Can we predict critical care mortality with non-conventional inflammatory markers in SARS-CoV-2 infected patients?

Autor: Rozanovic, Martin, Domokos, Kamilla, Márovics, Gergő, Rohonczi, Mirtill, Csontos, Csaba, Bogár, Lajos, Rendeki, Szilárd, Kiss, Tamás, Rozanovic, Melánia Nacira, Loibl, Csaba
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Zdroj: Clinical Hemorheology & Microcirculation; 2023, Vol. 84 Issue 1, p71-82, 12p
Abstrakt: BACKGROUND: Severe COVID-19 disease is associated with multiple organ involvement,then failure and often fatal outcomes.In addition,inflammatory mechanisms and cytokine storms,documented in many COVID-19 patients,are responsible for the progression of the disease and high mortality rates.Inflammatory parameters,such as procalcitonin(PCT) and C-reactive protein(CRP), are widely used in clinical practice. OBJECTIVE: To evaluate the predictive power of non-conventional inflammatory markers regarding mortality risk. METHODS: In our prospective study 52 patients were followed for 5 days after admission to an intensive care unit immediately with severe SARS-CoV-2 infection.We compared leukocyte-,platelet antisedimentation rate (LAR, PAR),neutrophil lymphocyte ratio(NLR), CRP, PCT levels. RESULTS: In non-surviving(NSU) patients LAR remained largely constant from D1 to D4 with a statistically significant drop(p < 0.05) only seen on D5.The NSU group showed statistically significant(p < 0.05) elevated LAR medians on D4 and D5, compared to the SU group.NLR values were continually higher in the non-survivor group.The difference between the SU and NSU groups were statistically significant on every examined day.PAR, CRP and PCT levels didn't show any significant differences between the SU and NSU groups. CONCLUSIONS: In conclusion, this study suggests that LAR and NLR are especially worthy of further investigation as prognostic markers.LAR might be of particular relevance as it is not routinely obtained in current clinical practice.It would seem beneficial to include LAR in data sets to train prognostic artificial intelligence. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
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