Serum lactate dehydrogenase level is associated with in-hospital mortality in critically Ill patients with acute kidney injury

Association between pre-ICU statin use and acute kidney injury and in hospital mortality in obese patients with sepsis

BACKGROUND

Acute kidney injury (AKI), a common complication in sepsis, especially for obese patients, is linked to increased morbidity and mortality. Statins, known for their lipid-lowering effects, also exhibit anti-inflammatory and immunomodulatory properties, suggesting potential benefits in sepsis and AKI.

MATERIALS AND METHODS

This retrospective cohort study leveraged data from the MIMIC-IV database. The study population was stratified into survivors and non-survivors based on in-hospital mortality. Demographic data, comorbidities, laboratory parameters, and treatment modalities were extracted. Multivariate logistic regression models were conducted to evaluate the relationship between statin use and outcomes, with adjustments for confounders. Subgroup analyses and propensity score-matching (PSM) were undertaken for further validation.

RESULTS

In this study of 8,921 sepsis patients, pre-ICU statin use was associated with significantly improved outcomes. Univariate analysis showed that statin use reduced the risk of AKI by 69% (OR = 0.31, 95% CI 0.27-0.44, p < 0.001) and decreased in-hospital mortality by 57% (OR = 0.43, 95% CI 0.22-0.54, p < 0.001). Multivariate regression confirmed the robustness of these findings, with fully adjusted models demonstrating a 31% reduction in AKI (OR = 0.67, p < 0.001) and a 22% reduction in mortality (OR = 0.67, p < 0.001). Subgroup and propensity score-matched analyses further supported these associations, showing consistent protective effects across patient subgroups and a reduction in both AKI and mortality.

CONCLUSION

Pre-ICU statin therapy is associated with a lower risk of AKI and improved in-hospital survival among obese patients with sepsis, suggesting its potential role as a protective measure in this high-risk population.

Association between lactate dehydrogenase to albumin ratio and ICU mortality in patients with acute kidney injury: a retrospective cohort study

Background

Acute kidney injury (AKI) is a prevalent and severe medical condition that is frequently observed in the intensive care unit (ICU). Although numerous biomarkers have been identified to predict the prognosis of AKI, the lactate dehydrogenase to albumin ratio [LDH/ALB ratio (LAR)] has not been extensively investigated. The principal objective of this study was to assess the relationship between LAR and all-cause mortality in patients with AKI.

Methods

A total of 6,831 AKI patients were included in this study, divided into survival (n = 5,152) and non-survival groups (n = 1,679). The association between LAR and mortality was examined through restricted cubic spline (RCS) analysis and Cox regression analysis. Subgroup analysis was used to search for interactive factors. Additionally, the prognostic capability of LAR was further evaluated using receiver operating characteristic (ROC) curve analysis.

Results

The LAR was remarkably higher in the non-survival group (p < 0.001). RCS indicated a non-linear correlation between LAR and ICU death (p for non-linearity < 0.001). A LAR of 10.4 was used as the cutoff point to generate the high-LAR and low-LAR subgroups, and the Kaplan-Meier curves revealed that the ICU cumulative survival rate for patients with AKI was significantly lower in the high-LAR group (log-rank p < 0.001). The LAR's prediction of ICU mortality in AKI patients yielded an area under the ROC curve of 0.65.

Conclusion

Our research suggests that LAR monitoring may be promising as a prognostic marker among patients with AKI. Higher LAR is associated with greater ICU mortality.

Prognostic factors influencing survival in nonagenarian patients admitted to the emergency department: a retrospective study

OBJECTIVE

The number of nonagenarians presenting to emergency departments (EDs) worldwide is rapidly increasing. These demographic faces unique challenges, including atypical clinical presentations, frailty, and a high burden of comorbidities. Despite their vulnerability, limited data exist on factors influencing survival in this group. This study aimed to identify prognostic factors affecting survival among nonagenarian patients admitted to the ED, focusing on clinical, biochemical, and treatment variables.

METHODS

A retrospective review was conducted, analyzing data on demographics, comorbidities, medication use, laboratory values, and hospital stay length for nonagenarian patients admitted to the ED at Göztepe Prof. Dr. Süleyman Yalçın City Hospital from 2020 to 2023. Survival analysis utilized Kaplan-Meier and Cox regression methods, with statistical significance set at p < 0.05.

RESULTS

Among 316 patients (mean age 91.61 ± 1.76 years; 72.2% female), the mortality rate was 17.7%. The most frequent comorbidities were hypertension (76.8%) and heart failure (35.9%). Cardiac failure and treatment with beta-blockers were strong independent predictors of poor survival. Biochemical markers linked to increased mortality included low albumin (HR 0.353, p < 0.001), low total protein (HR 0.933, p = 0.004), elevated CRP/albumin ratio (HR 1.016, p = 0.001), and high neutrophil/albumin ratio (HR 1.002, p = 0.014).

CONCLUSIONS

Nonagenarians admitted to the ED exhibit high comorbidity prevalence and mortality rates. Inflammation and malnutrition biomarkers, particularly the CRP/albumin ratio and total protein, are significant prognostic factors. Tailored management strategies focusing on these parameters could improve outcomes for this high-risk group. Further multicenter studies are needed to validate these findings and develop evidence-based care protocols.

Lactate dehydrogenase to albumin ratio and prognosis in patients with acute exacerbation of chronic obstructive pulmonary disease: a retrospective cohort study

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a global public health challenge and a major cause of death. The lactate dehydrogenase to albumin ratio (LAR) is a simple and practical indicator of disease prognosis, but its prognostic value in acute exacerbation of COPD (AECOPD) remains unclear. Therefore, we aimed to explore the prognostic value of LAR for the short-term all-cause mortality risk in patients with AECOPD.

METHODS

This retrospective cohort study included 654 patients with AECOPD from the MIMIC-IV database. LAR was analyzed after natural logarithm transformation and the patients were divided into three groups. The clinical outcome was the 1-month and 3-months all-cause mortality. The relationship between LAR and all-cause mortality was assessed using Kaplan-Meier survival analysis and a Cox regression model. Generalized additive models were employed to identify non-linear relationships, and a subgroup analysis was performed to determine the stability of the results.

RESULTS

The study showed that LAR levels significantly and positively correlated with short-term all-cause mortality in patients with AECOPD. Compared to the low LAR group, patients in the medium LAR group had a significantly increased 1-month all-cause mortality risk, with a hazard ratio (HR) of 1.74 (95% [Confidence Interval, CI] 1.16-2.63, P = 0.008). Patients in the high LAR group had an even higher 1-month all-cause mortality risk, with an HR of 2.58 (95% CI 1.75-3.80, P < 0.001). For 3-month all-cause mortality, patients in the medium LAR group had an HR of 1.54 (95% CI 1.10-2.16, P = 0.012), while those in the high LAR group had an HR of 2.18 (95% CI 1.58-3.01, P < 0.001). The results remained stable in all three adjusted models and in the subgroup analyses. The relationship between LAR and all-cause mortality due to AECOPD was non-linear, with inflection points at 8.13 and 6.05 for 1-month and 3-month all-cause mortality, respectively.

CONCLUSIONS

Elevated LAR is an independent predictive indicator of short-term all-cause mortality risk in patients with AECOPD and can be used to improve decision-making for the clinical management of these patients.

CLINICAL TRIAL NUMBER

Not applicable.

Dietary Inflammatory index and its association with fatty liver disease: a study in obese and non-obese populations

BACKGROUND

The worldwide incidence of non-alcoholic fatty liver disease (NAFLD) is a pressing health issue, with chronic inflammation critically influencing its development. The Dietary Inflammatory Index (DII) measures the inflammatory potential of one's diet. Our study aimed to investigate the association between DII and fatty liver disease in obese and non-obese individuals.

METHODS

Data from the 1999--2001 National Health and Nutrition Examination Survey (NHANES), encompassing 3456 adults aged 20 years and above, were utilized for the analysis. The multivariable analysis assessed the correlation between DII, NAFLD, and obesity while adjusting for demographic variables. The restricted cubic spline (RCS) method was also applied with restricted degrees of freedom to establish a non-linear relationship model between DII and NAFLD.

RESULTS

Our study demonstrated significant differences across DII tertiles in various demographic and clinical characteristics. An increase in t DII score by one standard deviation resulted in a 21% increase in the fatty liver risk. This association persisted after adjusting for age, sex, and other covariates. The risk of fatty liver disease increased significantly by 39% in the highest DII tertile. Regression analysis revealed a non-linear correlation between DII and the risk of fatty liver in obese adults. The subgroup analysis showed consistent findings across all subgroups, with particularly strong associations in specific demographic categories.

CONCLUSIONS

Our findings suggest a significant association between the DII score and risk of fatty liver disease, particularly in obese individuals. These results underscore the potential role of diet-induced inflammation in pathogenesis of NAFLD.

Macrophage-Specific Lactate Dehydrogenase Expression Modulates Inflammatory Function In Vitro

Key Points

Lactate dehydrogenase A deletion alters macrophage function. Lactate dehydrogenase A could serve as a potential therapeutic target in AKI.

Background

In AKI, macrophages play a major role in regulating inflammation. Classically activated macrophages (M1) undergo drastic metabolic reprogramming during their differentiation and upregulate the aerobic glycolysis pathway to fulfill their proinflammatory functions. NAD+ regeneration is crucial for the maintenance of glycolysis, and the most direct pathway by which this occurs is through the fermentation of pyruvate to lactate, catalyzed by lactate dehydrogenase A (LDHA). Our previous study determined that LDHA is predominantly expressed in the proximal segments of the nephron in the mouse kidney and increases with hypoxia. This study investigates the potential of LDHA as a therapeutic target for inflammation by exploring its role in macrophage function in vitro .

Methods

Bone marrow–derived macrophages (BMDMs) were isolated from myeloid-specific LDHA knockout mice derived from crossbreeding LysM-Cre transgenic mice and LDHA floxed mice. RNA sequencing and LC-MS/MS metabolomics analyses were used in this study to determine the effect of LDHA deletion on BMDMs after stimulation with IFN-γ .

Results

LDHA deletion in IFN-γ BMDMs resulted in a significant alteration of the macrophage activation and functional pathways and change in glycolytic, cytokine, and chemokine gene expression. Metabolite concentrations associated with proinflammatory macrophage profiles were diminished, whereas anti-inflammatory–associated ones were increased in LDHA knockout BMDMs. Glutamate and amino sugar metabolic pathways were significantly affected by the LDHA deletion. A combined multiomics analysis highlighted changes in Rap1 signaling, cytokine–cytokine receptor interaction, focal adhesion, and mitogen-activated protein kinase signaling metabolism pathways.

Conclusions

Deletion of LDHA in macrophages results in a notable reduction in the proinflammatory profile and concurrent upregulation of anti-inflammatory pathways. These findings suggest that LDHA could serve as a promising therapeutic target for inflammation, a key contributor to the pathogenesis of AKI.

Association between lactate dehydrogenase levels and all-cause mortality in ICU patients with heart failure: a retrospective analysis of the MIMIC-IV database

BACKGROUND

Heart failure (HF) patients admitted to the intensive care unit (ICU) often face high short-term mortality rates. This study aims to investigate the relationship between lactate dehydrogenase (LDH) levels and all-cause mortality in critically ill patients with HF.

METHODS

Data from the MIMIC-IV database were extracted for subjects eligible for HF diagnosis. We utilized the restricted cubic spline (RCS) method, Kaplan-Meier (K-M) survival curves, and Cox regression analysis to assess the association between lactate dehydrogenase (LDH) levels and all-cause mortality in HF patients. Overlap weighting (OW) and subgroup analysis were employed to enhance the robustness and reliability of the study.

RESULTS

A total of 3,065 subjects were enrolled in this study. RCS analysis revealed a nonlinear relationship between LDH levels and the risk of all-cause mortality in critically ill patients with HF, with a hazard ratio (HR) > 1 when LDH exceeded 315 U/L. The K-M survival curve indicated lower survival rates and shorter survival times in subjects with LDH ≥ 315 U/L. Elevated LDH levels were independently associated with increased in-hospital and 1-year mortality rates, with adjusted HR of 1.39 (95% CI: 1.16, 1.67) and 1.29 (95% CI: 1.14, 1.45), respectively. The results remained consistently robust in the OW analyses.

CONCLUSIONS

Elevated LDH levels were significantly associated with an increased risk of all-cause mortality in ICU-admitted HF patients. Further randomized trials are needed to confirm this association.

The predictive value of the serum creatinine-to-albumin ratio (sCAR) and lactate dehydrogenase-to-albumin ratio (LAR) in sepsis-related persistent severe acute kidney injury

BACKGROUND/OBJECTIVES

Sepsis-related acute kidney injury (SA-AKI) is a severe condition characterized by high mortality rates. The utility of the sCAR (secrum creatinine/albumin) and LAR (Lactate dehydrogenase/albumin) as diagnostic markers for persistent severe SA-AKI remains unclear.

METHODS

We acquired training set data from the MIMIC-IV database and validation set data from the First Affiliated Hospital of Harbin Medical University. Logistic regression analysis was used to identify key predictors of persistent severe SA-AKI, considering factors such as sCAR, LAR, PAR (Platelet/albumin), BAR (BUN/albumin), and LAO (Lactic/albumin). Independent predictors, sCAR and LAR, were combined into a composite Log(sCAR)_Log(LAR) score, denoted as the Log(sCAR)_Log(LAR) score. Possible confounding factors were screened out by univariate logistic regression, and multivariable logistic regression was applied to evaluate the association of Log (sCAR) _Log (LAR) score with persistent severe sepsis and other secondary clinical outcomes. The ROC curve was utilized to obtain the best cutoff value of the Log(sCAR)_Log(LAR) score. The Kaplan-Meier curve was used to evaluate the prognosis predictive ability of the risk model.

RESULTS

Logistic regression analysis indicated that sCAR and LAR independently predicted persistent severe SA-AKI. This led to the creation of Log(sCAR)_Log(LAR) score on the base of logarithms of sCAR and LAR. ROC curve analysis showed that the Log(sCAR)_Log(LAR) score was more effective in predicting persistent severe SA-AKI (AUC = 0.71) than Log(sCAR) (AUC = 0.69), Log(LAR) (AUC = 0.65), SOFA score (AUC = 0.66) and Δ Scr (AUC = 0.70). Multivariate regression identified that the SOFA score, PT, ΔScr, Tbil, chronic liver disease, and Vasopressor use as independent risk factors for persistent severe SA-AKI (P < 0.05). A basic clinical prediction model was created using these variables, and its predictive ability, recognition capability, and clinical utility improved with the inclusion of the Log(sCAR)_Log(LAR) score. The model's predictive ability for secondary outcomes, such as renal replacement therapy (RRT), also improved with the addition of the Log(sCAR)_Log(LAR) score. The sensitivity analysis further corroborated the stability of the Log(sCAR)_Log(LAR) score in predicting persistent severe SA-AKI and secondary outcomes, such as RRT.

CONCLUSIONS

The Log(sCAR)_Log(LAR) score effectively predicted persistent severe SA-AKI, potentially aiding intensive care physicians in risk assessment.

Pregnancy-related acute kidney injury leads to hypertension, reduced kidney function and cognitive impairment in postpartum rats

Introduction

Women with hypertensive disorders of pregnancy such as HELLP (hemolysis, elevated liver enzyme, low platelet) Syndrome are affected by acute kidney injury during pregnancy (PR-AKI) at higher rates than women without hypertension. Both hypertensive disorders of pregnancy and Acute Kidney Injury (AKI) outside the context of pregnancy have been associated with an increased risk of developing Chronic Kidney Disease (CKD) and cognitive impairment. In our current study, we set out to determine if PR-AKI led to the development of CKD and impaired cognition in the postpartum period and if HELLP syndrome exacerbates the impairments.

Methods

Using timed-pregnant Sprague Dawley rats, on gestational day (GD) 12, mini-osmotic pumps infusing anti-angiogenic factors were surgically placed in the intraperitoneal cavity to induce HELLP. On GD18, AKI was induced via bilateral renal reperfusion ischemia surgery. Mean arterial pressure and birth outcomes were used to assess the global effects of AKI, and liver enzymes were used to assess HELLP. CKD was assessed by measuring glomerular filtration rate (GFR), urinary output, and renal fibrosis. Anxiety-like behaviors, object recognition memory, spatial memory, and avoidance memory were assessed via behavioral experiments.

Results

HELLP + AKI rats demonstrated more evidence of renal injury, hypertension, and behavioral deficits compared to normal pregnant animals. In addition, AKI had a negative impact on birth outcomes and maternal survival.

Conclusion

HELLP + AKI together led to evidence of persistent hypertension, progressive renal dysfunction, and cognitive impairment, which were exacerbated compared to AKI or HELLP alone. These findings suggest that PR-AKI in the presence of a hypertensive disorder of pregnancy, such as HELLP, leads to the development of CKD, cognitive dysfunction, and hypertension.

A prediction nomogram for mortality in patients following wasp stings: a retrospective study

Numerous studies have shown that wasp stings can lead to serious, sometimes fatal, health outcomes. Predicting deaths associated with wasp stings remains challenging yet is of critical importance. This study was conducted to identify predictors and develop a visual model for predicting mortality following wasp stings. Clinical data from 486 patients were analyzed, dividing them into two groups: survival group (N = 435) and death group (N = 51). Various statistical methods were used to create a prognostic model, including one-way analysis, the least absolute shrinkage and selection operator (LASSO) regression, and binary logistic regression. The model's accuracy was evaluated through ROC curves, calibration plots, and decision curve analysis (DCA). The study identified four key predictors of mortality: receiving more than 50 stings, having serum lactate dehydrogenase (LDH) levels of ≥ 2200 U/L, activated partial thromboplastin time (APTT) of ≥ 90 s, and the requirement for invasive mechanical ventilation within 24 h. These factors contributed to a model with an area under the ROC curve of 0.980 (95% CI: [0.968-0.992]), indicating high calibration and applicability. The decision curve analysis confirmed the model's substantial net clinical benefit. Thus, the number of stings, serum LDH, APTT, and the need for early invasive mechanical ventilation are reliable, independent predictors of death among patients experiencing wasp stings. The developed predictive model exhibits high levels of accuracy, sensitivity, consistency, and practical use.

Association between lactate dehydrogenase to albumin ratio and acute kidney injury in patients with sepsis: a retrospective cohort study

BACKGROUND

Serum lactate dehydrogenase to albumin ratio (LAR) is associated with poor outcomes in malignancy and pneumonia. However, there are few studies suggesting that LAR is associated with the occurrence of acute kidney injury (AKI) in patients with sepsis, which was investigated in this study.

METHODS

We conducted a retrospective cohort study based on the Medical Information Mart for Intensive Care (MIMIC)-IV database. The primary outcome was the occurrence of AKI within 2 days and 7 days. Multivariable logistic regression models were used to calculate odds ratios to validate the association between LAR and AKI, in-hospital mortality, RRT use, and recovery of renal function, respectively.

RESULTS

A total of 4010 participants were included in this study. The median age of the participants was 63.5 years and the median LAR was 10.5. After adjusting for confounding variables, patients in the highest LAR quartile had a higher risk of AKI than those in the lowest LAR quartile within 2 days and 7 days, with odds ratios of 1.37 (95% confidence interval [CI]: 1.23-1.52) and 1.95 (95% CI: 1.72-2.22), respectively. The adjusted odds of AKI within 2 and 7 days were 1.16 (95% CI: 1.12-1.20) and 1.29 (95% CI: 1.24-1.35) for each 1 unit increase in LAR(log2), respectively.

CONCLUSION

This study demonstrated that elevated LAR was associated with poor prognosis in patients with sepsis. The risk of AKI and in-hospital mortality increased, the need for RRT increased, and the chance of recovery of renal function decreased with the increase of LAR.

Multifunctional laser-induced graphene circuits and laser-printed nanomaterials toward non-invasive human kidney function monitoring

Faced with the increasing prevalence of chronic kidney disease (CKD), portable monitoring of CKD-related biomarkers such as potassium ion (K+), creatinine (Cre), and lactic acid (Lac) levels in sweat has shown tremendous potential for early diagnosis. However, a rapidly manufacturable portable device integrating multiple CKD-related biomarker sensors for ease of sweat testing use has yet to be reported. Here, a portable electrochemical sensor integrated with multifunctional laser-induced graphene (LIG) circuits and laser-printed nanomaterials based working electrodes fabricated by fully automatic laser manufacturing is proposed for non-invasive human kidney function monitoring. The sensor comprises a two-electrode LIG circuit for K+ sensing, a three-electrode LIG circuit with a Kelvin compensating connection for Cre and Lac sensing, and a printed circuit board based portable electrochemical workstation. The working electrodes containing Cu and Cu2O nanoparticles fabricated by two-step laser printing show good sensitivity and selectivity toward Cre and Lac sensing. The sensor circuits are fabricated by generating a hydrophilic-hydrophobic interface on a patterned LIG through laser. This sensor recruited rapid laser manufacturing and integrated with multifunctional LIG circuits and laser-printed nanomaterials based working electrodes, which is a potential kidney function monitoring solution for healthy people and kidney disease patients.

COVID-19 increases mortality in hemodialysis patients: exploring links with inflammation and telomere attrition

BACKGROUND AND OBJECTIVE

An increased risk of mortality and hospitalization was consistently demonstrated in hemodialysis (HD) patients affected by pandemic coronavirus infection (COVID-19). In this study, we analyzed parameters that may impact mortality in COVID-19 HD patients, including neutrophil-to-lymphocyte ratio (NLR), lactate dehydrogenase (LDH), C-reactive protein (CRP), COVID-19 disease status and telomere length in peripheral blood cells (TL).

MATERIALS AND METHODS

A total of 130 chronic hemodialysis patients were enrolled and followed up for 18 months. Patients were categorized into groups based on their COVID-19 disease history and subsequent data about their survival status at the end of the study. Routine laboratory parameters were assessed using standard automated methods and TL was determined using the modified Cawthon method. Survival predictors were analyzed using Kaplan-Meier analysis.

RESULTS

Deceased patients (30%) were older with higher body mass index (BMI), higher levels of LDH, NLR index, CRP and lower TL and lymphocytes count compared to survivors. Kaplan-Meier survival analysis showed six parameters were significant mortality predictors in the following order of significance: COVID-19 history, 2-years cardiovascular mortality risk score, NLR, TL, CRP, LDH. Using binary logistic regression analysis Summary risk score, a combination of these six parameters revealed as the best predictor of patient's survival in this group of parameters (log rank 25.4, p < 0.001).

CONCLUSION

Compared to the general population, the mortality rate among HD patients persists at a higher level despite advancements in HD technology and patient care. The situation has been exacerbated by COVID-19, by significant increase in mortality rate among these patients.

Impact of β-blockers on in-hospital mortality in patients with heart failure: a retrospective propensity-score matched analysis based on MIMIC-IV database

Introduction

This study assessed the relationship between β-blockers treatment and in-hospital mortality among individuals diagnosed with heart failure (HF).

Methods

A retrospective cohort study was carried out on 9,968 HF patients sourced from the Medical Information Mart for Intensive Care (MIMIC)-IV database. Propensity score matching (PSM) was employed to balance the baseline differences. A multivariate regression analysis was utilized to evaluate the impact of β-blockers therapy on in-hospital mortality.

Results

Among the 9,968 patients, 6,439 (64.6%) were β-blockers users. Before matching, the overall in-hospital mortality rate was 12.2% (1,217/9,968). Following PSM, a total of 3,212 patient pairs were successfully matched. The analysis revealed a correlation between β-blockers therapy and decreased in-hospital mortality (odds ratio 0.51 [0.43-0.60], P < 0.001), as well as shorter Los (length of stay) hospital (β -1.43 [-1.96∼-0.09], P < 0.001). Notably, long-acting β-blockers treatment was linked to a decreased risk of in-hospital mortality (odds ratio 0.55 [0.46-0.65], P < 0.001) and a shorter Los hospital (β -1.21 [-1.80∼-0.63], P < 0.001). Conversely, the research results did not show a notable decrease in-hospital mortality (odds ratio 0.66 [0.44-1.01], P = 0.051) or Los hospital (β -1.01 [-2.2∼-0.25], P = 0.117) associated with short-acting β-blocker therapy.

Discussion

β-blockers therapy in the intensive care unit demonstrates potential benefits in lowering the risk of in-hospital mortality and reducing the duration of hospitalization among patients with HF. Specifically, long-acting β-blockers exhibit a protective effect by significantly decreasing both in-hospital mortality and Los hospital. Conversely, the study did not observe a substantial impact on in-hospital mortality or Los hospital duration in this cohort of patients following the administration of short-acting β-blockers.

Predictive role of PAR and LAR in refractory suppurative meningitis in infants

BACKGROUND

Meningitis can be caused by a variety of pathogenic microorganisms, which can lead to higher mortality and disability rates. However, the clinical manifestations of suppurative meningitis are often atypical in infants and young children, which makes early clinical diagnosis difficult.PAR and LAR are considered as a novel inflammatory biomarker and have been applied in tumors, IgA nephropathy, sepsis.

OBJECTIVE

To investigate the application of platelet/albumin (PAR) and lactate dehydrogenase/albumin (LAR) in refractory suppurative meningitis in infants.

METHODS

The relevant clinical data of 107 children with suppurative meningitis were retrospectively analyzed, and were divided into common group (82 cases) and refractory group (25 cases) according to the severity of the disease according to the relevant clinical consensus. The relevant clinical data and laboratory examination of the children in the two groups were compared. The diagnostic value of PAR and LAR in children with refractory suppurative meningitis was analyzed and multivariate Logistic regression analysis was performed.

RESULT

The PAR of children with suppurative meningitis in refractory group was lower than that in common group (P < 0.05), while LAR was higher than that in common group (P < 0.05). Meanwhile, multivariate Logistic regression analysis showed that LAR and cerebrospinal fluid glucose ≤ 1.5mmo/L were risk factors for poor prognosis (OR > 1, P < 0.05). PAR was a protective factor (OR < 1, P < 0.05).

CONCLUSION

PAR and LAR can be used for early diagnosis of refractory suppurative meningitis in children as protective and risk factors, respectively.

Association between lactate dehydrogenase and the risk of diabetic kidney disease in patients with type 2 diabetes

Objective

This study aims to investigate the association between lactate dehydrogenase (LDH) and the risk of diabetic kidney disease (DKD) in patients with type 2 diabetes (T2D).

Methods

The study enrolled patients with diagnosis of T2D between 2009 and 2018 from the National Nutrition and Health Examination Survey (NHANES) database. Demographic information, laboratory test, and diagnostic data were collected. Restricted cubic spline (RCS) plots were used to assess the dose-effect relationship between LDH levels and the risk of DKD in patients with T2D. Based on LDH levels, individuals were divided into higher and lower groups using dichotomy, and multivariate logistic regression analysis was conducted to explore the relationship between different LDH levels and the risk of DKD in T2D patients. Stratified analysis was performed to assess the consistency of the result.

Results

A total of 4888 patients were included in the study, with 2976 (60.9%) patients without DKD and 1912 (39.1%) patients with DKD. RCS plots showed that the risk of DKD increased with increasing LDH levels. Multifactorial logistic regression analysis revealed that T2D patients with higher LDH levels had a 45% increased risk of DKD compared to those with lower LDH levels (OR=1.45; 95% CI: 1.11-1.89). Furthermore, each standard deviation increase in LDH level was associated with a 24% increase in DKD incidence among T2D patients (OR=1.24; 95% CI: 1.07-1.44). Stratified analysis consistently supported these findings.

Conclusions

LDH can serve as a valuable biomarker for screening DKD in patients with T2D.

Lactate dehydrogenase to albumin ratio is associated with in-hospital mortality in patients with acute heart failure: Data from the MIMIC-III database

The effect of the lactate dehydrogenase to albumin ratio (LAR) on the survival of patients with acute heart failure (AHF) is unclear. We aimed to analyze the impact of LAR on survival in patients with AHF. We retrieved eligible patients for our study from the Monitoring in Intensive Care Database III. For each patient in our study, we gathered clinical data and demographic information. We conducted multivariate logistic regression modeling and smooth curve fitting to assess whether the LAR score could be used as an independent indicator for predicting the prognosis of AHF patients. A total of 2,177 patients were extracted from the database. Survivors had an average age of 69.88, whereas nonsurvivors had an average age of 71.95. The survivor group had a mean LAR ratio of 13.44, and the nonsurvivor group had a value of 17.38. LAR and in-hospital mortality had a nearly linear correlation, according to smooth curve fitting (P < 0.001). According to multivariate logistic regression, the LAR may be an independent risk factor in predicting the prognosis of patients with AHF (odd ratio = 1.09; P < 0.001). The LAR ratio is an independent risk factor associated with increased in-hospital mortality rates in patients with AHF.

Biofunctional coacervate-based artificial protocells with membrane-like and cytoplasm-like structures for the treatment of persistent hyperuricemia

Coacervate droplets formed by liquid-liquid phase separation have attracted considerable attention due to their ability to enrich biomacromolecules while preserving their bioactivities. However, there are challenges to develop coacervate droplets as delivery vesicles for therapeutics resulting from the lack of physiological stability and inherent lack of membranes in coacervate droplets. Herein, polylysine-polynucleotide complex coacervate droplets with favorable physiological stability are formulated to efficiently and facilely concentrate small molecules, biomacromolecules and nanoparticles without organic solvents. To improve the biocompatibility, the PEGylated phospholipid membrane is further coated on the surface of the coacervate droplets to prepare coacervate-based artificial protocells (ArtPC) with membrane-like and cytoplasm-like structures. The ArtPC can confine the cyclic catalytic system of uricase and catalase inside to degrade uric acid and deplete the toxicity of H2O2. This biofunctional ArtPC effectively reduces blood uric acid levels and prevents renal injuries in mice with persistent hyperuricemia. The ArtPC-based therapy can bridge the disciplines of synthetic biology, pharmaceutics and therapeutics.

One-year mortality prediction for patients with sepsis: a nomogram integrating lactic dehydrogenase and clinical characteristics

BACKGROUND

To explore the association between myocardial enzymes and one-year mortality, and establish a nomogram integrating myocardial enzymes and clinical characteristics to predict one-year mortality among sepsis patients.

METHODS

Data of 1,983 sepsis patients were extracted from Medical Information Mart for Intensive Care III database in this retrospective cohort study. All participants were randomly split into the training set for the development of model and testing set for the internal validation at the ratio of 7:3. Univariate logistic regression was used to screen variables with statistical differences which were made for stepwise regression, obtaining the predictors associated with one-year mortality of sepsis patients. Adopted multivariate logistic regression to assess the relationship between myocardial enzymes and one-year mortality of sepsis patients. A nomogram was established in predicting the one-year survival status of sepsis patients, and the performance of developed model were compared with LDH alone, sequential organ failure assessment (SOFA), simplified acute physiology score II (SAPS II) by receiver operator characteristic, calibration, and decision curves analysis.

RESULTS

The result found that LDH was associated with one-year mortality of sepsis patients [odds ratio = 1.28, 95% confidence interval (CI): 1.18-1.52]. Independent predictors, including age, gender, ethnicity, potassium, calcium, albumin, hemoglobin, alkaline phosphatase, vasopressor, Elixhauser score, respiratory failure, and LDH were identified and used to establish the nomogram (LDH-model) for predicting one-year mortality for sepsis patients. The predicted performance [area under curve (AUC) = 0.773, 95%CI: 0.748-0.798] of this developed nomogram in the training and testing sets (AUC = 0.750, 95%CI: 0.711-0.789), which was superior to that of LDH alone, SOFA score, SAPS II score. Additionally, calibration curve indicated that LDH-model may have a good agreement between the predictive and actual outcomes, while decision curve analysis demonstrated clinical utility of the LDH-model.

CONCLUSION

LDH level was related to the risk of one-year mortality in sepsis patients. A prediction model based on LDH and clinical features was developed to predict one-year mortality risk of sepsis patients, surpassing the predictive ability of LDH alone as well as conventional SAPS II and SOFA scoring systems.

Predictive value of lactate dehydrogenase combined with the abbreviated burn severity index for acute kidney injury and mortality in severe burn patients

BACKGROUND

Extensive burns are devastating trauma. This study aimed to explore the predictive value of early lactate dehydrogenase (LDH) level, the abbreviated burn severity index (ABSI) and their combination on acute kidney injury (AKI) and mortality after severe burns.

METHODS AND RESULTS

194 severe burn patients (TBSA ≥ 30%) were included. After multivariate analyses, early LDH value (first 24 h after admission) was an independent risk factor for early AKI (OR=1.095, CI,1.025-1.169,p = 0.007) and AKI (OR=1.452, CI,1.131-1.864, p = 0.003) in severe burn patients and was still a significant risk factor for mortality (OR=1.059, CI,1.006-1.115，p = 0.03). In ROC analysis, after combining LDH and ABSI, the AUC values were 0.925 for AKI, 0.926 for stage 3 AKI, and 0.904 for mortality. Based on cut-off values, patients were divided into different risk groups. The cumulative incidence of AKI (within 5 days, 30 days) and survival rate (within 60 days) were analyzed by the Kaplan-Meier method. The mortality, AKI incidence, and AKI staging showed a significant upward trend with the increasing risk level (P < 0.001).

CONCLUSION

Early LDH level is an independent risk factor for early AKI and AKI. LDH combined with ABSI can better predict mortality and AKI than single indicators.

Our Experience with SARS-CoV-2 Infection and Acute Kidney Injury: Results from a Single-Center Retrospective Observational Study

BACKGROUND

Renal failure in COVID-19 patients is reportedly related to multiple factors such as a direct SARS-CoV-2 cytopathic effect, cytokine storm, the association of pulmonary and/or cardiovascular lesions, the presence of thrombotic microangiopathy, endothelial damage, or the use of potentially nephrotoxic medications.

METHODS

We retrospectively analyzed 466 cases of SARS-CoV-2 infection, comparing 233 patients with acute kidney injury (AKI) with 233 patients without AKI in terms of their demographic characteristics, comorbidities, clinical background, laboratory investigations, time of AKI onset, therapy, and outcomes after using univariate analysis and a CART decision-tree approach. The latter was constructed in a reverse manner, starting from the top with the root and branching out until the splitting ceased, interconnecting all the predictors to predict the overall outcome (AKI vs. non-AKI).

RESULTS

There was a statistically significant difference between the clinical form distribution in the two groups, with fewer mild (2 vs. 5) and moderate (54 vs. 133) cases in the AKI group than in the non-AKI group and more severe and critical patients in the AKI cohort (116 vs. 92 and 60 vs. 3). There were four deaths (1.71%) in the non-AKI group and 120 deaths in the AKI group (51.5%) (p-value < 0.001). We noted statistically significant differences between the two study groups in relation to different tissue lesions (LDH), particularly at the pulmonary (CT severity score), hepatic (AST, ALT), and muscular levels (Creatine kinase). In addition, an exacerbated procoagulant and inflammatory profile in the study group was observed. The CART algorithm approach yielded decision paths that helped sort the risk of AKI progression into three categories: the low-risk category (0-40%), the medium-risk category (40-80%), and the high-risk category (>80%). It recognized specific inflammatory and renal biomarker profiles with particular cut-off points for procalcitonin, ferritin, LDH, creatinine, initial urea, and creatinine levels as important predictive factors of AKI outcomes (93.3% overall performance).

CONCLUSIONS

Our study revealed the association between particular risk factors and AKI progression in COVID-19 patients. Diabetes, dyspnea on admission, the need for supplemental oxygen, and admission to the intensive care unit all had a crucial role in producing unfavorable outcomes, with a death rate of more than 50%. Necessary imaging studies (CT scan severity score) and changes in specific biomarker levels (ferritin and C-reactive protein levels) were also noted. These factors should be further investigated in conjunction with the pathophysiological mechanisms of AKI progression in COVID-19 patients.

Tracking longitudinal biomarkers in burn patients with sepsis and acute kidney injury: an unsupervised clustering approach

BACKGROUND

Sepsis is a grave medical disorder characterized by a systemic inflammatory response to infection. Furthermore, it is a leading cause of morbidity and mortality, especially in hospitalized patients. Acute kidney injury (AKI) is a common complication of sepsis and is associated with increased morbidity and mortality. Patients with burns are particularly vulnerable to developing sepsis and AKI due to the extensive tissue damage and immune suppression resulting from burn injury. In this study, unsupervised clustering algorithms were used to track longitudinal biomarkers in patients with burns and assess their impact on mortality.

METHODS

This retrospective study included adult patients with burns aged ≥ 18 years, who were admitted to the burn intensive care unit of Hallym University and Hangang Sacred Heart Hospital between July 2010 and December 2021. The patients were divided into two subgroups: those with sepsis (538 patients) and those without sepsis (826 patients). The longitudinal biomarkers were grouped into three clusters using the k-means clustering algorithm. Each cluster was assigned a letter from A to C according to its mortality rate.

RESULTS

The odds ratio (OR) of pH was 9.992 in the positive group and 31.745 in the negative group in cluster C. The OR for lactate dehydrogenase (LD) was 3.704 in the positive group and 6.631 in the negative group in cluster C. The OR for creatinine was 2.784 in the positive group and 8.796 in the negative group in cluster C. The OR for blood urea nitrogen (BUN) in the negative group was 0.348, indicating a negative predictor of mortality. Regarding the application of Continuous Renal Replacement Therapy (CRRT) and ventilation, ventilation was significant in both groups. In contrast, CRRT application was not significant in the sepsis-positive group. Furthermore, it was not selected as a variable in the negative group.

CONCLUSIONS

The pH, LD, and creatinine were significant in both groups, while lactate and platelets were significant in the sepsis-positive group. In addition, albumin, glucose, and BUN were significant in the sepsis-negative group. Continuous renal replacement therapy was not significant in either group. However, the use of a ventilator was associated with poor prognosis.

Lactate Dehydrogenase and Hemorrhagic Stroke During Extracorporeal Membrane Oxygenation for COVID-19

PURPOSE

Hemorrhagic stroke (HS) is a devastating complication during extracorporeal membrane oxygenation (ECMO) but markers of risk stratification during COVID-19 are unknown. Lactate dehydrogenase (LDH) is a readily available biomarker of cell injury and permeability. We sought to determine whether an elevated LDH before ECMO placement is related to the occurrence of HS during ECMO for COVID-19.

METHODS

Adult patients with COVID-19 requiring ECMO between March 2020 and February 2022 were included. LDH values prior to ECMO placement were captured. Patients were categorized into high (> 750 U/L) or low (≤ 750 U/L) LDH groups. Multivariable regression modeling was used to determine the association between LDH and HS during ECMO.

RESULTS

There were 520 patients that underwent ECMO placement in 17 centers and 384 had an available LDH. Of whom, 122 (32%) had a high LDH. The overall incidence of HS was 10.9%, and patients with high LDH had a higher incidence of HS than those with low LDH level (17% vs 8%, p = 0.007). At 100 days, the probability of a HS was 40% in the high LDH group and 23% in those with a low LDH, p = 0.002. After adjustment for clinical covariates, high LDH remained associated with subsequent HS (aHR: 2.64, 95% CI 1.39-4.92). Findings were similar when restricting to patients supported by venovenous ECMO only.

CONCLUSION

Elevated LDH prior to ECMO cannulation is associated with a higher incidence of HS during device support. LDH can risk stratify cases for impending cerebral bleeding during ECMO.

Association of Dietary Inflammation Index and Helicobacter pylori Immunoglobulin G Seropositivity in US Adults: A Population-Based Study

Background

Dietary patterns play important role in Helicobacter pylori (H. pylori) infection. We aimed to investigate the potential relationship between Dietary Inflammation Index (DII) and H. pylori infection in US adults.

Methods

This cross-sectional study was based on National Health and Nutrition Examination Survey (1999-2000). Individuals aged ≥20 years who provided a 24 hr dietary intake history and underwent H. pylori testing were included in the analysis. Multivariate weighted logistic regression analysis, smooth curve fitting, and subgroup analysis were used to investigate the relationship between DII and H. pylori infection. Subgroup analyses were based on demographic and clinical variables.

Results

There were 4,000 individuals enrolled in our final analysis. The overall mean age was 45.92 years and 46.77% were males. The overall prevalence of H. pylori infection in the study population was 45.9%. The smooth curve fitting analysis indicated a near-linear relationship between DII and H. pylori. In multivariate weighted logistic regression analysis, the odds ratio (OR) of DII is 1.17 (95% confidence interval (CI), 1.09-1.27) for H. pylori infection. In subgroup analysis, DII still increased the risk of H. pylori infection independently.

Conclusions

The increased DII levels were associated with an increased risk of H. pylori infection among US adults. Further studies are needed to elucidate the exact mechanisms of DII and H. pylori infection.

Association between systemic immune-inflammation index and low muscle mass in US adults: a cross-sectional study

BACKGROUND

Chronic inflammatory responses have been reported to be associated with low muscle mass and systemic immune-inflammation index(SII) is a novel indicator of inflammation. The purpose of our study was to clarify the relationship between SII and low muscle mass.

METHODS

This study was a cross-sectional study based on National Health and Nutrition Examination Survey (2011-2018). SII was calculated as the platelet count × neutrophil count/lymphocyte count. Appendicular skeletal muscle index was used to define low muscle mass. The individuals were divided into four groups by the quartile of SII (Q1-Q4). Multivariate weighted logistic regression analysis, smooth curve fitting and subgroup analysis were used to investigate the relationship between SII and sarcopenia. Subgroup analysis were based on demographic and clinical variables.

RESULTS

There were 10,367 individuals enrolled in our final analysis. The overall mean age was 39.39 years and 49.17% were males. The overall prevalence of low muscle mass in the study population was 8.77%. The smooth curve fitting analysis indicated a near-linear relationship between SII and low muscle mass. In multivariate weighted logistic regression analysis, the odds ratio (OR) of Q4 is 1.28 (95% CI, 1.16-1.40) for low muscle mass when compared to lowest quartile of the SII. In subgroup analysis, SII still increased the risk of low muscle mass independently.

CONCLUSION

The increased SII levels were associated with an increased risk of low muscle mass in a large population. Our study increased the understanding between inflammation and low muscle mass. Anti-inflammation therapy may be important for low muscle mass.

Decreased level of serum NT-proCNP associates with disease severity in COVID-19

BACKGROUND

C-type natriuretic peptide (CNP) is an endothelium-derived paracrine molecule with an important role in vascular homeostasis. In septic patients, the serum level of the amino-terminal propeptide of CNP (NT-proCNP) shows a strong positive correlation with inflammatory biomarkers and, if elevated, correlates with disease severity and indicates a poor outcome. It is not yet known whether NT-proCNP also correlates with the clinical outcome of patients suffering from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. In the current study, we aimed to determine possible changes in the NT-proCNP levels of patients with coronavirus disease 2019 (COVID-19), with special regard to disease severity and outcome.

METHODS

In this retrospective analysis, we determined the serum level of NT-proCNP in hospitalized patients with symptoms of upper respiratory tract infection, using their blood samples taken on admission, stored in a biobank. The NT-proCNP levels of 32 SARS-CoV-2 positive and 35 SARS-CoV-2 negative patients were measured to investigate possible correlation with disease outcome. SARS-CoV-2 positive patients were then divided into two groups based on their need for intensive care unit treatment (severe and mild COVID-19).

RESULTS

The NT-proCNP was significantly different in the study groups (e.g. severe and mild COVID-19 and non-COVID-19 patients), but showed inverse changes compared to previous observations in septic patients: lowest levels were detected in critically ill COVID-19 patients, while highest levels in the non-COVID-19 group. A low level of NT-proCNP on admission was significantly associated with severe disease outcome.

CONCLUSIONS

Low-level NT-proCNP on hospital admission is associated with a severe COVID-19 disease course. The pathomechanism underlying this observation remains to be elucidated, while future studies in larger patient cohorts are necessary to confirm these observations and reveal therapeutic importance. Trial registration DRKS00026655 Registered 26. November 2021.

Machine learning in the prediction of cardiac surgery associated acute kidney injury with early postoperative biomarkers

Purpose

To establish novel prediction models for predicting acute kidney injury (AKI) after cardiac surgery based on early postoperative biomarkers.

Patients and methods

This study enrolled patients who underwent cardiac surgery in a Chinese tertiary cardiac center and consisted of a discovery cohort (n = 452, from November 2018 to June 2019) and a validation cohort (n = 326, from December 2019 to May 2020). 43 biomarkers were screened using the least absolute shrinkage and selection operator and logistic regression to construct a nomogram model. Three tree-based machine learning models were also established: eXtreme Gradient Boosting (XGBoost), random forest (RF) and deep forest (DF). Model performance was accessed using area under the receiver operating characteristic curve (AUC). AKI was defined according to the Kidney Disease Improving Global Outcomes criteria.

Results

Five biomarkers were identified as independent predictors of AKI and were included in the nomogram: soluble ST2 (sST2), N terminal pro-brain natriuretic peptide (NT-proBNP), heart-type fatty acid binding protein (H-FABP), lactic dehydrogenase (LDH), and uric acid (UA). In the validation cohort, the nomogram achieved good discrimination, with AUC of 0.834. The machine learning models also exhibited adequate discrimination, with AUC of 0.856, 0.850, and 0.836 for DF, RF, and XGBoost, respectively. Both nomogram and machine learning models had well calibrated. The AUC of sST2, NT-proBNP, H-FABP, LDH, and UA to discriminate AKI were 0.670, 0.713, 0.725, 0.704, and 0.749, respectively. In addition, all of these biomarkers were significantly correlated with AKI after adjusting clinical confounders (odds ratio and 95% confidence interval of the third vs. the first tertile: sST2, 3.55 [2.34-5.49], NT-proBNP, 5.50 [3.54-8.71], H-FABP, 6.64 [4.11-11.06], LDH, 7.47 [4.54-12.64], and UA, 8.93 [5.46-15.06]).

Conclusion

Our study provides a series of novel predictive models and five biomarkers for enhancing the risk stratification of AKI after cardiac surgery.

Relationship between serum lactate dehydrogenase and mortality after cardiac arrest: A retrospective cohort study

Serum lactate dehydrogenase (LDH) has been identified as an independent risk factor for predicting all-cause mortality in patients with multiple diseases. However, the prognostic value of LDH levels in post-cardiac arrest patients remains uncertain. This study aimed to assess the association between LDH and mortality in intensive care unit (ICU) patients after cardiac arrest. This retrospective observational study is based on data from the Dryad Digital Repository, which included 374 consecutive adult patients after cardiac arrest. Patients were divided into 2 groups based on median LDH values. A multivariate Cox proportional hazards model was established to assess the independent relationship between LDH and ICU mortality. Cumulative mortality was compared using Kaplan-Meier curves. The cohort included 374 patients, of which 51.9% (194/374) died in the ICU. The overall death rate from cardiac arrest was significantly higher for patients with LDH ≥ 335 IU/L (59.6%) than for those with LDH < 335 IU/L (44.1%). In multiple Cox regression models, hazard ratios (HR) and corresponding 95% confidence intervals (CI) for logLDH and the 2 LDH groups were 1.72 (1.07, 2.78) and 1.42 (1.04, 1.93), respectively. Participants with LDH ≥ 335IU/L had a higher incidence of ICU mortality than LDH < 335 IU/L, as shown by the Kaplan-Meier curves (P = .0085). Subgroup analysis revealed that the association between LDH and ICU mortality was vitally stable, with all P interactions from different subgroups >.05. Serum LDH levels are positively associated with ICU mortality in patients after cardiac arrest, especially for patients with LDH ≥ 335 IU/L.

Prediction of acute kidney injury after cardiac surgery: model development using a Chinese electronic health record dataset

Background

Acute kidney injury (AKI) is a major complication following cardiac surgery that substantially increases morbidity and mortality. Current diagnostic guidelines based on elevated serum creatinine and/or the presence of oliguria potentially delay its diagnosis. We presented a series of models for predicting AKI after cardiac surgery based on electronic health record data.

Methods

We enrolled 1457 adult patients who underwent cardiac surgery at Nanjing First Hospital from January 2017 to June 2019. 193 clinical features, including demographic characteristics, comorbidities and hospital evaluation, laboratory test, medication, and surgical information, were available for each patient. The number of important variables was determined using the sliding windows sequential forward feature selection technique (SWSFS). The following model development methods were introduced: extreme gradient boosting (XGBoost), random forest (RF), deep forest (DF), and logistic regression. Model performance was accessed using the area under the receiver operating characteristic curve (AUROC). We additionally applied SHapley Additive exPlanation (SHAP) values to explain the RF model. AKI was defined according to Kidney Disease Improving Global Outcomes guidelines.

Results

In the discovery set, SWSFS identified 16 important variables. The top 5 variables in the RF importance matrix plot were central venous pressure, intraoperative urine output, hemoglobin, serum potassium, and lactic dehydrogenase. In the validation set, the DF model exhibited the highest AUROC (0.881, 95% confidence interval [CI] 0.831–0.930), followed by RF (0.872, 95% CI 0.820–0.923) and XGBoost (0.857, 95% CI 0.802–0.912). A nomogram model was constructed based on intraoperative longitudinal features, achieving an AUROC of 0.824 (95% CI 0.763–0.885) in the validation set. The SHAP values successfully illustrated the positive or negative contribution of the 16 variables attributed to the output of the RF model and the individual variable’s effect on model prediction.

Conclusions

Our study identified 16 important predictors and provided a series of prediction models to enhance risk stratification of AKI after cardiac surgery. These novel predictors might aid in choosing proper preventive and therapeutic strategies in the perioperative management of AKI patients.

Serum Lactate Dehydrogenase Is a Sensitive Predictor of Systemic Complications of Acute Pancreatitis

BACKGROUND

Acute pancreatitis (AP) is a common and potentially life-threatening inflammatory disease that can cause various complications, including systemic inflammatory response syndrome (SIRS), pleural effusion, ascitic fluid, myocardial infarction, and acute kidney injury (AKI). However, there is still a lack of rapid and effective indicators to assess the disease. The aim of this study was to investigate the associations of high serum lactate dehydrogenase (LDH) levels with AP severity and systemic complications.

METHODS

AP patients treated from July 2014 to December 2020 were retrospectively enrolled. They were divided into elevated (n = 93) and normal (n = 143) LDH groups. Their demographic data, clinical data, hospital duration, and hospital expenses were analyzed. Linear and binary logistic regression analyses were used to determine whether elevated LDH is a risk factor for AP severity and complications after adjusting for confounders.

RESULTS

There were significant differences in AP severity scores (Ranson, MODS, BISAP, APACHE II, and CTSI), hospital duration, hospital expenses, and the incidences of complications (SIRS, pleural effusion, ascitic fluid, myocardial infarction, and AKI) between the elevated and normal LDH groups. After adjusting for confounders, elevated LDH was associated with AP severity scores and hospital duration and expenses (based on linear regression analyses) and was a risk factor for the occurrence of AP complications and interventions, that is, diuretic and vasoactive agent use (based on binary logistic regression analyses).

CONCLUSIONS

Elevated LDH is associated with high AP severity scores and high incidences of complications (SIRS, pleural effusion, ascitic fluid, myocardial infarction, and AKI).