Predictive Value of Lactate Dehydrogenase to Albumin Ratio (LAR) in Patients With Coronavirus Disease 2019 (COVID-19)

Abstract


Results
The study included 321 patients with COVID-19. The median age of the 321 patients was 63.0 (IQR 51.0-70.0), ranging from 19 to 95 years old and 180 (56.1%) patients were male. 142 (44.2%) patients had 1 or more coexisting comorbidity. The most common symptoms on admission were fever(289[90%]) and cough(258[80.4%]). In multivariable logistic regression, only older age (OR, 1.11; 95% CI, 1.05-1.16), WBC count (OR, 1.26; 95% CI, 1.11-1.44), lymphocyte count (OR, 0.78; 95% CI, 0.62-0.99) and LAR (OR, 1.29; 95% CI, 1.18-1.40) were found to be signi cantly associated with in-hospital death. ROC analysis showed that LAR had a higher AUC (0.917) and the highest speci city(84.0%) and sensitivity(84.6%). Furthermore, the results showed that LAR had a higher AUC (0.931) to differentiate critical from mild patients and had a sensitivity of 87.7% and a speci city of 82.1%. Besides, LAR had an AUC (0.861) to differentiate critical from severe patients and had a sensitivity of 86.0% and a speci city of 73.8% and the role of LAR to distinguish severe from mild patients was the worst.

Conclusions
To the best of our knowledge, this study is the rst for us to explore the predictive value of LAR for inhospital mortality and disease severity. A high LAR appears to predict higher odds of mortality and differentiate critical patients from mild or severe COVID-19 patients.

Background
Coronavirus Disease-2019 (COVID- 19) is an emerging acute infectious disease that was rst discovered in Wuhan, Hubei Province, China. Since then, it has quickly spread to over one hundred cities around the world. By December 1, 2020, more than 60 million people were infected with COVID-19, including more than 1.53 million deaths. The virus is considered to be transmitted human-to-human by close contact and respiratory droplets, and people of all ages are susceptible to this virus (1,2). The clinical characteristics of COVID-19 patients have been shown in recent studies (1,2). The main common clinical symptoms at the onset of the patients were dry-cough, fever, fatigue or myalgia. However, COVID-19 is capable of causing a series of illness ranging from asymptomatic infection to organ dysfunction such as acute respiratory distress syndrome (ARDS), acute liver injury, acute cardiac injury, acute kidney injury requiring intensive care unit (ICU) admission and even death also occur in the severe cases. However effective drugs are lacking and management remains mainly supportive. The majority of these mildly infected individuals had a good prognosis (1,3) ,while it was reported that the in-hospital mortality was very high among severe and critical patients (4). According to published data focus on COVID-19, the overall mortality rate was between 2.3% and 28.3% (5,6). Meanwhile, the mortality rate was up to 49% among critical individuals (6). Therefore, it is crucial to identify the risk factors of in-hospital mortality and disease severity for COVID-19 patients.
Several studies indicated that older patients with comorbidities, many laboratory biomarkers (such as peripheral blood in ammatory cells, cardiac troponin I, D-dimer, cytokines) and biomarker ratio (such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), IL-2R/lymphocytes and lymphocyte-to-C-reactive protein ratio (LCR)) were related with clinical progression and mortality of COVID-19 (7)(8)(9)(10)(11). Meanwhile, several studies have shown that increased lactate dehydrogenase and reduced serum albumin levels were risk factors associated with severity and in-hospital death (12)(13)(14), but the predictive role is still controversial among different studies. Based on the above, we proposed a biomarker ratio, lactate dehydrogenase to albumin ratio (LAR), may be more reliable than the predictive effect of either lactate dehydrogenase or albumin. Therefore, the purpose of our study was initiated to assess the predictive value of LAR for in-hospital mortality and early identi cation of critical COVID-19 patients.

Study design and patients
This was a retrospective study of all patients who were diagnosed with a laboratory-con rmed COVID-19 infection from 1 February to 29 February, 2020 in the Tongji hospital a liated to Huazhong University of Science and Technology. Patients were tracked until discharge from the hospital or death. We treated this cohort of patients with the latest version of the guidelines of Diagnosis and Treatment of Pneumonitis caused by the novel coronavirus. COVID-19 infection was con rmed by real-time RT-PCR testing of throatswab specimens or respiratory specimens. Laboratory investigations and chest computed tomography scans were also done for all inpatients. The treating physicians determined the frequency of related examinations. The medical interventions included antiviral therapy, antibiotics, corticosteroid therapy, oxygen support, renal replacement therapy and other corresponding treatment. Patients younger than 18 years were excluded. This study was approved by the Ethics Commission of 1st hospital a liated to Jilin University (No. 2020-405). Given the particularity of patients with COVID-19, the requirement for informed consent was waived.

Data collection
Data on the following parameters were collected from the medical records: demographic data: age, gender, underlying comorbid conditions(chronic heart disease, chronic lung disease, chronic kidney disease, chronic liver disease, hypertension, diabetes mellitus, and carcinoma), clinical symptoms at the onset of illness (fever, cough, sputum production, chest pain, myalgia or arthralgia, fatigue and confusion), laboratory results and outcomes(discharge or death). All COVID-19 patients were evaluated of different illness severity after admission, according to the guidelines of diagnosis and treatment for COVID-19 (Trial 6th edition) set by the National Health Commission of China. The COVID-19 is clinically classi ed as mild, severe and critically ill patients: mild patients had a fever, respiratory symptoms and radiological imaging showed pneumonia; severe patients were de ned if any of the following items was met: (1) shortness of breath with respiration rate ≥ 30 times per minute, (2) blood oxygen saturation ≤ 93% at resting time, (3) PaO2/FiO2 ≤ 300 mmHg; critically ill patients were de ned as those who required mechanical ventilation, shock and/or concomitant organ failure needing intensive care unit treatment. The discharge criteria included the following aspects: (1) normal temperature for more than 3 days; (2) signi cant subjective improvement in respiratory symptoms; (3) signi cant improvement in acute exudative in ammation of lung; (4) negative nucleic acid test at less twice (with the sampling interval ≥ 1 day). All the collected information was checked for missing or invalid data. Two researchers also independently reviewed the data collection forms to double check the data collected.

Statistical analysis
Continuous variables were expressed as mean ± standard deviation(SD) or median and interquartile ranges(IQR) and categorical variables were presented as number (%). The chi-square (χ 2 ) test was used to compare categorical variables. For normally and abnormally distributed continuous data, the independent sample t-test and Mann-Whitney U test were used, respectively. Multivariable logistic regression models were used to explore the risk factors associated with in-hospital mortality. The area under the receiver operating characteristic (ROC) curve was used to analyze the ability of LAR for predicting in-hospital mortality and distinguishing severity of COVID-19. The area under the curve (AUC), sensitivity and speci city were recorded. The odds ratio (OR) and 95% con dence interval (CI) were obtained for each variable. The difference was considered statistically signi cant when P < 0.05. All statistical analysis were performed using SPSS19.0 software (SPSS Inc, Chicago, USA).

Results
The study population included 321 patients with COVID- 19 The results of demographic, clinical characteristics and laboratory biomarkers in survivor and nonsurvivor groups are compared in Table 1. In univariable analysis, age, male, coexisting comorbidity, fever, sputum production, shortness of breath, and confusion were signi cantly different between survivor and non-survivor group (Table 1). We observed that white blood cell count, neutrophil count, aspartate aminotransferase, total bilirubin, creatinine, and lactate dehydrogenase were signi cantly increased, while lymphocyte count and platelet count were signi cantly decreased in non-survivors compared with survivors. We then further calculated the ratio of lactate dehydrogenase to albumin and found that the value of LAR was remarkably increased in non-survivors (    Then, all statistically signi cant variables were taken as candidates for ROC analysis and the optimal cutoff values calculated by the ROC analysis, and the areas under the curve(AUC) was presented in Fig. 1. ROC analysis showed that LAR had a higher AUC (0.917) than age (0.722), WBC count (0.779), lymphocyte count (0.188) to predict in-hospital death ( Table 3). The optimal cut-off values were 12.3 for LAR and the highest speci city and sensitivity were 84.0% and 84.6%. The test result variables: Age, WBC count, Lymphocyte count, LAR has at least one tie between the positive actual state group and the negative actual state group. Statistics may be biased. † Under the nonparametric assumption. ‡ Null hypothesis: true area = 0.5. Lymphocyte count* means lymphocyte count after negative calculation. Abbreviation: LAR= lactate dehydrogenase to albumin ratio.
Furthermore, to evaluate whether LAR plays a role in predicting disease severity, we also perform another ROC analysis. First, we divided the clinical classi cation of OVID-19 into three groups with different severity of illness : mild (n = 184), severe (n = 80) and critical (n = 57) patients. The results showed that LAR had a higher AUC (0.931) to differentiate critical from mild patients and had a sensitivity of 87.7% and a speci city of 82.1% (Fig. 2a). Besides, LAR had an AUC (0.861) to differentiate critical from severe patients and had a sensitivity of 86.0% and a speci city of 73.8% (Fig. 2b) and the role of LAR to distinguish severe from mild patients was the worst (Fig. 2c).

Discussion
This retrospective study included 321 COVID-19 patients and the total in-hospital mortality was 16.2%. And our study identi ed several risk factors for death in adults hospitalized with COVID-19 in Wuhan. In particular, older age, elevated WBC count, decreased lymphocyte count on admission were associated with higher odds of in-hospital death. Additionally, we found a new biomarker ratio, LAR was associated with higher odds of in-hospital death and critical illness.
In previous studies, older age has been identi ed as a signi cant independent predictor of in-hospital mortality in Middle East respiratory syndrome (MERS) and severe acute respiratory syndrome (SARS) (15)(16)(17). Similarly, several recent studies about COVID-19 also con rmed that COVID-19 was shown to tend to infect older age patients (13). Older age may be associated with coexisting comorbidities and thus increasing the in-hospital death rate. In the non-survivor group, most of the patients(69.2%) had one or more coexisting comorbidity. Our study showed that deceased patients had higher WBC count of 9.4(5. Previous studies also showed similar results (18,19). Our data indicated that the increase in white blood cell count is driven by elevated neutrophil count which may be related with concomitant infections. With the virus infection(such as SARS, MERS-CoV And COVID- 19), it was suspected that lymphocytes are essential to eliminating virally infected cells that result in the apoptosis of lymphocytes,especially CD4 + T lymphocytes and CD8 + T lymphocytes (20).
According to researches, the pathogenic mechanism of COVID-19 might cause cytokine storm syndromes and pulmonary tissue damage by a strong immune response. LDH is a cytoplasmic glycolytic enzyme found in almost every tissue and serum LDH was associated with a systemic in ammatory response in many pulmonary diseases and cancer prognosis (21)(22)(23). Several recent studies indicated that high LDH level was risk factors for in-hospital mortality and was used as predictor of the disease severity in COVID-19 patients (5,24,25). The potential mechanism may be that the elevated LDH level was related with lung and tissue damage and systemic in ammatory response in severe COVID-19 patients (24). Previous studies indicated that low serum albumin has been also associated with adverse outcomes in COVID-19 patients (26,27). Albumin is a water-soluble protein which is associated with nutritional status and systemic in ammatory response. However, the current study results about LDH and albumin were not consistent. LDH and albumin are both routinely tested laboratory markers in clinical practice, which makes them easily available. Just like the LCR is typically used as a prognostic marker for cancer, the LAR is rst used as a potential prognostic marker for esophageal squamous cell carcinoma [21] . To the best of our knowledge, we have rstly proposed LAR may be an effective predictor for in-hospital mortality and early identi cation of critical COVID-19 patients. LAR may serve to highlight a relatively elevated LDH or decreased albumin and have a better predictive effect. In our study, we found LAR (OR, 1.29; 95% CI, 1.18-1.40) was signi cantly associated with mortality in COVID patients and had a higher AUC (0.917) than age(0.722), WBC count(0.779), lymphocyte count(0.188) to predict in-hospital death.
The optimal cut-off values were 12.3 for LAR and the highest speci city and sensitivity were 84.0% and 84.6%. In multivariable logistic regression, LDH and albumin were not independent risk factors for inhospital mortality. Thus, LAR may be more sensitive and speci c in re ecting systemic in ammation than LDH or albumin. Besides, the role of LAR showed higher sensitivity(87.7%) and speci city(82.1%) in differentiating critical patients from mild or severe patients and health-care workers could pay more attention to critical patients and improve survival rate.
Several notable limitations should be mentioned in this study. First, this study is a retrospective research and not all clinical characteristics and laboratory biomarkers have been obtained, such as cytokines and coagulation markers. Therefore, the role of LAR might be underestimated in predicting in-hospital death and disease severity. Second, laboratory biomarkers were measured on admission and continuous monitoring and comparison is limited. Finally, the validity of the predictive value of LAR derived from our cohort remains tentative and further validation from multicenter research is necessary.

Conclusions
To the best of our knowledge, this study is the rst for us to explore the predictive value of LAR for inhospital mortality and disease severity. A high LAR appears to predict higher odds of mortality and differentiate critical patients from mild or severe COVID-19 patients. However, further large-scale studies are needed to evaluate the bene ts of LAR in COVID-19.  Legend: Lymphocyte count* means lymphocyte count after negative calculation