Document Type : Original Article

Authors

1 Division of Tropical Medicine and Infectious Diseases, Department of Internal Medicine, Faculty of Medicine, Diponegoro University, Dr. Kariadi Hospital, Semarang, Indonesia

2 Department of Internal medicine, Faculty of Medicine, Diponegoro University, Dr. Kariadi Hospital, Semarang Indonesia

3 Department of Microbiology, Faculty of Medicine, Diponegoro University, Dr. Kariadi Hospital, Semarang Indonesia

Abstract

Patients with severe and critical COVID-19 may exhibit sepsis and mortality resulting from multi-organ failure. Neutrophil-lymphocyte-ratio (NLR) values, C-reactive protein (CRP) levels, sequential organ failure assessment (SOFA), and acute physiology and chronic health evaluation II (APACHE-II) scores were used to assess the risk of mortality in sepsis patients resulting from severe COVID-19 infection. The adequacy of NLR, CRP, SOFA, and APACHE-II scores were evaluated as predictors of mortality in septic COVID-19 patients at Dr. Kariadi Hospital Semarang, Indonesia, between August 2021 and July 2022. The subjects included severe and critical COVID-19 patients who fulfilled the WHO interim guidelines and Sepsis-3 criteria. A total of 211 patients were included, which were divided into survivor (n = 116) and non-survivor (n = 95) groups. NLR values, CRP levels, SOFA, and APACHE-II scores were measured within 24 hours of patient admission. Univariate and multivariate logistic regression analyses were used to identify the risk factors for COVID-19 mortality. Receiver operating characteristic curve analysis was used to predict the mortality of severe COVID-19 patients. The results indicated that the APACHE-II score was an independent predictor of mortality in sepsis patients resulting from severe and critical COVID-19.

Graphical Abstract

Predictors of Mortality in Sepsis Patients Resulting from Severe and Critical COVID-19

Keywords

Main Subjects

 

Introduction

Coronavirus Disease 2019 (COVID-19) is an acute infection caused by the SARS-CoV-2 virus. Approximately 14% of COVID-19 patients progress to severe cases that require hospitalization and oxygen support [1]. Five percent are admitted to the intensive care unit (ICU) and develop acute respiratory distress syndrome (ARDS), sepsis, septic shock, multi-organ failure, and most ultimately die [1]. Sepsis is most commonly caused by bacterial and fungal infections, but it can also be caused by a viral infection. The World Health Organization (WHO) considers highly transmissible pathogens as global health issues. Examples include avian and swine influenza, coronaviruses, sepsis, and septic shock at the latest stage of infection [2]. Complex host immune dysregulation accompanies respiratory failure during severe COVID-19 infection [3]. Viral sepsis may sometimes occur through direct virus-induced tissue or cell injury [4]. Therefore, all aspects of the COVID-19 definition of Sepsis-3 may be applicable [5]. Karakike et al. conducted a systematic review and meta-analysis of COVID-19-related sepsis, evaluating the prevalence of organ failure, organ replacement, and the need for ICU admission as surrogate parameters for viral sepsis, based on Sepsis-3 criteria [6].

The scoring systems that are widely used to assess the severity of multi-organ failure and the prognosis of critically ill patients are SOFA and APACHE-II. The SOFA score for sepsis patients assesses the function of six organ systems, including respiratory, coagulation, cardiovascular, liver, central nervous system, and kidney function [7`]. The APACHE-II system scores disease severity and estimates mortality in critically ill patients based on age, reason for entering intensive care, an elective postoperative, emergency, or non-operative emergency condition, chronic disease, and 12 other physiological variables [8].

In addition to disease severity, inflammatory biomarkers are useful for assessing the prognosis of COVID-19 patients, such as the neutrophil-to-lymphocyte ratio (NLR) and C-reactive protein (CRP) levels [9, 10].

The neutrophil-to-lymphocyte ratio is an indicator of the systemic inflammatory response, which reflects lymphocyte sequestration in tissues along with massive granulocyte production [11]. C-reactive protein is an acute-phase protein that acts as an early indicator of inflammation or infection. [12]. In this study, we evaluated the NLR, CRP, SOFA, and APACHE-II scores as predictors of mortality in sepsis patients resulting from severe and critical COVID-19.

Materials and Methods

This prospective cohort study was conducted at Dr. Kariadi Hospital Semarang between August 2021 and July 2022. It included patients over the age of 18 with PCR-confirmed SARS-CoV-2 and severe and critical COVID-19 based on WHO interim guidelines [1]. Severe COVID-19 criteria included oxygen saturation of less than 90% on room air and severe respiratory distress symptoms (accessory muscle use, inability to finish complete sentences, and breathing rate higher than 30 breaths per minute). Critical COVID-19 criteria included acute respiratory distress syndrome (ARDS), sepsis, and septic shock, requiring life-saving therapy, such as invasive or non-invasive ventilation or vasopressor therapy [1]. Septic shock was characterized as sepsis with prolonged hypotension, which requires vasopressors to preserve MAP ≥65 mmHg and a serum lactate level >2 mmol/L (18 mg/dL) despite adequate resuscitation [3]. Pregnant women, hemophilia patients, and those suspected of having a bacterial infection were excluded. A research ethics clearance was obtained from the Health Research Ethics Committee (KEPK) RSUP Dr. Kariadi, No. 593/EC/KEPK-RSDK/2020.

Data extraction was performed using case record forms to collect baseline patient data. The logistic analyses included baseline data, such as demographics, history of illness, clinical symptoms, and laboratory variables, to assess their association with COVID-199 severity. Laboratory confirmation of COVID-19 was performed by the microbiology laboratory in Dr. Kariadi Hospital. Within 24 hours of admission, neutrophil-to-lymphocyte ratios, CRP levels, SOFA, and APACHE-II scores were determined.

Data are presented as means and standard deviations for continuous variables and as numbers and percentages for categorical variables. Differences between groups were analyzed using the Mann-Whitney U-test for continuous data or the Chi-squared test for categorical data. The risk factors for COVID-19 mortality were identified using univariate and multivariate logistic regression analyses. Variables with p < 0.25 in the univariate logistic regression analysis were included in the multivariate logistic regression analysis. The odds ratio (OR) and confidence interval (CI) were then computed. The receiver operating characteristic (ROC) curve was used to determine the optimal cut-off of variables for predicting COVID-19 mortality risk. IBM SPSS Statistics Version 22 was used for the statistical analysis.

Results and Discussion

The baseline characteristics of severe COVID-19 patients are listed in Table 1. From 211 patients of consecutive sampling, 95 patients died within 28 days. In the non-survivor group, more patients were males (69.5%; p = 0.237) and above 50 years old (p = 0.017). Comorbidities in the non-survivor group occurred in 87.4% of the patients and the most common comorbidity was hypertension in both groups.

The comparisons between the survivor and non-survivor severe COVID-19 groups were as follows: NLR value (8.73 ± 7.56 vs. 12.49 ± 13.05; p < 0.008), CRP levels 10.21 ± 9.29 vs. 11.76 ± 8.64; p < 0.079), SOFA score (2.85 ± 2.05 vs. 4.65 ± 2.97; p < 0.001), APACHE-II score (6.75 ± 4.66 vs 12.21 ± 6.09; p < 0.001), length of stay at hospital 19.69 ± 12.38 vs. 11.90 ± 5.56; p < 0.001), heart rate (93.4 ± 11.7 vs 100.37 ± 16.6; p = 0.001), and respiratory rate (25.79 ± 3.6 vs. 28.5 ± 5.05; p < 0.001), and SO2% (92.71 ± 2.98 vs 89.61 ±7.16; p < 0.001). The values for the laboratory abnormalities were not significantly higher in the non-survivor group for WBC, urea, creatinine, total bilirubin, D-dimer, ferritin, and procalcitonin. Of these, 112 (53%) were admitted to the ICU, while the rest were in the isolation ward. There were 17 patients on ventilatory support and 15 patients died (88%).

Receiver operating characteristic (ROC) curve analysis (Figure 1) revealed that the area under the curve of NLR, CRP, SOFA score, and APACHE-II score were 0.570, 0.606, 0.704, and 0.777, respectively.

The cut-off values for NLR, CRP, SOFA, and APACHE-II scores for severe COVID-19 patient mortality are summarized in Table 2. The cut-off value for NLR was 6.71. Elevated NLR was associated with a risk of mortality [OR= 1.50 (CI 95% 1.10–2.05); p = 0.008]. The cut-off value for CRP was 8.47. Elevated CRP was associated with an increased risk of mortality [OR = 1.24 (CI 95% 0.92–1.08); p = 0.079]. The cut-off SOFA score was 2.5 and the risk of mortality was [OR =1.91 (CI 95% 1.34–2.72); p = < 0.001]. The cut-off level for the APACHE-II score was 6.5 and the risk of mortality was [OR = 2.25 (CI 95%1.63–3.11); p < 0.001].

There was a significant relationship between the SOFA score (p < 0.001), APACHE-II score (p < 0.001), and NLR (p = 0.008) associated with 28-day mortality. There was no significant relationship between C-reactive protein levels (p = 0.079).

A multiple logistic regression analysis was performed to determine the impact of independent variables presumed to be mortality predictors of COVID-19 patients. Table 3 represents the independent variables that had p < 0.25 in the bivariate analysis.

The results of multivariate analysis showed that the APACHE-II score had a p-value <0.001 for 28-day mortality. Therefore, the APACHE-II score is a good independent predictor of mortality in severe and critical COVID-19 patients [OR = 3.533 (CI 95% 1.858–6.677); p <0.001].

Indonesia is one of the Southeast Asian countries affected by COVID-19. Though several investigations have examined into the risk factors for mortality of COVID-19, the findings might differ since conditions vary by country, particularly in terms of diagnosis ability, supporting examinations, and facilities such as ICU for severe and critical patients. This study is intended to provide an overview of risk factors for mortality in patients with severe and critical COVID-19 in Indonesia.

In this study, the mortality rate of sepsis patients from severe and critical COVID-19 is high. The majority of severe and critical COVID-19 patients did not receive treatment in the ICU immediately because of the limited number of beds. The mortality rate is further associated with older age, male sex, and comorbidities [13-15]. The non-survivor group was relatively older in age, which was significantly associated with the risk of death. Older patients may have a lower immune response resulting from changes in the immune system (i.e. immunosenescence). In addition, older patients tend to have more comorbidity [13].

In the non-survivor group, 69.5% were male. Galbadage et al. found that male sex was a consistent risk factor in both Asia and Europe for COVID-19 mortality [14]. In general, women have an innate or adaptive immune system, which is superior to men for the same age range [16]. Meanwhile, the presence of aberrant methylation of the ACE2 gene promoter was found to be higher in males, which may explain why the risk of COVID-19 infection in males is higher compared with that in females [17].

In the present study, hypertension, diabetes mellitus, cancer, heart failure, hepatitis, stroke, autoimmune disease, tuberculosis, and chronic renal disease were the most common comorbidities in the cohort. Comorbidities were also considered to affect the mortality of severe COVID-19 patients. Gold et al. reported that severe COVID-19 cases had higher rates of hypertension, diabetes mellitus, and respiratory diseases [15]. Surendra et al. found that hypertension, diabetes mellitus, heart disease, chronic obstructive pulmonary disease, chronic renal disease, immunocompromised condition, liver disease, malignancy, and obesity were the most common comorbidities associated with COVID-19 patients [18].

C-reactive protein is linearly related to the inflammation degree according to the immune response of each patient. The elevated CRP levels in early stages is correlated with disease severity [19, 20]. In the present study, although serum CRP was not correlated with COVID-19 mortality, CRP levels were higher in the non-survivor group. Castelli et al. reported that CRP was high during less severe stages of systemic inflammation and organ dysfunction. However, the values did not increase further during the more severe stages of the disease [21].

In this study, NLR values >6 had a significantly positive correlation with mortality in severe and critical COVID-19. Ciccullo et al. also found that severe COVID-19 cases exhibited a considerably higher NLR compared with mild or moderate cases [22]. Severe cases of COVID-19 tend to have high neutrophil counts and lower lymphocyte counts [11]. Absolute lymphopenia is a hallmark of severe and critical SARS-Cov-2 infection and is a significant feature of the clinical phase immediately preceding decreased respiratory function and the need for additional oxygen or ventilation [23].

Koo et al. reported that an animal model may also be used to observe interactions for both SARS-CoV-2 and the immune response. Macaques lost a large number of total lymphocytes during the early stages of infection, including CD4+ and CD8+ T cells, B cells, and NK cells [24]. Lymphopenia was identified in 83.2% of SARS-CoV-2-hospitalized patients [25]. In addition, alterations in the subsets of peripheral lymphocytes appear to be linked to severe cases [26].

In this study, a cut-off SOFA score >2.5 had a significantly positive correlation with mortality in severe and critical COVID-19 cases. Zhou et al. found that severe COVID-19 patients with higher SOFA scores were significantly correlated with an increased mortality rate [27]. According to a study by Liu et al., the SOFA score is a fairly sensitive marker for risk stratification of mortality in hospitalized COVID-19 patients, with a cut-off of 3 [28]. The SOFA score is used as a diagnostic marker for sepsis and septic shock, and also can describe the severity of multi-organ disorders [29].

We found that an APACHE-II score >6.5 was significantly correlated with mortality and was a good independent predictor of mortality in severe and critical COVID-19 patients within 28 days. Wilfong et al. reported that the APACHE-II score had the best performance for predicting the mortality of severe COVID-19 patients that required intensive care [30]. Zou et al. found a similar result, in which the APACHE-II score was better at predicting hospital mortality for COVID-19 patients [31]. In the present study, the APACHE-II score was an independent predictor of mortality in sepsis patients caused by severe and critical COVID-19. The APACHE-II score measures several important components that are strongly associated with the risk of patient mortality [8].

This study had limitations. First, we did not evaluate the various treatments for the patients and several important variables, such as other biomarkers, may have an impact on the mortality of severe and critical COVID-19 cases. Second, we did not perform serial blood cultures because of patient overcapacity and the limited healthcare workforce available during the study period.

Conclusion

In this study, the APACHE-II score was a good independent predictor of mortality than NLR, CRP, and SOFA score in sepsis patients as a result of severe and critical COVID-19 within 28 days. Besides, many other factors, such as various treatments and biomarkers may have an impact on the mortality of severe and critical COVID-19.

Acknowledgments

The authors thank Suhartono Suhartono for the data analysis as well as Budi Riyanto and Muchlis Achsan Udji Sofro for supporting this study.

Disclosure Statement

No potential conflict of interest was reported by the authors.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Authors' Contributions

All authors contributed to data analysis, drafting, and revising of the paper and agreed to be responsible for all the aspects of this work.

Orcid

Nur Farhanah

https://orcid.org/0000-0002-7385-3325

Supriadi Supriadi

https://orcid.org/0000-0002-8862-5931

 Hendro Wahjono

https://orcid.org/0000-0001-6234-8772

Suharyo Hadisaputro

https://orcid.org/0000-0002-8934-8964

Muhammad Hussein Gasem

https://orcid.org/0000-0002-6069-4820

 

HOW TO CITE THIS ARTICLE

Nur Farhanah, Supriadi Supriadi, Hendro Wahjono, Suharyo Hadisaputro, Muhammad Hussein Gasem. Predictors of Mortality in Sepsis Patients Resulting from Severe and Critical COVID-19. J. Med. Chem. Sci., 2023, 6(9) 2018-2027

DOI: https://doi.org/10.26655/JMCHEMSCI.2023.9.10

URL: http://www.jmchemsci.com/article_168955.html

[1]. World Health Organization (WHO), Living guidance for clinical management of COVID-19: Interim guidance, 2021 [Google Scholar], [Publisher]
[2]. World Health Organization: Improving the prevention, diagnosis and clinical management of sepsis, 2020 [Publisher]
[3]. Giamarellos-Bourboulis E.J., Netea M.G., Rovina N., Akinosoglou K., Antoniadou A., Antonakos N., Damoraki G., Gkavogianni T., Adami M.E., Katsaounou P. Ntaganou M., Complex immune dysregulation in COVID-19 patients with severe respiratory failure, Cell Host Microbe, 2020, 27:992 [Crossref], [Google Scholar], [Publisher]
[4]. Lin G.L., McGinley J.P., Drysdale S.B., Pollard A.J., Epidemiology and immune pathogenesis of viral sepsis, Frontiers in immunology, 2018, 9:2147 [Crossref], [Google Scholar], [Publisher]
[5]. Li H., Liu L., Zhang D., Xu J., Dai H., Tang N., Su X., Cao B., SARS-CoV-2 and viral sepsis: Observations and hypotheses, The Lancet, .2020, 395:1517 [Crossref], [Google Scholar], [Publisher]
[6]. Karakike E., Bourboulis E.J.G., Kyprianou M., Struzek C.F., Pletz M.W., Netea M.G.,  et al. Coronavirus disease 2019 as a cause of viral sepsis: A systematic review and meta-analysis, Critical care medicine, 2021, 49:2042 [Crossref], [Google Scholar], [Publisher]
[7]. Singer M., Deutschman C.S., Seymour C.W., Shankar-Hari M., Annane D., Bauer M., Bellomo R., Bernard G.R., Chiche J.D., Coopersmith C.M., Hotchkiss R.S., The third international consensus definitions for sepsis and septic shock (Sepsis- 3), JAMA, 2016, 315:801 [Crossref], [Google Scholar], [Publisher]
[8]. Knaus W.A., Draper E.A., Wagner D.P., Zimmerman J.E., APACHE II: a severity of disease classification system, Critical care medicine, 1985, 13:818 [Crossref], [Google Scholar], [Publisher]
[9]. Ma A., Cheng J., Yang J., Dong M., Liao X., Kang Y., Neutrophil-to-lymphocyte ratio as a predictive biomarker for moderate-severe ARDS in severe COVID-19 patients, Critical care, 2020, 24:288 [Crossref], [Google Scholar], [Publisher]
[10]. Huang I., Pranata R., Lim M.A., Oehadian A., Alisjahbana B., C-reactive protein, procalcitonin, D-dimer, and ferritin in severe coronavirus disease-2019: a meta-analysis, Therapeutic advances in respiratory disease, 2020, 14:1753466620937175 [Crossref], [Google Scholar], [Publisher]
[11]. Liu L., Zheng Y., Cai L., Wu W., Tang S., Ding Y., Liu W., Kou G., Xiong Z., Wang S., Zheng S., Neutrophilto-lymphocyte ratio, a critical predictor for assessment of disease severity inpatients with COVID-19, International journal of laboratory hematology, 2021, 43:329 [Crossref], [Google Scholar], [Publisher]
[12]. Sproston N.R., Ashworth J.J., Role of C-reactive protein at sites of inflammation and infection, Frontiers in immunology, 2018, 9:1 [Crossref], [Google Scholar], [Publisher]
[13]. Perrotta F., Corbi G., Mazzeo G., Boccia M., Aronne L., D’Agnano V., Komici K., Mazzarella G., Parrella R., Bianco A., COVID-19 and the elderly: insights into pathogenesis and clinical decision-making, Aging clinical and experimental research, 2020, 32:1599 [Crossref], [Google Scholar], [Publisher]
[14]. Galbadage T., Peterson B.M., Awada J., Buck A.S., Ramirez D.A., Wilson J., Gunasekera R.S., Systematic review and meta-analysis of sex-specific COVID-19 clinical outcomes, Frontiers in medicine, 2020, 7:348 [Crossref], [Google Scholar], [Publisher]
[15]. Gold M.S., Sehayek D., Gabrielli S., Zhang X., McCusker C., Ben-Shoshan M., COVID-19, and comorbidities: a systematic review and meta-analysis, Postgraduate medicine, 2020, 132:749 [Crossref], [Google Scholar], [Publisher]
[16]. Klein S.L., Flanagan K.L., Sex differences in immune responses, Nature Reviews Immunology, 2016, 16:626 [Crossref], [Google Scholar], [Publisher]
[17]. Fan R., Mao S.Q., Gu T.L., Zhong F.D., Gong M.L., Hao L.M., Yin F.Y., Dong C.Z., Zhang L.N., Preliminary analysis of the association between methylation of the ACE2 promoter and essential hypertension, Molecular medicine reports, 2017, 15:3905 [Crossref], [Google Scholar], [Publisher]
[18]. Surendra H., Elyazar I.R., Djaafara B.A., Ekawati L.L., Saraswati K., Adrian V., Oktavia D., Salama N., Lina R.N., Andrianto A., Lestari K.D., Clinical characteristics and mortality associated with COVID-19 in Jakarta, Indonesia: A hospital-based retrospective cohort study, The Lancet Regional Health-Western Pacific, 2021; 9:100108 [Crossref], [Google Scholar], [Publisher]
[19]. Luo X., Zhou W., Yan X., Guo T., Wang B., Xia H., Ye L., Xiong J., Jiang Z., Liu Y., Zhang B., Prognostic value of C-reactive protein in patients with COVID-19, Clinical Infectious Diseases, 2020, 71:2174 [Crossref], [Google Scholar], [Publisher]
[20]. Yitbarek G.Y., Ayehu G.W., Asnakew S., Ayele F.Y., Gare M.B., Mulu A.T., Dagnaw F.T., Melesie B.D., The role of C-reactive protein in predicting the severity of COVID-19 disease: A systematic review, SAGE Open Medicine, 2021, 9:20503121211050755 [Crossref], [Google Scholar], [Publisher]
 [21]. Castelli G.P., Pognani C., Meisner M., Stuani A., Bellomi D., Sgarbi L., Procalcitonin and C-reactive protein during systemic inflammatory response syndrome, sepsis, and organ dysfunction, Critical care, 2004, 8:R234 [Crossref], [Google Scholar], [Publisher]
[22]. Ciccullo A., Borghetti A., Verme L.Z.D., Tosoni A., Lombardi F., Garcovich M., Biscetti F., Montalto M., Cauda R., Di Giambenedetto S., Group G.A.C., Neutrophil-to-lymphocyte ratio and clinical outcome in COVID-19: a report from the Italian front line, International journal of antimicrobial agents, 2020, 56:106017 [Crossref], [Google Scholar], [Publisher]
[23]. Huang I, Pranata R. Lymphopenia in severe coronavirus disease-2019 (COVID-19): systematic review and meta-analysis. J Intensive Care. 2020, 8:36 [Crossref], [Google Scholar], [Publisher]
[24]. Koo B.S., Oh H., Kim G., Hwang E.H., Jung H., Lee Y., Kang P., Park J.H., Ryu C.M., Hong J.J., Transient lymphopenia and interstitial pneumonia with endothelitis in SARS-CoV-2–Infected macaques, The Journal of infectious diseases, 2020, 222:1596 [Crossref], [Google Scholar], [Publisher]
[25]. Guan W.J., Ni Z.Y., Hu Y., Liang W.H., Ou C.Q., He J.X., Liu L., Shan H., Lei C.L., Hui D.S., Du B., Clinical characteristics of coronavirus disease 2019 in China, New England journal of medicine, 2020, 382:1708 [Crossref], [Google Scholar], [Publisher]
[26]. Wang .F, Nie J., Wang H., Zhao Q., Xiong Y., Deng L., Song S., Ma Z., Mo P., Zhang Y., Characteristics of peripheral lymphocyte subset alteration in COVID-19 pneumonia, The Journal of infectious diseases, 2020, 221:1762 [Crossref], [Google Scholar], [Publisher]
[27]. Zhou F., Yu T., Du R., Fan G., Liu Y., Liu Z., Xiang J., Wang Y., Song B., Gu X., Guan L., Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study, The lancet, 2020, 395:1054 [Crossref], [Google Scholar], [Publisher]
[28]. Liu S., Yao N., Qiu Y., He C., Predictive performance of SOFA and qSOFA for in-hospital mortality in severe novel coronavirus disease, The American Journal of Emergency Medicine, 2020, 38:2074 [Crossref], [Google Scholar], [Publisher]
[29]. Liu C., Suo S., Luo L., Chen X., Ling C., Cao S., SOFA Score in relation to Sepsis: Clinical Implications in Diagnosis, Treatment, and Prognostic Assessment Computational and Mathematical Methods in Medicine, 2022, 2022:7870434 [Crossref], [Google Scholar], [Publisher]
[30]. Wilfong E.M., Lovly C.M., Gillaspie E.A., Huang L.C., Shyr Y., Casey J.D., Rini B.I., Semler M.W., Severity of illness scores at presentation predict ICU admission and mortality in COVID-19, Journal of emergency and critical care medicine (Hong Kong, China), 2021, 5 [Crossref], [Google Scholar], [Publisher]
[31]. Zou X., Li S., Fang M., Hu M., Bian Y., Ling J., Yu S., Jing L., Li D., Huang J., Acute Physiology and Chronic Health Evaluation II Score as a Predictor of Hospital Mortality in Patients of Coronavirus Disease 2019, Critical care medicine, 2020, 48:e657 [Crossref], [Google Scholar], [Publisher]