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Abstract: Background: Hemodynamic support using vasoactive agents is a mainstay in the management of patients with pediatric fluid-refractory septic shock (FRSS). However, evidence supporting the appropriate choice of vasoactive agent is limited. This study aimed to perform a systematic review and meta-analysis on the effect of different first-line vasoactive strategies on mortality in pediatric FRSS. Methods: MEDLINE, Embase, Scopus, CINAHL, Web of Science, the Cochrane Library, ClinicalTrials.gov , and the ISRCTN registry were searched up until December 2023. Randomized controlled trials and observational cohort studies reporting vasoactive agent-specific outcomes of children with FRSS were included. Mortality was assessed as primary outcome in studies on patients receiving dopamine, epinephrine, or norepinephrine as first-line. Random-effects meta-analyses were conducted. Prevalence ratio (PR) estimates were calculated between two drugs when was available in the same study. Findings: Of the 26,284 identified articles, 13 were included, for a total of 997 children. Twelve studies included 748 patients receiving a single vasoactive agent. Of these, 361 received dopamine, 271 epinephrine, and 116 norepinephrine. Overall pooled mortality for patients receiving a single vasoactive was 12% (95% CI 6%-21%) of which 11% (95% CI 3%-36%) for patients receiving dopamine, 17% (95% CI 6%-37%) for epinephrine, and 7% (95% CI 1%-48%) for norepinephrine. Four first-line dopamine (176 patients) and first-line epinephrine (142 patients): dopamine showed a tendency toward higher mortality (PR 1.38, 95% CI 0.81-2.38) and a significant higher need for mechanical ventilation (PR 1.12, 95% CI 1.02-1.22). Interpretation: Among children with FRSS receiving a single vasoactive agent, norepinephrine was associated with the lowest mortality rate. Comparing dopamine and epinephrine, patients receiving epinephrine needed less mechanical ventilation and showed a trend for lower mortality rate. Further research is needed to better delineate the first-line vasoactive agent in this population.

Abstract: Background: Critical illness stemming from severe traumatic injury is a leading cause of morbidity and mortality worldwide and involves the dysfunction of multiple organ systems, driven, at least in part, by dysregulated inflammation. We and others have shown a key role for genetic predisposition to dysregulated inflammation and downstream adverse critical illness outcomes. Recently, we demonstrated an association among genotypes at the single-nucleotide polymorphism (SNP) rs10404939 in LYPD4 , dysregulated systemic inflammation, and adverse clinical outcomes in a broad sample of ~1,000 critically ill patients. Methods: We sought to gain mechanistic insights into the role of LYPD4 in critical illness by bioinformatically analyzing potential interactions among rs10404939 and other SNPs. We analyzed a dataset of common (i.e., not rare) SNPs previously defined to be associated with genotype-specific, significantly dysregulated systemic inflammation trajectories in trauma patients, in comparison to a control dataset of common SNPs determined to exhibit an absence of genotype-specific inflammatory responses. Results: In the control dataset, this analysis implicated SNPs associated with phosphatidylinositol and various membrane transport proteins, but not LYPD4. In the patient subset with genotypically dysregulated inflammation, our analysis suggested the co-localization to lipid rafts of LYPD4 and the complement receptor CD55, as well as the neurally related CNTNAP2 and RIMS4. Segregation of trauma patients based on genotype of the CD55 SNP rs11117564 showed distinct trajectories of organ dysfunction and systemic inflammation despite similar demographics and injury characteristics. Conclusion: These analyses define novel interactions among SNPs that could enhance our understanding of the response to traumatic injury and critical illness.

Background: Severe heatstroke patients have a poor prognosis. There are few descriptions of the inflammatory response to heatstroke in clinical studies. Systemic immune-inflammation index(SII) is a new index to reflect the inflammatory state of disease.

Methods: This retrospective observational study included patients who had severe heatstroke between 2010 and 2023. Multivariate logistic regression and nomogram were performed to determine the ability of the SII to predict the prognosis of these patients, and subgroup analysis was performed according to SII levels.

Results: Of the 177 patients included in our study, 28 (15.8%) died. There was no difference in SII values between the first day (p = 0.810) and the second day (p = 0.184) in multivariate analysis. The SII value of the third day (SII 72) was elevated in patients with heatstroke who died compared to that in those who survived (p = 0.035). In multivariable logistic regression, Sequential Organ Failure Assessment (SOFA) score (OR = 1.717, 95%CI: 1.073-2.747, p = 0.024) and SII 72 (OR = 1.001, 95%CI: 1.000-1.002, p = 0.035) were found to be independent predictors of mortality. SII 72 combined with SOFA score distinguished between patients who died and those who survived better than did the separate SOFA score. Patients with SII 72 > 1000 had poor clinical prognosis.

Conclusions: Compared to SII results from the first and second days, third-day results more meaningfully predict poor heatstroke prognosis. SII 72 may be a good indicator, and when combined with SOFA, offers enhanced predictive value.

Abstract: Sepsis results from a dysregulated host immune response to infection and is responsible for ~11 million deaths each year. In the laboratory, many aspects of sepsis can be replicated using a cecal ligation and puncture (CLP) model, which is considered the most clinically relevant rodent model of sepsis. In the present study, histological and biomarker multiplex analyses revealed that the CLP model initiated a large-scale inflammatory response in mice by 24 h, with evidence of acute organ damage by 48-72 h. While many typical pro-inflammatory cytokine/chemokines were systemically elevated, a specific array including IL-10, eotaxin, MIP-1α, MIP-1β, MCP-1 and RANTES noticeably increased just prior to animals reaching the humane endpoint. Treatment of mice with 10 μg of a synthetic 68-amino acid peptide derived from an immunomodulatory molecule secreted by a parasitic worm of humans and livestock, Fasciola hepatica, termed Fasciola hepatica helminth defence molecule (FhHDM), potently suppressed the systemic inflammatory profile, protected mice against acute kidney injury, and improved survival between 48 and 72 h post-procedure. These results suggest that the anti-inflammatory parasite-derived FhHDM peptide has potential as a bio-therapeutic treatment for sepsis.

Introduction: Veno-venous extracorporeal membrane oxygenation (VV ECMO) improves hypoxemia and carbon dioxide clearance in patients with severe respiratory derangements. A greater understanding of the potential benefits of VV ECMO in trauma patients could lead to broader adoption. We hypothesize that trauma patients who receive VV ECMO have improved mortality outcomes when compared to those receiving conventional ventilator management given the rapid stabilization VV ECMO promotes.

Methods: We performed a single center, propensity score matched cohort study. All trauma patients from January 1, 2014, to October 30, 2023, who were placed on VV ECMO or who would have met institutional guidelines for VV ECMO but were managed with conventional ventilator strategies were matched 1:1. The primary outcome analysis was survival at hospital discharge. Significance was defined as p < 0.05.

Results: Eighty-one trauma VV ECMO patients and 128 patients who received conventional management met criteria for inclusion. After matching, VV ECMO and conventional treatment cohort characteristics were similar in age and MOI. Matched ISS, SI, lactate levels, and frequency of TBI were also similar. Finally, respiratory parameters including pre-intervention, pH, partial pressure of carbon dioxide (PaCO2), lactate levels, and oxygen saturation were similar between matched groups. VV ECMO patients had higher survival rates at discharge when compared to the matched conventional treatment group (70% v 41%, p < 0.001). Corresponding hazard ratio for VV ECMO use was 0.31 (95%CI 0.18-0.52; p < 0.001). The odds ratio of mortality in matched trauma patients who receive VV ECMO versus conventional treatment was 0.29 (95%CI 0.14-0.58; p < 0.001).

Conclusion: VV ECMO may represent a safe, alternative treatment approach for appropriately screened trauma patients with acute respiratory failure, however further studies are warranted.

Introduction: The prehospital environment is fraught with operational constraints, making it difficult to assess the need for resources such as lifesaving interventions (LSI) for adults with traumatic injuries. While invasive methods such as lactate have been found to be highly predictive for estimating injury severity and resource requirements, noninvasive methods, to include continuous vital signs (VS), have the potential to provide prognostic information that can be quickly acquired, interpreted, and incorporated into decision making. In this work, we hypothesized that an analysis of continuous VS would have predictive capacity comparable to lactate and other laboratory tests for the prediction of injury severity, need for LSIs and intensive care unit (ICU) admission.

Methods: In this pre-planned secondary analysis of 300 prospectively enrolled patients, venous blood samples were collected in the prehospital environment aboard a helicopter and analyzed with a portable lab device. Patients were transported to the primary adult resource center for trauma in the state of Maryland. Continuous VS were simultaneously collected. Descriptive statistics were used to describe the cohort and predictive models were constructed using a regularized gradient boosting framework with 10-fold cross-validation with additional analyses using Shapley additive explanations (SHAP).

Results: Complete VS and laboratory data from 166 patients were available for analysis. The continuous VS models had better performance for prediction of receiving LSIs and ICU length of stay compared to single (initial) VS measurements. The continuous VS models had comparable performance to models using only laboratory tests in predicting discharge within 24 hours (continuous VS model: AUROC 0.71; 95% CI, 0.68-0.75 vs. lactate model: AUROC 0.65; 95% CI, 0.68; 95% CI, 0.66-0.71). The model using all laboratory data yielded the highest sensitivity and sensitivity (AUROC 0.77; 95% CI, 0.74-0.81).

Discussion: The results from this study suggest that continuous VS obtained from autonomous monitors in an aeromedical environment may be helpful for predicting LSIs and the critical care requirements for traumatically injured adults. The collection and use of noninvasively obtained physiological data during the early stages of prehospital care may be useful for in developing user-friendly early warning systems for identifying potentially unstable trauma patients.

Abstract: Liver ischemia reperfusion (IR) injury significantly impacts clinical outcomes by increasing the risk of hepatic dysfunction after liver surgery. Fatty livers are more susceptible to IR stress. Recent studies have demonstrated that S100A9 plays a crucial role in both IR injury and the progression of liver steatosis. Nevertheless, the precise mechanisms underlying these effects remain unclear. In our study, transcriptome analysis of fatty livers subjected to IR insult in mice identified S100A9 as an important mediator. Employing loss-of-function approaches, we investigated the immune regulatory function of S100A9 and its downstream signaling in fatty liver IR injury. As expected, S100A9 emerged as one of the most significantly upregulated genes during the reperfusion stage in fatty livers. Genetic knockdown of S100A9 markedly ameliorated liver pathological damage, evidenced by reduced macrophage/neutrophil infiltration as well as the decreased expression of proinflammatory factors. Transcriptome/functional studies revealed that S100A9 triggered liver inflammatory response via regulating Toll-like receptor 2 (TLR2)/Activating transcription factor 4 (ATF4) signaling. Additionally, TLR2 expression was notably increased in macrophages from ischemic fatty livers. In vitro, recombinant S100A9-stimulated macrophages exhibited the elevated production of proinflammatory factors and TLR2/ATF4 pathway activation. Intriguingly, S100A9 facilitated ATF4 nuclear translocation and enhanced NEK7/NLRP3 inflammasome activation in macrophages. In conclusion, our study identified S100A9 as a key regulator responsible for macrophage NLRP3 inflammasome activation and subsequent inflammatory injury in fatty liver IR process. Targeting TLR2/ATF4 signaling may offer a novel therapeutic strategy for mitigating S100A9-mediated liver injury.

Background: Sepsis, a life-threatening response to infection leading to systemic inflammation and organ dysfunction, has been hypothesized to be influenced by metabolic alterations in cerebrospinal fluid (CSF). Despite extensive research, the specific metabolic pathways contributing to sepsis remain unclear. This study aims to elucidate the causal relationships between CSF metabolites and sepsis risk using Mendelian Randomization (MR), offering insights that could lead to novel therapeutic strategies.

Methods: We conducted a two-sample MR analysis using genetic variants as instrumental variables (IVs) to investigate 338 CSF metabolites identified through a genome-wide association study. Data on sepsis-related outcomes were extracted from the genome-wide association study (GWAS) catalog encompassing 486,484 individuals of European descent. IVs were rigorously selected based on stringent genetic association and linkage disequilibrium criteria. Statistical analyses, including inverse variance weighting (IVW) and weighted median methods, were performed using the 'TwoSampleMR' package in R software, supplemented by comprehensive sensitivity analyses to ensure the robustness of our findings.

Results: Our analysis identified 19 CSF metabolites causally associated with sepsis risk. Notably, metabolites such as 1-palmitoyl-2-stearoyl-gpc (16:0/18:0) and 2-hydroxyglutarate showed significant negative correlations with sepsis risk. The reverse MR analysis further revealed that sepsis could negatively impact certain CSF metabolite levels, particularly Ribonate, suggesting a bidirectional relationship. These relationships were substantiated by rigorous statistical testing and sensitivity analyses confirming the absence of horizontal pleiotropy and the stability of our results across various MR methods.

Conclusions: This study demonstrates significant causal associations between specific CSF metabolites and the risk of developing sepsis, highlighting the potential for these metabolites to serve as biomarkers or therapeutic targets. The bidirectional nature of these findings also suggests that sepsis itself may alter metabolic profiles, offering further avenues for intervention.

Background: New strategies are needed to mitigate further tissue injury during traumatic limb ischemia in cases requiring damage control resuscitation (DCR). Little is known about the pathophysiology and injury course in acute limb ischemia (ALI) with DCR in polytraumatized casualties. We therefore investigated the effects of therapeutic limb hypothermia in a swine model of ALI and DCR.

Methods: Fifteen swine underwent a published 6-hour DCR protocol of hemorrhage and then resuscitation. After hemorrhage, animals were randomized to 5oC or 15oC cooling of one hindlimb; the contralateral limb serving as an uncooled control. Physiologic variables, limb temperature, and limb tissue metabolites (glucose, lactate, and pyruvate) were measured throughout the DCR protocol. Muscle and nerve biopsies were obtained after the 6-hour protocol.

Results: Lactate and pyruvate levels were significantly lower in the cooled limbs than in the uncooled control limbs but did not differ between the 5oC and 15oC groups. Tissue glucose levels did not differ between the 5oC group, the 15oC group, and controls. Mean histologic muscle score was significantly higher in the 5oC group than in controls (p = 0.03). Mean nerve histology scores did not differ between the 5oC and paired control limbs, or between the mean muscle and nerve histology scores of the 15oC and paired control limbs.

Conclusion: Cooling to 15oC significantly reduced local tissue metabolites compared to paired controls, while producing no significant increase in histologic damage, whereas cooling to 5oC increased histologic muscle damage. These results suggest an approach to prevention of ischemic injury through local hypothermia but warrant further functional testing.

Introduction: Unplanned intensive care unit (ICU) admissions are associated with increased morbidity and mortality. This study uses interpretable machine learning to predict unplanned ICU admissions for initial nonoperative trauma patients admitted to non-ICU locations.

Methods: TQIP (2020-2021) was queried for initial nonoperative adult patients admitted to non-ICU locations. Univariable analysis compared patients who required an unplanned ICU admission to those who did not. Using variables that could be known at hospital admission, gradient boosting machines (CatBoost, LightGBM, XGBoost) were trained on 2021 data and tested on 2020 data. SHapley Additive exPlanations (SHAP) were used for interpretation.

Results: The cohort had 1,107,822 patients; 1.6% had an unplanned ICU admission. Unplanned ICU admissions were older (71 [58-80] vs. 61 [39-76] years, p < 0.01), had a higher Injury Severity Score (ISS) (9 [8-13] vs. 9 [4-10], p < 0.01), longer length of stay (11 [7-17] vs. 4 [3-6] days, p < 0.01), higher rates of all complications and most comorbidities and injuries (p < 0.05). All models had an AUC of 0.78 and an F1 score of 0.12, indicating poor performance in predicting the minority class. Mean absolute SHAP values revealed ISS (0.46), age (0.29), and absence of comorbidities (0.16) as most influential in predictions. Dependency plots showed greater SHAP values for greater ISS, age, and presence of comorbidities.

Conclusions: Machine learning may outperform prior attempts at predicting the risk of unplanned ICU admissions in trauma patients while identifying unique predictors. Despite this progress, further research is needed to improve predictive performance by addressing class imbalance limitations.