Association of Inflammatory Markers with Disease Severity and Outcome in Covid-19 Patients.

Objectives: The coronavirus pandemic was associated with a high mortality rate in the Republic of North Macedonia. Finding early markers of the disease's severity may predict outcomes and guide the treatment of the disease. The aim of our study was to evaluate the role of inflammatory markers in predicting the outcome of COVID-19 in hospitalized patients. Methods: The study included 104 PCR-confirmed COVID-19 patients who underwent hospital treatment at the Institute of Lung Diseases and Tuberculosis in Skopje, North Macedonia, between November 2020 and May 2021. Inflammatory markers were assessed in all patients and correlated with the disease severity and outcome in terms of survival or death. Results: IL-6 and LDH at admission were significantly elevated in patients with a severe or critical form of the disease and among non-survivors. In addition, IL-6 showed 87.9% of sensitivity and 61.8% of specificity for distinguishing non-survivors from survivors with a cut-off value of 21.7 pg/ml in the receiver operator curve (ROC). Procalcitonin was significantly increased in non-survivors. Parallel to the increase of disease severity, the values of CRP and LDH increased significantly during hospitalization. Conclusion: The results of the study indicate that a significant association exists between the highly increased levels of CRP, LDH, IL-6 and procalcitonin and the severity of the disease and mortality in COVID-19 patients. Their measurements and follow-up during the course of the disease could be used as predictors for prognosis and outcome but also as a subject for targeted therapy.

Maternal Lipids May Predict Fetal Growth in Type 2 Diabetes Mellitus and Gestational Diabetes Mellitus Pregnancies.

AIM: During diabetic pregnancy, complex metabolic changes occur in the lipid profile. The aim of the study was to determine the predictive values of maternal serum lipid levels on large-for-gestational age newborns during the third trimester in pregnancies of women with type 2 diabetes mellitus (DM2) and gestational diabetes mellitus (GDM). MATERIAL AND METHODS: Data of forty three pregnancies of women with DM2 and two hundred women with GDM were analyzed. The analysis encompassed the following parameters: age, body mass index (BMI), lipid parameters, HbA1c in first, second and third trimester of pregnancy, preeclampsia and baby birth weight. RESULTS: DM2 and GDM groups showed statistically significant differences in the following variables: total lipids, triglycerides, total cholesterol, BMI, age, baby birth weight, incidence of SGA and preterm delivery (9.4 ± 2.3 vs. 11.0 ± 2.3 mmol/L, 2.4 ± 1.4 vs. 3.4 ± 1.6 mmol/L, 5.5 ± 1.2 vs. 6.4 ± 1.4 mmol/L, 30.6 ± 5.4 vs. 26.9 ± 5.2 kg/m2, 34 ± 7.8 vs. 31.5 ± 5.6 years, 3183 ± 972 vs. 3533 ± 699 g., 20% vs. 7.5%, 27.9 vs. 14%, respectively, p < 0.05). Linear multiple regression analysis demonstrated that triglycerides, LDL-C and total cholesterol were independent predictors of LGA (p < 0.05). CONCLUSION: Triglycerides and LDL-C in the third trimester of pregnancy are independent predictors for fetal macrosomia in DM2 and GDM pregnancies. Thus, the maternal serum triglycerides and LDL-C levels determined in the maternal blood taken in the third trimester of pregnancy may indentify women who will give birth to LGA newborns.