Examining the association between serum lactic dehydrogenase and all-cause mortality in patients with metabolic syndrome: a retrospective observational study

Selenium Mitigates Caerulein and LPS-induced Severe Acute Pancreatitis by Inhibiting MAPK, NF-κB, and STAT3 Signaling via the Nrf2/HO-1 Pathway

Severe acute pancreatitis (SAP) leads to systemic inflammation, resulting in multiorgan damage. Acute lung injury and acute respiratory distress syndrome develop in one-third of SAP patients, with a high mortality rate of 60% due to secondary complications. Patients with pancreatitis often have selenium deficiency, and selenium supplements may provide beneficial effects. This study examined the protective role of selenium in a model of SAP induced by caerulein + lipopolysaccharide (cae + LPS). Mice were administered selenium (1 mg/kg) before being challenged with caerulein (6 injections of 50 μg/kg) and LPS (10 mg/kg). At 3 h after the last caerulein injection, blood was collected for estimating pancreatic enzymes and cytokine levels, and the mice were euthanized. We performed morphological and histological studies, measured levels of protease and oxidative stress markers and conducted western blot, ELISA, and RT-qPCR analyses. We examined lung tissue histologically and estimated myeloperoxidase levels. Selenium pretreatment significantly reduced pancreatic enzyme levels such as amylase, lipase, and proteases (specifically MMPs) and reversed tissue injury in the pancreas and lungs caused by cae + LPS. In addition, selenium-treated mice showed decreased levels of inflammatory markers and chemokines. Examination of the downstream inflammatory pathways confirmed the protective effect of selenium, which mediates its anti-inflammatory and antioxidant action by inhibiting the major inflammatory signaling pathways (MAPKs, NF-κB, and STAT3) and activating the phosphorylation of Nrf2 via Nrf2/HO-1 pathways. These findings suggest that selenium may be a potential therapeutic option for treating SAP-associated secondary complications.

Development and validation of a predictive model for metabolic syndrome in a large cohort of people living with HIV

BACKGROUND

The global prevalence of metabolic syndrome (MetS) in people living with HIV (PLWH) is on the rise in the post era of antiretroviral therapy (ART). Nevertheless, there are no validated predictive models available for assessing the risk of MetS in this specific population.

METHODS

This study included PLWH who participated in annual follow-ups at Southern Medical University Nanfang Hospital from September 2022 to November 2023. Participants enrolled in this study were divided into the training set and validation set based on the follow-up duration. We employed both multivariate logistic regression and lasso regression to develop three distinct prediction models. Subsequently, the optimal model was determined through comprehensive analyses, including receiver operating characteristic (ROC) curve analysis, calibration curve, and decision curve analysis (DCA). Ultimately, we generated a nomogram for the optimal model and analyzed the correlation between the model score and the components of MetS.

RESULTS

A total of 1017 participants were included in this study, with 814 in the training set and 203 in the validation set. The ultimate prediction model of MetS risk in PLWH incorporated five factors: age, CD8 + T cell counts, controlled attenuation parameter (CAP), gamma-glutamyl transferase (γ-GT) and lactate dehydrogenase (LDH). The area under the ROC curve (AUC) of the model in the training set and validation set was 0.849 and 0.834, respectively. Furthermore, we revealed a significant correlation between the model score and the MetS components. Additionally, the model score revealed significant group differences in MetS and related metabolic disorders.

CONCLUSIONS

This study established a potential model for predicting MetS in PLWH.

EASIX (endothelial activation and stress index) predicts mortality in patients with coronary artery disease

BACKGROUND

Coronary interventions reduce morbidity and mortality in patients with acute coronary syndrome. However, the risk of mortality for patients with coronary artery disease (CAD) additionally depends on their systemic endothelial health status. The 'Endothelial Activation and Stress Index' (EASIX) predicts endothelial complications and survival in diverse clinical settings.

OBJECTIVE

We hypothesized that EASIX may predict mortality in patients with CAD.

METHODS

In 1283 patients undergoing coronary catheterization (CC) and having a diagnosis of CAD, EASIX was measured within 52 days (range - 1 year to - 14 days) before CC and correlated with overall survival. In an independent validation cohort of 1934 patients, EASIXval was measured within 174 days (+ 28 days to + 11 years) after CC.

RESULTS

EASIX predicted the risk of mortality after CC (per log2: hazard ratio (HR) 1.29, 95% confidence interval: [1.18-1.41], p < 0.001) in multivariable Cox regression analyses adjusting for age, sex, a high-grade coronary stenosis ≥ 90%, left ventricular ejection fraction, arterial hypertension and diabetes. In the independent cohort, EASIX correlated with EASIXval with rho = 0.7. The long-term predictive value of EASIXval was confirmed (per log2: HR 1.53, [1.42-1.64], p < 0.001) and could be validated by integrated Brier score and concordance index. Pre-established cut-offs (0.88-2.32) associated with increased mortality (cut-off 0.88: HR training: 1.63; HR validation: 1.67, p < 0.0001 and cut-off 2.32: HR training: 3.57; HR validation: 4.65, p < 0.0001).

CONCLUSIONS

We validated EASIX as a potential biomarker to predict death of CAD patients, irrespective of the timing either before or after catheterization.

Role of Lactate Dehydrogenase as a Biomarker of Early Cardiac Remodeling: A Cross-Sectional Study

BACKGROUND

Lactate dehydrogenase (LDH) isoenzyme assay was used widely in the past to diagnose myocardial infarction (MI). Recent studies show that lactate dehydrogenase seems to be a promising biomarker of adverse left ventricular remodeling.

OBJECTIVES

Higher levels of these biomarkers were associated with lower odds for favorable reverse remodeling in patients with MI.

METHODS

The study was performed on patients with the first occurrence of acute myocardial infarction (ST-elevation myocardial infarction (STEMI) or non-ST-elevation myocardial infarction (NSTEMI)), aged 34 to 80 years who underwent catheterization at the admission or during their hospital stay depending on indications. In this study, we compared peak levels of lactate dehydrogenase (LDH) and left ventricular ejection fraction (LVEF). Peak values of LDH were used from the second to the fourth day of hospitalization. Echocardiography has been done in the first 72 hours, which represents an early phase of cardiac remodeling. The ejection fraction was evaluated using the Simpson method.

RESULTS

Spearman's rank test showed a negative, statistically significant correlation between LDH and ejection fraction ρ(80)=-0.543, p<0.001. Weighted least squares regression model included LDH concentration, age, and type of myocardial infarction (STEMI/NSTEMI), and the slope coefficient for the LDH level was -0.010 (95% confidence interval (CI): -0.013 to -0.006). With each unit of LDH increase, there was a decrease of 0.01% in left ventricular ejection fraction when age and type of myocardial infarction were held constant.

CONCLUSION

The increased LDH level could be a new predictor for early myocardial remodeling after the first occurrence of myocardial infarction independent of age and type of myocardial infarction.

High serum lactate dehydrogenase as a predictor of cardiac insufficiency at follow-up in elderly patients with acute myocardial infarction

BACKGROUND

Impairment of cardiac function progresses after acute myocardial infarction (AMI). Lactate dehydrogenase (LDH), a marker of cardiac injury and an enzyme in anaerobic glycolysis, is suggested as a risk factor for patient mortality in inflammatory diseases.

METHODS

In this study, 448 older and 445 younger AMI patients were recruited and followed up. The effect of baseline serum LDH on post-infarction cardiac function was assessed at follow-up.

RESULTS

Elderly patients in the high baseline LDH group had a high risk of being diagnosed with cardiac insufficiency during follow-up (adjusted hazard ratio: 3.643, P = 0.007), and the follow-up left ventricular ejection fraction of the quartile subgroup tended to decrease with increasing in baseline serum LDH (adjusted odds ratio: 1.301, P = 0.001) for each 100 U/L increase. The LVDd and LVVd of elderly patients in the high LDH group were not significantly different from those of patients in the normal LDH group at baseline but were further increased in the high LDH group at follow-up. In younger patients, the effect of LDH on post-infarction cardiac structure and function was similar to that in older patients, but unlike older patients, Cox regression analysis showed that LDH was not the predominant influence.

CONCLUSION

Longitudinal changes in cardiac function were independently associated with high baseline serum LDH levels in patients with AMI. Baseline LDH levels are superior to other myocardial injury markers and may be a useful parameter in predicting future cardiac dysfunction after AMI, especially in the elderly.

Using Machine Learning to Identify the Relationships between Demographic, Biochemical, and Lifestyle Parameters and Plasma Vitamin D Concentration in Healthy Premenopausal Chinese Women

INTRODUCTION

Vitamin D plays a vital role in maintaining homeostasis and enhancing the absorption of calcium, an essential component for strengthening bones and preventing osteoporosis. There are many factors known to relate to plasma vitamin D concentration (PVDC). However, most of these studies were performed with traditional statistical methods. Nowadays, machine learning methods (Mach-L) have become new tools in medical research. In the present study, we used four Mach-L methods to explore the relationships between PVDC and demographic, biochemical, and lifestyle factors in a group of healthy premenopausal Chinese women. Our goals were as follows: (1) to evaluate and compare the predictive accuracy of Mach-L and MLR, and (2) to establish a hierarchy of the significance of the aforementioned factors related to PVDC.

METHODS

Five hundred ninety-three healthy Chinese women were enrolled. In total, there were 35 variables recorded, including demographic, biochemical, and lifestyle information. The dependent variable was 25-OH vitamin D (PVDC), and all other variables were the independent variables. Multiple linear regression (MLR) was regarded as the benchmark for comparison. Four Mach-L methods were applied (random forest (RF), stochastic gradient boosting (SGB), extreme gradient boosting (XGBoost), and elastic net). Each method would produce several estimation errors. The smaller these errors were, the better the model was.

RESULTS

Pearson's correlation, age, glycated hemoglobin, HDL-cholesterol, LDL-cholesterol, and hemoglobin were positively correlated to PVDC, whereas eGFR was negatively correlated to PVDC. The Mach-L methods yielded smaller estimation errors for all five parameters, which indicated that they were better methods than the MLR model. After averaging the importance percentage from the four Mach-L methods, a rank of importance could be obtained. Age was the most important factor, followed by plasma insulin level, TSH, spouse status, LDH, and ALP.

CONCLUSIONS

In a healthy Chinese premenopausal cohort using four different Mach-L methods, age was found to be the most important factor related to PVDC, followed by plasma insulin level, TSH, spouse status, LDH, and ALP.

Associations of Nutritional, Environmental, and Metabolic Biomarkers with Diabetes-Related Mortality in U.S. Adults: The Third National Health and Nutrition Examination Surveys between 1988-1994 and 2016

Background: Nutritional, environmental, and metabolic status may play a role in affecting the progression and prognosis of type 2 diabetes. However, results in identifying prognostic biomarkers among diabetic patients have been inconsistent and inconclusive. We aimed to evaluate the associations of nutritional, environmental, and metabolic status with disease progression and prognosis among diabetic patients. Methods: In a nationally representative sample in the NHANES III (The Third National Health and Nutrition Examination Survey, 1988−1994), we analyzed available data on 44 biomarkers among 2113 diabetic patients aged 20 to 90 years (mean age: 58.2 years) with mortality data followed up through 2016. A panel of 44 biomarkers from blood and urine specimens available from NHANES III were included in this study and the main outcomes as well as the measures are mortalities from all-causes. We performed weighted logistic regression analyses after controlling potential confounders. To assess incremental prognostic values of promising biomarkers beyond traditional risk factors, we compared c-statistics of the adjusted models with and without biomarkers, separately. Results: In total, 1387 (65.2%) deaths were documented between 1988 and 2016. We observed an increased risk of all-cause mortality associated with higher levels of serum C-reactive protein (p for trend = 0.0004), thyroid stimulating hormone (p for trend = 0.04), lactate dehydrogenase (p for trend = 0.02), gamma glutamyl transferase (p for trend = 0.02), and plasma fibrinogen (p for trend = 0.03), and urine albumin (p for trend < 0.0001). In contrast, higher levels of serum sodium (p for trend = 0.005), alpha carotene (p for trend = 0.006), and albumin (p for trend = 0.005) were associated with a decreased risk of all-cause mortality. In addition, these significant associations were not modified by age, sex, or race. Inclusion of thyroid stimulating hormone (p = 0.03), fibrinogen (p = 0.01), and urine albumin (p < 0.0001), separately, modestly improved the discriminatory ability for predicting all-cause mortality among diabetic patients. Conclusions: Our nationwide study findings provide strong evidence that some nutritional, environmental, and metabolic biomarkers were significant predictors of all-cause mortality among diabetic patients and may have potential clinical value for improving stratification of mortality risk.

Serum LDH values in hypertensive disorders of pregnancy and their association with maternal and neonatal morbidity: A meta-analysis

BACKGROUND

Serum lactate dehydrogenase has been extensively studied in hypertensive disorders of pregnancy. However, to date, its clinical usefulness in the field remains unknown. The present meta-analysis has been designed to evaluate differences in serum LDH values among patients with hypertensive disorders of pregnancy and to help determine its diagnostic accuracy as well its predictive accuracy in determining adverse pregnancy outcomes.

METHODS

We searched Medline, Scopus, Clinicaltrials.gov, EMBASE, Cochrane Central Register of Controlled Trials CENTRAL and Google Scholar databases from their inception till 18 March 2021. Observational studies that assessed differences in serum LDH levels among women with hypertensive disorders of pregnancy and healthy controls were included. Meta-analysis was performed using Rstudio. Pooled mean differences (MD) were calculated with the Hartung-Knapp-Sidik-Jonkman. Meta-regression analyses, publication bias assessment and Trim and Fill function were also performed. The adequacy of the sample size was evaluated with Trial Sequential Analysis.

RESULTS

Fifty-two articles were included that comprised 5340 women with hypertensive disorders of pregnancy and 2890 healthy controls. The meta-analysis revealed significant differences among patients with preeclampsia (either mild or severe) compared with controls, as well as among patients with mild and severe preeclampsia. Significant asymmetry was noted after examining funnel plots, however, and the trim and fill analysis revealed that differences were significant only among cases with severe preeclampsia and healthy controls. Morbidity outcomes increased with LDH levels >600 IU/L and particularly when these exceeded 800 IU/L. However, confidence and prediction intervals indicated an underpowered sample size for the accurate determination of the odds of developing maternal morbidity.

CONCLUSION

Despite the extensive research in the field of hypertensive disorders of pregnancy, there is still lack of evidence concerning the diagnostic performance of serum LDH in clinical practice; hence, research should expand in this direction to evaluate its clinical utility.

Composition-Activity Relationships of Polysaccharides from Saccharina japonica in Regulating Gut Microbiota in Short-Term High-Fat Diet-Fed Mice

Saccharina japonica polysaccharide could modulate gut microbiota composition; however, the composition-activity relationship remains unclear, thus restricting its application. In the current study, we investigated the impact of eight different S. japonica polysaccharide fractions on the gut microbiota after day 2 and day 14 treatments on high-fat diet (HFD) feeding mice. The results showed that a 2 day HFD dramatically altered gut microbiota composition, and the additional 12 day HFD further strengthened the gut microbiota dysbiosis in the HFD group. LjA-1 and LjA-3 could partially alleviate the dysbiosis of gut microbiota composition and significantly alter gut microbiota function. Multiple linear regression analysis revealed that the sulfate content and the molecular weight distributions were the main factors affecting the dominant gut bacterial genera. Our findings reveal that gut microbiota homeostasis could be disordered by HFD at day 2 and provide insights into the quantitative composition-activity relationships of polysaccharides in regulating gut microbiota.

Association between serum lactate dehydrogenase and frailty among individuals with metabolic syndrome

While metabolic syndrome (MetS) is associated with frailty, the correlation of serum lactate dehydrogenase (sLDH) and frailty with MetS remain uncertain. To investigate the relationship between sLDH and frail components in the US with MetS. A total of 4,066 participants aged 40-90 years were assessed from the database of the third National Health and Nutrition Examination Survey, 1988-1994. The participants were classified into MetS and non-MetS groups. Multivariate logistic regression analysis with four models were performed to assess the odds ratio (OR) of the divided tertiles of sLDH levels with frailty, and frail components including slow walking (SW), weakness, exhaustion, low physical activity (LPA), and low body weight (LBW). Higher sLDH levels were positively associated with frailty in the MetS group (p = 0.024) but not in non-MetS group (p = 0.102). After covariate adjustments, the OR of frailty in the upper two tertiles compared to the lowest tertile and revealed statistical significance (p < 0.05). Frail components of SW, weakness, exhaustion, and LPA were associated with higher sLDH (p < 0.05) except for LBW in MetS and non-MetS groups. The results demonstrated the strong association of higher sLDH levels and frailty among US individuals with MetS.

The relationship between serum lactate dehydrogenase level and mortality in critically ill patients

Background: To assess the association between serum lactate dehydrogenase (LDH) levels and mortality in intensive care unit patients. Materials & methods: A total of 1981 patients in the eICU Collaborative Research Database were divided into four groups according to quartiles of LDH levels. Logistic regressions were performed. Results: Elevated LDH levels were significantly associated with higher mortality (intensive care unit mortality: Q2 vs Q1: 1.046 [0.622-1.758]; Q3 vs Q1: 1.667 [1.029-2.699]; and Q4 vs Q1: 1.760 [1.092-2.839]). Similar results persisted in patients with different acute physiology and chronic health evaluation IV scores, and with or without sepsis. Conclusion: The serum LDH level may aid in the early identification of mortality risk in critically ill patients.

A decision support system for the prediction of mortality in patients with acute kidney injury admitted in intensive care unit

Intensive care unit (ICU) is a very special unit of a hospital, where healthcare professionals provide treatment and, later, close follow-up to the patients. It is crucial to estimate mortality in ICU patients from many viewpoints. The purpose of this study is to classify the status of patients with acute kidney injury (AKI) in ICU as early mortality, late mortality, and survival by the application of Classification and Regression Trees (CART) algorithm to the patients' attributes such as blood urea nitrogen, creatinine, serum and urine neutrophil gelatinase-associated lipocalin (NGAL), alkaline phosphatase, lactate dehydrogenase (LDH), gamma-glutamyl transferase, laboratory electrolytes, blood gas, mean arterial pressure, central venous pressure and demographic details of patients. This study was conducted 50 patients with AKI who were followed up in the ICU. The study also aims to determine the significance of relationship between the attributes used in the prediction of mortality in CART and patients' status by employing the Kruskal-Wallis H test. The classification accuracy, sensitivity, and specificity of CART for the tested attributes for the prediction of early mortality, late mortality, and survival of patients were 90.00%, 83.33%, and 91.67%, respectively. The values of both urine NGAL and LDH on day 7 showed a considerable difference according to the patients' status after being examined by the Kruskal-Wallis H test.

Systemic inflammation in patients of chronic obstructive pulmonary disease with metabolic syndrome

Context:

India has 18% of the global population and an increasing burden of chronic respiratory diseases. The prevalence of Metabolic syndrome (MS) was found to be as high as 39.7% among Indian population. Metabolic syndrome is found to be more common in Chronic Obstructive Pulmonary Disease (COPD) when compared to the general population. This study was done to assess the prevalence of metabolic syndrome in COPD and the association of systemic inflammation in COPD patients with metabolic syndrome.

Methodology:

This study enrolled 150 consecutive consenting patients of stable COPD attending the outpatient pulmonology department. Detailed history, clinical examination, spirometry, and relevant routine laboratory investigations including complete blood count, fasting blood sugar, and lipid profile were done. In addition, hsCRP, Serum lactate and Vitamin D level was assessed in all patients. Diagnosis of COPD and Metabolic syndrome was done according to GOLD guidelines, 2018 and the International Diabetes Federation criteria respectively.

Result:

The prevalence of metabolic syndrome was found to be 27.3% in our COPD patients. The frequency of metabolic syndrome in GOLD stage I, II, III, and IV was 75%, 32%, 17%, and 13.5%, respectively. Logistic regression analysis showed a significant relationship of blood leucocyte count (OR = 0.342, CI = 0.171-0.686), hs-CRP (OR = 0.020, CI = 0.003-0.122), pack years (OR = 1.083, CI = 1.026-1.14) and vitamin D levels (OR = 1.219, CI = 1.093-1.359) with metabolic syndrome in COPD patients.

Conclusion:

Metabolic syndrome is a co-morbidity that is very often overlooked in patients of COPD. Systemic inflammation which is a common characteristic of both COPD and Metabolic syndrome has been found to be an important contributor towards cardiovascular morbidity and mortality.

Preoperative serum lactate dehydrogenase level as a predictor of major complications following thoracoscopic lobectomy: a propensity-adjusted analysis

OBJECTIVES

Despite the positive effects of a thoracoscopic approach on improving postoperative outcomes, the risk of major complications following thoracoscopic lobectomy is not negligible. We sought to assess the usefulness of the preoperative determination of serum biomarkers to refine risk stratification in this patient population.

METHODS

From 2009 to 2017, 626 patients (285 women, 341 men; median age: 67 years) underwent thoracoscopic lobectomy or anatomical segmentectomy for confirmed or suspected early-stage lung cancer or metastasis at our institution. Preoperative serum biomarkers, including albumin, C-reactive protein, haemoglobin and lactate dehydrogenase (LDH), were examined as predictors of postoperative cardiopulmonary complications using logistic regression analyses followed by causal inference.

RESULTS

The 90-day mortality, cardiopulmonary complication and overall morbidity rates were 1.0%, 13.1% and 18.1%, respectively. Although serum albumin, C-reactive protein and haemoglobin were not associated with cardiopulmonary complications in regression analyses, preoperative serum LDH level emerged as an independent morbidity predictor (odds ratio 1.008, 95% confidence interval 1.002-1.013; P = 0.006). The causal inference using the covariate balancing generalized propensity score methodology demonstrated similar results and an approximately positive linear relationship between the odds of cardiopulmonary complications and preoperative serum LDH level. For every 100 U/l increase in preoperative serum LDH, a 2-fold increase in the odds of cardiopulmonary complications was observed.

CONCLUSIONS

Our results suggest that the preoperative serum LDH level is an independent predictor of 90-day cardiopulmonary complications following thoracoscopic lobectomy or segmentectomy, even in properly selected patients. Therefore, we recommend incorporating early serum LDH measurements as a readily available method into the risk assessment process prior to major lung resection.