Background Information on the clinical characteristics and outcomes of hospitalized Covid-19 patients with or without diabetes mellitus (DM) is limited in the Arab region. This study aims to fill this gap. Methods In this single-center retrospective study, medical records of hospitalized adults with confirmed Covid-19 [RT-PCR positive for SARS-CoV2] at King Saud University Medical City (KSUMC)-King Khaled University Hospital (KKUH), Riyadh, Saudi Arabia from May to July 2020 were analyzed. Clinical, radiological and serological information, as well as outcomes were recorded and analyzed. Results A total of 439 patients were included (median age 55 years; 68.3% men). The most prevalent comorbidities were vitamin D deficiency (74.7%), DM (68.3%), hypertension (42.6%) and obesity (42.2%). During hospitalization, 77 out of the 439 patients (17.5%) died. DM patients have a significantly higher death rate (20.5% versus 12.3%; p = 0.04) and lower survival time (p = 0.016) than non-DM. Multivariate cox proportional hazards regression model revealed that age [Hazards ratio, HR 3.0 (95% confidence interval, CI 1.7–5.3); p < 0.001], congestive heart failure [adjusted HR 3.5 (CI 1.4–8.3); p = 0.006], smoking [adjusted HR 5.8 (CI 2.0–17.2); p < 0.001], β-blocker use [adjusted HR 1.7 (CI 1.0–2.9); p = 0.04], bilateral lung infiltrates [adjusted HR 1.9 (CI 1.1–3.3); p = 0.02], creatinine > 90 µmol/l [adjusted HR 2.1 (CI 1.3–3.5); p = 0.004] and 25(OH)D < 12.5 nmol/l [adjusted HR 7.0 (CI 1.7–28.2); p = 0.007] were significant predictors of mortality among hospitalized Covid-19 patients. Random blood glucose ≥ 11.1 mmol/l was significantly associated with intensive care admission [adjusted HR 1.5 (CI 1.0–2.2); p = 0.04], as well as smoking, β-blocker use, neutrophil > 7.5, creatinine > 90 µmol/l and alanine aminotransferase > 65U/l. Conclusion The prevalence of DM is high among hospitalized Covid-19 patients in Riyadh, Saudi Arabia. While DM patients have a higher mortality rate than their non-DM counterparts, other factors such as old age, congestive heart failure, smoking, β-blocker use, presence of bilateral lung infiltrates, elevated creatinine and severe vitamin D deficiency, appear to be more significant predictors of fatal outcome. Patients with acute metabolic dysfunctions, including hyperglycemia on admission are more likely to receive intensive care.

Background: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. Methods: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low–glucose and low-glucose hypoglycemia; very high–glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation. Results: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals. Conclusion: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

Background: The importance of telemedicine in diabetes care became more evident during the coronavirus disease 2019 (COVID-19) pandemic as many people with diabetes, especially those in areas without well-established telemedicine, lost access to their health care providers (HCPs) during this pandemic. Subjects and Methods: We describe a simplified protocol of a Diabetes Telemedicine Clinic that utilizes technological tools readily available to most people with diabetes and clinics around the world. We report the satisfaction of 145 patients and 14 HCPs who participated in the virtual clinic and 210 patients who attended the virtual educational sessions about “Diabetes and Ramadan.” Results: The majority of patients agreed or strongly agreed that the use of telemedicine was essential in maintaining a good glucose control during the pandemic (97%) and they would use the clinic again in the future (86%). A similar high satisfaction was reported by patients who attended the “Diabetes and Ramadan” virtual educational session and 88% of them recommended continuing this activity as a virtual session every year. Majority of the HCPs (93%) thought the clinic protocol was simple and did not require a dedicated orientation session prior to implementing. Conclusions: The simplicity of our Diabetes Telemedicine Clinic protocol and the high satisfaction reported by patients and HCPs make it a suitable model to be adopted by clinics, especially during pandemics or disasters in resource-limited settings. This clinic model can be quickly implemented and does not require technological tools other than those widely available to most people with diabetes, nowadays. We were able to successfully reduce the number of patients, HCPs, and staff physically present in the clinics during the COVID-19 pandemic without negatively impacting the patients’ nor the HCPs’ satisfaction with the visits.