Sepsis Associated Delirium

Interpretable machine learning model for predicting delirium in patients with sepsis: a study based on the MIMIC data

OBJECTIVE

The aim of this study was to construct interpretable machine learning models to predict the risk of developing delirium in patients with sepsis and to explore the impact of delirium on the 28-day survival rate of patients.

METHODS

We enrolled 10,321 patients with sepsis older than eighteen years from the MIMIC-IV (Medical Information Mart for Intensive Care) database. Sepsis is defined as the presence or suspected presence of infection, along with a SOFA (Sequential Organ Failure Assessment) score of ≥ 2. Four machine learning models, namely XGBoost (extreme gradient Boost), SVM (support vector machine), Logistic (logistic regression) and RF (random forest), were established for prediction, and the prediction model was constructed.

RESULTS

A total of 10,321 sepsis patients were included, among whom 4,691 (45.45%) developed delirium. The 28-day mortality rate was markedly elevated in the delirium group (log-rank P < 0.001). The XGBoost model has the best performance. Finally, 5 variables were selected to draw a nomogram: hypertension, SOFA score, chlorine, Hb (hemoglobin), creatinine. The receiver operating characteristic (ROC) curve of the predictive delirium model showed better predictive efficiency, with an AUC of 0.767 (95%CI (confidence interval): 0.726-0.798).

CONCLUSION

The nomogram built on the XGBoost model provides clinicians with an easy tool to quickly assess the risk of developing delirium in patients with sepsis. It provides a new idea and direction for the best model to predict delirium in patients with sepsis, so as to promote the development of delirium related research.

Evaluation of Presepsin for Early Diagnosis of Sepsis in the Emergency Department

Background: to date, there are no specific markers available for diagnosing sepsis. Diagnosis is, indeed, mainly determined by clinical suspicion and the evaluation of the patient's overall condition. This evaluation involves assessing various inflammatory markers, such as C-reactive protein (CRP) and procalcitonin (PCT), along with markers of tissue hypoxia, such as serum lactate. Additionally, it includes scores that account for complete blood count (CBC), organ function markers, and the patient's vital parameters, including SOFA, qSOFA, SIRS, and NEWS. Over the years, various potential biomarkers have been studied; among these presepsin appears to offer some significant advantages. Objective: Presepsin, which is the N-terminal fragment of the soluble component of CD14, is primarily elevated in infectious conditions. Its levels rise much earlier in the context of infection compared to currently used biomarkers. As a result, Presepsin shows promise for the early identification of septic patients and could aid in prognostic assessment, allowing clinicians to prioritize care for critically ill individuals. Methods: this study aims to evaluate the role of serum presepsin in the early diagnosis of sepsis in patients who present to the emergency room with a clinical suspicion of sepsis. The secondary objectives include comparing the diagnostic performance of presepsin with traditional biomarkers currently used for sepsis diagnosis and assessing its utility as a prognostic biomarker for mortality risk stratification, in comparison with validated severity prediction scores. Result: Presepsin had valuable diagnostic utility for sepsis (AUC 0.946, p < 0.001) comparable to PCT (AUC 0.905, p < 0.001). Conclusions: the combination of Presepsin, PCT, and EWS yielded the highest diagnostic accuracy for sepsis.

Risk factors and outcomes of hyperactive delirium in older medical inpatients admitted to non-intensive care unit: a prospective cohort study

BACKGROUND

Hyperactive delirium is a common complication in older medical inpatients in non-intensive care units. This condition increases the risk of diminished physical function, morbidity, and mortality. Moreover, antipsychotics and sedatives were widely used in these patients, contributing to many drug interactions and adverse drug reactions. This study aimed to evaluate the risk factors for hyperactive delirium and assess adverse outcomes among these susceptible patients.

METHODS

We conducted a prospective observational study to examine hyperactive delirium as an exposure and its association with adverse outcomes without intervention. A total of 238 medical patients aged ≥ 60 admitted to non-intensive care units at Ramathibodi Hospital between September 1, 2022, and December 31, 2023, were enrolled. The clinical characteristics, physical examination, and biochemical profiles at baseline were assessed. Adverse clinical outcomes at 90 days after discharge were evaluated by reviewing electronic medical records (EMRs). The Confusion Assessment Method and Richmond Agitation-Sedation Scale (RASS) score of + 1 to + 4 were used to diagnose hyperactive delirium. The Cox proportional hazard model was performed to identify risk factors and adverse clinical outcomes associated with hyperactive delirium, with results reported as hazard ratios (HRs) and 95% confidence intervals (CIs).

RESULTS

Overall, hyperactive delirium was diagnosed in 115 (48.3%) patients and had an incidence rate of 101.1 cases per 1000 person-days. The risk factors for hyperactive delirium were urinary incontinence (HR 1.69, 95% CI 1.11-2.57), clinical frailty scale (CFS) ≥ 5 (HR 2.79, 95% CI 1.69-4.62), and Montreal Cognitive Assessment (MoCA) score < 25 (HR 4.63, 95% CI 1.09-19.75). Within 90 days after discharge, 14 (12.2%) patients with delirium had died. Medical inpatients who experienced hyperactive delirium had an 8.23-fold increased risk of 90-day mortality following hospital discharge compared to those without delirium (HR 8.23, 95% CI 1.38-48.98).

CONCLUSIONS

The risk factors for hyperactive delirium were urinary incontinence, frailty (CFS score ≥ 5), and cognitive impairment (MoCA score < 25). Among older medical inpatients, hyperactive delirium was an independent predictor of 90-day mortality after discharge.

The frequency of sepsis-associated delirium in intensive care unit and its effect on nurse workload

AIM

To determine the frequency of sepsis-associated delirium (SAD) in the intensive care unit and its effect on nurse workload.

DESIGN

A cross-sectional and correlational design was used.

METHODS

The study was conducted with 158 patients in the adult intensive care unit of a hospital between October 28 and July 28, 2022. Data analysis included frequency, chi-squared/fisher's exact test, independent samples t-test, correlation analysis, simple and multiple linear regression analyses. The study adhered to the STROBE guidelines.

RESULTS

Sepsis was detected in 12.7% of the patients, delirium in 39.9%, and SAD in 10.1%. SAD was more common in males (19%) and 56.3% of the patients were admitted to the unit from the emergency department. Patients developing SAD had significantly higher age and mean sequential organ failure evaluation, acute physiology and chronic health evaluation II, and C-reactive protein and lactate scores, but their Glasgow Coma Scale scores were significantly low. There was a moderate positive relationship between the patients' Sequential Organ Failure Assessment score and the presence of SAD. The most common source of infection in patients diagnosed with SAD was bloodstream infection (44.4%). SAD significantly increased nurse workload and average care time (1.8 h) and it explained 22.8% of the total variance in nurse workload. Additionally, the use of antibiotics, vasopressors and invasive mechanical ventilation significantly increased nurse workload.

CONCLUSION

In the study, in patients who developed SAD increased nurse workload and average care time significantly. Preventive nursing approaches and effective management of SAD can reduce the rate of development of SAD and nurse workload.

IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE

It is important to work with routine screening, prevention and patient-nurse ratio appropriate to the workload for SAD.

The Protective Effect of Octanoic Acid on Sepsis: A Review

Sepsis, a systemic inflammation that occurs in response to a bacterial infection, is a significant medical challenge. Research conducted over the past decade has indicated strong associations among a patient's nutritional status, the composition of their gut microbiome, and the risk, severity, and prognosis of sepsis. Octanoic acid (OA) plays a vital role in combating sepsis and has a protective effect on both animal models and human patients. In this discussion, the potential protective mechanisms of OA in sepsis, focusing on its regulation of the inflammatory response, immune system, oxidative stress, gastrointestinal microbiome and barrier function, metabolic disorders and malnutrition, as well as organ dysfunction are explored. A comprehensive understanding of the mechanisms by which OA act may pave the way for new preventive and therapeutic approaches to sepsis.

S100P is a core gene for diagnosing and predicting the prognosis of sepsis

Sepsis, characterized as a severe systemic inflammatory response syndrome, typically originates from an exaggerated immune response to infection that gives rise to organ dysfunction. Serving as one of the predominant causes of death among critically ill patients, it's pressing to acquire an in-depth understanding of its intricate pathological mechanisms to strengthen diagnostic and therapeutic strategies. By integrating genomic, transcriptomic, proteomic, and metabolomic data across multiple biological levels, multi-omics research analysis has emerged as a crucial tool for unveiling the complex interactions within biological systems and unraveling disease mechanisms in recent years. Samples were collected from 23 cases of sepsis patients and 10 healthy volunteers from January 2019 to December 2020. The protein components in the samples were explored by independent data acquisition (DIA) analysis method, while Circular RNA (circRNA) categories were usually identified by RNA sequencing (RNA-seq) technology. Subsequent to the above steps, data quality monitoring was performed by employing software, and unqualified sequences were excluded, and conditions were set for differential expression network analysis (protein group and circRNA group were separately used log2 |FC|≥ 1 and log2 |FC|≥ 2, P < 0.050). Gene Ontology (GO) enrichment analysis and gene set enrichment analysis (GSEA) analysis were performed on common differentially expressed proteins, followed by protein-protein interaction between common differentially expressed genes and cytoscape software enrichment analysis, and subsequently its association with associated diseases (Disease Ontology (DO)) was investigated in an all-round manner. Afterwards, the distribution distinction of common differentially expressed genes in sepsis group and healthy volunteer group was displayed by heat map after Meta-analysis. Subsequent to the above procedures, pivotal targets with noticeable survival curve distinctions in two states were screened out after Meta-analysis. At last, their potential value was verified by in vitro cell experiment, which provided reference for further discussion of the diagnostic value and prognostic effect of target gene. A total of 174 DEPs and 308 DEcircRNAs were identified in the proteomics analysis, while a total of 12 common differentially expressed genes were identified after joint analysis. The protein-protein interaction (PPI) network suggested the degree of interaction between the dissimilar genes, and the heat map demonstrated their specific distribution in distinct groups. Through enrichment analysis, these proteins predominantly participated in a sequence of crucial processes such as intracellular material synthesis and secretion, changes in inflammatory receptors and immune inflammatory response. The meta-analysis identified that S100P is highly expressed in sepsis. As illustrated by the ROC curve, this gene has high clinical diagnostic value, and utimately confirmed its expression in sepsis through in vitro cell experiments. In these two groups of healthy people and septic patients, S100P demonstrated a more obvious trend of differential expression; Cell experiments also proved its value in diagnosis and prognosis judgment in sepsis; As a result, they may become diagnostic and prognostic markers for sepsis in clinical practice.

Analysis of the inflammatory storm response and heparin binding protein levels for the diagnosis and prognosis of sepsis-associated encephalopathy

BACKGROUND

Sepsis-associated encephalopathy (SAE) is a complication of impaired neurologic function during the development of sepsis. Its occurrence is closely related to severe systemic infection. The increase of serum Interleukin 6 kit and other inflammatory cytokines has certain clinical significance in the diagnosis of sepsis, However, there is no research at home or abroad indicating whether the high expression of related inflammatory cytokines (inflammatory cytokine storm, ICS) is valuable for the diagnosis and prognosis of SAE patients.

OBJECTIVES

The aim of this study was to analyze serum inflammatory cytokines 6 kit [IL-2/4/6/10, TNF-α, and gamma interferon (IFN-γ)], heparin-binding protein (HBP), and serum cholinesterase levels and their clinical significance in septic patients. In this study, we defined the values of inflammatory storm (IL-6 > 5000 pg/ml, IL-10 > 1000 pg/ml, and HBP > 300 ng/ml) to analyze the diagnostic value and 28-day prognostic predictive ability of inflammatory cytokine storm and the severity score in SAE patients.

METHODS

A total of 140 patients with sepsis in the ICU and EICU of the Lianyungang First People's Hospital were included in the present study from October 2021 to March 2023. Based on the Diagnostic criteria for SAE, the 140 cases were divided into 62 cases in the SAE group and 78 cases in the non-SAE group. On admission to the ICU/EICU, the patients gender, age, vital signs, and serum levels of various cytokines were recorded. The Glasgow Coma Scale (GCS), Sequential Organ Failure Scale (SOFA), and Acute Physiological and Chronic Health Score II (APACHE-II) scores were also assessed to analyze the risk cytokines for the occurrence of SAE.

RESULTS

The age, Sofa score, APACHE-II score, 28-day mortality rate, serological cellular inflammatory cytokines (IL-2/6/10, INF-α, and interferon-gamma), HBP were significantly higher in the SAE group than in the non-SAE group (P < 0.05). In addition, the GCS score and serum cholinesterase levels in the SAE group were lower than in the non-SAE group (P < 0.05). Subsequently, Multi-factor logistic regression analysis revealed that ultra-high IL-6 (> 5000 pg/ml), IL-10 (> 1000 pg/ml), and HBP (> 300 ng/ml) levels and elevated SOFA and APACHE-II scores were risk cytokines for the development of SAE (P < 0.05). 28-day mortality was significantly higher in patients in the SAE group and in the IL-6 > 5000 pg/ml group compared to patients in the USAE and IL-6 < 5000 pg/ml groups(P < 0.001).The four screened predictors of HBP > 300 ng/ml, IL-6 > 5000 pg/ml, decreased GCS score, and decreased APACHEII score were combined into a new predictive data model (risk score).In the SAE group, patients with high risk scores had a higher 28-day mortality rate compared with the low risk score group (P < 0.001).

CONCLUSIONS

The occurrence of SAE is closely correlated with age, concomitant diabetes, SOFA score, APACHE II score, serum cytosolic inflammatory cytokine levels (IL-2/6/10, TNF-α, and IFN-γ), HBP, and serum cholinesterase levels. In addition, inflammatory storms are associated with the mechanism of SAE, and high expression levels of the inflammatory cytokines IL-6 > 5000 pg/ml, IL-10 > 1000 pg/ml, and HBP > 300 ng/ml in patients with sepsis contribute to the early diagnosis of SAE. In addition, IL-6 > 5000 pg/ml was also associated with an increase in 28-day mortality (P < 0.05), suggesting that the level of inflammatory storms may be related to the mechanism of sepsis-related SAE and 28-day mortality. According to the LASSO results, when SAE patients admitted to the intensive care unit satisfy HBP > 300 ng/ml, IL6 > 5000 pg/ml, decreased GCS score, and increased APACHEII score, it suggests that the patient's 28-day mortality rate is higher, and it also validates that inflammatory storm can be used as a predictor of prognosis for SAE patients.

Outcomes of a delirium prevention program after major abdominal emergency surgery: An interventional study

BACKGROUND

Postoperative delirium is a common complication after emergency surgery. Delirium is associated with increased morbidity and mortality. Clinical approach varies and pharmacological treatment is ineffective. We aimed to investigate if a structured non-pharmacological multidisciplinary intervention could reduce postoperative delirium.

METHODS

An interventional study including all patients aged 65 years or older undergoing major abdominal emergency surgery in an 8 month period. The intervention consisted of improved screening, staff, patient, and family education, ward modifications and nurse-led daily motor and sensory stimulation. Data was obtained from medical records. Results were compared to an unmatched historic cohort. Primary outcome was occurrence of delirium, secondary outcomes were mortality, postoperative complications, and length of stay.

RESULTS

312 patients were included, 81 in the study group and 231 in the control group. Delirium occurred in 6.2% of the interventional group compared to 15.2% in the historic cohort (p = 0.038). In a multivariate regression analysis, the rate of delirium was significantly reduced in the interventional group; OR 0.185 95% CI (0.04-0.81), p = 0.026. The 90 day mortality was 14.8% in the interventional group and 8.7% in the historic cohort (p = 0.116). The rate of overall medical complications was significantly lower in the study group (37% vs. 63%, p < 0.001). Median length of stay was 6 days in both groups.

CONCLUSIONS

A structured cluster intervention may prevent the occurrence of postoperative delirium. The intervention did not reduce mortality or length of stay, but the need for supplementary nursing staff was eliminated.

Impact of beta-blocker usage on delirium in patients with sepsis in ICU: a cross-sectional study

Introduction

Delirium in patients with sepsis can be life-threatening. This study aims to investigate the impact of the use of beta-blockers on the occurrence of delirium in patients with sepsis in the ICU by utilizing a comprehensive dataset.

Methods

This is a cross-sectional study conducted using the data obtained from a single ICU in the USA. Patients diagnosed with sepsis and receiving beta-blockers were compared with those not receiving beta-blockers. Propensity score matching (PSM) and multiple regression analysis were employed to adjust for potential confounders.

Results

Among the 19,660 patients hospitalized for sepsis, the beta-blocker and non-user groups comprised 13,119 (66.73%) and 6,541 (33.27%) patients, respectively. Multivariable logistic regression models revealed a significant reduction of 60% in 7-day delirium for beta-blocker users (OR = 0.40, 95% CI: 0.37-0.43, p < 0.001), for 30-day delirium (OR = 0.32, 95% CI: 0.29-0.35, p < 0.001), and for 90-day delirium (OR = 0.33, 95% CI: 0.30-0.35, p < 0.001). The PSM results further strengthen the validity of these findings. An analysis of safety issues demonstrated that beta-blockers may have an impact on the risk of acute kidney injury. However, following PSM, the results are not considered robust. Furthermore, there was no discernible change in the odds of renal replacement therapy and the length of ICU stays.

Discussion

Our findings suggest a potential protective effect of beta-blockers against delirium in patients with sepsis. Nevertheless, the observational design limits causal inference, necessitating future randomized controlled trials to validate these findings.

Predictive model of risk factors for 28-day mortality in patients with sepsis or sepsis-associated delirium based on the MIMIC-IV database

Research on the severity and prognosis of sepsis with or without progressive delirium is relatively insufficient. We constructed a prediction model of the risk factors for 28-day mortality in patients who developed sepsis or sepsis-associated delirium. The modeling group of patients diagnosed with Sepsis-3 and patients with progressive delirium of related indicators were selected from the MIMIC-IV database. Relevant independent risk factors were determined and integrated into the prediction model. Receiver operating characteristic (ROC) curves and the Hosmer-Lemeshow (HL) test were used to evaluate the prediction accuracy and goodness-of-fit of the model. Relevant indicators of patients with sepsis or progressive delirium admitted to the intensive care unit (ICU) of a 3A hospital in Xinjiang were collected and included in the verification group for comparative analysis and clinical validation of the prediction model. The total length of stay in the ICU, hemoglobin levels, albumin levels, activated partial thrombin time, and total bilirubin level were the five independent risk factors in constructing a prediction model. The area under the ROC curve of the predictive model (0.904) and the HL test result (χ2 = 8.518) indicate a good fit. This model is valuable for clinical diagnosis and treatment and auxiliary clinical decision-making.

Association of triglyceride-glucose index and delirium in patients with sepsis: a retrospective study

OBJECTIVE

It is well known that glucose and lipid metabolism disorders and insulin resistance are common in sepsis, which affect the occurrence and prognosis of multiple organ dysfunction in septic patients. Previous study reported the predictive value of triglyceride-glucose index (TyG), a clinical indicator for insulin resistance, in postoperative delirium patients. However, it remains unclear whether the TyG index is a novel predictive biomarker for sepsis-associated delirium. The aim of this study is to explore the relationship between TyG index and the risk of delirium in patients with sepsis.

METHODS

Adult septic patients were identified from the MIMIC-IV database and divided into four groups based on the mean value of TyG. The primary outcome was the incidence of delirium. The association between TyG and the risk of developing delirium was evaluated by restricted cubic spline (RCS), multivariate logistic regression and subgroup analysis. Propensity Score Matching (PSM) method was used to balance the baseline data.

RESULTS

A total of 3,331 septic patients were included in the analysis, and further divided into four groups: Q1 (TyG ≤ 8.67), Q2 (8.67 < TyG ≤ 9.08), Q3 (9.08 < TyG ≤ 9.61), and Q4 (TyG > 9.61). The RCS curves demonstrated a non-linear positive relationship between TyG index and the risk of developing delirium, and an optimal cut-of value 9.09 was recommended. After balancing the baseline information by PSM, patients in the TyG > 9.09 group had a significant higher incidence of delirium compared with those in the TyG ≤ 9.09 group. In logistic regression analysis, TyG > 9.09 was significantly associated with lower risk of developing delirium in both original cohort (OR 1.54-1.78, all P < 0.001) and the PSM cohort (OR 1.41-1.48, all P < 0.001). No association was found between the TyG index and mortality (all P > 0.05). In subgroup analysis, our findings were consistent (all OR > 1 in all subgroups).

CONCLUSION

Our study demonstrated an independent association between TyG index and increased risk of delirium in septic patients, indicating that TyG index can serve as a biomarker for delirium in sepsis.

Cerebral autoregulation-directed optimal blood pressure management reduced the risk of delirium in patients with septic shock

Background

When resuscitating patients with septic shock, cerebrovascular reactivity parameters are calculated by monitoring regional cerebral oxygen saturation (rSO2) using near-infrared spectroscopy to determine the optimal blood pressure. Here, we aimed to analyze the impact of cerebral autoregulation-directed optimal blood pressure management on the incidence of delirium and the prognosis of patients with septic shock.

Methods

This prospective randomized controlled clinical study was conducted in the Xiangya Hospital of Central South University, China. Fifty-one patients with septic shock (December 2020-May 2022) were enrolled and randomly allocated to the experimental (n=26) or control group (n=25). Using the ICM+ software, we monitored the dynamic changes in rSO2 and mean arterial pressure (MAP) and calculated the cerebrovascular reactivity parameter tissue oxygen reactivity index to determine the optimal blood pressure to maintain normal cerebral autoregulation function during resuscitation in the experimental group. The control group was treated according to the Surviving Sepsis Campaign Guidelines. Differences in the incidence of delirium and 28-day mortality between the two groups were compared, and the risk factors were analyzed.

Results

The 51 patients, including 39 male and 12 female, had a mean age of (57.0±14.9) years. The incidence of delirium was 40.1% (23/51), and the 28-day mortality rate was 29.4% (15/51). The mean MAP during the first 24 h of intensive care unit (ICU) admission was higher ([84.5±12.2] mmHg vs. [77.4±11.8] mmHg, P=0.040), and the incidence of delirium was lower (30.8% vs. 60.0%, P=0.036) in the experimental group than in the control group. The use of cerebral autoregulation-directed optimal blood pressure (odds ratio [OR]=0.090, 95% confidence interval [CI]: 0.009 to 0.923, P=0.043) and length of ICU stay (OR=1.473, 95% CI: 1.093 to 1.985, P=0.011) were risk factors for delirium during septic shock. Vasoactive drug dose (OR=8.445, 95% CI: 1.26 to 56.576, P=0.028) and partial pressure of oxygen (PaO2) (OR=0.958, 95% CI: 0.921 to 0.996, P=0.032) were the risk factors for 28-day mortality.

Conclusions

The use of cerebral autoregulation-directed optimal blood pressure management during shock resuscitation reduces the incidence of delirium in patients with septic shock.

Trial Registration

ClinicalTrials.gov ldentifer: NCT03879317.

The Role of Neutrophil-to-Lymphocyte Ratio (NLR) in Urosepsis-Associated Delirium

Introduction Urosepsis is a systemic, dysregulated, inflammatory reaction to a urinary tract infection and can have severe effects on all systems, which can often lead to multi-organ failure and death. Sepsis-associated delirium is a common complication in critically ill patients, contributing to adverse outcomes and prolonged hospital stays. The neutrophil-to-lymphocyte ratio (NLR) has emerged as a potential biomarker for sepsis severity and prognosis. Material and methods Our study investigates the utility of NLR in the diagnostic strategies for urosepsis-associated delirium in a cohort of 76 patients with sepsis and septic shock admitted to the Intensive Care Unit (ICU). We performed a single-centre retrospective observational study in the Craiova Clinical Emergency Hospital between June and October 2023. Results Patients with urological conditions that were diagnosed with urosepsis included 76 patients. These patients were clustered as follows: a group with delirium (37 patients, 48.7%) and another group without delirium (39 patients, 51.3%). Complete blood count parameters were obtained upon admission, and delirium was assessed using standardized diagnostic criteria. We identified a strong significant positive correlation between elevated NLR values on ICU admission and the development of delirium during hospitalization in urosepsis patients. Receiver operating characteristic (ROC) analysis showed similar diagnostic performance for NLR score. Conclusions The findings suggest that NLR may serve as a valuable biomarker for early detection, risk stratification, and guiding therapeutic interventions in urosepsis-associated delirium, thus improving outcomes in critically ill patients.

Whole blood thiamine, intravenous thiamine supplementation and delirium occurrence in the intensive care unit: retrospective cohort analyses

BACKGROUND

Thiamine di-phosphate is an essential cofactor in glucose metabolism, glutamate transformation and acetylcholinesterase activity, pathways associated with delirium occurrence. We hypothesised that a deficiency in whole blood thiamine and intravenous thiamine supplementation could impact delirium occurrence.

AIM

To establish whether a deficiency in whole blood thiamine and/or intravenous thiamine supplementation within 72 h of intensive care admission is associated with delirium occurrence.

METHOD

The first dataset was secondary analysis of a previous study in an intensive care unit in the Netherlands, reported in 2017. The second dataset contained consecutive intensive care admissions 2 years before (period 1: October 2014 to October 2016) and after (period 2: April 2017 to April 2019) routine thiamine supplementation was introduced within 72 h of admission. Delirium was defined as a positive Confusion Assessment Method-Intensive Care Unit score(s) in 24 h.

RESULTS

Analysis of the first dataset (n = 57) using logistic regression showed no relationship between delirium and sepsis or whole blood thiamine, but a significant association with age (p = 0.014). In the second dataset (n = 3074), 15.1% received IV thiamine in period 1 and 62.6% during period 2. Hierarchical regression analysis reported reduction in delirium occurrence in the second period; this did not reach statistical significance, OR = 0.81 (95% CI 0.652-1.002); p = 0.052.

CONCLUSION

No relationship was detected between whole blood thiamine and delirium occurrence on admission, at 24 and 48 h. It remains unclear whether routine intravenous thiamine supplementation during intensive care admission impacts delirium occurrence. Further prospective randomised clinical trials are needed.

Lipid peroxidation-induced ferroptosis as a therapeutic target for mitigating neuronal injury and inflammation in sepsis-associated encephalopathy: insights into the hippocampal PEBP-1/15-LOX/GPX4 pathway

BACKGROUND

Sepsis-associated encephalopathy (SAE) refers to the widespread impairment of brain function caused by noncentral nervous system infection mediated by sepsis. Lipid peroxidation-induced ferroptosis contributes to the occurrence and course of SAE. This study aimed to investigate the relationship between neuronal injury and lipid peroxidation-induced ferroptosis in SAE.

METHODS

Baseline data were collected from pediatric patients upon admission, and the expression levels of various markers related to lipid peroxidation and ferroptosis were monitored in the serum and peripheral blood mononuclear cells (PBMCs) of patients with SAE as well as SAE model mice. The hippocampal phosphatidylethanolamine-binding protein (PEBP)-1/15-lysine oxidase (LOX)/ glutathione peroxidase 4 (GPX4) pathway was assessed for its role on the inhibitory effect of ferroptosis in SAE treatment.

RESULTS

The results showed elevated levels of S100 calcium-binding protein beta (S-100β), glial fibrillary acidic protein, and malondialdehyde in the serum of SAE patients, while superoxide dismutase levels were reduced. Furthermore, analysis of PBMCs revealed increased transcription levels of PEBP1, LOX, and long-chain fatty acyl-CoA synthetase family member 4 (ACSL4) in SAE patients, while the transcription levels of GPX4 and cystine/glutamate transporter xCT (SLC7A11) were decreased. In comparison to the control group, the SAE mice exhibited increased expression of S-100β and neuron-specific enolase (NSE) in the hippocampus, whereas the expression of S-100β and NSE were reduced in deferoxamine (DFO) mice. Additionally, iron accumulation was observed in the hippocampus of SAE mice, while the iron ion levels were reduced in the DFO mice. Inhibition of ferroptosis alleviated the mitochondrial damage (as assessed by transmission electron microscopy, hippocampal mitochondrial ATP detection, and the JC-1 polymer-to-monomer ratio in the hippocampus) and the oxidative stress response induced by SAE as well as attenuated neuroinflammatory reactions. Further investigations revealed that the mechanism underlying the inhibitory effect of ferroptosis in SAE treatment is associated with the hippocampal PEBP-1/15-LOX/GPX4 pathway.

CONCLUSION

These results offer potential therapeutic targets for the management of neuronal injury in SAE and valuable insights into the potential mechanisms of ferroptosis in neurological disorders.

Persistent neurocognitive deficits in cognitively impaired survivors of sepsis are explained by reductions in working memory capacity

Introduction

Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Mounting evidence suggests that many cognitively impaired sepsis survivors show long-term neurocognitive deficits in neuropsychological tasks. To date, the underlying mechanisms of these deficits are insufficiently understood. Based on previous evaluations we hypothesized that visual attention and working memory may be affected in a sample of cognitively impaired sepsis survivors.

Methods

We utilized psychophysical whole-and partial-report paradigms based on the computational theory of visual attention (TVA) to determine (i) whether sepsis survivors show changes in basic parameters of visual attention and working memory, (ii) whether the affected parameters are related to neuropsychological test results in a standard battery in sepsis survivors and matched healthy control participants, (iii) whether between-group differences in these basic parameters of visual attention could account for underperformance of sepsis survivors in neuropsychological tests when adjusting for potentially relevant clinical variables.

Results

We showed that, in sepsis survivors, the maximum number of elements consciously maintained in an instant, i.e. the working memory storage capacity K, is reduced (sepsis survivors: M = 3.0; healthy controls: M = 3.4). Moreover, K explained variance in neurocognitive outcomes -17% in attentional and 16 % in executive functions - in a standard neuropsychological battery. The association remained stable when adjusting for clinical variables.

Discussion

Thus, in our sample of cognitively impaired sepsis survivors, a reduction in working memory capacity seems to be a critical determinant of the neurocognitive sequelae. It should be the subject of future work on mechanisms but may also serve as surrogate outcome measure in interventional studies.

Evaluating early lymphocyte-to-monocyte ratio as a predictive biomarker for delirium in older adult patients with sepsis: insights from a retrospective cohort analysis

Background

This study aims to explore the value of the Lymphocyte-to-Monocyte Ratio (LMR) in predicting delirium among older adult patients with sepsis.

Methods

Retrospective data were obtained from the MIMIC-IV database in accordance with the STROBE guidelines. Patients aged 65 and above, meeting the Sepsis 3.0 criteria, were selected for this study. Delirium was assessed using the Confusion Assessment Method for the ICU (CAM-ICU). Demographic information, comorbid conditions, severity of illness scores, vital sign measurements, and laboratory test results were meticulously extracted. The prognostic utility of the Lymphocyte-to-Monocyte Ratio (LMR) in predicting delirium was assessed through logistic regression models, which were carefully adjusted for potential confounding factors.

Results

In the studied cohort of 32,971 sepsis patients, 2,327 were identified as meeting the inclusion criteria. The incidence of delirium within this subgroup was observed to be 55%. A univariate analysis revealed a statistically significant inverse correlation between the Lymphocyte-to-Monocyte Ratio (LMR) and the risk of delirium (p < 0.001). Subsequent multivariate analysis, which accounted for comorbidities and illness severity scores, substantiated the role of LMR as a significant predictive marker. An optimized model, achieving the lowest Akaike Information Criterion (AIC), incorporated 17 variables and continued to demonstrate LMR as a significant prognostic factor (p < 0.01). Analysis of the Receiver Operating Characteristic (ROC) curve indicated a significant enhancement in the Area Under the Curve (AUC) upon the inclusion of LMR (p = 0.035).

Conclusion

The Lymphocyte-to-Monocyte Ratio (LMR) serves as a significant, independent prognostic indicator for the occurrence of delirium in older adult patients with sepsis. Integrating LMR into existing predictive models markedly improves the identification of patients at elevated risk, thereby informing and potentially guiding early intervention strategies.

Risk factors, preventive interventions, overlapping symptoms, and clinical measures of delirium in elderly patients

Delirium is an acute reversible neuropsychiatric syndrome caused by multiple factors. It is associated with many adverse clinical outcomes including cognitive impairment, functional decline, prolonged hospitalization, and increased nursing service. The prevalence of delirium was high in department of cardiology, geriatric, and intensive care unit of hospital. With the increase in the aged population, further increases in delirium seem likely. However, it remains poorly recognized in the clinical practice. This article comprehensively discusses the latest research perspectives on the epidemiological data, risk factors, preventive interventions, overlapping symptoms, and clinical measures of delirium, including specific measures to manage delirium in clinical real-world situations. This article helps readers improve their knowledge and understanding of delirium and helps clinicians quickly identify and implement timely therapeutic measures to address various delirium subtypes that occur in the clinical settings to ensure patients are treated as aggressively as possible.

Patterns and outcomes of health-care associated infections in the medical wards at Bugando medical centre: a longitudinal cohort study

BACKGROUND

The burden of healthcare associated infections (HCAIs) in low- and middle-income countries (LMICs) remains underestimated due to diagnostic complexity and lack of quality surveillance systems. We designed this study to determine clinical diagnosis, laboratory-confirmed, associated factors and risks of HCAIs.

METHODS

This hospital-based longitudinal cohort study was conducted between March and June 2022 among adults (≥ 18 years) admitted in medical wards at BMC in Mwanza, Tanzania. Patients who were negative for HCAIs by clinical evaluations and laboratory investigations during admission were enrolled and followed-up until discharge or death. Clinical samples were collected from patients with clinical diagnosis of HCAIs for conventional culture and antimicrobial sensitivity testing.

RESULTS

A total of 350 adult patients with a median [IQR] age of 54 [38-68] years were enrolled in the study. Males accounted for 54.6% (n = 191). The prevalence of clinically diagnosed HCAIs was 8.6% (30/350) of which 26.7% (8/30) had laboratory-confirmed HCAIs by a positive culture. Central-line-associated bloodstream infection (43.3%; 13/30) and catheter-associated urinary tract infection (36.7%; 11/30) were the most common HCAIs. Older age was the only factor associated with development of HCAIs [mean (± SD); [95%CI]: 58.9(± 12.5); [54.2-63.5] vs. 51.5(± 19.1); [49.4-53.6] years; p = 0.0391) and HCAIs increased the length of hospital stay [mean (± SD); [95%CI]: 13.8 (± 3.4); [12.5-15.1] vs. 4.5 (± 1.7); [4.3-4.7] days; p < 0.0001].

CONCLUSION

We observed a low prevalence of HCAIs among adult patients admitted to medical wards in our setting. Central-line-associated bloodstream infections and catheter-associated urinary tract infections are common HCAIs. Significantly, older patients are at higher risk of acquiring HCAIs as well as patients with HCAIs had long duration of hospital stays.

A Lethal Combination of Delirium and Overcrowding in the Emergency Department

Delirium is a common public health concern that significantly impacts older patients admitted to the Emergency Department (ED). This condition is linked to adverse outcomes such as reduced long-term functionality, higher mortality rates, extended hospital stays, and increased medical costs. The identification of risk factors is crucial for the early recognition and management of delirium in ED patients. Aging, cognitive decline, polypharmacy, and sensory impairment are some of the most common general risk factors described in the literature. Although validated delirium assessment tools already exist, they are not practical for the fast-paced ED environment because of their extended evaluation period or specialized training request. Moreover, clear guidance is needed to select the most suitable tool for detecting delirium, balancing between the accuracy and the swiftness required in an overcrowded, high-stress, and understaffed healthcare setting. This narrative review aims to analyze the updated literature on delirium risk factors in older ED patients and focuses on the methods for better screening, managing, and treating this condition in the ED.

Development of a machine learning-based prediction model for sepsis-associated delirium in the intensive care unit

Septic patients in the intensive care unit (ICU) often develop sepsis-associated delirium (SAD), which is strongly associated with poor prognosis. The aim of this study is to develop a machine learning-based model for the early prediction of SAD. Patient data were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database and the eICU Collaborative Research Database (eICU-CRD). The MIMIC-IV data were divided into a training set and an internal validation set, while the eICU-CRD data served as an external validation set. Feature variables were selected using least absolute shrinkage and selection operator regression, and prediction models were built using logistic regression, support vector machines, decision trees, random forests, extreme gradient boosting (XGBoost), k-nearest neighbors and naive Bayes methods. The performance of the models was evaluated in the validation set. The model was also applied to a group of patients who were not assessed or could not be assessed for delirium. The MIMIC-IV and eICU-CRD databases included 14,620 and 1723 patients, respectively, with a median time to diagnosis of SAD of 24 and 30 h. Compared with Non-SAD patients, SAD patients had higher 28-days ICU mortality rates and longer ICU stays. Among the models compared, the XGBoost model had the best performance and was selected as the final model (internal validation area under the receiver operating characteristic curves (AUROC) = 0.793, external validation AUROC = 0.701). The XGBoost model outperformed other models in predicting SAD. The establishment of this predictive model allows for earlier prediction of SAD compared to traditional delirium assessments and is applicable to patients who are difficult to assess with traditional methods.

S100B as a predictor of delirium in critically ill obstetric patients: A nested case-control study

Background

Delirium is a neuropsychiatric illness that lasts for a short period of time. The incidence of delirium in the intensive care unit (ICU) varies from 20% to 80%.

Methods

A nested case-control study was carried out in the obstetric ICU. Individuals were divided into three groups: critically ill obstetric women who had delirium on admission (Group A), women who developed delirium within follow-up of 7 days (Group B), and women who did not develop delirium after follow-up of 7 days (Group C). The APACHE II score was used to assess critical illness severity. The Richmond Agitation-Sedation Scale was used to assess the alertness or sedation level of patients, and the Confusion Assessment Method (ICU scale) was used to assess the presence of delirium. S100B was measured by human S100B calcium-binding protein B ELISA kit (Elabscience Biotechnology, Houston, USA).

Results

Severe preeclampsia and antepartum eclampsia were significantly associated with delirium. S100B levels in Group B were found to be significantly higher than those in Group C. S100B levels were higher in patients with >2 morbidities in comparison to patients with two morbidities. At a cutoff value of >169.25 pg/ml, S100B had a sensitivity of 74% and a specificity of 87.2% to discriminate cases of delirium from nondelirium.

Conclusion

The rise in S100B levels was approximately three times greater in those who developed delirium as compared to those who did not. It is a more specific predictor of delirium.

Prior exposure to stress exacerbates neuroinflammation and causes long-term behavior changes in sepsis

Background

Neuroinflammation can occur during sepsis and is now regarded as the main mechanism underlying various related central nervous system (CNS) disorders. Another well-known factor causing neuroinflammation is psychological stress. In the current study, we examined the effects of prior exposure to stress on sepsis-induced neuroinflammation and CNS symptoms.

Experimental procedure

Balb/c mice were subjected to wet bedding stress for 2 days, then lipopolysaccharide (LPS) was intraperitoneally administered. For examining the neuroinflammation, the expression of proinflammatory cytokines and NF-κB activity in the brain was analyzed by RT-PCR and ELISA-based assay. Additionally, immunohistochemical study using Iba-1 was performed. Finally, behavior tests were examined one month after LPS treatment.

Result and conclusion

Stress exposure induced the upregulation of IL-1β, IL-6 and TNFα mRNA in the cerebral cortex 4 h after LPS administration. Suggesting an underlying mechanism, LPS-induced NF-κB activation was significantly upregulated with stress in the brain. Histologically, microglia in the cerebral cortex were reactive and became more abundant with stress, while these effects were further increased with LPS injection. Behavioral analysis conducted showed a significant increase of anxiety-like behaviors in the stressed mice. These results suggest that prior exposure to stress exacerbates neuroinflammation during sepsis and induces long-term behavior changes.

Application of magnetic resonance imaging-related techniques in the diagnosis of sepsis-associated encephalopathy: present status and prospect

Sepsis-associated encephalopathy (SAE) refers to diffuse brain dysfunction secondary to systemic infection without central nervous system infection. The early diagnosis of SAE remains a major clinical problem, and its diagnosis is still exclusionary. Magnetic resonance imaging (MRI) related techniques, such as magnetic resonance spectroscopy (MRS), molecular MRI (mMRI), arterial spin-labeling (ASL), fluid-attenuated inversion recovery (FLAIR), and diffusion-weighted imaging (DWI), currently provide new options for the early identification of SAE. This review collected clinical and basic research and case reports related to SAE and MRI-related techniques in recent years, summarized and analyzed the basic principles and applications of MRI technology in diagnosing SAE, and provided a basis for diagnosing SAE by MRI-related techniques.

Correlation of C-reactive Protein with Delirium in Obstetrics Intensive Care Unit: A Tertiary Center Experience

Background

Delirium is a neuropsychiatric illness. It affects critically ill patients on ventilator and increases mortality. The aim of this study was to evaluate the association of C-reactive protein (CRP) level with delirium in critically obstetrics women and its role in prediction of delirium.

Materials and methods

Arospective observational study was conducted in the intensive care unit (ICU), and the duration of study was one year. Total 145 subjects were recruited, 33 patients were excluded, and 112 subjects were studied. For study, group A (n = 36) includes critically ill obstetric women who had delirium on admission; group B (n = 37) includes critically ill obstetric women who developed delirium within 7 days; and group C (n = 39) that includes critically ill obstetric women who did not develop delirium after follow-up of 7 days was served as control. Disease severity was assessed by using acute physiologic assessment and chronic health evaluation (APACHE) II score, and Richmond Agitation-Sedation Scale (RASS) was used to assess awakeness. In awake patients (RASS of ≥3), delirium was assessed by the use of confusion assessment method for ICU tools. C-reactive protein measured by particle enhanced turbidimetric immunoassay-two point kinetic method.

Results

The mean ages of group A, B, and C were 26.44 ± 4.72, 27.46 ± 4.97, and 28.26 ± 5.67 years, respectively. C-reactive protein levels on the day of delirium development (group B) were found to be significantly higher than day 1 CRP levels of groups A and C. The mean Global Attentiveness Rating (GAR) was significantly lower in groups A and B as compared to that in group C (p < 0.001). On evaluating the correlation of CRP with GAR, it was found to be inverse and mild in strength for the correlation between CRP and GAR (r = -0.403, p < 0.001). At a cut-off value of >181 mg/L, CRP had sensitivity of 93.2% and specificity of 69.2%. The positive predictive value was 85% and the negative predictive value was 84.4% that differentiate delirium from non-delirium.

Conclusion

C-reactive protein is a useful tool for screening and prediction of delirium in critically ill obstetric patients.

How to cite this article

Shyam R, Patel ML, Solanki M, Sachan R, Ali W. Correlation of C-reactive Protein with Delirium in Obstetrics Intensive Care Unit: A Tertiary Center Experience. Indian J Crit Care Med 2023;27(5):315-321.

Deep Learning-Based Recurrent Delirium Prediction in Critically Ill Patients

OBJECTIVES

To predict impending delirium in ICU patients using recurrent deep learning.

DESIGN

Retrospective cohort study.

SETTING

Fifteen medical-surgical ICUs across Alberta, Canada, between January 1, 2014, and January 24, 2020.

PATIENTS

Forty-three thousand five hundred ten ICU admissions from 38,426 patients.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We used ICU and administrative health data to train deep learning models to predict delirium episodes in the next two 12-hour periods (0-12 and 12-24 hr), starting at 24 hours after ICU admission, and to generate new predictions every 12 hours. We used a comprehensive set of 3,643 features, capturing patient history, early ICU admission information (first 24 hr), and the temporal dynamics of various clinical variables throughout the ICU admission. Our deep learning architecture consisted of a feature embedding, a recurrent, and a prediction module. Our best model based on gated recurrent units yielded a sensitivity of 0.810, a specificity of 0.848, a precision (positive predictive value) of 0.704, and an area under the receiver operating characteristic curve (AUROC) of 0.909 in the hold-out test set for the 0-12-hour prediction horizon. For the 12-24-hour prediction horizon, the same model achieved a sensitivity of 0.791, a specificity of 0.807, a precision of 0.637, and an AUROC of 0.895 in the test set.

CONCLUSIONS

Our delirium prediction model achieved strong performance by applying deep learning to a dataset that is at least one order of magnitude larger than those used in previous studies. Another novel aspect of our study is the temporal nature of our features and predictions. Our model enables accurate prediction of impending delirium in the ICU, which can potentially lead to early intervention, more efficient allocation of ICU resources, and improved patient outcomes.

Screening of core genes prognostic for sepsis and construction of a ceRNA regulatory network

OBJECTIVE

To screen out core genes potentially prognostic for sepsis and construct a competing endogenous RNA (ceRNA) regulatory network.

METHODS

Subjects included in this project were 23 sepsis patients and 10 healthy people. RNA-seq for lncRNA, miRNA and mRNA was performed in the peripheral blood samples. Differentially expressed RNAs (DER) were screened out for further analysis. GO annotation and GSEA functional clustering were performed to view the functional enrichment of DEmRNAs. Core genes of prognostic significance were screened out with the weighted correlation network analysis (WGCNA). Meta-analysis and Survival analysis was devised in different microarray datasets. RT-qPCR was conducted to validate these core genes. A ceRNA network was accordingly constructed according to the correlation analysis and molecular interaction prediction.

RESULTS

RNA-seq and differential analysis screened out 1,044 DEmRNAs, 66 DEmiRNAs and 155 DElncRNAs. The GO and GSEA analysis revealed that DEmRNAs are mainly involved in inflammatory response, immune regulation, neutrophil activation. WGCNA revealed 4 potential core genes, including CD247, IL-2Rβ, TGF-βR3 and IL-1R2. In vitro cellular experiment showed up-regulated expression of IL-1R2 while down-regulated of CD247, IL-2Rβ, TGF-βR3 in sepsis patients. Correspondingly, a ceRNA regulatory network was build based on the core genes, and multiple lncRNAs and miRNAs were identified to have a potential regulatory role in sepsis.

CONCLUSION

This study identified four core genes, including CD247, IL-1R2, IL-2Rβ and TGF-βR3, with potential to be novel biomarkers for the prognosis of sepsis. In the meantime, a ceRNA network was constructed aiming to guide further study on prognostic mechanism in sepsis.

Sepsis-Associated Delirium: A Narrative Review

Delirium is characterized by an acutely altered mental status accompanied by reductions in cognitive function and attention. Delirium in septic patients, termed sepsis-associated delirium (SAD), differs in several specific aspects from the other types of delirium that are typically encountered in intensive care units. Since sepsis and delirium are both closely associated with increased morbidity and mortality, it is important to not only prevent but also promptly diagnose and treat SAD. We herein reviewed the etiology, pathogenesis, risk factors, prevention, diagnosis, treatment, and prognosis of SAD, including coronavirus disease 2019 (COVID-19)-related delirium. Delirium by itself not only worsens long-term prognosis, but it is also regarded as an important factor affecting the outcome of post-intensive care syndrome. In COVID-19 patients, the difficulties associated with adequately implementing the ABCDEF bundle (Assess, prevent, and manage pain; Both spontaneous awakening and breathing trials: Choice of analgesia and sedation; Delirium assess, prevent, and manage; Early mobility and exercise; Family engagement/empowerment) and the need for social isolation are issues that require the development of conventional care for SAD.

The Key Drivers of Brain Injury by Systemic Inflammatory Responses after Sepsis: Microglia and Neuroinflammation

Sepsis is a leading cause of intensive care unit admission and death worldwide. Most surviving patients show acute or chronic mental disorders, which are known as sepsis-associated encephalopathy (SAE). Although accumulating studies in the past two decades focused on the pathogenesis of SAE, a systematic review of retrospective studies which exclusively focuses on the inflammatory mechanisms of SAE has been lacking yet. This review summarizes the recent advance in the field of neuroinflammation and sheds light on the activation of microglia in SAE. Activation of microglia predominates neuroinflammation. As the gene expression profile changes, microglia show heterogeneous characterizations throughout all stages of SAE. Here, we summarize the systemic inflammation following sepsis and also the relationship of microglial diversity and neuroinflammation. Moreover, a collection of neuroinflammation-related dysfunction has also been reviewed to illustrate the possible mechanisms for SAE. In addition, promising pharmacological or non-pharmacological therapeutic strategies, especially those which target neuroinflammation or microglia, are also concluded in the final part of this review. Collectively, clarification of the vital relationship between neuroinflammation and SAE-related mental disorders would significantly improve our understanding of the pathophysiological mechanisms in SAE and therefore provide potential targets for therapies of SAE aimed at inhibiting neuroinflammation.

Post-Intensive Care Syndrome: A Problem Cannot Be Ignored in ICU. Comment on Inoue et al. Prevalence and Long-Term Prognosis of Post-Intensive Care Syndrome after Sepsis: A Single-Center Prospective Observational Study. J. Clin. Med. 2022, 11, 5257

Recently, we read with great interest the article by Inoue et al. [...].

Early Diagnosis of Murine Sepsis-Associated Encephalopathy Using Dynamic PET/CT Imaging and Multiparametric MRI

PURPOSE

Early diagnosis of sepsis-associated encephalopathy (SAE) is essential for the treatment and prognosis of septic patients. Static PET and MRI have shown promise for early diagnosis, while pharmacokinetic parameters from dynamic PET may provide better quantification for SAE. This study aims to compare the performance of dynamic 2-deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]F-FDG) PET and multiparametric MRI in early imaging SAE with a view to providing guidance for the early diagnosis of SAE.

PROCEDURES

Dynamic [¹⁸F]F-FDG-PET/CT scans and multiparametric MRI were performed in SAE mice induced by LPS. Standardized uptake value (SUV) was measured in static scan images and [¹⁸F]F-FDG pharmacokinetic parameters were analyzed with two-tissue compartment model and Patlak plot. MRI relative signal intensity (rT1) derived from T1-weighted images (pre and post contrast) and 4 parameters originating from diffusion-weighted data were measured.

RESULTS

Both SUV and dephosphorylation rate constant (k₄) increased in SAE model as early as 6 h post sepsis induction, while k₄ increased with the relative value (SAE/normal) significantly stronger than that of SUV. Moreover, the net influx constant (K_i) showed significant decrease in SAE as early as 6 h compared with normal mice. Increased signal intensity was identified in T1-weighted contrast enhanced images and rT1 value increased at 12 h post induction. Diffusion tensor imaging (DTI) revealed fractional anisotropy (FA) decreased at 12 h and 24 h in external capsule (ec) and declined axial diffusivity (AD) was shown in white matter at 24 h.

CONCLUSIONS

The dynamic PET (k₄) was more sensitive than static PET (SUV) for early diagnosis of SAE and declined K_i was firstly found in murine SAE, which indicated the advantage of dynamic PET/CT in early detection and differential diagnosis of SAE. While MRI has a higher soft tissue resolution than PET/CT and can classify more subtle brain areas, the comprehensive utilization of the two modalities is helpful for managing SAE.

[Risk factors for delirium after sedation in children with convulsion and establishment of a nomogram model for predicting the risk of delirium]

OBJECTIVES

To investigate the risk factors for delirium after sedation in children with convulsion, and to establish a nomogram model for predicting the risk of delirium.

METHODS

A total of 373 children with convulsion who were hospitalized in the pediatric ward of the Second Affiliated Hospital of Air Force Medical University from August 2020 to January 2022 were prospectively enrolled. There were 245 children in the modeling group and 128 children in the validation group. A multivariate logistic regression analysis was used to identify independent predictive factors for delirium after sedation and establish a nomogram model for predicting the risk of this disorder based on these factors. The calibration curve, the receiver operating characteristic curve, and the decision curve analysis were used to evaluate the accuracy, discriminatory ability, and clinical application value of this model, respectively.

RESULTS

The incidence of delirium after sedation was 22.3% (83/373) in the children with convulsion. The multivariate logistic regression analysis showed that age>5 years (OR=0.401, P<0.05) was a protective factor against delirium after sedation in these children, while presence of infection (OR=3.020, P<0.05), admission to the pediatric intensive care unit (OR=3.126, P<0.05), use of benzodiazepines (OR=5.219, P<0.05), history of status convulsion (OR=2.623, P<0.05), and history of delirium episodes (OR=3.119, P<0.05) were risk factors for delirium. The H-L deviation test of the nomogram prediction model showed a good degree of fit (χ2=9.494, P=0.302). Internal and external validation showed that the mean absolute errors between the actual and predicted values of the calibration curve were 0.030 and 0.018, respectively, and the areas under the receiver operating characteristic curve were 0.777 and 0.775, respectively. The decision curve analysis showed that the model provided significant net clinical benefit when the predicted risk threshold was >0.01.

CONCLUSIONS

Age, presence of infection, admission to the pediatric intensive care unit, use of benzodiazepines, history of status convulsion, and history of delirium episodes are closely associated with the development of delirium after sedation in children with convulsion. The nomogram model for predicting this disorder that is established based on these factors has relatively high accuracy, discriminatory ability, and clinical application value.

Incidence and interaction factors of delirium as an independent risk of mortality in elderly patients in the intensive units: a retrospective analysis from MIMIC-IV database

BACKGROUND

As delirium is a common problem in critcal elderly patients, the aim of the study was to investigate the interaction factors of delirium as an independent risk of mortality in elderly patients in the intensive care unit (ICU).

PATIENTS AND METHODS

Elderly patients (age ≥ 65) were selected from Medical Information Mart for Intensive Care (MIMIC)-IV database. Demographics data were collected on the 1st day of admission to ICU. The main outcome is in-hospital mortality. Propensity score matching analysis (PSMA) was used to remove the influence of comfounding factors between survival and nonsurvival groups. Chi-square test and logistic regression analysis was used to identify the association between delirium and in-hospital death. Stratified analysis and interaction analysis was used to evaluate the interaction factors of delirium as a risk of in-hospital mortality.

RESULTS

22,361 patients were selected, and in which 2809 patients died. 5453 patients had delirium (about 24.4%). There is a significant difference in delirium between the survival and nonsurvival groups before and after PSMA (p = 0.000 and p = 0.030). Logistic regression showed delirium, sequential organ failure assessment (SOFA), and hemoglobin were all significantly related to in-hospital death (p = 0.000). SOFA score and hemoglobin concentration were proved to be remarkable interaction factors of delirium (p = 0.000, and p = 0.041). Significant correlation between delirium and hospital mortality was inhibited when SOFA was more than 12 or hemoglobin was higher than 15 g/dL. In-hospital mortality (49.1% vs. 10.5%, p = 0.000) and shock incidence (87.9% vs. 15.8%, p = 0.000) of the patients with SOFA ≥ 12 was much higher than that of the patients with SOFA ≤ 11.

CONCLUSION

SOFA and hemoglobin are interaction factors of delirium as an independent risk of in-hospital mortality in elderly patients in the intensive care unit.

Cytokine profiles in intensive care unit delirium

Background

Neuroinflammation causing disruption of the blood-brain barrier and immune cell extravasation into the brain parenchyma may cause delirium; however, knowledge of the exact pathophysiologic mechanism remains incomplete. The purpose of our study was to determine whether cytokine profiles differ depending on whether delirium occurs in the setting of sepsis, coronavirus disease 2019 (COVID-19), or recent surgery.

Methods

This prospective observational cohort study involved 119 critically ill patients admitted to a multidisciplinary intensive care unit (ICU) during 2019 and 2020. Delirium was identified using the validated confusion assessment method for the ICU. Multiple delirium risk factors were collected daily including clinical characteristics, hospital course, lab values, vital signs, surgical exposure, drug exposure, and COVID-19 characteristics. Serums samples were collected within 12 hours of ICU admission and cytokine levels were measured.

Results:

The following proinflammatory cytokines were elevated in our delirium population: tumor necrosis factor (TNF)-α, interleukin (IL)-6, IL-18, C-C motif ligand (CCL) 2, CCL3, C-X-C motif chemokine ligand (CXCL)1, CXCL10, IL-8, IL-1 receptor antagonist, and IL-10. Analysis of relative cytokine levels in those patients that developed delirium in the setting of sepsis, COVID-19, and recent surgery showed elevations of CCL2, CXCL10, and TNF-α in both the sepsis and COVID-19 group in comparison to the postsurgical population. In the postsurgical group, granulocyte colony-stimulating factor was elevated and CXCL10 was decreased relative to the opposing groups.

Conclusions

We identify several cytokines and precipitating factors known to be associated with delirium. However, our study suggests that the cytokine profile associated with delirium is variable and contingent upon delirium precipitating factors.

Perioperative Hemodynamic Optimization in Patients at Risk for Delirium - A Randomized-Controlled Trial

Background

Post-operative delirium is common in elderly patients and associated with increased morbidity and mortality. We evaluated in this pilot study whether a perioperative goal-directed hemodynamic optimization algorithm improves cerebral oxygenation and can reduce the incidence of delirium.

Materials and Methods

Patients older than 70 years with high risk for post-operative delirium undergoing elective non-cardiac surgery were randomized to an intervention or control group. Patients in the intervention group received a perioperative hemodynamic optimization protocol based on uncalibrated pulse-contour analysis. Patients in the control group were managed according to usual standard of care. Incidence of delirium until day seven was assessed with confusion assessment method (CAM) and chart review. Cerebral oxygenation was measured with near-infrared spectroscopy.

Results

Delirium was present in 13 of 85 (15%) patients in the intervention group and 18 of 87 (21%) in the control group [risk difference -5.4%; 95% confidence interval, -16.8 to 6.1%; P = 0.47]. Intervention did not influence length of stay in hospital or in-hospital mortality. Amounts of fluids and vasopressors applied, mean arterial pressure, cardiac index, and near-infrared spectroscopy values were comparable between groups.

Conclusion

The hemodynamic algorithm applied in high-risk non-cardiac surgery patients did not change hemodynamic interventions, did not improve patient hemodynamics, and failed to increase cerebral oxygenation. An effect on the incidence of post-operative delirium could not be observed.

Clinical Trial Registration

[Clinicaltrials.gov], identifier [NCT01827501].

Sepsis-associated brain injury: underlying mechanisms and potential therapeutic strategies for acute and long-term cognitive impairments

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. Sepsis causes cerebral dysfunction in the short and long term and induces disruption of the blood–brain barrier (BBB), neuroinflammation, hypoperfusion, and accumulation of amyloid β (Aβ) and tau protein in the brain. White matter changes and brain atrophy can be detected using brain imaging, but unfortunately, there is no specific treatment that directly addresses the underlying mechanisms of cognitive impairments in sepsis. Here, we review the underlying mechanisms of sepsis-associated brain injury, with a focus on BBB dysfunction and Aβ and tau protein accumulation in the brain. We also describe the neurological manifestations and imaging findings of sepsis-associated brain injury, and finally, we propose potential therapeutic strategies for acute and long-term cognitive impairments associated with sepsis. In the acute phase of sepsis, we suggest using antibiotics (such as rifampicin), targeting proinflammatory cytokines, and preventing ischemic injuries and hypoperfusion. In the late phase of sepsis, we suggest targeting neuroinflammation, BBB dysfunction, Aβ and tau protein phosphorylation, glycogen synthase kinase-3 beta (GSK3β), and the receptor for advanced glycation end products (RAGE). These proposed strategies are meant to bring new mechanism-based directions for future basic and clinical research aimed at preventing or ameliorating acute and long-term cognitive impairments in patients with sepsis.

The Improvement of Sepsis-Associated Encephalopathy by P2X7R Inhibitor through Inhibiting the Omi/HtrA2 Apoptotic Signaling Pathway

The pathogenesis of sepsis-associated encephalopathy (SAE) involves many aspects, including intracellular peroxidative stress damage, mitochondrial dysfunction, and cell apoptosis. In this study, we mainly explored the influence of P2X7R on the cognitive function of SAE and its molecular mechanism. We established a sepsis model using lipopolysaccharide (LPS) stimulation, followed by an assessment of cognitive function using Morris water maze, and then Western Blot was used to analyze the expression of tight junction proteins ZO-1 and Occludin in the hippocampus of mice. TUNEL assay was used to analyze the apoptosis of brain cells in frozen brain slices of mice during sepsis. Human brain microvascular endothelial cells (HBMECs) were used to research the molecular mechanism of brain cell damage induced by P2X7R. The results showed that P2X7R inhibitors dramatically improved the survival rate of mice, relieved the cognitive dysfunction caused by LPS stimulation, and significantly reduced the brain cell apoptosis caused by LPS. In addition, the inhibition of P2X7R can also reduce the production and accumulation of reactive oxygen species (ROS) in HBMECs in vitro and inhibit the apoptosis signaling pathway associated with mitochondrial serine protease Omi/HtrA2 in HBMECs in vitro. These results suggest that P2X7R has strong value as a potential target for the treatment of SAE.

Intensive care unit delirium in patients with severe COVID-19: A prospective observational cohort study

Background:

Delirium is common in patients with severe coronavirus disease-19 (COVID-19). The purpose of our study was to determine whether severe COVID-19 is an independent risk factor for the development of delirium in patients treated in the intensive care unit (ICU).

Methods:

This prospective observational cohort study involved 162 critically ill patients admitted to a multidisciplinary ICU during 2019 and 2020. A validated screening tool was used to diagnose delirium. Multiple delirium risk factors were collected daily including clinical characteristics, hospital course, lab values, vital signs, surgical exposure, drug exposure, and COVID-19 characteristics. After univariate analysis, a multivariate logistic regression analysis was performed to determine independent risk factors associated with the development of delirium.

Results:

In our study population, 50 (31%) patients developed delirium. A total of 39 (24.1%) tested positive for COVID-19. Initial analysis showed COVID-19 to be more prevalent in those patients that developed delirium (40% vs. 17%; P = 0.003). Multivariate analysis showed opioid use (odds ratio [OR]: 24 [95% confidence intervals (CI): 16–27]; P ≤ 0.001), benzodiazepine use (OR: 23 [95% CI: 16–63] P = 0.001), and estimated mortality based on acute physiology and chronic health evaluation IV score (OR: 1.04 [95% CI: 1.01–1.07] P = 0.002) to be independently associated with delirium development. COVID-19 (OR: 1.44 [95% CI: 0.13–10.6]; P = 0.7) was not found to be associated with delirium.

Conclusion:

Delirium is prevalent in critically ill patients admitted to the ICU, including those with COVID-19. However, after adjustment for important covariates, we found in this cohort that COVID-19 was not an independent risk factor for delirium.

The Role of Mfsd2a in Nervous System Diseases

Major facilitator superfamily (MFS) is the maximum and most diversified membrane transporter, acting as uniporters, symporters and antiporters. MFS is considered to have a good development potential in the transport of drugs for the treatment of brain diseases. The major facilitator superfamily domain containing protein 2a (Mfsd2a) is a member of MFS. Mfsd2a-knockout mice have shown a marked decrease of docosahexaenoic acid (DHA) level in brain, exhibiting neuron loss, microcephaly and cognitive deficits, as DHA acts essentially in brain growth and integrity. Mfsd2a has attracted more and more attention in the study of nervous system diseases because of its critical role in maintaining the integrity of the blood-brain barrier (BBB) and transporting DHA, including inhibiting cell transport in central nervous system endothelial cells, alleviating BBB injury, avoiding BBB injury in cerebral hemorrhage model, acting as a carrier etc. Up to now, the clinical research of Mfsd2a in nervous system diseases is rare. This article reviewed the current research progress of Mfsd2a in nervous system diseases. It summarized the physiological functions of Mfsd2a in the occurrence and development of intracranial hemorrhage (ICH), Alzheimer's disease (AD), sepsis-associated encephalopathy (SAE), autosomal recessive primary microcephaly (MCPH) and intracranial tumor, aiming to provide ideas for the basic research and clinical application of Mfsd2a.

Mortality among patients with sepsis associated with a bispectral electroencephalography (BSEEG) score

We have previously developed a bispectral electroencephalography (BSEEG) device, which was shown to be effective in detecting delirium and predicting patient outcomes. In this study we aimed to apply the BSEEG approach for a sepsis. This was a retrospective cohort study conducted at a single center. Sepsis-positive cases were identified based on retrospective chart review. EEG raw data and calculated BSEEG scores were obtained in the previous studies. The relationship between BSEEG scores and sepsis was analyzed, as well as the relationship among sepsis, BSEEG score, and mortality. Data were analyzed from 628 patients. The BSEEG score from the first encounter (1st BSEEG) showed a significant difference between patients with and without sepsis (p = 0.0062), although AUC was very small indicating that it is not suitable for detection purpose. Sepsis patients with high BSEEG scores showed the highest mortality, and non-sepsis patients with low BSEEG scores showed the lowest mortality. Mortality of non-sepsis patients with high BSEEG scores was as bad as that of sepsis patients with low BSEEG scores. Even adjusting for age, gender, comorbidity, and sepsis status, BSEEG remained a significant predictor of mortality (p = 0.008). These data are demonstrating its usefulness as a potential tool for identification of patients at high risk and management of sepsis.

Perioperative Vascular Biomarker Profiling in Elective Surgery Patients Developing Postoperative Delirium: A Prospective Cohort Study

Background: Postoperative delirium (POD) ranks among the most common complications in surgical patients. Blood-based biomarkers might help identify the patient at risk. This study aimed to assess how serum biomarkers with specificity for vascular and endothelial function and for inflammation are altered, prior to or following surgery in patients who subsequently develop POD. Methods: This was a study on a subcohort of consecutively recruited elective non-cardiac as well as cardiac surgery patients (age > 60 years) of the single-center PROPDESC trial at a German tertiary care hospital. Serum was sampled prior to and following surgery, and the samples were subjected to bead-based multiplex analysis of 17 serum proteins (IL-3, IL-8, IL-10, Cripto, CCL2, RAGE, Resistin, ANGPT2, TIE2, Thrombomodulin, Syndecan-1, E-Selectin, VCAM-1, ICAM-1, CXCL5, NSE, and uPAR). Development of POD was assessed during the first five days after surgery, using the Confusion Assessment Method for ICU (CAM-ICU), the CAM, the 4-‘A’s test (4AT), and the Delirium Observation Scale (DOS). Patients were considered positive if POD was detected at least once during the visitation period by any of the applied methods. Non-parametric testing, as well as propensity score matching were used for statistical analysis. Results: A total of 118 patients were included in the final analysis; 69% underwent non-cardiac surgery, median overall patient age was 71 years, and 59% of patients were male. In the whole cohort, incidence of POD was 28%. The male gender was significantly associated with the development of POD (p = 0.0004), as well as a higher ASA status III (p = 0.04). Incidence of POD was furthermore significantly increased in cardiac surgery patients (p = 0.002). Surgery induced highly significant changes in serum levels of almost all biomarkers except uPAR. In preoperative serum samples, none of the analyzed parameters was significantly altered in subsequent POD patients. In postoperative samples, CCL2 was significantly increased by a factor of 1.75 in POD patients (p = 0.03), as compared to the no-POD cohort. Following propensity score matching, CCL2 remained the only biomarker that showed significant differences in postoperative values (p = 0.01). In cardiac surgery patients, postoperative CCL2 serum levels were more than 3.5 times higher than those following non-cardiac surgery (p < 0.0001). Moreover, after cardiac surgery, Syndecan-1 serum levels were significantly increased in POD patients, as compared to no-POD cardiac surgery patients (p = 0.04). Conclusions: In a mixed cohort of elective non-cardiac as well as cardiac surgery patients, preoperative serum biomarker profiling with specificity for vascular dysfunction and for systemic inflammation was not indicative of subsequent POD development. Surgery-induced systemic inflammation—as evidenced by the significant increase in CCL2 release—was associated with POD, particularly following cardiac surgery. In those patients, postoperative glycocalyx injury might furthermore contribute to POD development.

Poor outcomes of delirium in the intensive care units are amplified by increasing age: A retrospective cohort study

BACKGROUND

Delirium in patients in intensive care units (ICUs) is an acute disturbance and fluctuation of cognition and consciousness. Though increasing age has been found to be related to ICU delirium, there is limited evidence of the effect of age on delirium outcomes. The aim of this study is to investigate the relationship between age categories and outcomes among ICU delirium patients.

METHODS

Data were extracted from the electronic ICU (eICU) Collaborative Research Database with records from 3,931 patients with delirium. Patients were classified into non-aged (<65 years), young-old (65-74 years), middle-old (75-84 years), and very-old (≥85 years) groups. A Cox regression model was built to examine the role of age in death in ICU and in hospital after controlling covariates.

RESULTS

The sample included 1,667 (42.4%) non-aged, 891 (22.7%) young-old, 848 (21.6%) middle-old, and 525 (13.3%) very-old patients. The ICU mortality rate was 8.3% and the hospital mortality rate was 15.4%. Compared with the non-aged group, the elderly patients (≥65 yeras) had higher mortality at ICU discharge (χ² =13.726, P=0.001) and hospital discharge (χ ²=56.347, P<0.001). The Cox regression analysis showed that age was an independent risk factor for death at ICU discharge (hazard ratio [HR]=1.502, 1.675, 1.840, 95% confidence interval [CI] 1.138-1.983, 1.250-2.244, 1.260-2.687; P=0.004, 0.001, 0.002 for the young-, middle- and very-old group, respectively) as well as death at hospital discharge (HR=1.801, 2.036, 2.642, 95% CI 1.454-2.230, 1.638-2.530, 2.047-3.409; all P<0.001).

CONCLUSIONS

The risks of death in the ICU and hospital increase with age among delirious patients.