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, β-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.

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.

<b><i>Background:</i></b> Diabetes mellitus (DM) is known to negatively affect quality of life (QoL), yet very few studies have been done on QoL of patients with diabetes in the United Arab Emirates population. <b><i>Objectives:</i></b> The aim of this study was to assess the impact of DM on health-related QoL (HRQoL) of patients with diabetes of Emirati nationality. <b><i>Methods:</i></b> Two hundred and forty Emirati patients with diabetes, treated at the Dubai Diabetes Center, were randomly selected and interviewed using the Short Form-36 questionnaire to assess HRQoL domains. Appropriate statistical measures were performed to associate HRQoL domains with diabetes-related factors. <b><i>Results:</i></b> HRQoL satisfaction scores for physical and mental health domains were very high for the majority of participants. Male participants ranked significantly higher median scores in all HRQoL domains than females (77.36 vs. 65.28, <i>p</i> = 0.004). There was a significant (<i>p</i> &#x3c; 0.001) negative correlation between diabetes duration and the total averaged score for all sub-domains, and significant (<i>p</i> &#x3c; 0.001) negative correlations between glycated hemoglobin percentage (HBA1c%) and all sub-domains of HRQoL. Patients without complications had significantly better scores in all HRQoL sub-domains than patients suffering from any complications. Median total HRQoL score for those with neuropathy compared to those without neuropathy was 63.9 versus 82.6 (<i>p</i> &#x3c; 0.001), for nephropathy was 43.6 versus 72.5 (<i>p</i> &#x3c; 0.001), for retinopathy 50.7 versus 76.0 (<i>p</i> &#x3c; 0.001), for ischemic heart disease 54.1 versus 77.3 (<i>p</i> &#x3c; 0.001), and for cerebrovascular disease 36.7 versus 72.4 (<i>p</i> &#x3c; 0.001). Multiple regression showed 3 significant predictors for the total averaged score from all HRQoL sub-domains; these were age (<i>p</i> = 0.007), HbA1c% (<i>p</i> &#x3c; 0.001), and the number of complications related to DM (<i>p</i> = 0.001). <b><i>Conclusion:</i></b> HRQoL in Emirati patients with diabetes was significantly associated with the presence of diabetes-related complications, glycemic control, and age of the patient. The assessment of QoL in patients with diabetes can be a valuable measure for the healthcare providers to assess patient’s well-being.