Identification of Risk Factors Associated With Mortality Among Patients With COVID-19 Using Random Forest Model: A Historical Cohort Study
There is conflicting evidence about factors associated with Clinical course and risk factors for mortality of adult inpatients. We aimed to identify the demographic, clinical, treatment, and laboratory data factors associated with mortality in the Khoy district. We performed a retrospective cohort study including COVID-19 infected patients who were admitted to Qamar-Bani Hashim hospital from 2 November 2020 to 4 December 2020. We used random forest methods to explore the risk factors associated with death. The applied method was evaluated using sensitivity, specificity, accuracy, and the area under the curve. Age, pulmonary symptoms, patients need a ventilator, brain symptoms, nasal airway, job were the most important risk factors for mortality of COVID-19 in the random forest (RF) method. The RF method showed the highest accuracy, 82.9 and 79.3, for training and testing samples, respectively. However, this method resulted in the highest specificity (89.5% for training and 95.7% for testing sample) and the highest sensitivity (91.9% for training and 94.5% for testing sample). The potential risk factors consisting of older age, pulmonary symptoms, the use of a ventilator, brain symptoms, nasal airway, and the job could help clinicians to identify patients with poor prognosis at an early stage.
2. Daneshfar M, Dadashzadeh N, Ahmadpour M, Ragati Haghi H, Rahmani V, Forouzesh M, et al. Lessons of mortality following COVID-19 epidemic in the United States especially in the geriatrics. J Nephropharmacol 2021;10:e06.
3. Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet 2020;395:507-13.
4. Tabatabaii SA, Soltani P, Khanbabaee G, Sharma D, Valizadeh R, Farahbakhsh N, et al. SARS Coronavirus 2, Severe Acute Respiratory Syndrome, and Middle East Respiratory Syndrome in Children: A Review on Epidemiology, Clinical Presentation, and Diagnosis. Arch Pediatr Infect Dis 2020;8:e104860.
5. Valizadeh R, Dadashzadeh N, Zakeri R, James Kellner S, Rahimi MM. Drug therapy in hospitalized patients with very severe symptoms following COVID-19. J Nephropharmacol 2020;9:e21.
6. Raoofi A, Takian A, Sari AA, Olyaeemanesh A, Haghighi H, Aarabi M. COVID-19 pandemic and comparative health policy learning in Iran. Arch Iran Med 2020;23:220-34.
7. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020;395:497-506.
8. Verity R, Okell LC, Dorigatti I, Winskill P, Whittaker C, Imai N, et al. Estimates of the severity of coronavirus disease 2019: a model-based analysis. Lancet Infect Dis 2020;20:669-77.
9. Ahmadinejad Z, Assari R, Yazdi NA, Mazloomi SH, Javanshayani P, Afousi HK, et al. COVID-19 pandemic and biological therapy in rheumatologic disorders: how to deal with? Reumatismo 2020;72:173-7.
10. Guan W, Ni Z, Hu Y, Liang W, Ou C, He J, et al.. Clinical characteristics of coronavirus disease. N Engl J Med 2020;382:1708-720.
11. Lim LW, Yip LW, Tay HW, Ang XL, Lee LK, Chin CF, et al. Sustainable practice of ophthalmology during COVID-19: challenges and solutions. Graefes Arch Clin Exp Ophthalmol 2020;258:1427-36.
12. Mohamed-Ahmed O, McDonald B, Pardinaz-Solis R, Sigfrid L, McMullen C, Moore S, et al. The International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) response to the Zika virus outbreak. F1000Res 2016;5.
13. Breiman L. Random forests. Mach Learn 2001;45:5-32.
14. Khalifa M, Zabani I. Improving Utilization of Clinical Decision Support Systems by Reducing Alert Fatigue: Strategies and Recommendations. Stud Health Technol Inform 2016;226:51-4.
15. Buntine W, Niblett T. A further comparison of splitting rules for decision-tree induction. Mach Learn 1992;8:75-85.
16. Tayefi M, Esmaeili H, Karimian MS, Zadeh AA, Ebrahimi M, Safarian M, et al. The application of a decision tree to establish the parameters associated with hypertension. Comput Methods Programs Biomed 2017;139:83-91.
17. Alberti KG, Zimmet P, Shaw J. International Diabetes Federation: a consensus on Type 2 diabetes prevention. Diabet Med 2007;24:451-63.
18. Kumar R, Indrayan A. Receiver operating characteristic (ROC) curve for medical researchers. Indian pediatr 2011;48:277-87.
19. Barzegar A, Ghadipasha M, Rezaei N, Forouzesh M, Valizadeh R. New hope for treatment of respiratory involvement following COVID-19 by bromhexine. J Nephropharmacol 2021;10:e11.
20. Mirsoleymani S, Taherifard E, Taherifard E, Taghrir MH, Ahmadi Marzaleh M, Nekooghadam SM, et al. Predictors of Mortality Among COVID-19 Patients With or Without Comorbid Diabetes Mellitus. Acta Med Iran 2021;59:393-9.
21. Shankar A, Saini D, Roy S, Mosavi Jarrahi A, Chakraborty A, Bharti SJ, et al. Cancer care delivery challenges amidst coronavirus disease–19 (COVID-19) outbreak: specific precautions for cancer patients and cancer care providers to prevent spread. Asian Pac J Cancer Prev 2020;21:569-73.
22. Ssentongo P, Ssentongo AE, Heilbrunn ES, Ba DM, Chinchilli VM. Association of cardiovascular disease and 10 other pre-existing comorbidities with COVID-19 mortality: A systematic review and meta-analysis. PloS one 2020;15:e0238215.
23. Modi C, Boehm V, Ferraro S, Stein G, Seljak U. How deadly is COVID-19? A rigorous analysis of excess mortality and age-dependent fatality rates in Italy. medRxiv, 2020.
24. CDC COVID-19 Response Team. Coronavirus Disease 2019 in Children—United States, February 12–April 2, 2020. MMWR Morb Mortal Wkly Rep 2020;69:422-6.
25. Lippi G, Mattiuzzi C, Sanchis‐Gomar F, Henry BM. Clinical and demographic characteristics of patients dying from COVID‐19 in Italy versus China. J Med Virol 2020;92:1759-60.
26. Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus–infected pneumonia in Wuhan, China. JAMA 2020;323:1061-9.
27. Wu C, Chen X, Cai Y, Zhou X, Xu S, Huang H, et al. Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA Intern Med 2020;180:934-43.
28. Valizadeh R. Clinical and Demographic Characteristics of Patients with COVID-19 Who Died in Modarres Hospital. Maced J Med Sci 2020;8:144-9.
29. Zali A, Gholamzadeh S, Mohammadi G, Looha MA, Akrami F, Zarean E, et al. Baseline Characteristics and Associated Factors of Mortality in COVID-19 Patients; an Analysis of 16000 Cases in Tehran, Iran. Arch Acad Emerg Med 2020;8:e70.
30. Li X, Xu S, Yu M, Wang K, Tao Y, Zhou Y, et al. Risk factors for severity and mortality in adult COVID-19 inpatients in Wuhan. J Allergy Clin Immunol 2020;146:110-8.
31. Zheng Z, Peng F, Xu B, Zhao J, Liu H, Peng J, et al. Risk factors of critical & mortal COVID-19 cases: A systematic literature review and meta-analysis. J Infect 2020;81:e16-25.
32. Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW, et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area. JAMA 2020;323:2052-9.
33. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020;395:1054-62.
34. Hou W, Zhang W, Jin R, Liang L, Xu B, Hu Z. Risk factors for disease progression in hospitalized patients with COVID-19: a retrospective cohort study. Infect Dis (Lond) 2020:1-8.
35. Mikami T, Miyashita H, Yamada T, Harrington M, Steinberg D, Dunn A, et al. Risk factors for mortality in patients with COVID-19 in New York City. J Gen Intern Med 2021;36:17-26.
36. Lotfi B, Farshid S, Dadashzadeh N, Valizadeh R, Rahimi MM. Is Coronavirus Disease 2019 (COVID-19) Associated with Renal Involvement? A Review of Century Infection. Jundishapur J Microbiol 2020;13:e102899.
37. Rahimi MM, Jahantabi E, Lotfi B, Forouzesh M, Valizadeh R, Farshid S. Renal and liver injury following the treatment of COVID-19 by remdesivir. J Nephropathol 2021;10:e10.
38. Padilla-Raygoza N, Sandoval-Salazar C, León-Verdín MG, de Jesús Gallardo-Luna M, Navarro-Olivos E, Magos-Vazquez FJ, et al. Risk Factors for Mortality by Novel Corona Virus Disease, in Mexico: A Cross-Sectional Study. ARC J Public Health Community Med 2020;5:14-9.
|Issue||Vol 59, No 8 (2021)|
|Decision tree Random forests Variable importance Coronavirus disease 2019 (COVID-19) Mortality|
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