Jandric, Milka (57214108236)Milka (57214108236)JandricZlojutro, Biljana (46061719400)Biljana (46061719400)ZlojutroMomcicevic, Danica (56690345100)Danica (56690345100)MomcicevicDragic, Sasa (56690301200)Sasa (56690301200)DragicKovacevic, Tijana (56689986900)Tijana (56689986900)KovacevicDjajic, Vlado (6508151347)Vlado (6508151347)DjajicStojiljkovic, Milos P. (7003831355)Milos P. (7003831355)StojiljkovicLoncar-Stojiljkovic, Dragana (6508357052)Dragana (6508357052)Loncar-StojiljkovicSkrbic, Ranko (6506440995)Ranko (6506440995)SkrbicDjuric, Dragan M. (36016317400)Dragan M. (36016317400)DjuricKovacevic, Pedja (55377814500)Pedja (55377814500)Kovacevic2025-06-122025-06-122024https://doi.org/10.3233/THC-241006https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215144460&doi=10.3233%2fTHC-241006&partnerID=40&md5=bcc6f0a61aa7303d3b33c4645e827c72https://remedy.med.bg.ac.rs/handle/123456789/777BACKGROUND: Critically ill COVID-19 patients are usually subjected to clinical, laboratory, and radiological diagnostic procedures resulting in numerous findings. Utilizing these findings as indicators for disease progression or outcome prediction is particularly intriguing. OBJECTIVES: Exploring the significance of dynamic changes in haematological and biochemical parameters in predicting the mortality of critically ill COVID-19 patients. METHODS: The present study was a prospective and observational study involving mechanically ventilated 75 critically ill adult COVID-19 patients with hypoxemic respiratory failure. The collected data included baseline patient characteristics, treatment options, outcome, and laboratory findings at admission and 7 days after. The dynamics of the obtained findings were compared between survivors and non-survivors. RESULTS: The 28-day survival rate was 61.3%. In the group of non-survivors significant dynamic changes were found for C-reactive protein (p= 0.001), interleukin-6 (p< 0.001), lymphocyte (p= 0.003), neutrophil-lymphocyte ratio (p= 0.003), platelets (p< 0.001), haemoglobin (p< 0.001), iron (p= 0.012), and total iron-binding capacity (p< 0.001). Statistically significant changes over time were found for ferritin (p= 0.010), D-dimer (p< 0.001), hs-troponin T (p< 0.002), lactate dehydrogenase (p= 0.001), glucose (p= 0.023), unsaturated iron-binding capacity (p= 0.008), and vitamin D (p< 0.001). CONCLUSION: The dynamic changes in inflammatory, haematological and biochemical parameters can predict disease severity, and outcome. © 2025 - IOS Press. All rights reserved.COVID-19intensive carelaboratory parametersoutcomeprediction