Research article/ Open Access
DOI:10.31488/EJRM.136
Biomarkers as Prognosis of COVID-19 Disease: Retrospective Cohort Study
Priscila Matovelle-Ochoa1,2, Barbara Oliván-Blázquez3,4,5*, Rosa Magallón-Botaya2,3,4,6, Itziar Lamiquiz-Moneo7,8, Fátima Méndez-López3,4, Cruz Bartolomé-Moreno3,4,6,9
1. Geriatrics Department, San Juan de Dios Hospital, Zaragoza, Spain
2. Department of Medicine, Psychiatry and Dermatology, Faculty of Medicine, University of Zaragoza, Zaragoza, Spain
3. Group B21-20R, Health Research Institute of Aragon (IISA), Zaragoza, Spain
4. Network for Research on Chronicity, Primary Care, and Health Promotion (RICAPPS), RD21/0016/0001, Spain
5. Department of Psychology and Sociology, University of Zaragoza, Zaragoza, Spain
6. Aragonese Healthcare Service (SALUD), Zaragoza, Spain
7. Department of Human Anatomy and Histology, School Medicine, University of Zaragoza, Spain
8. Unidad de Lípidos, IIS Aragón, CIBERCV, Miguel Servet Universitary hospital, Zaragoza, Spain
9. Family and Community Care Teaching Department of Zaragoza Sector I, Zaragoza, Spain
*Corresponding author: Bárbara Oliván-Blázquez. Department of Psychology and Sociology, University of Zaragoza. Pedro Cerbuna, 12, 50009 Zaragoza Spain. Aragonese Research Group in Primary Care (Grupo Aragonés de Investigación en Atención Primaria/GAIAP); Aragón Health Research Institute, San Juan Bosco, 13, 50009 Zaragoza Zaragoza, Spain.
Abstract
Background: Coronavirus infection has been the cause of millions of deaths worldwide. Some analytical parameters on admission could help predict prognosis and mortality. This study aims to describe the main Laboratory findings of hospitalized patients with COVID-19 and to identify the relationship between intensive care unit access, length of stay and in-hospital mortality. Methods: A retrospective cohort study was performed. Demographic and analytical variables of all patients diagnosed with COVID-19 hospitalized in Aragon (Spain) between March and June 2020 were analyzed. Results: We describe the characteristics of 2640 patients hospitalized with COVID-19, 85% were significantly older, with a median age of 72.3 ± 16.7 years, predominantly male (52.8%). The in-hospital mortality rate was 30%. Patients admitted to the intensive care unit had significantly higher baseline levels of hematocrit, fibrinogen, lactate dehydrogenase, leukocytes and neutrophils (p<0.001 in all). On the other hand, these patients had lower levels of eosinophils, lymphocytes and monocytes (p<0.001 in all). Only hemoglobin and D-dimer showed a significant and positive correlation with longer hospital and ICU stays (r=0.050 with p=0.031; r=0.203 with p=0.008; r=0.175 with p<0.001 and r=0.199 with p=0.001, respectively. Multivariable regression based on death showed that age, higher values of lactate dehydrogenase, neutrophils and lower values of eosinophils and female sex could explain up to 30% of the probability of death. Conclusion: Laboratory parameters can help clinicians predict the severity of COVID-19 and subsequently improve prognosis and decrease mortality rates. However, more studies are needed to better understand these changes and their relationship to prognosis.
Key words: COVID-19, Laboratory findings, prognosis, in-hospital mortality, intensive care unit
Introduction
At the end of 2019, in Wuhan, China, a disease originated due to coronavirus (COVID-19) [1]. According to the World Health Organization (WHO) (2021), SARS-CoV-2 is a highly transmissible and pathogenic coronavirus that induces severe acute respiratory syndrome; it has caused more than 2 million deaths in the first 12 months since its appearance. It has also generated critical social problems throughout the world. This infection continues to spread, with more than 200 million confirmed cases and 223 countries, areas, or territories [2].
Spain has been one of the European countries most affected by the COVID-19 pandemic as of Mach 17th, with more than 11 000 cases and 491 deaths [3]. Spain had one of the highest burdens of coronavirus disease worldwide [4]. The first wave period was between March and June 2020 [5].
A total of 611,583 individuals from 5 official national registries (Spain, Italy, China, England, and New York were analyzed in a meta-analysis. The purpose was to study COVID-19 and mortality rates by decades of age. The overall mortality rate was 12.10% and varied widely among countries, with the lowest rate in China (3.1%) and the highest rate in the United Kingdom (20.8%) and New York state (20.99%). Patients younger than 50 years had a mortality rate of less than 1.1%, and mortality increased exponentially after that age in all five national registries [6].
The COVID-19 clinical manifestations can range from asymptomatic, presenting mild respiratory symptoms, to a severe threat of death caused by respiratory and cardiac failure [7,8].
The beginning of the pandemic was a real challenge for emergency physicians to identify the prognosis of patients with COVID-19; therefore it was essential that several studies identified the risk factors for an early prediction of the progression of the disease.
Several studies have shown that older age, male sex, and comorbidities such as hypertension, diabetes, and cardiovascular disease have been associated with worse outcomes in COVID-19 patients [8-11].
Laboratory findings were also essential to predict severity, admission to the intensive care unit (ICU) and even death. A multicenter study including 32 hospitals in Spain studied Laboratory data as predictors of in-hospital mortality. They found that C-reactive protein (CRP), troponin levels, creatinine, and platelet count independently associated with an increased risk of in-hospital mortality [11].
This line in a meta-analysis which included 148 studies (12,149 patients), points to hypoalbuminemia, lymphopenia, and also elevated levels of interleukin 6, leucocytes, D-dimer (DD), and lactate dehydrogenase were more commonly seen in patients with severe COVID-19 illness and non-survivors [12].
Another meta-analysis of seven studies with 1905 patients found that severity and the possibility of transferring the patient to the intensive care unit were significantly associated with lymphopenia, increased CRP, and increased LDH [13].
A meta-analysis that included seven studies of diagnosis and prognosis of COVID-19 showed that an elevated count of leukocyte and neutrophils indicate progressive disease. Thrombocyte count is crucial in both diagnosis and prognosis. Additionally, they found that lymphocyte, DD, and CRP levels indicate severity but did not demonstrate diagnostic value of COVID-19 [14].
Another study showed that patients with infection or sepsis admitted to an ICU had higher levels of D-dimer, which were associated with 28-day mortality [15]. Two more studies published that patients with greater severity and mortality had higher levels of DD [16,27].
Also, a systematic review that included 24 studies identified that DD in patients with COVID-19 is associated with greater severity, disease progression, acute respiratory distress syndrome, and death (with low-quality evidence) [18].
As we can see, Laboratory data are essential at the time of diagnosis in patients with COVID-19, and this information may help physicians to predict ICU admission, length of stay and in-hospital mortality, there is not much data in this field. The aim of this study is to describe the main Laboratory findings of hospitalized patients with COVID-19 in Aragon-Spain and to identify the relationship between ICU admission, length of stay and in-hospital mortality.
Materials and Methods
Study design
We conducted a retrospective cohort study and analyzed demographics and analytical variables of all patients diagnosed with COVID-19. They were hospitalized in Aragón (Spain) from the beginning of the current pandemic to 30 June 2020. This information was pseudonymized from the BIGAN platform, where demographics and analytical values were requested from all users with an Aragón health card at the time of their hospital admission and in the Intensive Care Unit (ICU). This information has been obtained pseudonymized from The BIGAN Information Platform, which integrates all the data collected from the Department of Health and the Aragón Health Service. The Clinical Research Ethics Committee of Aragón approved the study protocol (PI20/262).
Participants and sample size
In the present study, all hospitalized adults in Aragón (Spain), older than 18 years, diagnosed with COVID-19 who had a positive result in the polymerase chain reaction (PCR) diagnostic test were included. For each patient included in the study, their age at the time of hospital admission was reported. A total of 6286 adults were diagnosed with COVID-19 in the study period and only 2640 (42%) required hospital admission.
Laboratory measurements
Blood samples were drawn by venipuncture at the time of hospital admission and ICU admission, obtaining two types of tubes for the hemogram with EDTA (ethylenediaminetetraacetic acid) and with citrate in the case of coagulation determinations. All subjects included in the current study had complete blood cell counts and hemostatic parameters, including red cell distribution width (RWD), Basophils, mean corpuscular hemoglobin concentration (MCHC), creatine phosphokinase (CPK), D-dimer concentration, eosinophils, fibrinogen levels, mean cell hemoglobin (MCH), hematocrit, Hemoglobin, lactate dehydrogenase (LDH), leukocytes, lymphocytes, monocytes, neutrophils, platelets, prothrombin time, troponin, medium corpuscular volume (MCV), Mean platelet volume (MPV) and erythrocyte sedimentation rate (ESR).
Hematocrit was calculated as the product of red blood cells times mean corpuscular volume divided by 10. Hemoglobin concentration was calculated from the transmission of light at 535 nm of the lysed solution versus the transmission of light generated by a blank. The MCH is the weight of hemoglobin in the mean erythrocyte, calculated by dividing the hemoglobin and the number of red cells by 10. The MCH is the mean weight of hemoglobin in a measured dilution, calculated as the hemoglobin divided by the hematocrit per 100. The mean corpuscular volume was obtained from the mean volume of the erythrocytes calculated from the histogram of the red blood cells of each channel. The RDW is the width or width of the size distribution of the erythrocyte population calculated from the red blood cell histogram as the coefficient of variation. Each type of white blood cell was calculated as the number of leukocytes in each series measured directly and multiplied by the calibration factor. The number of platelets was calculated from the platelet histogram multiplied by a calibration factor. At the same time, the VMP represents the mean volume of the platelet population under the fitted platelet curve multiplied by a calibration factor.
The methodology for the coagulometry tests was spectrophotometry, based on the change in scattered light associated with fibrin clot formation, analyzing two wavelengths of 671 nm and 405 nm, using the ACL TOP 550 CTS and ACL TOP 750 CTS auto analyzers available in the clinical Laboratories of the Aragon’s Health Service.
Statistical analysis
Continuous variables are expressed as mean ± SD or median (25th percentile - 75th percentile) as applicable, and categorical (nominal) variables are reported as percentages of the total sample. Differences between independent variables were calculated by T-Student or U Mann Whitney test, as appropriate, while categorical variables were compared using the chi-squared test. The lineal regression model adjusted the differences between independent variables by sex and age. Multivariable regression based on UCI admission or death was analyzed by binary logistic regression. All statistical analyses were performed with R version 3.5.0, and significance was set at p < 0.05.
Results
There were 6286 adults diagnosed with COVID-19 from March through June 30, 2020 in Aragon (Spain), 2640 (42%) required hospital admission, and of these, 268 (10% of total hospital admissions) were admitted to the ICU. The 2268 hospitalized subjects were significantly older, with 72.3 ± 16.7 years old, and predominantly male with 1393 subjects (52.8%) versus 3646 positive Covid-19 non-hospitalized adults, who had a mean age of 54,9 ± 21.5 years old and were primarily female (63.2%) (p<0.001 and p<0.001, respectively). Of the total of 2268 hospitalized subjects, 779 died (29.5%), compared to 100 subjects (37.3%) who died among those admitted to the ICU, indicating that the percentage of death was significantly higher for ICU admission patients (p<0.001). The hospitalized subjects who died were especially older, with a mean age of 83.1 ± 10.3 years old, versus the rest of those who did not die, who had a mean age of 67.5 ± 16.7 (p<0.001, Figure 1).
Figure 1:Flow chart ICU: Intensive care unit
Table 1 shows the comparison of baseline analytical values as a function of the need for ICU admission, indicating that subjects admitted to the ICU have significantly higher baseline levels of MCHC, hematocrit, fibrinogen, LDH, leukocytes, and neutrophils (p=0.027, p<0.001, p<0.001, p<0.001, p<0.001 and p<0.001, respectively). On the other hand, these patients had significantly lower baseline levels of basophils, eosinophils, lymphocytes, and monocytes (p=0.027, p<0.001, p<0.001, and p<0.001, respectively, Table 1).
Table 1:Comparison of analytical reference values according to their need for ICU admission.
| Subjects not admitted to the ICU (N=2372) | Subjects admitted to the ICU (N=268) | p | |
|---|---|---|---|
| Hematocrit, % | 41.1 (37.3 – 44.4) | 42.1 (38.1 – 46.0) | <0.001 |
| Haemoglobin, g/dL | 13.6 (12.3 – 14.7) | 13.8 (12.7 – 15.2) | 0.138 |
| MCH, pg | 30.3 (28.9 – 31.5) | 30.2 (29.0 – 31.4) | 0.781 |
| RDW, % | 14.0 (13.3- 15.1) | 13.8 (13.1- 14.5) | 0.018 |
| MCV, fL | 90.3 (86.6 – 93.8) | 89.9 (86.9 – 93.1) | 0.544 |
| ESR, mm/h | 50.0 (20.0 – 86.0) | 49.0 (19.0 – 83.0) | 0.618 |
| Platelets, U103/μL | 188 (145 – 245) | 191 (143- 249) | 0.767 |
| VPM, fL | 9.30 (8.60 – 10.1) | 9.30 (8.50 – 10.1) | 0.995 |
| Leukocytes, U103/μL | 6.47 (4.67 – 8.60) | 7.65 (5.17 – 10.0) | < 0.001 |
| Lymphocytes, U103/ μL | 1.02 (0.700 – 1.49) | 0.803 (0.595 – 1.100) | < 0.001 |
| Monocytes, U103/μL | 0.532 (0.378 – 0.717) | 0.414 (0.292 – 0.587) | < 0.001 |
| Eosinophils, U103/μL | 0.010 (0.000- 0.050) | 0.000 (0.000 – 0.008) | < 0.001 |
| Basophils, U103/μL | 0.020 (0.010- 0.036) | 0.017 (0.009- 0.031) | 0.027 |
| Neutrophils, U103/μL | 4.73 (3.30 – 6.90) | 6.23 (4.13- 8.88) | < 0.001 |
| CPK, U/L | 72.5 (43.0 – 148) | 107 (54.0 – 215) | 0.847 |
| D-dimer, ng/mL | 840 (482 – 1680) | 1023 (563 – 1736) | 0.130 |
| Fibrinogen, mg/dL | 669 (513 – 794) | 798 (661 – 947) | < 0.001 |
| LDH, U/L | 290 (224- 383) | 453 (307 – 630) | < 0.001 |
| Prothrombin time, s | 13.5 (12.4– 14.9) | 13.9 (12.8 – 15.2) | 0.254 |
| Troponin, ng/L | 13.0 (7.10– 31.67) | 14.5 (11.8- 29.6) | 0.191 |
Quantitative variables following not normal distribution were expressed as median (percentile 25th- percentile 75th). The p-value was adjusted by sex and age. MCH: mean cell hemoglobin; MCHC: mean corpuscular hemoglobin concentration; RWD denotes red cell distribution width; MCV: medium corpuscular volume; ESR: erythrocyte sedimentation rate; VPM: Mean platelet volume; CPK: creatine phosphokinase; LDH: lactate dehydrogenase; s: seconds. ICU: intensive care unit.
Interestingly, the multivariable regression model shows that higher concentrations of fibrinogen and leucocyte; and lower concentrations of monocytes, as well as older age and being male, are risk factors for ending up in the ICU. They showed that combining these five factors could explain 10% of the probability of requiring admission to the ICU (Table 2).
Table 2:Multivariable regression based on ICU admission
| OR | 95% CI | P | R2 Nagelkerke | |
|---|---|---|---|---|
| F i b r i n o g e n , mg/dL | 0.0013 | 0.000480 to 0.00218 | 0.003 | 0.10289 |
| Leukocytes , U103/μL | 0.1435 | 0.08196 to 0.2080 | <0.001 | |
| M o n o c y t e s , U103/μL | -2.2083 | -2.2083 -3.38536 to -1.1500 | <0.001 | |
| Age, years | -0.030 | -0.0458 to -0.0148 | <0.001 | |
| Sex, Women | -0.682 | -1.248 to -0.1477 | <0.001 |
Multivariable binary logistic regression with the ICU admission as the dependent variable. OR: Odd Ratio; CI: Confidence Interval. ICU: intensive care unit.
The mean hospitalization time was 17.01 ± 23.2 days, with a maximum of 222 days, compared to the mean length of stay in the ICU, which was 19.0 days ±18.6 with a maximum of 157 days (Table 3), showing a correlation between baseline Laboratory parameters and hospitalization and ICU hospitalization time. Higher values of Hemoglobin, MCH, MCHC, RDW, ESR, Platelets, VPM, D-dimer, fibrinogen, and prothrombin time correlated significantly and positively with longer hospital stay time. In contrast, hematocrit, leukocytes, and lymphocytes' values correlated significantly and negatively with hospital stay time. Regarding ICU hospitalization time, higher values of hemoglobin and D-dimer correlated significantly and positively with longer ICU stay time. In comparison, lower values of RDW, MCV, ESR, VPM, and basophils correlated significantly and inversely with ICU stay time. Interestingly, only hemoglobin and D-dimer showed significant and positive correlation with both longer hospital stays and ICU stays (r=0.050 with p=0.031; r=0.203 with p=0.008; r=0.175 with p<0.001 and r=0.199 with p=0.001, respectively, Table 3).
Table 3:Correlation between baseline analytical parameters and hospitalization - ICU hospitalization time
| Correlation with hospitalization time | p | Correlation with ICU stay | p | |
|---|---|---|---|---|
| Hematocrit, % | -0.101 | < 0.001 | 0.085 | |
| Haemoglobin, g/dL | 0.050 | 0.031 | 0.203 | 0.008 |
| MCH, pg | 0.055 | 0.006 | 0.104 | 0.092 |
| RDW, % | 0.053 | 0.012 | -0.127 | 0.046 |
| MCV, fL | -0.008 | 0.693 | -0.127 | 0.046 |
| ESR, mm/h | ||||
| Platelets, U103/μL | 0.053 | 0.012 | -0.051 | 0.429 |
| VPM, fL | 0.175 | <0.001 | -0.156 | 0.015 |
| Leukocytes, U103/μL | -0.077 | <0.001 | -0.099 | 0.124 |
| Lymphocytes, U103/ μL | -0.055 | 0.027 | -0.087 | 0.281 |
| Monocytes, U103/μL | 0.025 | 0.245 | 0.030 | 0.647 |
| Eosinophils, U103/μL | -0.036 | 0.092 | -0.079 | 0.216 |
| Basophils, U103/μL | -0.029 | 0.170 | -0.156 | 0.015 |
| Neutrophils, U103/μL | -0.024 | 0.266 | -0.026 | 0.703 |
| CPK, U/L | -0.045 | 0.121 | 0.003 | 0.968 |
| D-dimer, ng/mL | 0.175 | < 0.001 | 0.199 | 0.001 |
| Fibrinogen, mg/dL | 0.088 | 0.002 | 0.109 | 0.161 |
| LDH, U/L | -0.039 | 0.118 | 0.004 | 0.964 |
| Prothrombin time, s | 0.172 | < 0.001 | 0.055 | 0.455 |
| Troponin, ng/L | 0.038 | 0.064 | 0.072 | 0.243 |
The p value calculated by Spearman correlation. MCH: mean cell hemoglobin;
MCHC: mean corpuscular hemoglobin concentration; RWD denotes red cell
distribution width; MCV: medium corpuscular volume; ESR: erythrocyte sedimentation
rate; VPM: Mean platelet volume; CPK: creatine phosphokinase;
LDH: lactate dehydrogenase; s: seconds. ICU: intensive care unit.
Among the 2,268 hospitalized patients during the first wave of COVID-19 in Aragón, 779 adults who died had significantly higher values of RDW, MCV, ESR, VPM, leukocytes, neutrophils, CPK, D-dimer, LDH, prothrombin time and troponin. (p<0.001, p=0.014, p<0.001, p=0.005, p<0.001, p<0.001, p=0.007, p=0.004, p<0.001, p<0.001 and p=0.023, respectively). On the other hand, those patients had significantly lower values of hematocrit, Hemoglobin, MCHC, lymphocytes, and eosinophils (p=0.036, p<0.001, p<0.001, p=0.00,1, and p<0.001, respectively, Table 4).
Table 4:Comparison between analytical reference values and whether the patient is dead or not.
| Deceased patients (N=779) | Non-deceased patients (N=1861) | p | |
|---|---|---|---|
| Hematocrit, % | 39.8 (36.0 – 43.7) | 41.72 (38.3 – 44.73) | 0.036 |
| Haemoglobin, g/dL | 12.9 (11.7- 14.3) | 13.8 (12.7- 14.9) | <0.001 |
| MCH, pg | 33.2 (32.5 – 33.8) | 33.6 (32.9 – 34.2) | <0.001 |
| RDW, % | 14.6 (13.9 – 15.9) | 13.8 (13.2 – 14.7) | <0.001 |
| MCV, fL | 91.7 (87.0 – 95.6) | 89.9 (86.5 – 93.0) | 0.014 |
| ESR, mm/h | 73.0 (39.3 – 108) | 42.0 (16.0- 79.0) | <0.001 |
| Platelets, U103/μL | 181 (138- 234) | 191 (149 – 251) | 0.154 |
| VPM, fL | 9.50 (8.70 – 10.4) | 9.20 (8.50 – 10.0) | 9.20 (8.50 – 10.0) |
| Leukocytes, U103/μL | 7.80 (5.40 – 10.7) | 6.29 (4.60 – 8.20) | <0.001 |
| Lymphocytes, U103/ μL | 0.822 (0.531 – 1.27) | 1.04 (0.745 – 1.50) | 0.001 |
| Monocytes, U103/μL | 0.497 (0.321 – 0.745) | 0.528 (0.387 – 0.700) | 0.732 |
| Eosinophils, U103/μL | 0.002 (0.000 – 0.021) | 0.010 (0.000 – 0.052) | <0.001 |
| Basophils, U103/μL | 0.018 (0.010 – 0.036) | 0.020 (0.010 – 0.036) | 0.654 |
| Neutrophils, U103/μL | 6.29 (4.17 – 9.10) | 4.48 (3.22 – 6.50) | <0.001 |
| CPK, U/L | 93.0 (45.0 – 189) | 74.0 (44.0 – 143) | 0.007 |
| D-dimer, ng/mL | 1388 (773 – 3011) | 721 (452 – 1337) | 0.004 |
| Fibrinogen, mg/dL | 677 (542 – 824) | 686 (525 – 822) | 0.091 |
| LDH, U/L | 337 (244 – 474) | 289 (223 – 379) | < 0.001 |
| Prothrombin time, s | 14.1 (12.8 – 16.33) | 13.4 (12.4 – 14.5) | < 0.001 |
| Troponin, ng/L | 38.8 (21.8 – 78.9) | 13.0 (6.09 – 18.65) | 0.023 |
Quantitative variables following not normal distribution were expressed as median (percentile 25th- percentile 75th). The p-value was adjusted by sex and age. MCH: mean cell haemoglobin; MCHC: mean corpuscular haemoglobin concentration; RWD denotes red cell distribution width; MCV: medium corpuscular volume; ESR: erythrocyte sedimentation rate; VPM: Mean platelet volume; CPK: creatine phosphokinase; LDH: lactate dehydrogenase; s: seconds. ICU: intensive care unit.
In the same line, multivariable regression based on death showed r values of RDW, LDH, neutrophils, MCV, and age, and lower values of MCHC, eosinophils, and female sex could explain up to 30% of the probability of death (Table 5).
Table 5:Multivariable regression based on death
| OR | 95% CI | P | R2 Nagelkerke | |
|---|---|---|---|---|
| RDW, % | 0.2653 | 0.181 to 0.353 | <0.001 | 0.3017 |
| MCHC, g/dL | -0.1489 | -0.288 to -0.0192 | 0.031 | |
| E o s i n o p h i l s , U103/μL | -2.546 | -4.617 to -0.655 | 0.012 | |
| LDH, U/L | 0.002219 | 0.001 to 0.003 | <0.001 | |
| N e u t r o p h i l s , U103/μL | 0.08678 | 0.051 to 0.124 | <0.001 | |
| MCV, fL | 0.04043e | 0.0174 to 0.064 | <0.001 | |
| Age, years | 0.07655 | 0.064 to 0.090 | <0.001 | |
| Sex, Women | -0.3947 | -0.678 to -0.114 | 0.006 |
Multivariable binary logistic regression with death as the dependent variable. OR: Odd Ratio; CI: Confidence Interval. RWD denotes red cell distribution width; MCHC: mean corpuscular hemoglobin concentration; LDH: lactate dehydrogenase; MCV: medium corpuscular volume.
Discussion
In this study, we describe the characteristics of 2640 hospitalized patients with COVID-19 infection admitted in the hospitals of Aragón-Zaragoza, focusing on the alterations in Laboratory tests.
Our study found an in-hospital mortality rate of 29%, like a multicenter study performed in Spain. In contrast, the reported mortality rate in other the dies in Spain has ranged from 11-24% [19-21].
The mortality rate of hospitalized patients diagnosed with COVID-19 worldwide varies from 1.4% in a case series in China to 16% in Ireland and the United States [22,23].
Mortality differences have been attributed to the different diagnostic techniques for COVID-19, demographic characteristics, and prevalence of comorbidities, which also may influence the inclusion criteria in the studies [24].
Regarding demographics, the median age in our cohort was 72 years old, like the results found in a multicenter study conducted in the United Kingdom (UK) [25]. Lower ages were reported in Spanish reports [19,20,26]. One Chinese study described a median age of less than 50 [27].
It is also important to mention that several studies found the highest mortality rate among older patients, as described in this study [20,26,28,29].
In relation to gender, multiple studies found that male sex is another risk factor for severity, admission to ICU, and mortality of COVID-19 [12,30,31]. As described by Klein and Flanangan, this difference would be associated with sex differences in the immune response that may impact the susceptibility to infectious diseases, inflammatory response, and consequences of COVID-19 [32].
Regarding Laboratory tests in this study, we described that patients with higher levels of fibrinogen, LDH, leukocytes, and lymphopenia at admission were associated with a higher probability of being admitted to the ICU. Similar results were found in a systematic review and meta-analysis written by Zhang et al. [13], in which patients with elevated LDH, CRP, and lymphopenia require appropriate management and, if necessary, admission to the ICU.
In this line, we found that a combination of 5 variables (older age, male, elevated fibrinogen and leukocyte counts, and lower concentration of monocytes) can explain 10% of the probability of requiring admission to the ICU. Studies conducted in USA and Europe also have similar findings (older age, male, elevated counts of fibrinogen and leucocytes) [23,33].
A report found differences in Leucocytes between severe and non-severe COVID-19 patients [34]. Patients in both groups increased their leukocyte count due to activation of the immune system to fight a viral infection. However, the severe group had a significantly higher leukocyte count [34,35]. Also, it is essential to remember that leukocytes alone may be influenced by many factors such as inflammatory response and glucocorticoid treatment, which increases it. In this line, a Chinese report describes that also mononuclear cells (monocytes and lymphocytes) play an essential role in immune response and pathogen elimination. The immune defense activates monocytes and natural killer cells, so they found an increased number of monocytes in patients with COVID-19 infection, in contrast to our study [36,37]. Contrastingly, lower levels of lymphocyte counts were related to severe COVID-19 infection and higher mortality [13,14,38]. These Laboratory findings may help physicians to know the prognosis and whether or not the patient will need to be admitted to the ICU.
It should also be noted that the analytical parameters may be related to the length of stay. Our study found that hemoglobin and D-dimer showed a significant and positive correlation with more extended hospital stays and ICU stays. One study written by Pillai et al. found that an NLR >18 and high levels of procalcitonin, sodium, and potassium were associated with a hospital stay of >14 days [39]. There are few studies on this subject. It would be of interest to study it as prognostic predictor.
Also, some Laboratory parameters are related to in-hospital mortality, as it has been shown in many studies that D-dimer is higher in survivors than in non-survivors [18,40,41]. This Laboratory parameter originates from fibrin lysis, with higher levels denoting activation of coagulation and fibrinolysis, with COVID-19 being associated with hemostatic abnormalities [42]. Zhan et al. found that higher levels (cutoff point >2.0 μg/mL) of D-dimer at admission can help predict in-hospital mortality [43] and could play a role as a triage marker for intensive care patients [28], which could help clinicians tailor treatment and prognosis.
As mentioned above, a higher number of leukocytes and neutrophils were associated with severe COVID-19 and were also found in several studies to be associated with mortality.
Another parameter found to be higher in patients who died was LDH. Increased lactate dehydrogenase denotes tissue/cell destruction and is a sign suggesting viral infection or lung damage, such as SARS-CoV-2 induced pneumonia [44]. Yan et al. developed a mortality prediction model using machine learning tools. They included 485 patients diagnosed with COVID-19 in Wuhan and analyzed 75 clinical features, including the concentrations of blood markers.
They found that three blood markers (LDH, lymphocytes, and high-sensitivity-CRP) could predict patient mortality 10 days in advance with an accuracy of more than 90%. Particularly just one elevated biomarker (LDH) in blood, it was highly indicative of COVID-19 mortality [45].
Another elevated parameter that denotes worse prognosis and increased mortality is troponins. Several studies have found the same results as ours [19,28,46,47].
Conclusions
Coronavirus infection has been a challenge for the health system worldwide and knowing the analytical parameters at the time of admission could help to understand the prognosis and severity of the disease. It will be essential to see this parameter.
Our study concludes that five factors (being old, male, higher concentrations of fibrinogen, leucocyte, and lower levels of monocytes) may explain 10% of the probability of requiring admission to the ICU. Biomarkers such as Hemoglobin and D-dimer showed a significant and positive correlation with the index hospital stay, and ICU stays, so up to 30% of the probability of death could be explained if you are old and have higher values of LDH, neutrophils, and lower values of eosinophils. Laboratory findings may help physicians to predict the severity of COVID-19 and subsequently improve prognosis and decrease mortality rates. Nonetheless, further studies are needed to understand better these changes and their relation to prognosis [11,19].
Acknowledgments
We wish to thank the Network for Research on Chronicity, Primary Care, and Health Promotion (RD21/0016/0001) (RICAPPS-Health Institute Carlos III, Spain); Research Group B21_20R of the Department of Research, Innovation and University of the Government of Aragon (Spain); Feder Funds “A way to make Europe”, for their support in the development of the study.
Conflicts of Interest
The authors declare no conflict of interest.
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Received:May 16, 2022;
Accepted: June 06, 2022;
Published: June 09, 2022.
To cite this article : Matovelle-Ochoa P, Oliván-Blázquez B, Magallón-Botaya R, et al. Biomarkers as Prognosis of COVID-19 Disease: Retrospective Cohort Study. European Journal of Respiratory Medicine. 2022; 4(2): 344 - 341. doi: 10.31488/EJRM.136.
© 2022 Matovelle-Ochoa P, et al