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Retrospective Analysis of Covid-19 Clinical and Laboratory Data: Constructing a Multivariable Model Across Different Comorbidities Publisher Pubmed



Shokrollahi Barough M1, 2, 3 ; Darzi M4 ; Yunesian M5 ; Amini Panah D6, 9 ; Ghane Y6, 9 ; Mottahedan S1 ; Sakinehpour S7 ; Kowsarirad T7 ; Hosseinifarjam Z3 ; Amirzargar MR8 ; Dehghani S5 ; Shahriyary F8 ; Kabiri MM12 ; Nojomi M10 Show All Authors
Authors
  1. Shokrollahi Barough M1, 2, 3
  2. Darzi M4
  3. Yunesian M5
  4. Amini Panah D6, 9
  5. Ghane Y6, 9
  6. Mottahedan S1
  7. Sakinehpour S7
  8. Kowsarirad T7
  9. Hosseinifarjam Z3
  10. Amirzargar MR8
  11. Dehghani S5
  12. Shahriyary F8
  13. Kabiri MM12
  14. Nojomi M10
  15. Saraygordafshari N11
  16. Mostofi SG1
  17. Yassin Z6
  18. Mojtabavi N1, 2
Show Affiliations
Authors Affiliations
  1. 1. Department of Immunology, School of Medicine Iran University of Medical Sciences, Tehran, Iran
  2. 2. Immunology research center institute of immunology and infectious diseases Iran University of Medical Sciences, Tehran, Iran
  3. 3. ATMP Department, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran, Iran
  4. 4. Genetics Department, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran, Iran
  5. 5. Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  6. 6. Antimicrobial resistance research center, institute of immunology and infectious diseases Iran University of Medical Sciences, Tehran, Iran
  7. 7. Radiation Sciences Department, School of paramedicine, Iran University of Medical Sciences, Tehran, Iran
  8. 8. Department of Hematology & Blood Banking, School of Allied Medicine, Iran University of Medical Sciences, Tehran, Iran
  9. 9. Department of Infectious Disease, School of Medicine, Antimicrobial Resistance Research Center, Iran University of Medical Sciences, Tehran, Iran
  10. 10. Preventive Medicine and Public Health Research Center, Iran University of Medical Sciences, Iran
  11. 11. Department of Medical Biotechnology, Faculty of Allied Medical sciences Iran University of Medical sciences, Iran
  12. 12. School of engineering, the University of Warwick, Coventry, United Kingdom

Source: Journal of Infection and Public Health Published:2024


Abstract

Background: The clinical pathogenesis of COVID-19 necessitates a comprehensive and homogeneous study to understand the disease mechanisms. Identifying clinical symptoms and laboratory parameters as key predictors can guide prognosis and inform effective treatment strategies. This study analyzed comorbidities and laboratory metrics to predict COVID-19 mortality using a homogeneous model. Method: A retrospective cohort study was conducted on 7500 COVID-19 patients admitted to Rasoul Akram Hospital between 2022 and 2022. Clinical and laboratory data, along with comorbidity information, were collected and analyzed using advanced coding, data alignment, and regression analyses. Machine learning algorithms were employed to identify relevant features and calculate predictive probability scores. Results: The frequency and mortality rates of COVID-19 among males (19.3 %) were higher than those among females (17 %) (p = 0.01, OR = 0.85, 95 % CI = 0.76–0.96). Cancer (p < 0.05, OR = 1.9, 95 % CI = 1.48–2.4) and Alzheimer's (p < 0.05, OR = 2.36, 95 % CI = 1.89–2.9) were the two most common comorbidities associated with long-term hospitalization (LTH). Kidney disease (KD) was identified as the most lethal comorbidity (45 % of KD patients) (OR = 5.6, 95 % CI = 5.05–6.04, p < 0.001). Age > 55 was the most predictive parameter for mortality (p < 0.001, OR = 6.5, 95 % CI = 1.03–1.04), and the CT scan score showed no predictive value for death (p > 0.05). WBC, Cr, CRP, ALP, and VBG-HCO3 were the most significant critical data associated with death prediction across all comorbidities (p < 0.05). Conclusion: COVID-19 is particularly lethal for elderly adults; thus, age plays a crucial role in disease prognosis. Regarding death prediction, various comorbidities rank differently, with KD having a significant impact on mortality outcomes. © 2024 The Author(s)
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