Literature DB >> 33145337

Serum lactate dehydrogenase level may predict acute respiratory distress syndrome of patients with fever infected by SARS-CoV-2.

Yang Zhou1,2, Ning Ding1,2, Guifang Yang1,2, Wen Peng1,2, Fengning Tang3, Cuirong Guo3, Xiangping Chai1,2.   

Abstract

Entities:  

Year:  2020        PMID: 33145337      PMCID: PMC7575930          DOI: 10.21037/atm-20-2411

Source DB:  PubMed          Journal:  Ann Transl Med        ISSN: 2305-5839


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As of March 9, 2020, more than 100,000 cases of coronavirus disease-2019 (COVID-19) were reported in more than 100 countries with thousands deaths globally. It is now known that Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is a new type of coronavirus causing COVID-19 infection (1). The most common clinical feature of SARS-CoV-2 infection is fever (2). Moreover, acute respiratory distress syndrome (ARDS) is the most frequent cause of admission to intensive care unit in COVID-19 patients (1). Lactate dehydrogenase (LDH), a key enzyme in the glycolytic pathway and a cytoplasmic enzyme found in most organs, has been linked to inflammation response and cell damage. Currently, the role of serum LDH levels in ARDS patients infected by SARS-CoV-2 is unclear. Between January 30 and Feb 22, 2020, 77 fever patients diagnosed with SARS-CoV-2 infection were admitted to the hospital of Changsha Public Health Center. In all patients, fever was defined assessed as follows: reported a fever history during the time from the onset symptom to admission, fever was defined as a rise in body temperature and presence of axillary temperature ≥37.0 °C. Exclusion criteria included onset symptoms without fever, and patients with cancer. Clinical information of COVID-19 patients such as age, gender, days from onset of symptoms, medical history, physical examination, clinical presentation, laboratory tests, and imaging studies during admission were collected. Laboratory findings including erythrocyte sedimentation rate, C-reactive protein, procalcitonin, liver and renal function, blood chemistry, coagulation test, complete blood count, LDH and creatine kinase were collected. ARDS was diagnosed as a decrease in the PaO2/FiO2 index below 300 mmHg according to the Berlin definition. Data were statistical analyzed with Student’s t-test, Mann-Whitney U-test, Fisher exact test and Chi-square analysis. Variables that were significant on univariate analysis were included in multivariate logistic regression analysis. Receiver-operator characteristic (ROC) analysis for ARDS was applied to determine the cut-off point and area under the curve (AUC). Survival curves without ARDS were established using Kaplan-Meier method and the log-rank test. The 77 fever patients were categorized as non-ARDS group (n=63, 81.81%) and ARDS group (n=14, 18.19%). The baseline characteristics are shown in . Univariate and multivariable regression analyses identified that serum LDH level was a predictor of ARDS in SARS-CoV-2-infected patients with fever (, OR: 1.02; 95% CI, 1.00–1.04). The AUC of ROC curve showing the ability of LDH levels to predict development of ARDS was 0.809, and the best threshold of ≥273 U/L on admission revealed a sensitivity of 57.1% and a specificity of 93.7% (). Survival curves for development of ARDS are showed in . Analysis of the curves indicate that patients with LDH ≥273 U/L are more likely to develop ARDS (P<0.001, log-rank test).
Table 1

Characteristics of SARS-CoV-2-infected patients with fever

CharacteristicsTotal (n=77)Non-ARDS (n=63)ARDS (n=14)P value
Age, years, mean (SD)47.99±15.7546.37±15.6555.29±14.570.055
Gender, n (%)0.073
   Female33 (42.86%)30 (47.62%)3 (21.43%)
   Male44 (57.14%)33 (52.38%)11 (78.57%)
Hubei exposure52 (67.53%)42 (66.67%)10 (71.43%)0.731
Systolic pressure, mmHg, mean (SD)124.47±11.87124.95±11.88122.29±12.030.451
Diastolic pressure, mmHg, mean (SD)78.30±8.9678.70±9.1776.50±8.030.410
Heart rate, beats per min, mean (SD)91.01±13.8788.73±13.44101.29±11.160.002
Respiratory rate, IQR20 [20, 21]20 [20, 20]21.5 [20, 23]<0.001
Days from illness onset to first hospital admission (days), IQR5 [3, 7]5 [3, 7.5]4.5 [3, 6.75]0.779
Signs and symptoms, n (%)
   Fatigue32 (41.56%)27 (42.86%)5 (35.71%)0.624
   Cough48 (62.34%)38 (60.32%)10 (71.43%)0.438
   Anorexia2 (2.60%)2 (3.17%)0 (0.00%)0.499
   Myalgia8 (10.39%)6 (9.52%)2 (14.29%)0.597
   Dyspnea11 (14.29%)5 (7.94%)6 (42.86%)<0.001
   Expectoration20 (25.97%)18 (28.57%)2 (14.29%)0.270
   Sore throat5 (6.49%)5 (7.94%)0 (0.00%)0.276
   Dizziness3 (3.90%)3 (4.76%)0 (0.00%)0.405
   Headache7 (9.09%)5 (7.94%)2 (14.29%)0.455
Any comorbidity, n (%)
   Hypertension14 (18.18%)9 (14.29%)5 (35.71%)0.060
   Cardiovascular disease3 (3.90%)2 (3.17%)1 (7.14%)0.488
   Diabetes4 (5.19%)3 (4.76%)1 (7.14%)0.717
Laboratory tests
   White blood cell count, ×109/L, mean (SD)4.52±1.524.62±1.414.07±1.910.076
   Neutrophil count, ×109/L, mean (SD)3.05±1.303.04±1.203.14±1.720.787
   Lymphocyte count, ×109/L, mean (SD)1.52±3.631.69±4.000.75±0.340.001
   Hemoglobin, g/L, mean (SD)130.16±21.49128.98±22.67135.43±14.620.313
   Platelet count, ×109/L, mean (SD)173.06±113.71177.16±123.21154.64±52.430.506
   C-reactive protein, mg/L, mean (SD)19.8 (8.6, 39)16.2 (7.6, 38.1)33 (21.9, 74.8)0.011
   Procalcitonin, ng/mL, IQR0.05 (0.05, 0.05)0.05 (0.05, 0.05)0.05 (0.05, 0.05)0.465
   Erythrocyte sedimentation rate, mm/h, IQR48 [27, 72]46 [25, 77]51.5 [45.5, 66]0.837
   Alanine aminotransferase, U/L, mean (SD)24.90±12.8424.44±13.0126.98±12.290.507
   Aspartate aminotransferase, U/L, mean (SD)30.09±14.0327.87±11.6340.08±19.320.003
   Albumin, g/L, IQR37 [34.7, 39.1]38 [35, 40]34 [31.9, 35.6]0.002
   Total bilirubin, mmol/L, mean (SD)12.64±5.2112.61±5.2912.79±5.070.909
   Direct bilirubin, mmol/L, mean (SD)4.64±2.394.52±2.305.19±2.780.343
   Lactate dehydrogenase, U/L, mean (SD)204.30±75.70187.88±61.97278.20±89.41<0.001
   Creatinine, μmol/L, mean (SD)56.17±24.6656.78±26.5753.42±13.360.648
   Blood urea nitrogen, mmol/L, mean (SD)4.43±1.874.26±1.895.18±1.600.097
   Uric acid, μmol/L, mean (SD)258.68±99.46261.41±104.09246.41±77.220.613
   Prothrombin time, s, mean (SD)11.95±0.9811.83±1.0012.50±0.670.020
   Activated partial thromboplastin time, s, mean (SD)32.94±3.5733.06±3.6632.39±3.200.526
   D-dimer, ug/mL, IQR0.2 (0.1-0.4)0.2(0.1, 0.4)0.4 (0.1, 0.5)0.065
Chest radiography, n (%)
   Unilateral pneumonia6 (7.79%)6 (9.52%)0 (0.00%)0.229
   Bilateral pneumonia64 (83.12%)50 (79.37%)14 (100.00%)0.062

SARS-CoV-2, severe acute respiratory syndrome coronavirus-2; ARDS, acute respiratory distress syndrome; IQR, interquartile range; SD, standard deviation.

Table 2

Univariate and Multivariate analyses for the association between SARS-CoV-2-infected patients with ARDS and without ARDS

CharacteristicsUnivariate analysisMultivariate analysis
OR95% CIP valueOR95% CIP value
Lactate dehydrogenase, U/L1.01(1.01, 1.02)0.0011.02(1.00, 1.04)0.020
Aspartate aminotransferase, U/L1.05(1.01, 1.10)0.0081.00(0.93, 1.07)0.964
Albumin, g/L0.81(0.69, 0.95)0.0091.00(0.70, 1.35)0.862
Prothrombin time, s2.07(1.09, 3.93)0.0261.42(0.46, 4.35)0.617
Lymphocyte count, ×109/L0.05(0.01, 0.40)0.0050.19(0.01, 3.38)0.261
C-reactive protein, mg/L1.03(1.00, 1.05)0.0160.99(0.94, 1.03)0.487
Heart rate, beats per min1.08(1.02, 1.14)0.0041.10(1.00, 1.21)0.059
Respiratory rate, breaths per min1.76(1.16, 2.67)0.0082.00(0.97, 4.13)0.062
Dyspnea8.70(2.15, 35.22)0.0022.15(0.11, 42.83)0.617

SARS-CoV-2, severe acute respiratory syndrome coronavirus-2; OR, odds ratio; CI, confidence interval.

Figure 1

Receiver operating characteristic curves. The AUC value of LDH in predicting ARDS. Blue shading shows the bootstrap estimated 95% CI with AUC. LDH, lactate dehydrogenase; ARDS, acute respiratory distress syndrome.

Figure 2

Kaplan-Meier curve showing development of ARDS in SARS-CoV-2-infected patients with fever stratified by LDH levels < and ≥273 U/L on admission. LDH, lactate dehydrogenase; ARDS, acute respiratory distress syndrome.

SARS-CoV-2, severe acute respiratory syndrome coronavirus-2; ARDS, acute respiratory distress syndrome; IQR, interquartile range; SD, standard deviation. SARS-CoV-2, severe acute respiratory syndrome coronavirus-2; OR, odds ratio; CI, confidence interval. Receiver operating characteristic curves. The AUC value of LDH in predicting ARDS. Blue shading shows the bootstrap estimated 95% CI with AUC. LDH, lactate dehydrogenase; ARDS, acute respiratory distress syndrome. Kaplan-Meier curve showing development of ARDS in SARS-CoV-2-infected patients with fever stratified by LDH levels < and ≥273 U/L on admission. LDH, lactate dehydrogenase; ARDS, acute respiratory distress syndrome. LDH is an important enzyme in anaerobic metabolism in almost all living organisms (3). Several studies suggested that serum LDH was elevated in severe COVID-19 patients (4,5). Consistently, we show that patients infected by SARS-CoV-2 with high levels of LDH on admission are more likely to develop ARDS. Inflammation and cell damage play an important role in the pathological processes of pulmonary tissues (6). Higher LDH levels have been found in COVID-19 patients than in patients with SARS-CoV-2 negative confirmed pneumonia (7). Yuan et al. found that COVID-19 mRNA clearance ratio was highly associated with LDH levels (8). Research has shown that SARS-CoV-2 as a positive-sense RNA virus may activate inflammasomes, leading to cellular pyroptosis and aggressive symptoms (9). This may partly explain the association of LDH with ARDS in COVID-19 patients. However, we found that the best threshold for predicting ARDS was 273 U/L. LDH level was independently associated with ARDS, and could strongly predict the incidence of ARDS. To our knowledge, this is the first study reporting the association of LDH with ARDS in COVID-19 patients with fever on admission. Our findings will help physicians to evaluate the condition of the illness at an earlier stage. However, we note the following limitations to our study. First, this is a single-center retrospective study. Secondly, the serum level of LDH was only tested on admission. Thus, it should be tested at different times for better evaluation of its predicting value. Third, since all patients were from Changsha, our results may not apply to other regions since the clinical features of COVID-19 may vary in other regions. The article’s supplementary files as
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