ABSTRACT
Coronavirus Disease (COVID-19) was declared a pandemic by WHO in March 2020. Since then, additional novel coronavirus variants have emerged challenging the current healthcare system worldwide. There is an increased need for hospital care, especially intensive care unit (ICU), for the patients severely affected by the disease. Most of the studies analyzed COVID-19 infected patients in the hospitals and established the positive correlation between clinical parameters such as high levels of D-dimer, C-reactive protein, and ferritin to the severity of infection. However, little is known about the course of the ICU admission. The retrospective study carried out at University Hospital Sharjah, UAE presented here reports an integrated analysis of the biochemical and radiological factors among the newly admitted COVID-19 patients to decide on their ICU admission. The descriptive statistical analysis revealed that patients with clinical presentations such as acute respiratory distress syndrome (ARDS) (p<0.0001) at the time of admission needed intensive care. The ROC plot indicated that radiological factors including high chest CT scores (>CO-RADS 4) in combination with biochemical parameters such as higher levels of blood urea nitrogen (>6.7 mg/dL;66% sensitivity and 75.8% specificity) and ferritin (>290 µg/mL, 71.4% sensitivity and 77.8% specificity) may predict ICU admission with 94.2% accuracy among COVID-19 patients. Collectively, these findings would benefit the hospitals to predict the ICU admission amongst COVID-19 infected patients.
Subject(s)
COVID-19 , Blood Urea Nitrogen , Ferritins , Humans , Intensive Care Units , Retrospective Studies , Tomography, X-Ray ComputedABSTRACT
Currently, type 2 diabetes mellitus (T2DM) and obesity are major global public health issues, and their prevalence in the United Arab Emirates (UAE) are among the highest in the world. In 2019, The UAE diabetes national prevalence was 15.4%. In recent years there has been a considerable investigation of predictive biomarkers associated with these conditions. This study analysed fasting (8 h) blood samples from an obese, normoglycemic cohort and an obese, T2DM cohort of UAE nationals, employing clinical chemistry analysis, 1D 1H NMR and mass spectroscopy (FIA-MS/MS and LC-MS/MS) techniques. The novel findings reported for the first time in a UAE population revealed significant differences in a number of metabolites in the T2DM cohort. Metabolic fingerprints identified by NMR included BCAAs, trimethylamine N-oxide, ß-hydroxybutyrate, trimethyl uric acid, and alanine. A targeted MS approach showed significant differences in lysophosphatidylcholines, phosphatidylcholines, acylcarnitine, amino acids and sphingomyelins; Lyso.PC.a.C18.0, PC.ae.C34.2, C3.DC..C4.OH, glutamine and SM.C16.1, being the most significant metabolites. Pearson's correlation studies showed associations between these metabolites and the clinical chemistry parameters across both cohorts. This report identified differences in metabolites in response to T2DM in agreement with many published population studies. This contributes to the global search for a bank of metabolite biomarkers that can predict the advent of T2DM and give insight to its pathogenic mechanisms.
