Hypoglycemia and mortality in sepsis patients: A systematic review and meta-analysis

Unveiling shared diagnostic biomarkers and molecular mechanisms between T2DM and sepsis: Insights from bioinformatics to experimental assays

Septic patients with T2DM were prone to prolonged recovery and unfavorable prognoses. Thus, this study aimed to pinpoint potential genes related to sepsis with T2DM and develop a predictive model for the disease. The candidate genes were screened using protein-protein interaction networks (PPI) and machine learning algorithms. The nomogram and receiver operating characteristic curve were developed to assess the diagnostic efficiency of the biomarkers. The relationship between sepsis and immune cells was analyzed using the CIBERSORT algorithm. The biomarkers were validated by qPCR and western blotting in basic experiments, and differences in organ damage in mice were studied. Three genes (MMP8, CD177, and S100A12) were identified using PPI and machine learning algorithms, demonstrating strong predictive capabilities. These biomarkers presented significant differences in gene expression patterns between diseased and healthy conditions. Additionally, the expression levels of biomarkers in mouse models and blood samples were consistent with the findings of the bioinformatics analysis. The study elucidated the common molecular mechanisms associated with the pathogenesis of T2DM and sepsis and developed a gene signature-based prediction model for sepsis. These findings provide new targets for the diagnosis and intervention of sepsis complicated with T2DM.

Fetal Speckle Tracking Echocardiography Measured Global Longitudinal Strain and Strain Rate in Congenital Heart Disease: A Systematic Review and Meta-Analysis

Fetal two-dimensional speckle tracking echocardiography (2D-STE) is a novel technique that provides information on fetal heart function by measuring global longitudinal strain (GLS) and global longitudinal strain rate (GLSR). These features assess the longitudinal deformity of the fetal cardiac wall. 2D-STE is shown to be of prognostic value in children and adults with congenital heart disease (CHD). Therefore, its importance in fetal life should also be considered. This systematic review and meta-analysis provides an overview of the literature on 2D-STE (GLS/GLSR) in fetuses with CHD, focusing on the left and right ventricles (LV/RV). Findings indicated that LV-GLS was significantly lower in fetuses with coarctation of the aorta (CoA) and Tetralogy of Fallot (ToF) compared to controls. Conversely, fetuses with a single left ventricle exhibited higher LV-GLS. RV-GLS was significantly lower in fetuses with hypoplastic left heart syndrome (HLHS) and ToF compared to controls. LV-GLSR was significantly lower in fetuses with CoA. Overall, considerable heterogeneity was observed, possibly due to differences in study design. More prospective longitudinal studies on 2D-STE in fetuses with CHD, considering heterogeneity parameters, could offer better insights into this promising technique.

Derived Time in Range and Other Metrics of Poor Glycemic Control Associated With Adverse Hospital Outcomes in Patients With Diabetes Mellitus Admitted to Non-ICU Wards at a Tertiary-Level Hospital in Colombia: A Cross-Sectional Study

Aim: This study is aimed at assessing the prevalence of poor glycemic control using different metrics and its association with in-hospital adverse outcomes. Methods: This cross-sectional study was conducted in diabetic patients admitted to a third-level hospital in Colombia between January and July 2022. Poor glycemic control was determined using capillary glucose metrics, including mean glucose values outside the target range, derived time in range (dTIR) (100-180 mg/dL) < 70%, coefficient of variation (CV > 36%), and hypoglycemia (<70 mg/dL). Multiple regression models were adjusted for hospital outcomes based on glycemic control, as well as other sociodemographic and clinical covariates. Results: A total of 330 Hispanic patients were included. A total of 27.6% had mean glucose measurements outside the target range, 33% had a high CV, 64.8% had low dTIR, and 28.8% experienced hypoglycemia. The in-hospital mortality rate was 8.8%. An admission HbA1c level greater than 7% was linked to an increased mortality risk (p = 0.016), as well as a higher average of glucometer readings (186 mg/dL vs. 143 mg/dL; p < 0.001). A lower average of dTIR (41.0% vs. 60.0%; p < 0.001) was also associated with a higher mortality risk. Glycemic variability was correlated with an increased risk of mortality, hypoglycemia, delirium, and length of hospital stay (LOS). Conclusion: A significant number of hospitalized diabetic patients exhibit poor glycemic control, which has been found to be associated with adverse outcomes, including increased mortality. Metrics like dTIR and glycemic variability should be considered as targets for glycemic control, highlighting the need for enhanced management strategies.

Triglyceride-glucose index and clinical outcomes in sepsis: A retrospective cohort study of MIMIC-IV

Although accumulating researches were done for investigating the relationship between triglyceride-glucose index (TyG index) and different diseases, none of the researches have been made in sepsis yet. In this study, we aimed to explore the relationship between TyG index and clinical outcomes in sepsis based on a large critical care public database. Sepsis patients in Medical Information Mart for Intensive Care IV (MIMIC-IV) Database were included. The exposure was TyG index, which was calculated by the equation: ln (TG (mg/dL) × FBG (mg/dL)/2). The outcomes were in-hospital mortality and 1-year mortality. The relationship between TyG index and outcomes was performed by Cox regression analysis. Smooth fitting curves were constructed by using generalized additive model. Kaplan-Meier analyses for cumulative hazard of 1-year mortality in different groups were done. 1103 sepsis patients were included with a median TyG index of 9.78. The mortalities of in-hospital and 1-year were 37.53% (n = 414) and 42.25% (n = 466), respectively. After adjusting confounders, there was a significantly negative relationship between TyG index and mortalities of in-hospital and 1-year. With the per unit increment in TyG index, the risk of in-hospital and 1-year mortality both decreased by 21% (HR = 0.79, 95% CI: 0.66-0.94, p = 0.0086 and HR = 0.79, 95% CI: 0.66-0.94, p = 0.0080, respectively). A negative relationship between TyG index and clinical outcomes in sepsis was found.

Combined sepsis- and renal dysfunction-induced hypoglycaemia in an older patient taking cibenzoline

Key Clinical Message

An 86-year-old geriatric patient with sepsis presented cibenzoline-induced hypoglycaemia, although within the boundary range of cibenzoline blood concentration.

Abstract

An 86-year-old geriatric patient taking cibenzoline for ametropic hypertrophic cardiac tendinopathy was admitted to our hospital for the treatment of sepsis. Upon admission, blood cibenzoline levels of 400.1 ng/mL were observed. Antibiotic therapy was initiated and cibenzoline was discontinued. On Day 16, cibenzoline was administered orally at a reduced dose of 50 mg/day. Several days after restarting cibenzoline, the patient developed hypoglycaemia (64 mg/dL), prompting the administration of 20% glucose. The present case demonstrates a rational timeline for cibenzoline administration, considering the patient's renal dysfunction and sepsis. Clinicians should exercise caution when managing older patients with severe infections who are receiving cibenzoline, and should consider the possibility of blood glucose fluctuations regardless of cibenzoline blood levels. Further research is warranted to better understand and address the potential side effects of cibenzoline administration in geriatric populations.

Pre-hospital glycemia as a biomarker for in-hospital all-cause mortality in diabetic patients - a pilot study

BACKGROUND

Type 2 Diabetes Mellitus (T2DM) presents a significant healthcare challenge, with considerable economic ramifications. While blood glucose management and long-term metabolic target setting for home care and outpatient treatment follow established procedures, the approach for short-term targets during hospitalization varies due to a lack of clinical consensus. Our study aims to elucidate the impact of pre-hospitalization and intra-hospitalization glycemic indexes on in-hospital survival rates in individuals with T2DM, addressing this notable gap in the current literature.

METHODS

In this pilot study involving 120 hospitalized diabetic patients, we used advanced machine learning and classical statistical methods to identify variables for predicting hospitalization outcomes. We first developed a 30-day mortality risk classifier leveraging AdaBoost-FAS, a state-of-the-art ensemble machine learning method for tabular data. We then analyzed the feature relevance to identify the key predictive variables among the glycemic and routine clinical variables the model bases its predictions on. Next, we conducted detailed statistical analyses to shed light on the relationship between such variables and mortality risk. Finally, based on such analyses, we introduced a novel index, the ratio of intra-hospital glycemic variability to pre-hospitalization glycemic mean, to better characterize and stratify the diabetic population.

RESULTS

Our findings underscore the importance of personalized approaches to glycemic management during hospitalization. The introduced index, alongside advanced predictive modeling, provides valuable insights for optimizing patient care. In particular, together with in-hospital glycemic variability, it is able to discriminate between patients with higher and lower mortality rates, highlighting the importance of tightly controlling not only pre-hospital but also in-hospital glycemic levels.

CONCLUSIONS

Despite the pilot nature and modest sample size, this study marks the beginning of exploration into personalized glycemic control for hospitalized patients with T2DM. Pre-hospital blood glucose levels and related variables derived from it can serve as biomarkers for all-cause mortality during hospitalization.

Lactobacillus rhamnosus GG ameliorates hyperuricemia in a novel model

Hyperuricemia (HUA) is a metabolic syndrome caused by abnormal purine metabolism. Although recent studies have noted a relationship between the gut microbiota and gout, whether the microbiota could ameliorate HUA-associated systemic purine metabolism remains unclear. In this study, we constructed a novel model of HUA in geese and investigated the mechanism by which Lactobacillus rhamnosus GG (LGG) could have beneficial effects on HUA. The administration of antibiotics and fecal microbiota transplantation (FMT) experiments were used in this HUA goose model. The effects of LGG and its metabolites on HUA were evaluated in vivo and in vitro. Heterogeneous expression and gene knockout of LGG revealed the mechanism of LGG. Multi-omics analysis revealed that the Lactobacillus genus is associated with changes in purine metabolism in HUA. This study showed that LGG and its metabolites could alleviate HUA through the gut-liver-kidney axis. Whole-genome analysis, heterogeneous expression, and gene knockout of LGG enzymes ABC-type multidrug transport system (ABCT), inosine-uridine nucleoside N-ribohydrolase (iunH), and xanthine permease (pbuX) demonstrated the function of nucleoside degradation in LGG. Multi-omics and a correlation analysis in HUA patients and this goose model revealed that a serum proline deficiency, as well as changes in Collinsella and Lactobacillus, may be associated with the occurrence of HUA. Our findings demonstrated the potential of a goose model of diet-induced HUA, and LGG and proline could be promising therapies for HUA.

The impact of chelation compliance in health outcome and health related quality of life in thalassaemia patients: a systematic review

Understanding consequences of poor chelation compliance is crucial given the enormous burden of post-transfusional iron overload complications. We systematically reviewed iron-chelation therapy (ICT) compliance, and the relationship between compliance with health outcome and health-related quality of life (HRQoL) in thalassaemia patients. Several reviewers performed systematic search strategy of literature through PubMed, Scopus, and EBSCOhost. The preferred reporting items of systematic reviews and meta-analyses (PRISMA) guidelines were followed. Of 4917 studies, 20 publications were included. The ICT compliance rate ranges from 20.93 to 75.3%. It also varied per agent, ranging from 48.84 to 85.1% for desferioxamine, 87.2-92.2% for deferiprone and 90-100% for deferasirox. Majority of studies (N = 10/11, 90.91%) demonstrated significantly negative correlation between compliance and serum ferritin, while numerous studies revealed poor ICT compliance linked with increased risk of liver disease (N = 4/7, 57.14%) and cardiac disease (N = 6/8, 75%), endocrinologic morbidity (N = 4/5, 90%), and lower HRQoL (N = 4/6, 66.67%). Inadequate compliance to ICT therapy is common. Higher compliance is correlated with lower serum ferritin, lower risk of complications, and higher HRQoL. These findings should be interpreted with caution given the few numbers of evidence.

A prediction model for assessing hypoglycemia risk in critically ill patients with sepsis

BACKGROUND

Few studies have reported the risk factors or developed a risk predictive model of hypoglycemia patients with sepsis.

OBJECTIVE

To develop a predictive model to assess the hypoglycemia risk in critically ill patients with sepsis.

METHODS

For this retrospective study, we collected the data from the Medical Information Mart for Intensive Care III and IV (MIMIC-III and MIMIC-IV). All eligible patients from the MIMIC-III were randomly divided into the training set for development of predictive model and testing set for internal validation of the predictive model at a ratio of 8:2. Patients from the MIMIC-IV database were used as the external validation set. The primary endpoint was the occurrence of hypoglycemia. Univariate and multivariate logistic model was used to screen predictors. Adopted receiver operating characteristics (ROC) and calibration curves to estimate the performance of the nomogram.

RESULTS

The median follow-up time was 5.13 (2.61-9.79) days. Diabetes, dyslipidemia, mean arterial pressure, anion gap, hematocrit, albumin, sequential organ failure assessment, vasopressors, mechanical ventilation and insulin were identified as the predictors for hypoglycemia risk in critically ill patients with sepsis. We constructed a nomogram for predicting hypoglycemia risk in critically ill patients with sepsis based on these predictors. An online individualized predictive tool: https://ghongyang.shinyapps.io/DynNomapp/. The established nomogram had a good predictive ability by ROC and calibration curves in the training set, testing set and external validation cohort.

CONCLUSION

A predictive model of hypoglycemia risk was constructed, with a good ability in predicting the risk of hypoglycemia in critically ill patients with sepsis.

Development and Validation of a Prognostic Model for Multi-Drug-Resistant Non-Hospital-Acquired Bloodstream Infection

Bloodstream infections (BSI) are an increasing cause of admissions to hospitals. Non-hospital-acquired BSI are defined by blood cultures that are positive less than 48 hours after admission, but a relevant difference exists between community-acquired and healthcare-associated (HCA) BSI in terms of risk of multidrug resistance (MDR). We planned a retrospective study in three different cohorts in order to develop and to temporally and spatially validate an easy and rapid prognostic model for identifying MDR non-hospital-acquired (non-HA) BSI. The pathogens most involved in BSI are Staphylococcus spp. and Escherichia coli, responsible for about 75% of all MDR isolated. The model includes age, gender, long-term care facility admission, immunocompromise, any recent invasive procedures and central line placement, recent intravenous treatment and antibiotic treatment. It shows an acceptable performance, especially for intermediate probabilities of MDR infection, with a C-index of 70%. The model was proposed in a nomogram that could allow better targeting of antibiotic therapy for non-HA BSI admitted in hospital. However, it should be further validated to determine its applicability in other populations.

Risk and protective factors for self-harm and suicide in children and adolescents: a systematic review and meta-analysis protocol

INTRODUCTION

Self-harm and suicide are major public health concerns among children and adolescents. Many risk and protective factors for suicide and self-harm have been identified and reported in the literature. However, the capacity of these identified risk and protective factors to guide assessment and management is limited due to their great number. This protocol describes an ongoing systematic review and meta-analysis which aims to examine longitudinal studies of risk factors for self-harm and suicide in children and adolescents, to provide a comparison of the strengths of association of the various risk factors for self-harm and suicide and to shed light on those that require further investigation.

METHODS AND ANALYSIS

We perform a systematic search of the literature using the databases EMBASE, PsycINFO, Medline, CINAHL and HMIC from inception up to 28 October 2020, and the search will be updated before the systematic review publication. Additionally, we will contact experts in the field, including principal investigators whose peer-reviewed publications are included in our systematic review as well as investigators from our extensive research network, and we will search the reference lists of relevant reviews to retrieve any articles that were not identified in our search. We will extract relevant data and present a narrative synthesis and combine the results in meta-analyses where there are sufficient data. We will assess the risk of bias for each study using the Newcastle-Ottawa Scale and present a summary of the quantity and the quality of the evidence for each risk or protective factor.

ETHICS AND DISSEMINATION

Ethical approval will not be sought as this is a systematic review of the literature. Results will be published in mental health journals and presented at conferences focused on suicide prevention.

PROSPERO REGISTRATION NUMBER

CRD42021228212.

A Review on Non-Enzymatic Electrochemical Biosensors of Glucose Using Carbon Nanofiber Nanocomposites

Diabetes mellitus has become a worldwide epidemic, and it is expected to become the seventh leading cause of death by 2030. In response to the increasing number of diabetes patients worldwide, glucose biosensors with high sensitivity and selectivity have been developed for rapid detection. The selectivity, high sensitivity, simplicity, and quick response of electrochemical biosensors have made them a popular choice in recent years. This review summarizes the recent developments in electrodes for non-enzymatic glucose detection using carbon nanofiber (CNF)-based nanocomposites. The electrochemical performance and limitations of enzymatic and non-enzymatic glucose biosensors are reviewed. Then, the recent developments in non-enzymatic glucose biosensors using CNF composites are discussed. The final section of the review provides a summary of the challenges and perspectives, for progress in non-enzymatic glucose biosensors.

The association of ESBL Escherichia coli with mortality in patients with Escherichia coli bacteremia at the emergency department

Background: Escherichia coli is a common bloodstream infection pathogen in the emergency department (ED). Patients with extended-spectrum beta-lactamase (ESBL) E. coli have a higher risk of morbidity. However, there is still debate surrounding ESBL E. coli-associated mortality in community, intensive care unit, and tertiary care settings. In addition, there have been few studies regarding mortality in ESBL E. coli in ED settings, and results have been contradictory. Methods: This was a retrospective cohort study conducted at the Department of Emergency Medicine, Faculty of Medicine, Khon Kaen University in Thailand aimed at evaluating the possible association between ESBL E. coli bacteremia and mortality in the ED. The inclusion criteria were age 18 years or over, clinical presentation suspicious of infection, and positive blood culture for E. coli. Predictors for mortality were analyzed by logistic regression analysis. Results: During the study period, 273 patients presented at the ED with hemoculture positive for E. coli. Of those, 27 (9.89%) died. Five factors remained in the final model, of which plasma glucose levels, serum lactate levels, and ESBL E. coliwere significantly associated with 28-day mortality in the ED with adjusted odds ratios of 0.970, 1.258, and 12.885, respectively. Plasma glucose of less than 113 mg/dL yielded a sensitivity of 80.95% and specificity of 64.29%, while serum lactate over 2.4 mmol/L had a sensitivity of 81.48% and specificity of 45.50%. Conclusion: ESBL E. coli, plasma glucose, and serum lactate levels were associated with 28-day mortality in patients with E. coli bacteremia presenting at the ED.

J-shaped associations and joint effects of fasting glucose with inflammation and cytokines on COVID-19 mortality

OBJECTIVES

The aim of this study was to investigate the dose-response relationship of admission fasting glucose (FBG) with corona virus disease 2019 (COVID-19) mortality and to further evaluate potential interactions of hyperglycemia with inflammation and hypercoagulation on COVID-19 outcomes.

METHODS

This retrospective study included 2555 consecutively hospitalized patients with COVID-19, until death or discharge, in Wuhan Union hospital between January 1 and April 9, 2020. The poor early outcomes included admission to intensive care unit, intubation, and deaths occurring within 28 days. We used splines nested in Cox regression to visualize dose-response associations and generalized additive models to fit three-dimensional (3D) trend plots for joint effects of FBG with markers of inflammation and coagulation.

RESULTS

J-shaped associations existed between hospitalized mortality or poor early outcomes and FBG with a nadir at 5 mmol/L, which were more evident in women. 3D plots demonstrated significant joint effect trends, and patients with hyperglycemia and high neutrophil-lymphocyte ratio, C-reactive protein, lactate dehydrogenase, procalcitonin, d-dimer, and interleukin-6 had 7.4-25.3-fold risks; the proportions of joint associations attributed to additive interactions reached 30% to 54%.

CONCLUSIONS

FBG was associated with hospitalized mortality and poor early outcomes in a J-shaped manner, and a combination of hyperglycemia, inflammation, hypercoagulation, and cytokines conferred a dramatically higher risk.

Acute glycemic variability and risk of mortality in patients with sepsis: a meta-analysis

BACKGROUND

Acute glycemic variability (GV) has been correlated with the severity of sepsis. The aim of the study was to evaluate the potential association between acute GV and mortality risk in patients with sepsis.

METHODS

Cohort studies comparing the risk of death within 3 months between septic patients with higher versus lower acute GV were retrieved by systematic search of Medline, Embase, Web of Science, Wanfang and CNKI databases. We used a random-effect model to pool the data by incorporating the between-study heterogeneity. Sensitivity analyses were performed to evaluate the stability of the findings.

RESULTS

Ten studies including 4296 patients were available for the meta-analysis. Pooled results showed that septic patients with higher acute GV had significantly increased mortality risk compared to those with lower acute GV, as evidenced by results using different parameters including standard deviation of blood glucose (SDBG, risk ratio [RR]: 1.74, 95% confidence interval [CI] 1.36-2.24, p < 0.001; I2 = 0%), coefficient of variation of blood glucose (RR: 1.91, 95% CI 1.57-2.31, p < 0.001; I2 = 0%), mean amplitude of glycemic excursion (RR: 1.81. 95% CI 1.36-2.40, p < 0.001; I2 = 0%), and glycemic lability index (RR: 2.52, 95% CI 1.72-3.68, p < 0.001; I2 = 0%). Sensitivity analyses by excluding one study at a time did not significantly affect the results (p all < 0.05).

CONCLUSIONS

Higher acute GV may be a predictor of mortality risk in patients with sepsis.

Let-7i-5p Mediates the Therapeutic Effects of Exosomes from Human Placenta Choriodecidual Membrane-Derived Mesenchymal Stem Cells on Mitigating Endotoxin-Induced Mortality and Liver Injury in High-Fat Diet-Induced Obese Mice

Obesity complicates sepsis and increases the mortality of sepsis. We examined the effects of exosomes (from human placenta choriodecidual membrane-derived mesenchymal stem cells, pcMSCs) on preventing sepsis in obesity and the mitigating role of hsa-let-7i-5p microRNA. Obese mice (adult male C57BL/6J mice fed a high-fat diet for 12 weeks) received normal saline (HFD), endotoxin (10 mg/kg, intraperitoneal (ip); HFDLPS), endotoxin with exosomes (1 × 10⁸ particles/mouse, ip; HLE), or endotoxin with let-7i-5p microRNA inhibitor-pretreated exosomes (1 × 10⁸ particles/mouse, ip; HLEi). Our data demonstrated that the 48-h survival rate in the HLE (100%) group was significantly higher than in the HFDLPS (50%) and HLEi (58.3%) groups (both p < 0.05). In the surviving mice, by contrast, levels of liver injury (injury score, plasma aspartate transaminase and alanine transaminase concentrations, tissue water content, and leukocyte infiltration in liver tissues; all p < 0.05), inflammation (nuclear factor-κB activation, hypoxia-inducible factor-1α activation, macrophage activation, and concentrations of tumor necrosis factor-α, interleukin-6, and leptin in liver tissues; all p < 0.05), and oxidation (malondialdehyde in liver tissues, with p < 0.001) in the HLE group were significantly lower than in the HFDLPS group. Levels of mitochondrial injury/dysfunction and apoptosis in liver tissues in the HLE group were also significantly lower than in the HFDLPS group (all p < 0.05). Inhibition of let-7i-5p microRNA offset the effects of the exosomes, with most of the aforementioned measurements in the HLEi group being significantly higher than in the HLE group (all p < 0.05). In conclusion, exosomes mitigated endotoxin-induced mortality and liver injury in obese mice, and these effects were mediated by let-7i-5p microRNA.