Investigation of the relationship of CO-RADS and CT patterns with laboratory parameters in COVID-19 patients and a new perspective on the total CT scoring system.

BACKGROUND: It is important to determine the correlation of the CO-RADS classification and computed tomography (CT) patterns of the lung with laboratory data. To investigate the relationship of CO-RADS categories and CT patterns with laboratory data in patients with a positive RT-PCR test. We also developed a structured total CT scoring system and investigated its correlation with the total CT scoring system. METHOD: The CT examinations of the patients were evaluated in terms of the CO-RADS classification, pattern groups and total CT score. Structured total CT score values were obtained by including the total CT score values and pattern values in a regression analysis. The CT data were compared according to the laboratory data. RESULTS: A total of 198 patients were evaluated. There were significant differences between the CO-RADS groups in terms of age, ICU transfer, oxygen saturation, creatinine, LDH, D-dimer, high-sensitivity cardiac troponin-T (hs-TnT), CRP, structured total CT score values, and total CT score values. A significant difference was also observed between the CT pattern groups and oxygen saturation, creatinine and CRP values. When the structured total CT score values and total CT score values were compared they were observed to be correlated. CONCLUSIONS: Creatinine can be considered as an important marker for the CO-RADS and pattern classifications in lung involvement. LDH can be considered as an important marker of parenchymal involvement, especially bilateral and diffuse involvement. The structured total CT scoring system is a new system that can be used as an alternative.

Oxidative Status and Thiol/Disulfide Homeostasis Are Changed During 75 g Oral Glucose Tolerance Test over a Five-Hour Period.

BACKGROUND: Oral glucose loading may affect oxidative status during oral glucose tolerance test (OGTT). We aimed to investigate how oxidant and antioxidant markers and thiol/disulfide parameters change during OGTT. METHODS: OGTT was performed to 42 volunteers who were considered risk of type 2 diabetes and were divided into three groups (normoglycemic, prediabetes, diabetes) according glucose levels during OGTT. Glucose, insulin, c-peptide, total antioxidant status (TAS), total oxidant status (TOS), total thiol and native thiol were investigated with auto-anaylzer for five-hours period. RESULTS: Decrease of TAS and increase of TOS levels began with the increase in glucose and insulin levels. The increase of TAS started at third hour and reached the highest levels at fifth hour. OSI levels were higher at fourth hour than fasting and first hours in normoglycemic and diabetes groups. In the prediabetic group, TAS were higher than the other groups, TOS peak was at the second hour (p < 0.05). Native thiol and total thiol levels showed variable course during OGTT, both parameters increased at the end of the process (p < 0.05). Disulfide levels showed an increase trend but it was not statistically different in normoglycemic and diabetes groups. In prediabetes group, second hour disulfide level was lower than fasting state and disulfide was significantly increased at third, fourth and fifth hours and fifth hour disulfide level was also higher than fasting. CONCLUSION: Oxidative stress parameters and thiol/disulfide balance were found to deteriorate within five-hours after glucose loading in all groups. These results indicates that oxidative stress occurs during OGTT.

Comparison of measured and calculated osmolality levels.

BACKGROUND: Serum osmolality levels are measured to determine acid-base and electrolyte imbalance in serum. In cases where measurement is not possible, the serum osmolality value can be calculated by various calculation methods. In this study, we compared the Worthley osmolality calculation method which is used most frequently mentioned in literature and the measurements made with vapor pressure osmometer used in our laboratory. We compared whether there was a difference between the results obtained by measurement and calculation method in different age groups. METHODS: 221 serum samples of patients who were admitted to the Eskisehir Osmangazi University Hospital Biochemistry Laboratory between December 2016 and May 2018 were included in this study. Glucose, blood urea nitrogen and sodium values were recorded to determine the calculated osmolality values of the patients. RESULTS: There was a statistically significant difference between the measured osmolality values and the calculated osmolality values of the patients (p < 0.001). When compared according to age groups, there was a significant difference between calculated osmolality values (p = 0.006), but there was no difference in measured osmolality values (p = 0.787) in different age groups. It has been observed that this difference in the calculated osmolality values between the age groups is derived from the adult group (18-65, p < 0.001). CONCLUSION: Our results showed that it is not reliable to calculate serum osmolality values, especially in the adult age group. According to our results the calculated osmolality values are higher than our measured osmolality values.