Can serum NSE predict and evaluate sepsis-associated encephalopathy: A protocol for a systematic review and meta-analysis.

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 systematic review and meta-analysis will aim 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 AND ANALYSIS: We will conduct a systematic review and meta-analysis of serum NSE for the diagnostic and prognostic value of SAE patients. The primary objective is to evaluate the diagnostic accuracy of serum NSE as an independent biomarker for SAE. The secondary objective is to determine the prognostic strength of serum NSE as an independent biomarker of mortality in septic patients determine. We will perform a systematic search and descriptive review using the MEDLINE database and the PubMed interface. We will assign two independent reviewers to review all collected titles and associated abstracts, review full articles, and extract study data. We will use the Quality Assessment of Diagnostic Accuracy Studies version 2 (QUADAS-2) assessment tool according to the recommendation by the Cochrane Collaboration to evaluate quality and risk of bias of the selected studies. Subgroup and sensitivity analyses will also be used to assess heterogeneity. Review Manager version 5.4 and Stata16.0. will be used for statistical analysis. ETHICS AND DISSEMINATION: The meta-analysis will provide ICU physicians with the most current information to predict which patients are at risk of SAE and take corresponding intervention measures to reduce morbidity and ameliorate neurological outcomes. There is no need for ethics approval for this review. The findings will be disseminated in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: CRD42023398736.

Biomarker Assessment of a High-Risk, Data-Driven Pediatric Sepsis Phenotype Characterized by Persistent Hypoxemia, Encephalopathy, and Shock.

OBJECTIVES: Identification of children with sepsis-associated multiple organ dysfunction syndrome (MODS) at risk for poor outcomes remains a challenge. We sought to the determine reproducibility of the data-driven "persistent hypoxemia, encephalopathy, and shock" (PHES) phenotype and determine its association with inflammatory and endothelial biomarkers, as well as biomarker-based pediatric risk strata. DESIGN: We retrained and validated a random forest classifier using organ dysfunction subscores in the 2012-2018 electronic health record (EHR) dataset used to derive the PHES phenotype. We used this classifier to assign phenotype membership in a test set consisting of prospectively (2003-2023) enrolled pediatric septic shock patients. We compared profiles of the PERSEVERE family of biomarkers among those with and without the PHES phenotype and determined the association with established biomarker-based mortality and MODS risk strata. SETTING: Twenty-five PICUs across the United States. PATIENTS: EHR data from 15,246 critically ill patients with sepsis-associated MODS split into derivation and validation sets and 1,270 pediatric septic shock patients in the test set of whom 615 had complete biomarker data. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The area under the receiver operator characteristic curve of the modified classifier to predict PHES phenotype membership was 0.91 (95% CI, 0.90-0.92) in the EHR validation set. In the test set, PHES phenotype membership was associated with both increased adjusted odds of complicated course (adjusted odds ratio [aOR] 4.1; 95% CI, 3.2-5.4) and 28-day mortality (aOR of 4.8; 95% CI, 3.11-7.25) after controlling for age, severity of illness, and immunocompromised status. Patients belonging to the PHES phenotype were characterized by greater degree of systemic inflammation and endothelial activation, and were more likely to be stratified as high risk based on PERSEVERE biomarkers predictive of death and persistent MODS. CONCLUSIONS: The PHES trajectory-based phenotype is reproducible, independently associated with poor clinical outcomes, and overlapped with higher risk strata based on prospectively validated biomarker approaches.

Meta-analysis of evaluating neuron specific enolase as a serum biomarker for sepsis-associated encephalopathy.

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.

Combining biomarkers of BNIP3 L, S100B, NSE, and accessible measures to predict sepsis-associated encephalopathy: a prospective observational study.

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.

The expression of CD86 in CD3+CD56+ NKT cells is associated with the occurrence and prognosis of sepsis-associated encephalopathy in sepsis patients: a prospective observational cohort study.

The role of CD3+CD56+ natural killer T (NKT) cells and its co-signaling molecules in patients with sepsis-associated encephalopathy (SAE) is unknown. In this prospective observational cohort study, we initially recruited 260 septic patients and eventually analyzed 90 patients, of whom 57 were in the SAE group and 37 were in the non-SAE group. Compared to the non-SAE group, 28-day mortality was significantly increased in the SAE group (33.3% vs. 12.1%, p = 0.026), while the mean fluorescence intensity (MFI) of CD86 in CD3+CD56+ NKT cells was significantly lower (2065.8 (1625.5 ~ 3198.8) vs. 3117.8 (2278.1 ~ 5349), p = 0.007). Multivariate analysis showed that MFI of CD86 in NKT cells, APACHE II score, and serum albumin were independent risk factors for SAE. Furthermore, the Kaplan-Meier survival analysis indicated that the mortality rate was significantly higher in the high-risk group than in the low-risk group (χ2 = 14.779, p < 0.001). This study showed that the decreased expression of CD86 in CD3+CD56+ NKT cells is an independent risk factor of SAE; thus, a prediction model including MFI of CD86 in NKT cells, APACHE II score, and serum albumin can be constructed for diagnosing SAE and predicting prognosis.

Neurofilament light chains to assess sepsis-associated encephalopathy: Are we on the track toward clinical implementation?

Sepsis is the most common cause of admission to intensive care units worldwide. Sepsis patients frequently suffer from sepsis-associated encephalopathy (SAE) reflecting acute brain dysfunction. SAE may result in increased mortality, extended length of hospital stay, and long-term cognitive dysfunction. The diagnosis of SAE is based on clinical assessments, but a valid biomarker to identify and confirm SAE and to assess SAE severity is missing. Several blood-based biomarkers indicating neuronal injury have been evaluated in sepsis and their potential role as early diagnosis and prognostic markers has been studied. Among those, the neuroaxonal injury marker neurofilament light chain (NfL) was identified to potentially serve as a prognostic biomarker for SAE and to predict long-term cognitive impairment. In this review, we summarize the current knowledge of biomarkers, especially NfL, in SAE and discuss a possible future clinical application considering existing limitations.

High Mobility Group Box 1 (HMGB1): Potential Target in Sepsis-Associated Encephalopathy.

Sepsis-associated encephalopathy (SAE) remains a challenge for intensivists that is exacerbated by lack of an effective diagnostic tool and an unambiguous definition to properly identify SAE patients. Risk factors for SAE development include age, genetic factors as well as pre-existing neuropsychiatric conditions. Sepsis due to certain infection sites/origins might be more prone to encephalopathy development than other cases. Currently, ICU management of SAE is mainly based on non-pharmacological support. Pre-clinical studies have described the role of the alarmin high mobility group box 1 (HMGB1) in the complex pathogenesis of SAE. Although there are limited data available about the role of HMGB1 in neuroinflammation following sepsis, it has been implicated in other neurologic disorders, where its translocation from the nucleus to the extracellular space has been found to trigger neuroinflammatory reactions and disrupt the blood-brain barrier. Negating the inflammatory cascade, by targeting HMGB1, may be a strategy to complement non-pharmacologic interventions directed against encephalopathy. This review describes inflammatory cascades implicating HMGB1 and strategies for its use to mitigate sepsis-induced encephalopathy.

Paediatric sepsis-associated encephalopathy (SAE): a comprehensive review.

Sepsis-associated encephalopathy (SAE) is one of the most common types of organ dysfunction without overt central nervous system (CNS) infection. It is associated with higher mortality, low quality of life, and long-term neurological sequelae, its mortality in patients diagnosed with sepsis, progressing to SAE, is 9% to 76%. The pathophysiology of SAE is still unknown, but its mechanisms are well elaborated, including oxidative stress, increased cytokines and proinflammatory factors levels, disturbances in the cerebral circulation, changes in blood-brain barrier permeability, injury to the brain's vascular endothelium, altered levels of neurotransmitters, changes in amino acid levels, dysfunction of cerebral microvascular cells, mitochondria dysfunction, activation of microglia and astrocytes, and neuronal death. The diagnosis of SAE involves excluding direct CNS infection or other types of encephalopathies, which might hinder its early detection and appropriate implementation of management protocols, especially in paediatric patients where only a few cases have been reported in the literature. The most commonly applied diagnostic tools include electroencephalography, neurological imaging, and biomarker detection. SAE treatment mainly focuses on managing underlying conditions and using antibiotics and supportive therapy. In contrast, sedative medication is used judiciously to treat those showing features such as agitation. The most widely used medication is dexmedetomidine which is neuroprotective by inhibiting neuronal apoptosis and reducing a sepsis-associated inflammatory response, resulting in improved short-term mortality and shorter time on a ventilator. Other agents, such as dexamethasone, melatonin, and magnesium, are also being explored in vivo and ex vivo with encouraging results. Managing modifiable factors associated with SAE is crucial in improving generalised neurological outcomes. From those mentioned above, there are still only a few experimentation models of paediatric SAE and its treatment strategies. Extrapolation of adult SAE models is challenging because of the evolving brain and technical complexity of the model being investigated. Here, we reviewed the current understanding of paediatric SAE, its pathophysiological mechanisms, diagnostic methods, therapeutic interventions, and potential emerging neuroprotective agents.

Diagnostic and prognostic value of serum S100B in sepsis-associated encephalopathy: A systematic review and meta-analysis.

Background: In sepsis, brain dysfunction is known as Sepsis-associated encephalopathy (SAE), which often results in severe cognitive and neurological sequelae and increases the risk of death. Our systematic review and meta-analysis aimed to explore the diagnostic and prognostic value of serum S100 calcium-binding protein B (S100B) in SAE patients. Methods: We conducted a systematic search of the databases PubMed, Web of Science, Embase, Cochrane databases, CNKI, VIP, and WFSD from their inception dates until August 20, 2022. A Meta-analysis of the included studies was also performed using Review Manager version 5.4 and Stata16.0. Results: This meta-analysis included 28 studies with 1401 serum samples from SAE patients and 1591 serum samples from no-encephalopathy septic (NE) patients. The Meta-Analysis showed that individuals with SAE had higher serum S100B level than NE controls (MD, 0.49 [95% CI (0.37)-(0.60), Z =8.29, P < 0.00001]), and the baseline level of serum S100B in septic patients with burn was significantly higher than average (1.96 [95% CI (0.92)-(2.99), Z =3.71, P < 0.0002]) In addition, septic patients with favorable outcomes had lower serum S100B levels than those with unfavorable outcomes (MD, -0.35 [95% CI (-0.50)-(-0.20), Z =4.60, P < 0.00001]). Conclusion: Our Meta-Analysis indicates that higher serum S100B level in septic patients are moderately associated with SAE and unfavorable outcomes (The outcomes here mainly refer to the mortality). The serum S100B level may be a useful diagnostic and prognostic biomarker of SAE.

Neurological complications of sepsis.

PURPOSE OF REVIEW: Sepsis, defined as life-threatening organ dysfunction caused by a dysregulated host response to infection, is a leading cause of hospital and ICU admission. The central and peripheral nervous system may be the first organ system to show signs of dysfunction, leading to clinical manifestations such as sepsis-associated encephalopathy (SAE) with delirium or coma and ICU-acquired weakness (ICUAW). In the current review, we want to highlight developing insights into the epidemiology, diagnosis, prognosis, and treatment of patients with SAE and ICUAW. RECENT FINDINGS: The diagnosis of neurological complications of sepsis remains clinical, although the use of electroencephalography and electromyography can support the diagnosis, especially in noncollaborative patients, and can help in defining disease severity. Moreover, recent studies suggest new insights into the long-term effects associated with SAE and ICUAW, highlighting the need for effective prevention and treatment. SUMMARY: In this manuscript, we provide an overview of recent insights and developments in the prevention, diagnosis, and treatment of patients with SAE and ICUAW.

Identification of biomarkers and therapeutic targets related to Sepsis-associated encephalopathy in rats by quantitative proteomics.

BACKGROUND: Sepsis-associated encephalopathy (SAE) is a common and severe complication of sepsis. While several studies have reported the proteomic alteration in plasma, urine, heart, etc. of sepsis, few research focused on the brain tissue. This study aims at discovering the differentially abundant proteins in the brains of septic rats to identify biomarkers of SAE. METHODS: The Prague-Dawley rats were randomly divided into sepsis (n = 6) or sham (n = 6) groups, and then the whole brain tissue was dissected at 24 h after surgery for further protein identification by Quantitative iTRAQ LC-MS/MS Proteomics. Ingenuity pathway analysis, Gene ontology knowledgebase, and STRING database are used to explore the biological significance of proteins with altered concentration. RESULTS: Among the total of 3163 proteins identified in the brain tissue, 57 were increased while 38 were decreased in the sepsis group compared to the sham group. Bioinformatic analyses suggest that the differentially abundant proteins are highly related to cellular microtubule metabolism, energy production, nucleic acid metabolism, neurological disease, etc. Additionally, acute phase response signaling was possibly activated and PI3K/AKT signaling was suppressed during sepsis. An interaction network established by IPA revealed that Akt1, Gc-globulin, and ApoA1 were the core proteins. The increase of Gc-globulin and the decrease of Akt1 and ApoA1 were confirmed by Western blot. CONCLUSION: Based on the multifunction of these proteins in several brain diseases, we first propose that Gc-globulin, ApoA1, PI3K/AKT pathway, and acute phase response proteins (hemopexin and cluster of alpha-2-macroglobulin) could be potential candidates for the diagnosis and treatment of SAE. These results may provide new insights into the pathologic mechanism of SAE, yet further research is required to explore the functional implications and clinical applications of the differentially abundant proteins in the brains of sepsis group.

What's new on septic encephalopathy? Ten things you need to know.

Sepsis associated encephalopathy (SAE) is a frequent complication of sepsis and is associated with a higher risk of short-term mortality and long-term cognitive impairment. The EEG is a sensitive complement of the clinical examination that can also detect and quantify encephalopathy and identify features with prognostic value, such as lack of reactivity. Moreover, despite their effect on outcome is still debated, the EEG is the only tool to detect non-convulsive seizures which can occur in a septic setting. Understanding the pathophysiology of SAE is fundamental to define potential therapeutic targets. Neuroinflammation plays an important role in the development of SAE and many blood and imaging biomarkers have recently shown a promising ability to distinguish SAE form non-SAE patient. In recent years, some interesting mediators of inflammation were successfully targeted in animal models, with a significant reduction in the neuroinflammation and in sepsis-induced cognitive decline. However, the complexity of the host response to sepsis currently limits the use of immunomodulation therapies in humans. Alteration in regulatory systems of cerebral blood flow, namely cerebral autoregulation (CA) and neurovascular coupling, contribute to SAE development. Nowadays, clinicians have access to different tools to assess them at the bedside and CA-based blood pressure protocols should be implemented to optimize cerebral perfusion. Its inauspicious consequences, its complex physiopathology and the lack of efficacious treatment make of SAE a highly active research subject.

Prediction and risk assessment of sepsis-associated encephalopathy in ICU based on interpretable machine learning.

Sepsis-associated encephalopathy (SAE) is a major complication of sepsis and is associated with high mortality and poor long-term prognosis. The purpose of this study is to develop interpretable machine learning models to predict the occurrence of SAE after ICU admission and implement the individual prediction and analysis. Patients with sepsis admitted to ICU were included. SAE was diagnosed as glasgow coma score (GCS) less than 15. Statistical analysis at baseline was performed between SAE and non-SAE. Six machine learning classifiers were employed to predict the occurrence of SAE, and the adjustment of model super parameters was performed by using Bayesian optimization method. Finally, the optimal algorithm was selected according to the prediction efficiency. In addition, professional physicians were invited to evaluate our model prediction results for further quantitative assessment of the model interpretability. The preliminary analysis of variance showed significant differences in the incidence of SAE among patients with pathogen infection. There were significant differences in physical indicators like respiratory rate, temperature, SpO2 and mean arterial pressure (P < 0.001). In addition, the laboratory results were also significantly different. The optimal classification model (XGBoost) indicated that the best risk factors (cut-off points) were creatinine (1.1 mg/dl), mean respiratory rate (18), pH (7.38), age (72), chlorine (101 mmol/L), sodium (138.5 k/ul), SAPSII score (23), platelet count (160), and phosphorus (2.4 and 5.0 mg/dL). The ranked features derived from the best model (AUC is 0.8837) were mechanical ventilation, duration of mechanical ventilation, phosphorus, SOFA score, and vasopressin usage. The SAE risk prediction model based on XGBoost created here can make very accurate predictions using simple indicators and support the visual explanation. The interpretable model was effectively evaluated by professional physicians and can help them predict the occurrence of SAE more intuitively.

Sepsis and the brain: a review for acute and general physicians.

Sepsis-associated encephalopathy (SAE) describes acute cognitive dysfunction secondary to systemic or peripheral infection occurring outside of the central nervous system (CNS). Symptoms can range from mild confusion to coma and may precede the clinical signs of sepsis. Recognition that SAE is a potential differential diagnosis in patients presenting with delirium is important, as SAE is a diagnosis of exclusion. Physicians should also be aware that severe SAE is associated with a high mortality. Although mortality is often secondary to multiorgan failure rather than neurological sequelae, long-term cognitive and psychological morbidities have been reported in sepsis survivors. Early treatment (which can include prompt identification and source control of the infection) and good supportive care might improve cognitive outcomes. Future work should aim to improve understanding of both acute and chronic SAE with a focus on therapeutic interventions and improving patient outcomes.

[Research Progress in Clinical Electrophysiological Assessment of Patients with Sepsis-Associated Encephalopathy].

Sepsis-associated encephalopathy(SAE) caused by infections outside the central nervous system always presents extensive brain damage.It is common in clinical practice and associated with a poor prognosis.There are problems in the assessing and diagnosing of SAE.Many factors,such as sedation and mechanical ventilation,make it difficult to assess SAE,while electrophysiological examination may play a role in the assessment.We reviewed the studies of electrophysiological techniques such as electroencephalography and somatosensory evoked potentials for monitoring SAE,hoping to provide certain evidence for the clinical evaluation and diagnosis of SAE.

Sepsis-Induced Brain Dysfunction: Pathogenesis, Diagnosis, and Treatment.

Dysregulated host response to infection, which cause life-threatening organ dysfunction, was defined as sepsis. Sepsis can cause acute and long-term brain dysfunction, namely, sepsis-associated encephalopathy (SAE) and cognitive impairment. SAE refers to changes in consciousness without direct evidence of central nervous system infection. It is highly prevalent and may cause poor outcomes in sepsis patients. Cognitive impairment seriously affects the life quality of sepsis patients and increases the medical burden. The pathogenesis of sepsis-induced brain dysfunction is mainly characterized by the interaction of systemic inflammation, blood-brain barrier (BBB) dysfunction, neuroinflammation, microcirculation dysfunction, and brain dysfunction. Currently, the diagnosis of sepsis-induced brain dysfunction is based on clinical manifestation of altered consciousness along with neuropathological examination, and the treatment is mainly involves controlling sepsis. Although treatments for sepsis-induced brain dysfunction have been tested in animals, clinical treat sepsis-induced brain dysfunction is still difficult. Therefore, we review the underlying mechanisms of sepsis-induced brain injury, which mainly focus on the influence of systemic inflammation on BBB, neuroinflammation, brain microcirculation, and the brain function, which want to bring new mechanism-based directions for future basic and clinical research aimed at preventing or ameliorating brain dysfunction.

Clinical features, electroencephalogram, and biomarkers in pediatric sepsis-associated encephalopathy.

To date, no specific diagnostic criteria for sepsis-associated encephalopathy (SAE) have been established. We studied 33 pediatric patients with sepsis prospectively and evaluated the level of consciousness, the presence of delirium, electroencephalographic (EEG) findings, and plasma levels of neuron-specific enolase and S100-calcium-binding protein-B. A presumptive diagnosis of SAE was primarily considered in the presence of a decreased level of consciousness and/or delirium (clinical criteria), but specific EEG abnormalities were also considered (EEG criteria). The time course of the biomarkers was compared between groups with and without clinical or EEG criteria. The Functional Status Scale (FSS) was assessed at admission, discharge, and 3-6 months post-discharge. Clinical criteria were identified in 75.8% of patients, EEG criteria in 26.9%, both in 23.1%, and none in 23.1%. Biomarkers did not differ between groups. Three patients had an abnormal FSS at discharge, but no one on follow-up. A definitive diagnostic pattern for SAE remained unclear. Clinical criteria should be the basis for diagnosis, but sedation may be a significant confounder, also affecting EEG interpretation. The role of biomarkers requires a better definition. The diagnosis of SAE in pediatric patients remains a major challenge. New consensual diagnostic definitions and mainly prognostic studies are needed.

Role of microRNAs As Biomarkers in Sepsis-Associated Encephalopathy.

Sepsis-associated encephalopathy (SAE) is a neurological complication of sepsis, characterized by brain dysfunction without any direct central nervous system infection. The diagnosis of SAE is currently a challenge. In fact, problems in making a diagnosis of SAE cause a great variability of incidence that can reach up to 70% of all septic patients. Even more, despite SAE is the most frequent type of encephalopathy occurring in critically ill patients, the molecular mechanisms that guide its progression have not been completely elucidated. On the other hand, miRNAs have proven to be excellent biomarkers for both diagnosis and prognosis, especially in brain pathologies because of their small size they can cross the blood-brain barrier easier than other biomolecules. The identification of new miRNAs as biomarkers may help to improve SAE diagnosis and prognosis and also to design new therapies for this clinical manifestation that produces diffuse cerebral dysfunction. This review is focused on SAE physiopathology and the need to have clear criteria for its diagnosis; thus, this work postulates some miRNA candidates to be used for SAE biomarkers because of their role in both, neurological damage and sepsis.

Electroacupuncture Improves Cognition in Rats With Sepsis-Associated Encephalopathy.

BACKGROUND: Sepsis-associated encephalopathy (SAE) is a common complication of sepsis. Although sepsis is effectively managed with the administration of antibiotics and source control, which may include surgical intervention, SAE usually leads to prolonged cognitive dysfunction affecting the quality of life of the patients. In this study, we investigated the possible effect of electroacupuncture (EA) on cognition in a model of SAE induced by cecal ligation and puncture (CLP). MATERIALS AND METHODS: The rats were randomly divided into four groups: the control group, the CLP group, the CLP with EA treatment group (CLP + EA), and the CLP with sham EA treatment group (CLP + sham EA). EA at DU20, LI11, and ST36 or sham EA was performed 30 min daily for 10 consecutive days starting from 2 days before CLP. Then cognitive function was examined by the Morris water maze test. On day 14 after CLP surgery, the synaptic injury, neuron loss, and oxidative stress were studied. RESULTS: Rats with EA treatment showed improved survival rate, spatial learning, and memory abilities. The dendritic spine density, the synaptic proteins, and the hippocampal neuron number were also increased after EA treatment. Furthermore, EA suppressed oxidative stress through regulating the level of malondialdehyde and superoxide dismutase and enhanced the expression of antioxidant nuclear factor erythroid-2-related factor-2 and hemeoxygenase-1. But sham EA did not have the same effect. CONCLUSIONS: EA may protect against SAE-induced cognitive dysfunction by inhibiting synaptic injury, neuronal loss, and oxidative stress, and the nuclear factor erythroid-2-related factor-2/hemeoxygenase-1 signaling pathway may be involved in this effect.

Ethyl pyruvate protects against sepsis-associated encephalopathy through inhibiting the NLRP3 inflammasome.

BACKGROUND: With the advance of antibiotics and life support therapy, the mortality of sepsis has been decreasing in recent years. However, the incidence of sepsis-associated encephalopathy (SAE), a common complication of sepsis, is still high. There are few effective therapies to treat clinical SAE. We previously found that ethyl pyruvate (EP), a metabolite derivative, is able to effectively inhibit the NLRP3 inflammasome activation. Administration of ethyl pyruvate protects mice against polymicrobial sepsis in cecal ligation and puncture (CLP) model. The aim of present study is to investigate if ethyl pyruvate is able to attenuate SAE. METHODS: After CLP, C57BL/6 mice were intraperitoneally or intrathecally injected with saline or ethyl pyruvate using the sham-operated mice as control. New Object Recognition (NOR) and Morris Water Maze (MWM) were conducted to determine the cognitive function. Brain pathology was assessed via immunohistochemistry. To investigate the mechanisms by which ethyl pyruvate prevent SAE, the activation of NLRP3 in the hippocampus and the microglia were determined using western blotting, and cognitive function, microglia activation, and neurogenesis were assessed using WT, Nlrp3-/- and Asc-/- mice in the sublethal CLP model. In addition, Nlrp3-/- and Asc-/- mice treated with saline or ethyl pyruvate were subjected to CLP. RESULTS: Ethyl pyruvate treatment significantly attenuated CLP-induced cognitive decline, microglia activation, and impaired neurogenesis. In addition, EP significantly decreased the NLRP3 level in the hippocampus of the CLP mice, and inhibited the cleavage of IL-1ß induced by NLRP3 inflammsome in microglia. NLRP3 and ASC deficiency demonstrated similar protective effects against SAE. Nlrp3-/- and Asc-/- mice significantly improved cognitive function and brain pathology when compared with WT mice in the CLP models. Moreover, ethyl pyruvate did not have additional effects against SAE in Nlrp3-/- and Asc-/- mice. CONCLUSION: The results demonstrated that ethyl pyruvate confers protection against SAE through inhibiting the NLRP3 inflammasome.