Various biomarkers like certain complete blood cell count parameters and the derived ratios including neutrophil–lymphocyte ratio are commonly used to evaluate disease severity. Our study aimed to establish if baseline levels of complete blood cell count-derived biomarkers and CRP, measured before any treatment which can interfere with their values, could serve as a predictor of development of pneumonia and the need for hospitalization requiring oxygen therapy. We retrospectively analyzed the laboratory data of 200 consecutive patients without comorbidities, who denied usage of medications prior to blood analysis and visited a COVID-19 ambulance between October and December 2021. Multivariate regression analysis extracted older age, elevated CRP and lower eosinophil count as significant independent predictors of pneumonia (p = 0.003, p = 0.000, p = 0.046, respectively). Independent predictors of hospitalization were higher CRP (p = 0.000) and lower platelet count (p = 0.005). There was no significant difference in the neutrophil–lymphocyte and platelet–lymphocyte ratios between examined groups. Individual biomarkers such as platelet and eosinophil count might be better in predicting the severity of COVID-19 than the neutrophil–lymphocyte and platelet–lymphocyte ratios.
A "true" lateral of the femoral neck is obtained by rotating the fluoroscopic beam up until the image shows the femoral neck and shaft in parallel. The angle the fluoroscopic beam has rotated up to obtain this view is the estimated FT.
Introduction. Timely detection of insulin resistance is of great importance and a number of indices have been developed for its evaluation, among which the homeostasis model assessment of insulin resistance index is the most commonly used in clinical practice. However, it can be calculated via two different models - homeostasis model assessment 1 and homeostasis model assessment 2. Most studies determine the cut-off values of the study population using the homeostasis model assessment 1, while recently most physicians use homeostasis model assessment 2 in everyday clinical practice. The aim of our study was to examine whether there was a difference in the values of homeostasis model assessment of insulin resistance and homeostasis model assessment of panceratic beta cells function calculated using these two models. Material and Methods. Laboratory findings of 42 patients who were diagnosed with glycemia and insulinemia were used in this study. Fasting and postprandial glycemia and insulinemia were used to calculate homeostasis model assessment indices using homeostasis model assessment 1 and homeostasis model assessment 2. Results. When comparing the values of the homeostasis model assessment of insulin resistance and homeostasis model assessment B indices, calculated via homeostasis model assessment 1 and homeostasis model assessment 2, we found a statistically significant difference (p < 0.001) which was also obtained when comparing the values of the homeostasis model assessment B index. Linear correlation analysis showed a significant positive correlation between the measured values of the homeostasis model assessment of insulin resistance (calculated via both models) and postprandial insulinemia at 120 minutes (p < 0.005). Conclusion. The results indicate that homeostasis model assessment 2 yields significantly lower homeostasis model assessment of insulin resistance and homeostasis model assessment B index values than when calculated by the homeostasis model assessment, which may be a stumbling block in the use of homeostasis model assessment index. It is necessary to pay attention which homeostasis model assessment model was used to define the cut-off values of these indices, and to use the same model in the diagnosis of insulin resistance in each patient in everyday clinical practice.
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