Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 1 de 1
Add filters

Document Type
Year range
Saglik Bilimlerinde Ileri Arastirmalar Dergisi / Journal of Advanced Research in Health Sciences ; 5(3):179-185, 2022.
Article in Turkish | CAB Abstracts | ID: covidwho-2321492


Objective: The Covid-19 pandemic has revealed the importance of an evidence-based efficient triage system in the early identification of high risk patients and the rational use of limited medical resources for reducing mortality. The aim of this study was to evaluate the role of various inflammatory indices that can be easily calculated using readily accessible, inexpensive routine test parameters in risk stratification and prediction of prognosis in patients with Covid-19. Material and Methods: The study was carried out retrospectively with the data of 8036 patients with Covid-19, who were grouped according to their prognosis in outpatient and inpatient follow-ups, and inpatients as survivors and death. Using the complete blood count and C-reactive protein baseline results of the patients at admission, neutrophillymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), monocytelymphocyte ratio (MLR), MVP-platelet ratio (MPR), platelet mass index (PMI), systemic immune-inflammatory index (SII), systemic inflammatory response index (SIRI), and multi-inflammatory indices (MII) were calculated. Results: Our results demonstrate that almost all of the inflammatory indices were significantly different in severe patients and in patients with high mortality risk, but not all of them had a predictive value. It has been seen that the most effective factors in determining the disease severity at the onset of Covid-19 are SIRI and age, and SII, MII-1 and MII-3 may also contribute to this prediction. Our results have also revealed that NLR is the most effective independent factor to predict mortality both at disease onset and for inpatients. Conclusion: Inflammatory indices, especially SIRI, NLR, SII, MII-1 and MII-3 can substantially contribute to clinical decisions in the early identification of high-risk patients and predicting mortality beginning from the onset of Covid-19.