|Year : 2021 | Volume
| Issue : 6 | Page : 306-311
The predictive and prognostic role of hematologic and biochemical parameters in the emergency department among coronavirus disease 2019 patients
Chun-Yen Huang1, Huang-Wen Tsai2, Chia-Ying Liu3, Tse-Hsuan Liu4, Huei-Ling Huang4, Chih-Chun Chang5, Wei-Chi Chen6, Jen-Tang Sun7
1 Department of Emergency Medicine, Far Eastern Memorial Hospital, New Taipei City, Taiwan
2 Division of Pediatric Surgery, Department of Surgery; Division of Trauma, Department of Surgery, Far Eastern Memorial Hospital, New Taipei City, Taiwan
3 Department of Internal Medicine, Far Eastern Memorial Hospital, New Taipei City, Taiwan
4 Department of Clinical Pathology, Far Eastern Memorial Hospital, New Taipei City, Taiwan
5 Department of Clinical Pathology, Far Eastern Memorial Hospital, New Taipei City; Department of Nursing, Cardinal Tien Junior College of Healthcare and Management, Yilan, Taiwan
6 Department of Nursing, Cardinal Tien Junior College of Healthcare and Management, Yilan; Public Health Bureau, New Taipei City, Taiwan
7 Department of Emergency Medicine, Far Eastern Memorial Hospital, New Taipei City; School of Medicine, College of Medicine, Tzu Chi University, Hualien, Taiwan
|Date of Submission||06-Sep-2021|
|Date of Decision||19-Oct-2021|
|Date of Acceptance||27-Oct-2021|
|Date of Web Publication||27-Dec-2021|
Dr. Jen-Tang Sun
Department of Emergency Medicine, Far Eastern Memorial Hospital, No. 21, Sec. 2, Nanya S. Road, Banqiao, New Taipei City
Source of Support: None, Conflict of Interest: None
Coronavirus disease 2019 (COVID-19) had caused a worldwide pandemic with public health emergencies since 2020. For the symptomatic patients, high mortality rate was observed if without timely and optimized management. In this study, we aimed to investigate the predictive and prognostic roles of hematologic and biochemical parameters obtained in the emergency department (ED) for COVID-19 patients. We conducted a retrospective study in a dedicated COVID-19 medical center, recruiting a total of 228 COVID-19 patients with 86 severe and 142 non-severe cases. Both the hematologic and biochemical parameters obtained in the ED upon arrival were analyzed to evaluate the association of the biomarkers with disease severity and prognosis among COVID-19 patients. Among these parameters, neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP), procalcitonin (PCT), lactate dehydrogenase (LDH), ferritin, and D-dimer were significantly higher in the severe group than the non-severe one, whereas the platelet count and lymphocyte-to-monocyte ratio were significantly lower. Receiver operating characteristic curve analysis revealed that the areas under curve of CRP, PCT, LDH, ferritin, D-dimer, and NLR for differentiating the severity of COVID-19 were 0.713, 0.755, 0.763, 0.741, 0.733, and 0.683, respectively, whereas the areas under curve of CRP, PCT, LDH, ferritin, D-dimer, and NLR for differentiating the mortality of COVID-19 were 0.678, 0.744, 0.680, 0.676, 0.755, and 0.572, respectively. Logistic regression analysis revealed that CRP, PCT, LDH, ferritin, D-dimer, and NLR were independent indicators for prediction of severe COVID-19, and LDH and ferritin were independent factors associated with the mortality in COVID-19. In conclusion, higher CRP, PCT, LDH, ferritin, D-dimer, and NLR were associated with severe COVID-19, whereas higher LDH and ferritin were associated with the mortality in COVID-19. These findings could help early risk stratification in the ED and contribute to optimized patient management.
Keywords: Coronavirus disease 2019, C-reactive protein, cycle threshold value, ferritin, lactate dehydrogenase, neutrophil-to-lymphocyte ratio
|How to cite this article:|
Huang CY, Tsai HW, Liu CY, Liu TH, Huang HL, Chang CC, Chen WC, Sun JT. The predictive and prognostic role of hematologic and biochemical parameters in the emergency department among coronavirus disease 2019 patients. Chin J Physiol 2021;64:306-11
|How to cite this URL:|
Huang CY, Tsai HW, Liu CY, Liu TH, Huang HL, Chang CC, Chen WC, Sun JT. The predictive and prognostic role of hematologic and biochemical parameters in the emergency department among coronavirus disease 2019 patients. Chin J Physiol [serial online] 2021 [cited 2022 Aug 17];64:306-11. Available from: https://www.cjphysiology.org/text.asp?2021/64/6/306/333803
Chun-Yen Huang and Huang-Wen Tsai have contributed equally to this work.
| Introduction|| |
Coronavirus disease 2019 (COVID-19), the acute respiratory syndrome caused by severe acute respiratory distress syndrome coronavirus 2 (SARS-CoV-2) infection, had been announced as the pandemics to public health emergency since January 2020. Despite a series of anti-pandemic policies were applied, an outbreak still happened in mid-May 2021 in Taiwan. Fortunately, the transmission chain was successfully blocked and the number of newly confirmed COVID-19 cases had remarkably decreased after 2 months of hard work.
As the clinical manifestations of COVID-19 varied from time to time, from asymptomatic to fulminant, stratification of COVID-19 patients was important on the severity of disease. Hence, several risk factors should be clarified, especially in severely ill patients at their initial arrival to the emergency department (ED). Previous studies demonstrated that age, gender, and known comorbidities could be risk factors for severe illness with COVID-19., Besides, it was reported that hematologic and biochemical parameters, such as C-reactive protein (CRP), procalcitonin (PCT), lactate dehydrogenase (LDH), ferritin, D-dimer, and neutrophil-to-lymphocyte ratio (NLR), were associated with not only the severity but also the prognosis in COVID-19 patients.,,, Furthermore, since most of these biomarkers were rapidly available in the ED, they could help early identification for severe COVID-19 cases and initiate early referral to the specialized unit as necessary. However, these biomarkers were time-sensitive as the disease progressed, and hence could be variable in different studies or areas. It also remained unknown whether the similar events surrounded among Taiwanese COVID-19 population. Hence, we aimed to investigate the predictive and prognostic role of hematologic and biochemical parameters obtained in the ED for the COVID-19 patients.
| Materials and Methods|| |
Patients and study design
A retrospective study was performed on the clinical characteristics and laboratory (based on real-time reverse transcription–polymerase chain reaction [RT-PCR])-confirmed cases with COVID-19 who were admitted to the ED in Far Eastern Memorial Hospital (FEMH), one of the dedicated COVID-19 medical centers from May 14 to July 14, 2021. Diagnosis of COVID-19 should be based on the interim guidance of the World Health Organization (WHO). Therapeutic management was followed as the guidance announced by the Taiwan Centers for Disease Control (CDC), Ministry of Health and Welfare. Confirmed COVID-19 patients should have a positive result of RT-PCR for SARS-CoV-2 RNA. In addition, severe cases were considered for those with SpO2 <94% on room air at sea level, respiratory frequency more than 30 breaths/min, or a ratio of arterial partial pressure of oxygen to fraction of inspired oxygen (PaO2/FiO2) <300 mmHg. Individuals who were younger than the age of 20 years, with incomplete laboratory survey at admission, transferred out, or with an inpatient do-not-resuscitate (DNR) order were excluded from the study. The informed consent was waived as the anonymous, retrospective, and observational character of this study, which was approved by the Institutional Review Board of FEMH (110146-E).
Clinical features and laboratory data
Epidemiological characteristics and laboratory data were obtained through the chart review of electronic medical records. Clinical data, including patient age, gender, comorbidities (malignancies, type 2 diabetes mellitus, hypertension, chronic obstructive pulmonary disease, heart disease, hepatitis B virus infection, chronic kidney disease, abnormal liver function tests, and miscellaneous), the length of intensive care unit and hospital stay, survival to discharge, the hematologic (complete blood cell count and differential count of white cells), and biochemical parameters (CRP, PCT, LDH, ferritin, and D-dimer) in the ED were recorded. NLR, platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) were then calculated on the basis of complete blood cell count and differential count of white cells. RT-PCR for SARS-CoV-2 RNA was performed using the Roche cobas Z480 and 6800 analyzers and the LabTurbo AIO 48 system in accordance with the protocol from Taiwan CDC.
COVID-19 patients were categorized into severe and non-severe groups. Continuous variables were expressed as the median with interquartile range and were analyzed by Mann–Whitney U-test. Categorical variables were expressed as the count with percentage and were analyzed by Chi-square test with Pearson's correlation. The odds ratio (OR) with 95% confidence interval was then presented. Besides, optimal cutoff values were determined through receiver operating characteristic (ROC) curve analysis and calculation of Youden index for prediction of the severity and mortality of COVID-19. Binary logistic regression analysis was performed with adjustment of patient age, gender, and comorbidities. P < 0.05 was considered statistically significant. All statistical analyses were performed using the SPSS 19.0 software (SPSS Inc., Chicago, IL, USA).
| Results|| |
During the study interval, a total of 7146 patients were admitted to our ED for suspicion of SARS-CoV-2 infection. Among these, 557 had SARS-CoV-2 infection by RT-PCR confirmation; 313 were transferred to quarantine hotels and 244 were admitted for RT-PCR-confirmed COVID-19. For these 244 patients, four had incomplete laboratory survey upon admission, five were transferred out, one escaped from hospital, and six had the inpatient DNR order were excluded [Figure 1]. Eventually, 228 patients were enrolled and 86 of these were diagnosed as severe COVID-19. The epidemiological data are shown in [Table 1]. The proportions of old age, hypertension, and chronic kidney disease were significantly higher in the severe group than the non-severe one. It was also observed that COVID-19 patients were prone to have type 2 diabetes mellitus, heart disease, and abnormal liver function tests, but there was no statistical significance. Severe COVID-19 patients also had significantly longer length of intensive care unit and hospital stay, and remarkably lower survival to discharge in comparison with non-severe COVID-19 patients.
|Figure 1: Patient selection procedure and flowchart of inclusion. ED: Emergency department, SARS-CoV-2: Severe acute respiratory syndrome coronavirus 2, RT-PCR: Reverse transcription–polymerase chain reaction, DNR: Do-not-resuscitate, COVID-19: Coronavirus disease 2019.|
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|Table 1: Comparison of baseline characteristics between severe and non-severe groups among coronavirus disease 2019 patients|
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Hematologic and biochemical parameters in predicting the severity of coronavirus disease 2019
As shown in [Table 2], we found that severe COVID-19 patients had significantly higher absolute neutrophil count, NLR, PLR, CRP, PCT, LDH, ferritin, and D-dimer when compared with non-severe ones. In contrast, the platelet count, absolute lymphocyte count, and LMR were significantly lower in the severe group than the non-severe group. ROC analysis was then conducted to determine the optimal cutoff value in each category. As shown in [Figure 2], the areas under curve of age, CRP, PCT, LDH, ferritin, D-dimer, NLR, PLR, and LMR for differentiating the severity of COVID-19 were 0.679, 0.713, 0.755, 0.763, 0.741, 0.733, 0.683, 0.570, and 0.418, respectively. PLR and LMR were not considered as potential predictive parameters and were not utilized for subsequent analysis. In addition, the areas under curve of age, CRP, PCT, LDH, ferritin, D-dimer, NLR, PLR, and LMR for predicting the mortality of COVID-19 were 0.853, 0.678, 0.744, 0.680, 0.676, 0.755, 0.572, 0.467, and 0.501, respectively. The optimal cutoff values of each parameter for differentiating the severity and mortality of COVID-19 are presented in [Table 3] and [Table 4] along with the sensitivity and specificity, respectively. Binary logistic regression analysis was further performed to adjust confounding factors of age, gender, and comorbidities (including type 2 diabetes mellitus, hypertension, heart disease, chronic kidney disease, and abnormal liver function tests) that could potentially be associated with severe COVID-19 [Table 5]. After adjustment, parameters including CRP, PCT, LDH, ferritin, D-dimer, and NLR still remained to be significant risk factors for predicting severe COVID-19. Besides, LDH and ferritin were independent parameters for predicting the mortality of COVID-19.
|Table 2: Comparison of laboratory parameters between severe and non-severe groups among coronavirus disease 2019 patients|
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|Table 3: The area under curve, optimal cutoff value, sensitivity, and specificity of hematologic and biochemical parameters for differentiating severe coronavirus disease 2019|
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|Table 4: The area under curve, optimal cutoff value, sensitivity, and specificity of hematologic and biochemical parameters for predicting the mortality of coronavirus disease 2019|
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|Table 5: The association of hematologic and biochemical parameters with severity and mortality of coronavirus disease 2019|
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|Figure 2: ROC curve analysis for hematologic and biochemical parameters differentiating the severity (a) and mortality (b) of COVID-19. ROC: Receiver operating characteristic, CRP: C-reactive protein, PCT: Procalcitonin, LDH: Lactate dehydrogenase, NLR: Neutrophil-to-lymphocyte ratio, PLR: Platelet-to-lymphocyte ratio, LMR: Lymphocyte-to-monocyte ratio.|
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| Discussion|| |
In this study, our results mainly revealed that certain hematologic and biochemical parameters, including CRP, PCT, LDH, ferritin, D-dimer, and NLR, were positively correlated with severe COVID-19 in the ED. Besides, higher LDH and ferritin were associated with the mortality in COVID-19. To the best of our knowledge, this was the first study indicating the association of these hematologic and biochemical parameters obtained in the ED in correlation with the severity and mortality of COVID-19 in Taiwanese population. Laboratory evaluation of these biomarkers should be examined carefully when the possibility of COVID-19 could not be ruled out for patients who visited the ED because of acute respiratory symptoms.
According to the literature review, NLR was a simple tool in predicting the prognosis of various clinical situations, including sepsis, bacterial pneumonia, malignancies,, coronary artery disease, and out-of-hospital cardiac arrest., Recent studies and meta-analyses also demonstrated the association of NLR with the severity and mortality of COVID-19,,,,, though the optimal cutoff ratio of NLR varied among studies and countries. Besides, certain factors could affect the value of NLR, such as the underlying comorbidities, disease progression, medication (especially for glucocorticosteroid therapy), and so on. Hence, only the initial laboratory parameters collected in the ED were collected and analyzed in our study. Similar to the previous investigations, our results revealed that higher NLR in the ED was associated with disease severity of COVID-19 in Taiwanese population.
It had been known that several inflammatory reactants in the acute phase, such as CRP, ferritin, LDH, and D-dimer, could be elevated in response to the release of proinflammatory cytokine interleukin-6 (IL-6) during SARS-CoV-2 infection., IL-6 had been demonstrated as one of the key mediators instigating cytokine storm, a hyperinflammatory status eventually leading to interstitial pneumonia and acute respiratory distress syndrome in severe SARS-CoV-2 infection. Indeed, it was observed that plasma levels of CRP, PCT, ferritin, LDH, and D-dimer were significantly higher in the severe COVID-19 group in previous studies,, as well as in our results. Other studies also indicated that IL-6 was an independent indicator for predicting the severity and mortality in COVID-19 patients., Since measurement of IL-6 was not easy and timely available in most ED, laboratory evaluation of CRP, PCT, ferritin, LDH, D-dimer, and NLR could be considered and hence aid physician in assessing the risk factors as well as offering optimized treatments as soon as possible for COVID-19 patients visiting ED.
Recently, it was reported that the E gene cycle threshold (Ct) value in RT-PCR was seemingly not associated with disease severity of COIVID-19. In our study population, however, the E gene Ct value was significantly lower in severe COVID-19 patients than that in non-severe COVID-19 patients (23.12 [19.70–25.80] vs. 24.26 [20.90–28.03], P = 0.014). Furthermore, the E gene Ct value was also significantly lower in COVID-19 patients with mortality than that in COVID-19 patients without (20.11 [17.78–22.40] vs. 24.20 [20.75–27.59], P < 0.001). There was no significant correlation between the E gene Ct value and the hematologic as well as biochemical parameters detected in our study, using the optimal cutoff value of each parameter for differentiating the severity and mortality of COVID-19. Whether the E gene Ct value was associated with the severity and mortality of COVID-19 remains controversial and further investigation should be warranted.
There were several limitations in our study. First, this was a retrospective study designed in a single medical center. Next, the patient number was limited as the outbreak of COVID-19 transmission had been successfully suppressed and effectively controlled within 2 months. Finally, since the disease progression could vary from patients to patients when arrival to the ED, there could be a potential deviation to a certain extent in our data.
| Conclusion|| |
Higher CRP, PCT, LDH, ferritin, D-dimer, and NLR were associated with severe COVID-19, which could help early risk stratification in the ED and contribute to optimized patient management.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]
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