Laboratory markers used to predict mortality in severe COVID-19

Authors

  • Ahmet Bindal Sanliurfa Education and Training Hospital, Department of Intensive Care, Sanliurfa, Türkiye
  • Mehmet Patmano Health Sciences University, Kayseri City Hospital, Department of General Surgery, Kayseri, Türkiye
  • Funda Cansun Sanliurfa Education and Training Hospital, Department of Thoracic Surgery, Sanliurfa, Türkiye

Keywords:

COVID-19, neutrophil-lymphocyte ratio, bilirubin, C-reactive protein, white blood cell, predictive factors

Abstract

Aim: Herein, we aimed to examine the laboratory parameters of COVID-19 patients and differentiate the parameters that can be used in mortality prediction.

Material and Methods: The study retrospectively examined the patients who needed intensive care unit due to COVID-19 between March 2020 and December 2020.  Three hundred and seventy-four patients who met the study criteria were included in the study. Two main groups were formed: patients discharged from the intensive care unit with no mortality and patients with a mortal course. Patients discharged constituted Group- 1, and patients who died constituted Group- 2. Patients were examined regarding demographic features, clinical, and laboratory characteristics.

 

Results: Group- 1 consisted of survived patients (n=148, 39.5%), while Group- 2 patients were the patients with mortal course (n=226, 60.4%). In Group-1, 84 (56.8%) of the patients were male, while in Group-2, 127 (56.2%) were male. In the mortality group, procalcitonin, CRP, BUN, D-dimer, troponin, LDH, lactate, and INR values were significantly higher, albumin value was lower (p< 0.001).  PLT and D-dimer were found as independent variables of mortality according to the logistic regression analysis.

Conclusion: High procalcitonin and D-dimer values obtained with routinely examined rapid and easily accessible blood tests of COVID-19 patients may contribute to mortality prediction.

 

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Published

2022-06-24

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Section

Original Articles

How to Cite

1.
Laboratory markers used to predict mortality in severe COVID-19. Ann Med Res [Internet]. 2022 Jun. 24 [cited 2025 Feb. 23];29(6):545-9. Available from: http://annalsmedres.org/index.php/aomr/article/view/4182