Research Article

The factor analysis approach to mortality prediction in COVID-19 severe disease using laboratory values: a retrospective study

Volume: 5 Number: 2 March 15, 2022
EN

The factor analysis approach to mortality prediction in COVID-19 severe disease using laboratory values: a retrospective study

Abstract

Aim: Factor analysis is a statistical approach used mainly in social science scale development systems. The aim of this study was to evaluate the performance of factorial structures formed by laboratory values in predicting mortality in severe COVID-19 patients. Material and Method: The study included 281 patients diagnosed with ‘‘severe coronavirus infection’’ according to the WHO COVID-19 clinical management guideline who were treated in a 13-bed adult tertiary-level critical care unit of a tertiary level hospital. For a total of 23 variables (ALT, AST, BUN, creatinine, Na, K, LDH, CRP, CK, ferritin, D-dimer, INR, TB, Glu, NLR, WBC, fibrinogen, % NEU, PLT, HTC, % LYM, TLC, Alb), laboratory values were collected. A two-step method was used to determine if exploratory factors might be used in place of laboratory variables. First, the ability of individual laboratory variables to predict mortality was obtained by analysis of the receiver operating characteristic (ROC) analysis. Then, the ability of factors created from these variables to predict mortality was measured using ROC analysis. The area under curve (AUC) values were compared between the two conditions. Results: The Kaiser-Meyer-Olkin (KMO) value calculated using factor analysis on the variables was found to be 0.661. The significance level of the Bartlett’s Test was <0.001. The correlation matrix determinant was found to be 0.001. CRP, ferritin, LDH, D-dimer, PLT, and TLC all had AUC values >0.6. A five-factor structure was created based on the Scree Plot. The fifth factor, which included CRP, fibrinogen, and ferritin, was the highest for predicting mortality (AUC: 0.677). According to the individual laboratory variables, the first factor comprising TLC, CK, and NLR, had the most remarkable success (AUC: 0,642). Conclusions: The factor analysis approach can be used to present an alternative perspective for predicting mortality in COVID-19 critical disease. The factor including CRP, fibrinogen, and ferritin predicted mortality at the highest rate in this study.

Keywords

References

  1. World Health Organization (WHO). Coronavirus Disease (COVID-19) Dashboard. WHO. Accessed date: September 26 2020; Available from: https://covid19.who.int/, (n.d.).
  2. Wynants L, Van Calster B, Collins GS, et al. Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal. BMJ 2020; 369: m1328
  3. Doganci S, Ince ME, Ors N, et al. A new COVID-19 prediction scoring model for in-hospital mortality: experiences from Turkey, single center retrospective cohort analysis. Eur Rev Med Pharmacol Sci 2020; 24: 10247-57.
  4. Sperrin M, Grant SW, Peek N. Prediction models for diagnosis and prognosis in Covid-19. BMJ 2020; 369: m1464.
  5. Wu C, Chen X, Cai Y, 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.
  6. Güngörer B. Baseline demographic, clinical and laboratory risk factors for predicting admission to intensive care unit in patients diagnosed with COVID-19 in the emergency department. Anatolian Curr Med J 2021; 3: 279-83.
  7. Yıldırım Ö, Bayram M, Özmen RS, et al. Evaluation of hematological indices in terms of COVID-19 related mortality and ICU admission. J Health Sci Med 2021; 4: 666-9.
  8. Wang D, Hu B, Hu C, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA. 2020; 323: 1061-9.

Details

Primary Language

English

Subjects

Health Care Administration

Journal Section

Research Article

Publication Date

March 15, 2022

Submission Date

January 1, 2022

Acceptance Date

February 8, 2022

Published in Issue

Year 2022 Volume: 5 Number: 2

APA
Kara, U., Şimşek, F., Özhan, M. Ö., Ince, M. E., Özkan, G., Şenkal, S., & Coşar, A. (2022). The factor analysis approach to mortality prediction in COVID-19 severe disease using laboratory values: a retrospective study. Journal of Health Sciences and Medicine, 5(2), 528-533. https://doi.org/10.32322/jhsm.1052191
AMA
1.Kara U, Şimşek F, Özhan MÖ, et al. The factor analysis approach to mortality prediction in COVID-19 severe disease using laboratory values: a retrospective study. J Health Sci Med / JHSM. 2022;5(2):528-533. doi:10.32322/jhsm.1052191
Chicago
Kara, Umut, Fatih Şimşek, Mehmet Özgür Özhan, et al. 2022. “The Factor Analysis Approach to Mortality Prediction in COVID-19 Severe Disease Using Laboratory Values: a Retrospective Study”. Journal of Health Sciences and Medicine 5 (2): 528-33. https://doi.org/10.32322/jhsm.1052191.
EndNote
Kara U, Şimşek F, Özhan MÖ, Ince ME, Özkan G, Şenkal S, Coşar A (March 1, 2022) The factor analysis approach to mortality prediction in COVID-19 severe disease using laboratory values: a retrospective study. Journal of Health Sciences and Medicine 5 2 528–533.
IEEE
[1]U. Kara et al., “The factor analysis approach to mortality prediction in COVID-19 severe disease using laboratory values: a retrospective study”, J Health Sci Med / JHSM, vol. 5, no. 2, pp. 528–533, Mar. 2022, doi: 10.32322/jhsm.1052191.
ISNAD
Kara, Umut - Şimşek, Fatih - Özhan, Mehmet Özgür - Ince, Mehmet Emin - Özkan, Gökhan - Şenkal, Serkan - Coşar, Ahmet. “The Factor Analysis Approach to Mortality Prediction in COVID-19 Severe Disease Using Laboratory Values: a Retrospective Study”. Journal of Health Sciences and Medicine 5/2 (March 1, 2022): 528-533. https://doi.org/10.32322/jhsm.1052191.
JAMA
1.Kara U, Şimşek F, Özhan MÖ, Ince ME, Özkan G, Şenkal S, Coşar A. The factor analysis approach to mortality prediction in COVID-19 severe disease using laboratory values: a retrospective study. J Health Sci Med / JHSM. 2022;5:528–533.
MLA
Kara, Umut, et al. “The Factor Analysis Approach to Mortality Prediction in COVID-19 Severe Disease Using Laboratory Values: a Retrospective Study”. Journal of Health Sciences and Medicine, vol. 5, no. 2, Mar. 2022, pp. 528-33, doi:10.32322/jhsm.1052191.
Vancouver
1.Umut Kara, Fatih Şimşek, Mehmet Özgür Özhan, Mehmet Emin Ince, Gökhan Özkan, Serkan Şenkal, Ahmet Coşar. The factor analysis approach to mortality prediction in COVID-19 severe disease using laboratory values: a retrospective study. J Health Sci Med / JHSM. 2022 Mar. 1;5(2):528-33. doi:10.32322/jhsm.1052191

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