Prognostic Value of Lactate Dehydrogenase for Mid-Term Mortality in Acute Decompensated Heart Failure: A Comparison to Established Biomarkers and Brain Natriuretic Peptide

Proliferation capability of natural killer cells upon cytokines stimulation correlated negatively with serum lactate dehydrogenase level in coronary artery disease patients

Background

Natural killer (NK) cells are proposed to participate in coronary artery disease (CAD) development. However, little is known about how CAD patients' NK cells respond to different stimulatory factors in terms of proliferation capability.

Methods and results

Twenty-nine CAD patients' peripheral blood NK cells were isolated and individually treated with IL-2, IL-12, IL-15, IL-18, IL-21, cortisone acetate, hydrocortisone, or ascorbic acid for 36 hours, followed by cell cycle analysis using flow cytometry. The ratio of S and G2/M phase cell number to total cell number was defined as a proliferation index (PrI) and used for proliferative capability indication. The results showed that these eight factors resulted in different life cycle changes in the 29 NK cell samples. Remarkably, 28 out of 29 NK cell samples showed an obvious increase in PrI upon ascorbic acid treatment. The serum lactate dehydrogenase (LDH) level of the 29 CAD patients was measured. The results showed a negative correlation between serum LDH level and the CAD patients' NK cell PrI upon stimulation of interleukins, but not the non-interleukin stimulators. Consistently, a retrospective analysis of 46 CAD patients and 32 healthy donors showed that the circulating NK cell number negatively correlated with the serum LDH level in CAD patients. Unexpectedly, addition of LDH to NK cells significantly enhanced the production of IFN-γ, IL-10 and TNF-α, suggesting a strong regulatory role on NK cell's function.

Conclusion

Ascorbic acid could promote the proliferation of the CAD patients' NK cells; LDH serum level may function as an indicator for NK cell proliferation capability and an immune-regulatory factor.

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.

Advances in nanotechnological approaches for the detection of early markers associated with severe cardiac ailments

Mortality from cardiovascular disease (CVD) accounts for over 30% of all deaths globally, necessitating reliable diagnostic tools. Prompt identification and precise diagnosis are critical for effective personalized treatment. Nanotechnology offers promising applications in diagnostics, biosensing and drug delivery for prevalent cardiovascular diseases. Its integration into cardiovascular care enhances diagnostic accuracy, enabling early intervention and tailored treatment plans. By leveraging nanoscale innovations, healthcare professionals can address the complexities of CVD progression and customize interventions based on individual patient needs. Ongoing advancements in nanotechnology continue to shape the landscape of cardiovascular medicine, offering potential for improved patient outcomes and reduced mortality rates from these pervasive diseases.

Effect of supplementing lysins and methionine to low-protein diets on growth performance, hepatic antioxidant capacity, immune status, and glycolytic activity of tibetan sheep

Reducing the levels of dietary protein is an effective nutritional approach in lowering feed cost and nitrogen emissions in ruminants. The purpose of this study was to evaluate the effects of dietary Lys/Met ratio in a low protein diet (10%, dry matter basis) on the growth performance and hepatic function (antioxidant capacity, immune status, and glycolytic activity) in Tibetan lambs. Ninety two-month-old rams with an average weight of 15.37 ± 0.92 kg were randomly assigned to LP-L (dietary Lys/Met = 1:1), LP-M (dietary Lys/Met = 2:1) and LP-H (dietary Lys/Met = 3:1) treatments. The trial was conducted over 100 d, including 10 d of adaption to the diets. Hepatic phenotypes, antioxidant capacity, immune status, glycolytic activity and gene expression profiling was detected after the conclusion of the feeding trials. The results showed that the body weight was higher in the LP-L group when compared to those on the LP-M group (P < 0.05). In addition, the activities of the catalase (CAT) and glutathione peroxidase (GSH-Px) in the LP-L group were significantly increased compared with the LP-M group (P < 0.05), while the malondialdehyde (MDA) levels in LP-H group were significantly decreased (P < 0.05). Compared with LP-H group, both hepatic glycogen (P < 0.01) and lactate dehydrogenase (LDH) (P < 0.05) were significantly elevated in LP-L group. For the LP-L group, the hepatocytes were arranged radially with the central vein in the center, and hepatic plates exhibited tight arrangement. Transcriptome analysis identified 29, 179, and 129 differentially expressed genes (DEGs) between the LP-M vs. LP-L, LP-H vs. LP-M, and LP-H vs. LP-L groups, respectively (Q-values < 0.05 and |log2Fold Change| > 1). Gene Ontology (GO) and correlation analyses showed that in the LP-L group, core genes (C1QA and JUNB) enriched in oxidoreductase activity were positively correlated with antioxidant indicators, while the MYO9A core gene enriched in the immune response was positively associated with immune indicators, and core genes enriched in molecular function (PDK3 and PDP2) were positively correlated with glycolysis indicators. In summary, low-protein diet with a low Lys/Met ratio (1:1) could reduce the hepatic oxidative stress and improve the glycolytic activity by regulating the expression of related genes of Tibetan sheep.

The role of glycolytic metabolic pathways in cardiovascular disease and potential therapeutic approaches

Cardiovascular disease (CVD) is a major threat to human health, accounting for 46% of non-communicable disease deaths. Glycolysis is a conserved and rigorous biological process that breaks down glucose into pyruvate, and its primary function is to provide the body with the energy and intermediate products needed for life activities. The non-glycolytic actions of enzymes associated with the glycolytic pathway have long been found to be associated with the development of CVD, typically exemplified by metabolic remodeling in heart failure, which is a condition in which the heart exhibits a rapid adaptive response to hypoxic and hypoxic conditions, occurring early in the course of heart failure. It is mainly characterized by a decrease in oxidative phosphorylation and a rise in the glycolytic pathway, and the rise in glycolysis is considered a hallmark of metabolic remodeling. In addition to this, the glycolytic metabolic pathway is the main source of energy for cardiomyocytes during ischemia-reperfusion. Not only that, the auxiliary pathways of glycolysis, such as the polyol pathway, hexosamine pathway, and pentose phosphate pathway, are also closely related to CVD. Therefore, targeting glycolysis is very attractive for therapeutic intervention in CVD. However, the relationship between glycolytic pathway and CVD is very complex, and some preclinical studies have confirmed that targeting glycolysis does have a certain degree of efficacy, but its specific role in the development of CVD has yet to be explored. This article aims to summarize the current knowledge regarding the glycolytic pathway and its key enzymes (including hexokinase (HK), phosphoglucose isomerase (PGI), phosphofructokinase-1 (PFK1), aldolase (Aldolase), phosphoglycerate metatase (PGAM), enolase (ENO) pyruvate kinase (PKM) lactate dehydrogenase (LDH)) for their role in cardiovascular diseases (e.g., heart failure, myocardial infarction, atherosclerosis) and possible emerging therapeutic targets.

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.

Emerging biomarkers for the detection of cardiovascular diseases

Background

The prevalence of cardiovascular disease (CVD) has been continuously increasing, and this trend is projected to continue. CVD is rapidly becoming a significant public health issue. Every year there is a spike in hospital cases of CVD, a critical health concern in lower- and middle-income countries. Based on identification of novel biomarkers, it would be necessary to study and evaluate the diagnostic requirements or CVD to expedite early detection.

Main body

The literature review was written using a wide range of sources, such as well-known medical journals, electronic databases, manuscripts, texts, and other writings from the university library. After that, we analysed the specific markers of CVD and compiled a systematic review. A growing body of clinical research aims to identify people who are at risk for cardiovascular disease by looking for biomolecules. A small number of biomarkers have been shown to be useful and reliable in medicine. Biomarkers can be used for a variety of clinical applications, such as predicting heart disease risk, diagnosing disease, or predicting outcomes. As a result of the ability for a single molecule to act as a biomarker, its usefulness in medicine is expected to increase significantly.

Conclusions

Based on assessing the current trends in the application of CVD markers, we discussed and described the requirements for the application of CVD biomarkers in coronary heart disease, cerebrovascular disease, rheumatic heart disease, and other cardiovascular illnesses. Furthermore, the current review focuses on biomarkers for CVD and the procedures that should be considered to establish the comprehensive nature of the expression of biomarkers for cardiovascular illness.

Impact of lactate dehydrogenase on prognosis of patients undergoing cardiac surgery

Background

Lactate dehydrogenase (LDH) has been reported in multiple heart diseases. Herein, we explored the prognostic effects of preoperative LDH on adverse outcomes in cardiac surgery patients.

Methods

Retrospective data analysis was conducted from two large medical databases: Medical Information Mart for Intensive Care (MIMIC) III and MIMIC IV databases. The primary outcome was in-hospital mortality, whereas the secondary outcomes were 1-year mortality, continuous renal replacement therapy, prolonged ventilation, and prolonged length of intensive care unit and hospital stay.

Results

Patients with a primary endpoint had significantly higher levels of LDH (p < 0.001). Multivariate regression analysis presented that elevated LDH was independently correlated with increased risk of primary and secondary endpoints (all p < 0.001). Subgroup analyses showed that high LDH was consistently associated with primary endpoint. Moreover, LDH exhibited the highest area under the curve (0.768) for the prediction of primary endpoint compared to the other indicators, including neutrophil–lymphocyte ratio (NLR), lymphocyte-monocyte ratio (LMR), platelet–lymphocyte ratio (PLR), lactate, and simplified acute physiology score (SAPS) II. The above results were further confirmed in the MIMIC IV dataset.

Conclusions

Elevated preoperative LDH may be a robust predictor of poor prognosis in cardiac surgery patients, and its predictive ability is superior to NLR, LMR, PLR, lactate, and SAPS II.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-022-02848-7.

Ambient NO2 exposure induced cardiotoxicity associated with gut microbiome dysregulation and glycerophospholipid metabolism disruption

An average daily increase of 10 μg/m³ in NO₂ concentrations could lead to an increased mortality in cardiovascular, cerebrovascular of 1.89%, 2.07%, but the mechanism by which NO₂ contributes to cardiotoxicity is rarely reported. In order to assess the cardiotoxicity of NO₂ inhalation (5 ppm), we firstly investigate the change of gut microbiota, serum metabonomics and cardiac proteome. Non-targeted LC-MS/MS metabonomics showed that NO₂ stress could perturb the glycerophospholipid metabolism in the serum, which might destabilize the bilayer configuration of cardiac lipid membranes. Furthermore, we observed that NO₂ inhalation caused augmented intercellular gap and inflammatory infiltration in the heart. Although 16 S rRNA gene amplification sequencing demonstrated that NO₂ exposure did not influence the intestinal microbial abundance and diversity, but glycerophospholipid metabolism disruption might be finally reflected in gut microbiom dysregulation, such as Sphingomonas, Koribacter, Actinomarina and Bradyrhizobium Turicibacter, Rothia, Globicatella and Aerococcus. Proteome mining revealed that differentially expressed genes (DEGs) in the heart after NO₂ stress were involved in necroptosis, mitophagy and ferroptosis. We further revealed that NO₂ increased the number of cardiac mitochondria with depletion of cristae by regulating the expression of Mfn2 and Hsp70. This study indicating Mfn2-meidcated imbalanced mitochondrial dynamics as a potential mechanism after NO₂-induced heart injury and suggesting microbiome dysregulation/glycerophospholipid metabolism exerts critical roles in cardiotoxicity caused by NO₂.

Prognostic Value of a Novel Parameter in Patients with Infective Endocarditis

Background

Infective endocarditis (IE) has a high rate of mortality and the prognosis of IE was poor. The purpose of this investigation was to explore the value of lactate dehydrogenase (LDH)/lymphocyte and compare it with LDH/lymphocyte percentage (L-LWR) in predicting the in-hospital mortality in IE patients.

Methods

The investigation cohort contained 147 IE patients between January 2017 and December 2019. We retrospectively went over the medical records and selected admission indexes.

Results

Compared with IE patients with adverse events, significantly higher levels of LDH/lymphocyte and significantly lower levels of L-LWR were discovered in IE patients without adverse events. After adjustments, L-LWR (odds ratio (OR): 4.558, 95% confidence interval (CI) 1.362-15.256, P = 0.014) still maintained its significant independence. In addition, L-LWR had the highest area under curve (AUC) (0.780, 0.704-0.844, P < 0.001) with good sensitivity (81.89%) and specificity (65.00%) when 34 was selected as the best cutoff value.

Conclusions

L-LWR is a reliable, low-priced, easily applicable, and independent prognostic parameter for in-hospital death with good performance in patients with IE.

Machine learning-based in-hospital mortality prediction models for patients with acute coronary syndrome

OBJECTIVES

The purpose of this study is to identify the risk factors of in-hospital mortality in patients with acute coronary syndrome (ACS) and to evaluate the performance of traditional regression and machine learning prediction models.

METHODS

The data of ACS patients who entered the emergency department of Fujian Provincial Hospital from January 1, 2017 to March 31, 2020 for chest pain were retrospectively collected. The study used univariate and multivariate logistic regression analysis to identify risk factors for in-hospital mortality of ACS patients. The traditional regression and machine learning algorithms were used to develop predictive models, and the sensitivity, specificity, and receiver operating characteristic curve were used to evaluate the performance of each model.

RESULTS

A total of 6482 ACS patients were included in the study, and the in-hospital mortality rate was 1.88%. Multivariate logistic regression analysis found that age, NSTEMI, Killip III, Killip IV, and levels of D-dimer, cardiac troponin I, CK, N-terminal pro-B-type natriuretic peptide (NT-proBNP), high-density lipoprotein (HDL) cholesterol, and Stains were independent predictors of in-hospital mortality. The study found that the area under the receiver operating characteristic curve of the models developed by logistic regression, gradient boosting decision tree (GBDT), random forest, and support vector machine (SVM) for predicting the risk of in-hospital mortality were 0.884, 0.918, 0.913, and 0.896, respectively. Feature importance evaluation found that NT-proBNP, D-dimer, and Killip were top three variables that contribute the most to the prediction performance of the GBDT model and random forest model.

CONCLUSIONS

The predictive model developed using logistic regression, GBDT, random forest, and SVM algorithms can be used to predict the risk of in-hospital death of ACS patients. Based on our findings, we recommend that clinicians focus on monitoring the changes of NT-proBNP, D-dimer, Killip, cTnI, and LDH as this may improve the clinical outcomes of ACS patients.

Abnormal Coagulation Function of Patients With COVID-19 Is Significantly Related to Hypocalcemia and Severe Inflammation

This study aimed to detect, analyze, and correlate the clinical characteristics, blood coagulation functions, blood calcium levels, and inflammatory factors in patients with mild and severe COVID-19 infections. The enrolled COVID-19 infected patients were from Wuhan Jin Yin-tan Hospital (17 cases, Wuhan, China), Suzhou Infectious Disease Hospital (87 cases, Suzhou, China), and Xuzhou Infectious Disease Hospital (14 cases, Xuzhou, China). After admission, basic information was collected; X-ray and chest CT images were obtained; and data from routine blood tests, liver and kidney function, myocardial enzymes, electrolytes, blood coagulation function, (erythrocyte sedimentation rate) ESR, C-reactive protein (CRP), IL-6, procalcitonin (PCT), calcitonin, and other laboratory tests were obtained. The patients were grouped according to the clinical classification method based on the pneumonia diagnosis and treatment plan for new coronavirus infection (trial version 7) in China. The measurements from mild (56 cases) and severe cases (51 cases) were compared and analyzed. Most COVID-19 patients presented with fever. Chest X-ray and CT images showed multiple patchy and ground glass opacities in the lungs of COVID 19 infected patients, especially in patients with severe cases. Compared with patients with mild infection, patients with severe infection were older (p = 0.023) and had a significant increase in AST and BUN. The levels of CK, LDH, CK-MB, proBNP, and Myo in patients with severe COVID-19 infection were also increased significantly compared to those in patients with mild cases. Patients with severe COVID-19 infections presented coagulation dysfunction and increased D-dimer and fibrin degradation product (FDP) levels. Severe COVID-19 patients had low serum calcium ion (Ca²⁺) concentrations and high calcitonin and PCT levels and exhibited serious systemic inflammation. Ca²⁺ in COVID-19 patients was significantly negatively correlated with PCT, calcitonin, D-dimer, PFDP, ESR, CRP and IL-6. D-dimer in COVID-19 patients was a significantly positively correlated with CRP and IL-6. In conclusion, patients with severe COVID-19 infection presented significant metabolic dysfunction and abnormal blood coagulation, a sharp increase in inflammatory factors and calcitonin and procalcitonin levels, and a significant decrease in Ca²⁺. Decreased Ca²⁺ and coagulation dysfunction in COVID-19 patients were significantly correlated with each other and with inflammatory factors.

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.

Risk factors and electrocardiogram characteristics for mortality in critical inpatients with COVID-19

Background

The novel severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) has spread worldwide.

Hypothesis

The possible risk factors that lead to death in critical inpatients with coronavirus disease 2019 (COVID‐19) are not yet fully understood.

Methods

In this single‐center, retrospective study, we enrolled 113 critical patients with COVID‐19 from Renmin Hospital of Wuhan University between February 1, 2020 and March 15, 2020. Patients who survived or died were compared.

Results

A total of 113 critical patients with COVID‐19 were recruited; 50 (44.3%) died, and 63 (55.7%) recovered. The proportion of patients with ventricular arrhythmia was higher in the death group than in the recovery group (P = .021) and was higher among patients with myocardial damage than patients without myocardial damage (P = .013). Multivariate analysis confirmed independent predictors of mortality from COVID‐19: age > 70 years (HR 1.84, 95% CI 1.03‐3.28), initial neutrophil count over 6.5 × 10⁹/L (HR 3.43, 95% CI 1.84‐6.40), C‐reactive protein greater than 100 mg/L (HR 1.93, 95% CI 1.04‐3.59), and lactate dehydrogenase over 300 U/L (HR 2.90, 95% CI 1.26‐6.67). Immunoglobulin treatment (HR 0.39, 95% CI 0.21‐0.73) can reduce the risk of death. Sinus tachycardia (HR 2.94, 95% CI 1.16‐7.46) and ventricular arrhythmia (HR 2.79, 95% CI 1.11‐7.04) were independent ECG risk factors for mortality from COVID‐19.

Conclusions

Old age (>70 years), neutrophilia, C‐reactive protein greater than 100 mg/L and lactate dehydrogenase over 300 U/L are high‐risk factors for mortality in critical patients with COVID‐19. Sinus tachycardia and ventricular arrhythmia are independent ECG risk factors for mortality from COVID‐19.

Danshen (Salvia miltiorrhiza) restricts MD2/TLR4-MyD88 complex formation and signalling in acute myocardial infarction-induced heart failure

Heart failure (HF) represents a major public health burden. Inflammation has been shown to be a critical factor in the progression of HF, regardless of the aetiology. Disappointingly, the majority of clinical trials targeting aspects of inflammation in patients with HF have been largely negative. Many clinical researches demonstrate that danshen has a good efficacy on HF, and however, whether danshen exerts anti‐inflammatory effects against HF remains unclear. In our study, the employment of a water extracted and alcohol precipitated of danshen extract attenuated cardiac dysfunction and inflammation response in acute myocardial infarction‐induced HF rats. Transcriptome technique and validation results revealed that TLR4 signalling pathway was involved in the anti‐inflammation effects of danshen. In vitro, danshen reduced the release of inflammatory mediators in LPS‐stimulated RAW264.7 macrophage cells. Besides, the LPS‐stimulated macrophage conditioned media was applied to induce cardiac H9C2 cells injury, which could be attenuated by danshen. Furtherly, knock‐down and overexpression of TLR4 were utilized to confirm that danshen ameliorated inflammatory injury via MyD88‐dependent TLR4‐TRAF6‐NF‐κB signalling pathway in cardiomyocytes. Furthermore, by utilizing co‐immunoprecipitation, danshen was proved to suppress MD2/TLR4 complex formation and MyD88 recruitment. In conclusion, our results demonstrated that danshen ameliorates inflammatory injury by controlling MD2/TLR4‐MyD88 complex formation and TLR4‐TRAF6‐NF‐κB signalling pathway in acute myocardial infarction‐induced HF.

Prognostic value of lactate dehydrogenase for in-hospital mortality in severe and critically ill patients with COVID-19

Background: Lactate dehydrogenase (LDH) has been proved to be a prognostic factor for the severity and poor outcomes of coronavirus disease 2019 (COVID-19). In most studies, patients with various levels of COVID-19 severity were pooled and analyzed which may prevent accurate evaluation of the relationship between LDH and disease progression and in-hospital death. In this study, we aimed to evaluate the association of LDH with in-hospital mortality in severe and critically ill patients with COVID-19. Methods: This single-center retrospective study enrolled 119 patients. Survival curves were plotted using Kaplan-Meier method and compared by log-rank test. Multivariate Cox regression models were used to determine the independent risk factors for in-hospital mortality. Receiver-operator curves (ROCs) were constructed to evaluate the predictive accuracy of LDH and other prognostic biomarkers. Results: Compared to the survival group, LDH levels in the dead group were significantly higher [559.5 (172, 7575) U/L vs 228 (117, 490) U/L, (P < 0.001)]. In Multivariate Cox regression, it remained an independent risk factor for in-hospital mortality (Hazard ratio 5.985, 95.0%CI: 1.498-23.905; P=0.011). A cutoff value of 353.5 U/L predicted the in-hospital mortality with a sensitivity of 94.4% and a specificity of 89.2% respectively. Conclusion: LDH is a favorable prognostic biomarker with high accuracy for predicting in-hospital mortality in severe and critically ill patients with COVID-19. This may direct physicians worldwide to effectively prioritize resources for patients at high risk of death and to implement more aggressive treatments at an earlier phase to save patients' lives.