Document Type : Original Article

Authors

1 Research Center for Non-communicable Diseases, Jahrom University of Medical Sciences, Jahrom, Iran

2 Student Research Committee, Jahrom University of Medical Sciences, Jahrom, Iran

3 Department of Neurosurgery, School of Medicine, Chamran Hospital, Namazi Teaching Hospital, Shiraz University of Medical Science, Iran

4 Student Research Committee, Guilan University of Medical Sciences, Rasht, Iran

Abstract

Objective: The goal of our study was to determine the prognostic value of CURB-65,
Sequential Organ Failure Assessment (SOFA), pneumonia severity index (PSI), MuLBSTA,
and Acute Physiology and Chronic Health Evaluation (APACHE) II upon admission in
patients with coronavirus disease 2019 (COVID-19, as well as the prediction cut-off value
for death regarding these parameters.
Methods: This observational retrospective study was performed in COVID-19 triage
in Peymaniyeh hospital in Jahrom in 2021. In order to calculate SOFA, APACHE II, PSI,
MuLBSTA, and CURB-65, data were collected from patients who were selected by available
sampling method from PCR-confirmed COVID-19 patients. Thirty-day mortality was
assessed as the primary outcome. ROC analysis was conducted using the STATA software to
evaluate the prognostic value of the scoring systems. DeLong test was utilized to compare
AUC of scores using a web based tool.
Results:Ninety-two patients were included in this study with the mean age of 51.02±17.81
years (male to female ratio was 1:1). SOFA had an AUC of 0.656 (P=0.130), but other indices
had statistically significant values of AUC. Based on the comparison of the AUCs, SOFA
was the worst scoring system in COVID-19 as it had significantly lower AUC than PSI and
APACHE II (P<0.05); while its comparison with MULBSTA and CURB65 was not statistically
significant (P>0.05).
Conclusion: It seems that APACHE II and PSI are the best prognostic factors in our study
with no statistical difference compared together (P>0.05). The sensitivity of APACHE II and
PSI was 0.857 with the specificity of 0.927 and 0.976, respectively. The optimal cut-off point
was 13 and 50 for APACHE II and PSI, respectively

Keywords

Main Subjects

1. Shi Y, Wang G, Cai XP, Deng JW, Zheng L, Zhu HH, et al. A noverview of COVID-19. J Zhejiang Univ Sci B. 2020;21(5):343-60. doi: 10.1631/jzus.B2000083.
2. Abiri S, Ghanaatpisheh A, Sohrabpour M, Sanie Jahromi MS,Habibzadeh SR, Shahi B, et al. Worldwide one-year dynamics of COVID-19 manifestations: a systematic review and meta-analysis. Updates in Emergency Medicine. 2022;2(1):23-33.
3. Sanie Jahromi MS, Aghaei K, Taheri L, Kalani N, Hatami N,Rahmanian Z. Intensive care unit of COVID-19 during the
different waves of outbreaks in Jahrom, south of Iran. J Med Chem Sci. 2022;5(5):734-42.
4. Sahraeai R, Sarikhani Y, Kalani N, Hatami N, Abiri AA, Eftekharian F. Prevalence of gastrointestinal symptoms in
patients with COVID-19 in Jahrom County, Fras province, southwest of Iran. J Med Chem Sci. 2022;5(4):483-90. doi:
10.26655/jmchemsci.2022.4.5.
5. Schröder I. COVID-19: a risk assessment perspective. ACS Chem Health Saf. 2020;27(3):160-9. doi: 10.1021/acs.
chas.0c00035.
6. Heldt FS, Vizcaychipi MP, Peacock S, Cinelli M, McLachlan L, Andreotti F, et al. Early risk assessment for COVID-19 patients from emergency department data using machine learning. Sci Rep. 2021;11(1):4200. doi: 10.1038/s41598-021-83784-y.
7. Núñez-Gil IJ, Fernández-Pérez C, Estrada V, Becerra-Muñoz VM, El-Battrawy I, Uribarri A, et al. Mortality risk assessment in Spain and Italy, insights of the HOPE COVID-19 registry.Intern Emerg Med. 2021;16(4):957-66. doi: 10.1007/s11739-020-02543-5.
8. Steinberg DI. ACP Journal Club. Review: risk prediction scales have different strengths and weaknesses for predicting
mortality in community-acquired pneumonia. Ann Intern Med. 2011;154(8):Jc4-12. doi: 10.7326/0003-4819-154-8-
201104190-02012.
9. Loke YK, Kwok CS, Niruban A, Myint PK. Value of severity scales in predicting mortality from community-acquired
pneumonia: systematic review and meta-analysis. Thorax. 2010;65(10):884-90. doi: 10.1136/thx.2009.134072.
10. Morris A. ACP Journal Club. Review: CURB65, CRB65, and pneumonia severity index similarly predict mortality
in community-acquired pneumonia. Ann Intern Med.2011;154(8):JC4-13. doi: 10.7326/0003-4819-154-8-
201104190-02013.
11. Chalmers JD, Singanayagam A, Akram AR, Mandal P, Short PM, Choudhury G, et al. Severity assessment tools for
predicting mortality in hospitalised patients with community-acquired pneumonia. Systematic review and meta-analysis.Thorax. 2010;65(10):878-83. doi: 10.1136/thx.2009.133280.
12. Vincent JL, Moreno R, Takala J, Willatts S, De Mendonça A, Bruining H, et al. The SOFA (Sepsis-related Organ Failure
Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine. Intensive Care Med. 1996;22(7):707-10. doi: 10.1007/bf01709751.
13. Fine MJ, Auble TE, Yealy DM, Hanusa BH, Weissfeld LA, Singer DE, et al. A prediction rule to identify low-risk
patients with community-acquired pneumonia. N Engl J Med.1997;336(4):243-50. doi: 10.1056/nejm199701233360402.
14. Guo L, Wei D, Zhang X, Wu Y, Li Q, Zhou M, et al.Clinical features predicting mortality risk in patients with
viral pneumonia: the MuLBSTA score. Front Microbiol.2019;10:2752. doi: 10.3389/fmicb.2019.02752.
15. Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of disease classification system. Crit Care Med.1985;13(10):818-29.
16. Baud D, Qi X, Nielsen-Saines K, Musso D, Pomar L, Favre G. Real estimates of mortality following COVID-19 infection.Lancet Infect Dis. 2020;20(7):773. doi: 10.1016/s1473-3099(20)30195-x.
17. Goksuluk D, Korkmaz S, Zararsiz G, Karaagaoglu AE. easyROC: an interactive web-tool for ROC curve analysis
using R language environment. R J. 2016;8(2):213-229.
18. Chen J, Liu B, Du H, Lin H, Chen C, Rao S, et al.Performance of CURB-65, PSI, and APACHE II for
predicting COVID-19 pneumonia severity and mortality.Eur J Inflamm. 2021;19:20587392211027083. doi:10.1177/20587392211027083.
19. Preetam M, Anurag A. MuLBSTA score in COVID-19 pneumonia and prediction of 14-day mortality risk: a study in
an Indian cohort. J Family Med Prim Care. 2021;10(1):223-7.doi: 10.4103/jfmpc.jfmpc_1766_20.
20. Cheng P, Wu H, Yang J, Song X, Xu M, Li B, et al. Pneumonia scoring systems for severe COVID-19: which one is better. Virol J. 2021;18(1):33. doi: 10.1186/s12985-021-01502-6.
21. Akhter S, Ali U, Rizvi N, Quratulain. A Comparison of three severity assessment scores: APACHI II SOFA and CURB
65 for predicting inpatient mortality in patients with acute exacerbation of COPD (AECOPD). Eur Respir J. 2015;46(Suppl
59): PA2169. doi: 10.1183/13993003.congress-2015.PA2169.
22. Kalani N, Hatami N, Haghbeen M, Yaqoob U, Raeyat Doost E. COVID-19 health care for Afghan refugees as a minor
ethnicity in Iran: clinical differences and racial equality in health. Acta Med Iran. 2021;59(8):466-471. doi: 10.18502/
acta.v59i8.7249.