Evaluation of the effect values of risk factors by clustering method in patients who died due to COVID-19 disease

Year 2022, Volume: 8 Issue: 5, 678 - 684, 04.09.2022

Salih Metin , Suna Eraybar , Hüseyin Aygün , İlker Ercan , Canan Demir

https://doi.org/10.18621/eurj.1140623

Abstract

Objectives: The aim of this study is to determine the factors that may be associated with mortality in patients who died due to COVID-19 and to determine the effect sizes of the factors that make a statistically significant difference.

Methods: The patients who died due to COVID-19 between 01.03.2020 and 01.03.2021 in Bursa province were evaluated retrospectively. In addition to demographic information such as age, gender, nationality, existing chronic diseases of the patients, COVID- PCR test results, length of hospital stay, intensive care unit follow up times, intubation application times were recorded. The effect size of the variables on mortality were evaluated.

Results: Total of 3,510 deaths due to COVID-19 were evaluated. Of these, 2,107 (60%) were male and 1,403 (40%) were female. Three thousand three hundred and seventy-four (96.12%) patients are 50 years or older. In both sexes, the highest number of deaths were in the age range of 70-79. The most common comorbidities were hypertension (HT) (n = 1,182; 34.16%) and diabetes mellitus (DM) (n =776; 22.43%). HT and DM had a strong effect value between the groups (p < 0.001 and p < 0.001, phi effect values: 0.661 and 0.681, respectively). Although there was a statistically significant difference for the age variable, it had an insignificant effect value (p = 0.008, 𝛿 = 0.074).

Conclusions: Risk factors frequently reported for COVID-19 deaths but there are no studies showing the true effect values. In this study, HT and DM had a strong effect separately, gender and coronary artery disease (CAD) variables were moderate, chronic obstructive pulmonary disease (COPD), lung cancer and other chronic disease variables had weak effect values, age and non-lung cancers had insignificant effect.

Keywords

Chronical disease, COVID-19, COVID-19 related deaths, effect value, risk factors

References

• 1. Shao A, Zhou Y, Tu S, Sheng J. A novel scoring system in mortality prediction of severe patients with COVID-19. EClinicalMedicine 2020;24:100450.
• 2. WHO Coronavirus Disease (COVID-19) Dashboard. Available at ‘https://covid19.who.int/’. Accessed on Apr 24, 2022
• 3. Republic of Turkey Ministry of Health. COVID-19 Information Page. Available at ‘https://covid19.saglik.gov.tr/TR-66935/genel-koronavirus-tablosu.html’. Accessed on Apr 24, 2022.
• 4. Cobos-Siles M, Cubero-Morais P, Arroyo-Jiménez I, Rey Hemandez M, Hernández-Gómez L, Vargas-Parra DJ, et al. Cause-specific death in hospitalized individuals infected with SARS-CoV-2: more than just acute respiratory failure or thromboembolic events. Intern Emerg Med 2020;15:1533-44.
• 5. Fu L, Wang B, Yuan T, Chen X, Ao Y, Fitzpatrick T, et al. Clinical characteristics of coronavirus disease 2019 (COVID-19) in China: a systematic review and meta-analysis. J Infect 2020;80:656-65.
• 6. Giorgi Rossi P, Marino M, Formisno D, Venturelli F, Vincentini M, Grilli R, et al. COVID-19 Working Group. Characteristics and outcomes of a cohort of COVID-19 patients in the Province of Reggio Emilia, Italy. PLoS One 2020;15:e0238281.
• 7. Goodacre S, Thomas B, Lee E, Sutton L, Loban A, Waterhouse S, et al. Characterisation of 22445 patients attending UK emergency departments with suspected COVID-19 infection: Observational cohort study. PLoS One 2020;15:e0240206.
• 8. Noor, FM, Islam M. Prevalence of clinical manifestations and comorbidities of coronavirus (COVID-19) infection: a meta-analysis. Fortune J Health Sci 2020;3: 55-97.
• 9. Wu C, Chen X, Cai Y, Xia J, Zhou X, Xu S, et al. Risk factors associated with acute respiratory distress dyndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA Intern Med 2020;180:934-43.
• 10. Becerra-Muñoz VM, Núñez-Gil IJ, Eid CM, García Aguado M, Romero R, Huang J, et al. Clinical profile and predictors of in-hospital mortality among older patients hospitalised for COVID-19. Age Ageing 2021;50:326-34
• 11. CDC COVID-19 Response Team. Severe Outcomes Among Patients with Coronavirus Disease 2019 (COVID-19) - United States, February 12-March 16, 2020. MMWR Morb Mortal Wkly Rep 2020;69:343-6.
• 12. Albitar O, Ballouze R, Ooi JP, Sheikh Ghadzi SM. Risk factors for mortality among COVID-19 patients. Diabetes Res Clin Pract 2020;166:108293.
• 13. Liu SP, Zhang Q, Wang W, Zhang M, Liu C, Xiao X, et al. Hyperglycemia is a strong predictor of poor prognosis in COVID-19. Diabetes Res Clin Pract 2020;167:108338.
• 14. Caramelo F, Ferreira N, Oliveiros B. Estimation of risk factors for COVID-19 mortality- preliminary results. MedRxiv 2020. doi: https://doi.org/10.1101/2020.02.24.20027268
• 15. Gansevoort RT, Hilbrands LB. CKD is a key risk factor for COVID-19 mortality. Nat Rev Nephrol 2020;16:705-6.
• 16. Ranzani OT, Bastos LSL, Gelli JGM, Marchesi JF, Baião F, Hamacher S, et al. Characterisation of the first 250,000 hospital admissions for COVID-19 in Brazil: a retrospective analysis of nationwide data. Lancet Respir Med 2021;9:407-18.
• 17. de Souza FSH, Hojo-Souza NS, Batista BDO, da Silva CM, Guidoni DL. On the analysis of mortality risk factors for hospitalized COVID-19 patients: a data-driven study using the major Brazilian database. PLoS One 2021;16:e0248580.
• 18. Zhang J, Wang X, Jia X, Li J, Hu K, Chen G, et al. Risk factors for disease severity, unimprovement, and mortality in COVID-19 patients in Wuhan, China. Clin Microbiol Infect 2020;26:767-72.
• 19. Yu C, Lei Q, Li W, Wang X, Liu W, Fan X,et al. Clinical characteristics, associated factors, and predicting COVID-19 mortality risk: a retrospective study in Wuhan, China. Am J Prev Med 2020;59:168-75
• 20. Cen Y, Chen X, Shen Y, Zhang XH, Lei Y, Xu C, et al. Risk factors for disease progression in patients with mild to moderate coronavirus disease 2019-a multi-centre observational study. Clin Microbiol Infect 2020;26:1242-7.
• 21. 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
• 22. Laguna-Goya R , Utrero-Rico A., Talayero P, Lasa-Lazaro M, Ramirez-Fernandez A, Naranjo L, et al. IL-6-based mortality risk model for hospitalized patients with COVID-19. J Allergy Clin Immunol 2020;146:799-807.e9.
• 23. Romano J, Kromrey JD, Coraggio J, Skowronek J . Appropriate statistics for ordinal level data: should we really be using t-test and Cohen's d for evaluating group differences on the NSSE and other surveys? Paper presented at the annual meeting of the Florida Association of Institutional Research, February 1 -3, 2006, Cocoa Beach, Florida.
• 24. Emami A, Javanmardi F, Pirbonyeh N, Akbari A. Prevalence of underlying diseases in hospitalized patients with COVID-19: a systematic review and meta-Analysis. Arch Acad Emerg Med 2020;8:e35.
• 25. Tadic M, Cuspidi C, Grassi G, Mancia G. COVID-19 and arterial hypertension: Hypothesis or evidence? J Clin Hypertens (Greenwich) 2020;22:1120-6.
• 26. Tadic M, Cuspidi C, Sala C. COVID-19 and diabetes: is there enough evidence? J Clin Hypertens (Greenwich) 2020;22:943-8.
• 27. Nakanishi T, Pigazzini S, Degenhardt F, Cordioli M, Butler-Laporte G, Maya-Miles D, et al. Age-dependent impact of the major common genetic risk factor for COVID-19 on severity and mortality. J Clin Invest 2021;131:e152386.