diagnoses were associated with median (interquartile range) delay of 48 (27-64) min in antibiotic administration but were not independently associated with inpatient mortality as risk ratios remained close to 1 across VAS scores.

This prospective single-academic center study identified patient subgroups at risk of impaired diagnostic accuracy of sepsis, with clinicians often overdiagnosing rather than underdiagnosing these groups. Prompt abnormal laboratory test results can "rescue" initial missed diagnoses, serving as potential clinician- and systems-level intervention points to reduce missed diagnoses. Missed diagnoses delayed antibiotics, but not mortality after controlling for severity of illness.