LABORATORIO DE URGENCIAS

 

 

Increased Lactate Dehydrogenase to Albumin Ratio - Mortality in Septic ICU Patients

 

A Retrospective Cohort Study

Xiaojia Xiao, MMed; Jia-Jun Wu, BM; Yao Liu, BM; Zhijun Suo, MMed; Haigang Zhang, MMed; Hong-Bo Xu, MD

 Medicine (2024) 103:52

 

 

Sepsis is a serious public health problem with high mortality and morbidity rates, causing a significant social burden.[1.
It has been reported that global age-standardized mortality for sepsis in 2017 was 148.1 deaths per 100,000 population.[2]
Early identification of septic patients at high risk of mortality is of significance, as it can contribute to timely and appropriate management of sepsis.[3]
Although several scoring systems have been used in clinical practice, their use is cumbersome and time consuming due to too many parameters. Therefore, it is still valuable to explore convenient and promising biomarkers for sepsis prognosis.
Lactate dehydrogenase (LDH) is an enzyme, catalyzes the last step of glycolysis.[4]
It has been considered as be a marker of cell injury and can reflect the degree of tissue damage.[5]
Several studies have reported that elevated LDH is related to poor outcome in patients with severe infection.[6–8]
On the other hand, albumin, mainly synthesized by the liver, is a multifunctional plasma protein.[9]
Hypoalbuminemia is common in critical illness such as sepsis, and associated with the intensity of the inflammatory response.[10]
Thus, LDH and albumin levels should be separated in sepsis. It may be reasonable to hypothesized that the ratio between LDH and albumin would provide integrated information as a strong prognostic marker for sepsis. In the present study, we aimed to investigate the association between admission LDH to albumin ratio (LAR) and 28-day and 90-day all-cause mortality in patients with sepsis

2.METHODS
2.1. Data sources
This retrospective study was conducted based on the Medical Information Mart for Intensive Care (MIMIC) IV database (version 2.1), which was approved by the Institutional Review Board of the Massachusetts Institute of Technology and Beth Israel Deaconess Medical Center. The MIMIC database contains comprehensive and high-quality data of patients admitted to intensive care units (ICUs). The informed consent was waived because all private information in the database depository has been removed to protect patient privacy. This study was reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology guidelines.
2.2. Study population
Adult septic patients were included in this study. Sepsis diagnosis was according to Sepsis 3.0 criteria.[12]
Patients met one of the following criteria were excluded: without LDH or albumin data during the first 24 hours after ICU admission, age < 18 years, and length of ICU stay < 24 hours. Moreover, if patients were admitted to the ICU more than once, only data from the first ICU admission were extracted.
2.3. Data extraction
We used PostgreSQL (version 9.6) to extract patient information from the MIMIC-IV database. These variables included demographics (age, sex, race), vital signs (temperature, respiratory rate, heart rate, mean arterial pressure, pulse oxygen saturations), comorbidities (myocardial infarction, congestive heart failure, diabetes mellitus, chronic pulmonary disease, liver disease, chronic kidney disease, cerebrovascular disease, malignant tumor, acute kidney injury, septic shock), laboratory parameters [white blood cells (WBC), platelets, hemoglobin, red blood cell distribution width (RDW), glucose, creatinine, blood urea nitrogen, bicarbonate, anion gap, sodium, potassium, international normalized ratio (INR), prothrombin time (PT), partial thromboplastin time (PTT), bilirubin, alanine aminotransferase, aspartate transaminase (AST), LDH, and albumin], scoring systems [sequential organ failure assessment (SOFA), simplified acute physiology score II (SAPS II)]. Only the first value was extract if a variable was measured more than once during the first 24 hours of ICU stay. Additionally, we extracted the data about
the use of ventilator and renal replacement treatment (RRT) within 24 hours after ICU admission. Comorbidities, with the exception of septic shock, were diagnosed in accordance with the International Classification of Diseases (ICD)-9 and ICD-10 codes. In this study, septic shock was defined as having received any vasopressor or inotropic infusion within 24 hours after ICU admission.[13]
LAR was calculated by the formula: LDH [IU/L] / albumin [g/dL]
2.4. Study endpoints
* The primary endpoint was 28-day all-cause mortality.
* The secondary endpoints was 90-day all-cause mortality.
2.5. Management of missing data and outliers
STATA software (version 14) was used to treat missing data and outliers. The details of missing data are provided in
supplementary materials (Table S1, Supplemental Digital Content,http://links.lww.com/MD/O209). To reduce bias, variables with missing values greater than 10% were excluded, and variables with missing values less than 10% were replaced with the mean or median as appropriate. The outliers were adjusted using the “winsor2” command with a replacement cut (1,99).
2.6. Statistical analysis
Patients were divided into 3 groups according to the tertiles of LAR for descriptive analysis. Continuous variables were expressed as mean ± standard deviation (SD) or median (interquartile range) and compared by one-way analysis of variance test or Kruskal-Wallis test if appropriate. Categorical variables were displayed as numbers (percentages) and analyzed using Chi-square or Fisher exact test where appropriate.
The survival curves for the 3 tertile groups were estimated using the Kaplan–Meier method and compared using the log-rank test. Multivariable Cox proportional hazards regression was conducted to investigate the association between LAR and 28- and 90-day mortality. Because LAR was skewed distributed, it was log2 transformed for regression analysis when it entered as a continuous variable. Adjusted covariates were selected according to clinical relevance and at least 10% change in effective estimate.[14]
The variance inflation factor was calculated to detect multicollinearity and variance inflation factor greater than 5 was considered an indicator of multicollinearity. Crude model was adjusted for nothing. Model 1 was adjusted for age,sex and race. Model 2 was additionally adjusted for myocardial infarction, congestive heart failure, diabetes mellitus, chronic pulmonary disease, liver disease, chronic kidney disease, cerebrovascular disease, malignant tumor, acute kidney injury, septic shock, mechanical ventilation, renal replacement therapy, SOFA and SAPSII score. Model 3 was further adjusted for mean arterial pressure, WBC, Hemoglobin, platelet, RDW, glucose, creatinine, bicarbonate, anion gap, INR, bilirubin and AST. Restricted cubic spline Cox regression analysis was performed to assess the shape
of the association between LAR and outcomes. If a non-linearvrelationship was found, a two-piecewise linear regression modelvwas conducted to determine the threshold effect of LAR onvsurvival outcome. To assess the robustness of the findings, stratifiedvanalysis was conducted through different subgroups, including sex, age (≥65 and <65), race, myocardial infarct, congestive heart failure, diabetes mellitus, chronic pulmonary disease, liver disease, chronic kidney disease, cerebrovascular disease, malignant tumor, acute kidney injury, septic shock, use of ventilator,      RRT, SOFA score (≥8 and <8) and SAPS II score (≥40 and <40).
Moreover, we conducted 2 sensitivity analyses. First, patients with missing values were excluded. Second, patients who were administrated human serum albumin between 1 day before ICU admission and 6 hours after ICU admission were excluded, given the potential effect of the infusion of human serum albumin on plasma levels. We also performed receiver operating 3 characteristic (ROC) curve analysis to assess whether LAR, in combination with SAPS II score and SOFA score, could improve the predictive value for 28-day mortality in sepsis. Statistical analyses were performed using the R software (version 4.2.1) and Free Statistics software (version 1.7.1). A two-sided P < .05 was considered statistically significant.

3.RESULTS
3.1. Baseline characteristics In this study, a total of 5784 patients with sepsis were finally enrolled. The baseline characteristics are displayed in the Table 1. The patients’ mean age was 64.0 ± 17.1 years, and 57.1% of them were male, while 61.9% were white. The 28 and 90-day mortality rates of all patients were 26.5% and 34.3%, respectively. Patients with higher LAR values had an increased probability of mortality. With an increase of LAR, there was an increase in levels of WBC, RDW, glucose, creatinine, anion gap, potassium, INR, PT, PPT, alanine aminotransferase, AST, bilirubin, LDH, while the platelet, bicarbonate levels decreased.
Patients with a higher LAR were more likely to have comorbidities such as myocardial infarction, liver disease, malignancy, acute kidney injury and septic shock, and less likely to have co-morbidities such as diabetes mellitus, chronic kidney disease or cerebrovascular disease. In addition, patients with higher LAR values had higher SOFA and SAPS II scores, and required support of from ventilator and RRT.
3.2. Association between LAR and clinical outcomes
The survival curves for 28-day mortality according to the LAR tertiles, showing that septic patients in the low LAR group had a significantly higher 28-day survival rate (P for log-rank test < 0.0001). Similar results were found regarding the 90-day mortality (P for log-rank test < 0.0001) (Fig. 2B).
The results of the Cox regression analysis for the association between LAR and short-term mortality in septic patients are presented in Table 2. It was showed that a higher log2-LAR was independently associated with the risk of 28-day all-cause mortality [crude model: hazard ratio (HR) = 1.36, 95% confidence interval (CI) = 1.32–1.41; model 1: HR = 1.43, 95% CI = 1.38– 1.47; model 2: HR = 1.21, 95% CI = 1.17–1.26; model 3: HR = 1.36, 95% CI = 1.29–1.42; all P < .001].
We also analyzed LAR as a categorical variable according to its tertile, using the first tertile group as a reference. The HRs were 1.84 (95% CI 1.59–2.13) and 3.15 (95% CI 2.74–3.61) for the second and third tertile groups, respectively, in the crude model. The results remained consistent in 3 other adjusted models (Table 2). Furthermore, similar results were also observed for the association between LAR and 90-day all-cause mortality (Table 2).
Furthermore, we used multivariable adjusted restricted cubic spline Cox regression to explore the shape of the association between log2-LAR and mortality risk, and found that there was a linear relationship between log2-LAR and 28-day/90-day mortality in septic patients (Figure S1)..
3.3. Subgroup analysis
The results of subgroup analyses regarding the association between log2-LAR and 28-day all-cause mortality. (Figure3)  The trend in effect size was consistent across allsubgroups. There were significant interactions in these subgroups, including sex, liver disease, chronic kidney disease, cerebrovascular disease, acute kidney disease, SASP II and SOFA (all P for interaction < .05). Males with sepsis were at higher risk of 28-day mortality as log2-LAR increased (HR = 1.40, 95% CI = 1.31–1.49).
Similarly, septic patients without comorbidities of liver disease, chronic kidney disease, cerebrovascular disease, or acute kidney disease had a significant higher risk of 28-day mortality with the increasing log2-LAR (HR = 1.40, 95% CI = 1.32–1.49, HR = 1.38, 95% CI = 1.31–1.46, HR = 1.38, 95% CI = 1.31–1.45, HR = 1.50, 95% CI = 1.36–1.65,4 respectively). Additionally, septic patients with lower SOFA (<8) or SAPS II scores (<40) had a significant higher risk of 28-day mortality (HR = 1.52, 95% CI = 1.39–1.67, HR = 1.60, 95% CI = 1.42–1.80, respectively). The stratified analysis for 90-day mortality showed similar results .
3.4. Sensitivity analysis
In order to verify the stability of our findings, we conducted 2 sensitivity analyses. The association between LAR and 28-day and 90-day mortality in sepsis patients remained strong after excluding patients with missing values (Table S2) Additionally, this associations were still reliable, when patients who were administrated human serum albumin between 1 day before ICU admission and 6 hours after ICU admission were excluded (Table S3).

4.DISCUSSION
In this study, we investigated the association between LAR and short-term mortality in septic patients using data from robustness. Our findings suggest that LAR is a promising biomarker for identifying septic patients at a higher risk of shortterm mortality. LDH has been widely proposed to be a prognostic indicator in several diseases, including sepsis.[15,16]
During sepsis, LDH levels can increase due to multiple factors, including cell injury, hypoxia, inflammation, and liver and kidney dysfunction. LDH is a marker of cell injury.[5] The immune response in the progression of sepsis
can cause damage to cells, leading to an increase in LDH levels.[7]
Sepsis can also cause a decrease in oxygen delivery to tissues, leading to hypoxia.[17] When cells enter a hypoxic-ischemia state, LDH levels can rise dramatically within minutes, indicating that the cells are in a state of stress.[18]
Additionally, cell injuries due to localized infection and organ injuries due to systemic inflammatory response or shock increase serum LDH levels, which makes LDH a useful tool for identifying tissue damage due to injury or
disease.[19]
Furthermore, it has been reported that serum levels of LDH was positively related to interleukin-1β and lactate levels.[15] Therefore, the increased level of LDH may reflect the extent of tissue damage, inflammatory response, necrosis and hypoxia.
Albumin plays an important role in various physiological processes such as blood volume regulation, immune modulation, antioxidation, nutrition and transportation.[9,10]
Hypoalbuminemia is common in critical illnesses and is considered a risk factor for adverse outcomes in many conditions, such as sepsis.[20,21] Though hypoalbuminemia reflects undernutrition, it is more likely to reflect the degree of physiological stress caused by disease-related or trauma-induced inflammation.[10]
In the early stages of sepsis, elevated interleukin-1 or tumor necrosis factor can induce the decreased albumin production in the liver through the potential inflammatory state, which is the common cause of hypoalbuminemia.[22]
With infection progression, sepsis causes systemic inflammatory factors, which can impair vascular endothelium function and increase capillary vessel permeability, leading to albumin leakage from the vessels and a decrease in plasma albumin levels.[23,24]
In addition, sepsis-induced kidney injury leads to proteinuria via glomerular infiltration upregulation and cause albumin leakage.[25]
Moreover, impaired gastrointestinal function during sepsis also contributes to hypoalbuminemia due to nutrient malabsorption.[26] Thus, hypoalbuminemia in sepsis may be an indicator of system inflammatory, capillary leakage and organ damage, all of which are related to sepsis prognosis.Given the above, it may explain the association of elevated LAR values with a high risk of mortality in sepsis. LAR has also been suggested as an independent predictor of poor outcome in several conditions. One study reported that LAR was an independent prognostic factor for in-hospital mortality in patients with lower respiratory tract infections.[27]
The  study had several limitations that should be acknowledged. First, our study was a single-center retrospective study with inherent limitations regarding selection bias and residual confounding. Second, LAR was only collected at ICU admission, thus, it could not reflect the association of dynamic changes in LAR and sepsis prognosis. Third, the causality between LAR and sepsis mortality cannot be speculated from this study due to the nature of the observational study. In spite of these limitations, our study is meaningful as LAR could be a prognostic biomarker for septic patients. Further large-scale, multicenter prospective studies are required in the future.

5.CONCLUSION
Elevated LAR was found to be significantly associated with an increased risk of all-cause mortality at 28 and 90 days in septic patients. LAR was suggested to be promising biomarker for identifying septic patients with a higher risk of short-term mortality
These findings indicated that higher LAR was associated with poor prognosis compared with lower LAR values, which was consistent with our study. Additional stratified and sensitivity analyses showed the consistent trend of the effect size (all HR > 1), suggesting the reliability of the association of LAR and sepsis prognosis.
In this study, we found that the area under the ROC curve of LAR was superior to LAH and albumin alone, and similar to SOFA. However, the AUC of LAR was lower than that of SAPS II. Considering the convenience of LAR over SAPS II, the potential value of LAR should be acknowledged to some extent.
Furthermore, we observed that the area under the ROC curve increased when LAR was combined with SOFA score and SAPS II score, suggesting that the combination improves the predictive power for mortality.

NOTE: The complete work, graphs, and tables can be consulted in the publication mentioned at the beginning.

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