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IS THERE ASSOCIATION BETWEEN MIDKINE LEVELS AND PROGNOSIS OF COVID-19 DİSEASE?
  • +11
  • Ahmed Bilal Genc,
  • Selcuk Yaylaci,
  • Hamad Dheir,
  • Ahmed Cihad Genc,
  • İlhan Yıldırım,
  • Havva Kocayigit,
  • Fatma Betül Tuncer,
  • Hande Toptan,
  • Erdem Çokluk,
  • Bekir Enes Demiryurek,
  • Ahmet Nalbant,
  • Tezcan Kaya,
  • Ali Tamer,
  • Oğuz Karabay
Ahmed Bilal Genc
Sakarya Universitesi
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Selcuk Yaylaci
Sakarya University
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Hamad Dheir
Sakarya University
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Ahmed Cihad Genc
Sakarya Universitesi
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İlhan Yıldırım
Sakarya Universitesi
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Havva Kocayigit
Sakarya Universitesi
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Fatma Betül Tuncer
Sakarya Universitesi
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Hande Toptan
Sakarya Universitesi
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Erdem Çokluk
Sakarya Universitesi
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Bekir Enes Demiryurek
Sakarya University
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Ahmet Nalbant
Sakarya University
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Tezcan Kaya
Sakarya University
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Ali Tamer
Sakarya Universitesi
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Oğuz Karabay
Sakarya University
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Abstract

Aim: The aim of this study was to measure plasma midkine levels in patients with COVID-19 and to assess its clinical significance. Material and Method: 88 patients followed in our hospital with a diagnosis of COVID-19 were included in the study. Demographic characteristics, clinical and laboratory data of the patients were recorded, and the relationship between midkine level and prognosis and other parameters were investigated. Results: Of the 88 patients included in the study, 43 (48.9%) were female and 45 (51.1%) were male. 24 (27%) of our cases were died. The mean age of non-survivals was 70 ± 12.3 and the survivals were 61.9 ± 18.2 years. Mortality predictors due to COVID-19 in group 2 patients were significantly higher than those in group 2 (p <0.05). The median (IR) value of the MK level was 152.5±125 pg/ml in all patients, 143±149 pg/ml in survivors and 165.5±76 pg/ml in those who died (p= 0.546). The difference between these two groups compared according to mortality was not statistically significant The area under the ROC curve was found to be 0.542 (95% CI 0.423-0.661, p= 0.546). Conclusion: MK is not a biomarker that can reinforce known predictors of mortality in COVID-19 patients and can provide better predictions of mortality.