COVID-19 among people with diabetes mellitus in Saudi Arabia: Current situation and new perspectives

Changes in screening, diagnosis, management, and outcomes of gestational diabetes during the COVID-19 pandemic: A systematic review

Background

Gestational diabetes mellitus (GDM) is the most common medical complication of pregnancy, and it can lead to complications for the mother and the infant/fetus. This was especially evident during the COVID-19 pandemic. Therefore, the present systematic review aimed to describe the changes in screening, diagnosis, management, and outcomes of gestational diabetes during the COVID-19 pandemic.

Methods

The systematic review was conducted from December 2019 until January 1, 2022. To find articles related to the purpose of the study, PubMed, Scopus, Web of Science, and WHO were searched using relevant and validated keywords using MeSH/Emtree.

Results

In total, 675 entries were ascertained from the database inquiry, and 17 scholarly works were deemed suitable for inclusion in the final review. The salient conclusions derived from this review were as follows: (a) During the COVID-19 pandemic, there was a significant decrease in the use of OGTTs and a rise in the use of HbA1c assays for both GDM screening and diagnosing. (b) A predominant number of physicians incorporated some variation of telemedicine to remotely supervise and conduct follow-up evaluations of patients with GDM. Various strategies are presented for the provision of prenatal care to women afflicted with GDM, such as concentrating on high-risk demographics, the initiation of lifestyle modifications at early stages, and the implementation of remote patient monitoring techniques. The 'single test procedure' is identified as the most suitable for the preliminary screening of GDM. The OGTT should be assigned clinical precedence in patients at high risk during the ongoing COVID-19 pandemic. Additionally, Medical Nutrition Therapy (MNT) was established as the primary management strategy, and the most influential determinant of the transition from dietary adjustments to pharmacotherapy was the Fasting Blood Glucose (FBG) levels during the second trimester.

Conclusion

Suggested strategies for GDM screening and management during the pandemic integrated into routine antenatal care, emphasized the importance of remote diabetes education and technology utilization during health emergencies.

Prediction of in-hospital mortality rate in COVID-19 patients with diabetes mellitus using machine learning methods

Background

Since its emergence in December 2019, until June 2022, coronavirus 2019 (COVID-19) has impacted populations all around the globe with it having been contracted by ~ 535 M people and leaving ~ 6.31 M dead. This makes identifying and predicating COVID-19 an important healthcare priority.

Method and Material

The dataset used in this study was obtained from Shahid Beheshti University of Medical Sciences in Tehran, and includes the information of 29,817 COVID-19 patients who were hospitalized between October 8, 2019 and March 8, 2021. As diabetes has been shown to be a significant factor for poor outcome, we have focused on COVID-19 patients with diabetes, leaving us with 2824 records.

Results

The data has been analyzed using a decision tree algorithm and several association rules were mined. Said decision tree was also used in order to predict the release status of patients. We have used accuracy (87.07%), sensitivity (88%), and specificity (80%) as assessment metrics for our model.

Conclusion

Initially, this study provided information about the percentages of admitted Covid-19 patients with various underlying disease. It was observed that diabetic patients were the largest population at risk. As such, based on the rules derived from our dataset, we found that age category (51-80), CPR and ICU residency play a pivotal role in the discharge status of diabetic inpatients.

The Outcome of BNT162b2, ChAdOx1-Sand mRNA-1273 Vaccines and Two Boosters: A Prospective Longitudinal Real-World Study

To date, the effectiveness of COVID-19 vaccines and booster doses has yet to be evaluated in longitudinal head-to-head studies. This single-center longitudinal study assessed the effectiveness of ChAdOx1 nCoV-19, BNT162b2, and mRNA-1273 vaccines and assessed two BNT162b2 boosters in 1550 participants, of whom 26% had comorbidities. In addition, the SARS-CoV-2 antibody dynamics was monitored. A group of 1500 unvaccinated subjects was included as the controls. The study's endpoint was the development of virologically-proven COVID-19 cases after vaccine completion, while the secondary endpoint was hospitalizations due to severe COVID-19. Overall, 23 (4.6%), 16 (3%), and 18 (3.8%) participants vaccinated with ChAdOx1 nCoV-19, BNT162b2, and mRNA-1273, respectively, developed COVID-19 after vaccine completion, with an effectiveness of 89%, 92%, and 90%. Ten COVID-19 cases were reported in participants with comorbidities, three of whom were hospitalized. No hospitalizations occurred after boosters. SARS-CoV-2 antibody levels peaked 2-4 weeks after the second vaccine dose but declined after a mean of 28.50 ± 3.48 weeks. Booster doses significantly enhanced antibody responses. Antibody titers ≤ 154 U/mL were associated with a higher risk of COVID-19 emergence. Thus, COVID-19 vaccines effectively reduced COVID-19 and prevented severe disease. The vaccine-induced SARS-CoV-2 antibody responses declined after 28-32 weeks. Booster doses induced significant maintained responses. SARS-CoV-2 antibody levels may help determine the timing and need for vaccine booster doses.

A Review of the Impact of Pharmacogenetics and Metabolomics on the Efficacy of Metformin in Type 2 Diabetes

Metformin is the most often prescribed drug for people with type 2 diabetes (T2D). More than 120 million patients with T2D use metformin worldwide. However, monotherapy fails to achieve glycemic control in a third of the treated patients. Genetics contribute to some of the inter-individual variations in glycemic response to metformin. Numerous pharmacogenetic studies have demonstrated that variations in genes related to pharmacokinetics and pharmacodynamics of metformin's encoding transporters are mainly associated with metformin response. The goal of this review is to evaluate the current state of metformin pharmacogenetics and metabolomics research, discuss the clinical and scientific issues that need to be resolved in order to increase our knowledge of patient response variability to metformin, and how to improve patient outcomes. Metformin's hydrophilic nature and absorption as well as its action mechanism and effectiveness on T2D initiation are discussed. The impacts of variations associated with various genes are analysed to identify and evaluate the effect of genetic polymorphisms on the therapeutic activity of metformin. The metabolic pattern of T2D and metformin is also indicated. This is to emphasise that studies of pharmacogenetics and metabolomics could expand our knowledge of metformin response in T2D.

Association of COVID-19 patient’s condition with fasting blood glucose and body mass index: A retrospective study

BACKGROUND: The COVID-19 pandemic broke out in 2019 and rapidly spread across the globe. Most of the severe and dead cases are middle-aged and elderly patients with chronic systemic diseases. OBJECTIVE: This study aimed to assess the association between fasting blood glucose (FPG) and body mass index (BMI) levels in patients with coronavirus disease 2019 (COVID-19) under different conditions. METHODS: Experimental-related information (age, gender, BMI, and FPG on the second day of admission) from 86 COVID-19 cases (47 males and 39 females) with an average age of (39 ± 17) years was collected in April and November 2020. These cases were divided into three groups according to the most severe classification of each case determined by the clinical early warning indicators of severe-critically illness, the degree of progression, and the treatment plan shown in the diagnosis and treatment plan of COVID-19 pneumonia. Statistical models were used to analyze the differences in the levels of FPG and BMI, age, and gender among the three groups. RESULTS: 1. Experimental group: 21 patients with asymptomatic or and mild symptoms (group A), 45 patients with common non-progression (group B), and 20 patients with common progression and severe symptoms (group C). 2. The age differences among the three groups were statistically significant and elderly patients had a higher risk of severe disease (t= 4.1404, 3.3933, 9.2123, P= 0.0001, 0.0012, 0.0000). There was a higher proportion of females than males in the normal progression and severe disease cases (χ2= 5.512, P= 0.019). 3. The level of FPG was significantly higher in group C than in group A (t= 3.1655, P= 0.0030) and B (t= 2.0212, P= 0.0475). The number of diabetes or IFG in group C was significantly higher than in group A (χ2= 5.979, P= 0.014) and group B (χ2= 6.088, P= 0.014). 4. BMI was significantly higher in group C than in groups A (t= 3.8839, P= 0.0004) and B (t= 3.8188, P= 0.0003). The number of overweight or obese patients in group C was significantly higher than in groups A (χ2= 8.838, P= 0.003) and B (χ2= 10.794, P= 0.001). 5. Patients’ age, gender, and FPG were independent risk factors for COVID-19 disease progression (β= 0.380, 0.191, 0.186; P= 0.000, 0.034, 0.045). CONCLUSION: The levels of FPG and BMI were significantly increased in the population with common progressive and severe COVID-19. FPG and age are independent risk factors for the progression of COVID-19.

COVID-19 and Diabetes Mellitus: From Pathophysiology to Clinical Management

An increase in the severity of the coronavirus disease 2019 (COVID-19) was observed in patients infected with the acute severe metabolism syndrome coronavirus type 2 (SARS-CoV-2). Patients who have COVID-19 infection may also be more susceptible to hyperglycemia. When paired with other risk factors, hyperglycemia might alter immune and inflammatory responses, predisposing people to significant COVID-19 and perhaps deadly outcomes. Angiotensin-converting accelerator 2 (ACE2), a component of the renin-angiotensin-aldosterone system (RAAS), is the principal entry receptor for SARS-CoV-2; nevertheless, dipeptidyl enzyme 4 (DPP4) may potentially serve as a binding target. However, preliminary data did not indicate a substantial effect on the susceptibility to SARS-CoV-2 using glucose-lowering DPP4 inhibitors. Because of their pharmacologic characteristics, salt-glucose cotransporter 2 (SGLT2) inhibitors should not be advised for COVID-19 patients because they may have adverse effects. Currently, taking a hypoglycemic drug should be the most efficient way to manage acute glycemia. The majority of market proof is said to categorize two diabetes mellitus (DM) and fails to distinguish between the two primary categories of DM due to its widespread use. For grouping one DM and COVID-19, there is now some constrained proof available. Most of those findings are just preliminary, so further research will undoubtedly be required to determine the best course of action for DM patients.

Prognosis of COVID-19 in the middle eastern population, knowns and unknowns

Since its emergence in China in 2019, the SARS-CoV-2 virus has affected all countries worldwide. The virus is easily transmitted from one person to another via infected aerosols or contaminated surfaces. Unlike its counterparts, the prognosis of COVID-19 ranges from asymptomatic to critical disease or death. Several factors play a role in determining the severity of the disease in infected patients. Among others, is the pre-existence of an underlying medical condition such as diabetes, cancer, and others. Furthermore, although children are less prone to the severe form of the COVID-19 disease, they require attention due to the report of many atypical presentations of the infection, post-asymptomatic exposure. In the Middle East, little is known about the prognosis of the SARS-CoV-2 infection in high-risk categories, notably patients with diabetes, cancer, and pregnant women. The aim of this review is to summarize the current knowledge about this group of population in the middle eastern region as well as to highlight the gap in the literature. We have found that the majority of the papers were from the Gulf countries. Although, few studies were conducted; high-risk patients appear to have an increased risk of morbidity and mortality from COVID-19 compared to their counterparts. Higher levels of inflammatory markers, C-reactive protein, erythrocyte sedimentation rate, D-dimer, and ferritin levels were also observed. Children are often asymptomatic or present with atypical presentations. More studies should be conducted to determine the clinical biomarkers of COVID-19 in high-risk categories to help in patient risk stratification and management in the middle eastern population.

Prevalence of COVID-19 Infection among Patients with Diabetes and Their Vaccination Coverage Status in Saudi Arabia: A Cross-Sectional Analysis from a Hospital-Based Diabetes Registry

Patients with diabetes have a higher risk of severe infection and mortality due to COVID-19. Considering the current limited effective pharmacological treatments, vaccination remains one of the most effective means to control the pandemic. The current study aimed to determine the prevalence of COVID-19 infection and the rate of COVID-19 vaccination coverage among patients with type 2 diabetes mellitus. The patients were identified from a diabetes hospital registry at Prince Sultan Military Medical City, Riyadh, Saudi Arabia in July 2021. The history of COVID-19 infection and the vaccination status were retrieved from the National Health Electronic Surveillance Network (HESN) program and the Seha platform, respectively. A total of 11,573 patients were included in this study (representing 99.5% of all patients in the registry). A total of 1981 patients (17.1%) had a history of confirmed COVID-19 infection. The rate of vaccination with a 1st dose was 84.8% (n = 9811), while the rate of full vaccination with the 2nd dose was 55.5% (n = 6422). The analysis showed that a higher proportion of male patients were fully vaccinated than female patients (61.0% versus 51.2%, p < 0.001). There were statistically significant differences among the age groups, with the full vaccination rate ranging from 59.0% for the 61–70-year-old age group to 49.0% for the > 80-year-old age group (p < 0.001). The patients with no previous history of COVID-19 infection were more likely to get fully vaccinated than those with a previous history of the infection (63.9% versus 14.6%, respectively, p < 0.001). The factors associated with a higher likelihood of unvaccinated status included the female gender (adjusted odds ratio (aOR) = 1.705 (95% confidence interval (CI): 1.528–1.902)), elderly patients in the age group of 61–70 (aOR (95% CI) = 1.390 (1.102–1.753)), the age group of 71–80 (aOR (95% CI) = 1.924 (1.499–2.470)) and the age group of >80 (aOR (95% CI) = 3.081 (2.252–4.214), and prior history of COVID-19 infection (aOR (95% CI) = 2.501 (2.223–2.813)). In conclusion, a considerable proportion of patients with type 2 diabetes had confirmed COVID-19 infection. Continued targeted efforts are needed to accelerate vaccination coverage rates among patients with diabetes in general and the particular subgroups identified in this study.

Digital Health Platforms in Saudi Arabia: Determinants from the COVID-19 Pandemic Experience

COVID-19 poses a significant burden to healthcare systems. Healthcare organisations with better health innovation infrastructures have faced a reduced burden and achieved success in curbing COVID-19. In Saudi Arabia, digital technologies have played a vital role in fighting SARS-CoV-2 transmission. In this paper, we aimed to summarise the experience of optimising digital health technologies in Saudi Arabia as well as to discuss capabilities and opportunities during and beyond the COVID-19 pandemic. A literature search was conducted up to September 2021 to document the experience of using DHTPs in Saudi Arabia in response to the COVID-19 outbreak. We also considered any published data, press briefings, and announcements by the MOH in Saudi Arabia. The findings were synthesised in narrative form. Health officials succeeded in optimising and maintaining a strategy to mitigate the spread of the virus via different digital technologies, such as mobile health applications, artificial intelligence, and machine learning. The quick digital response in Saudi Arabia was facilitated by governmental support and by considering users and technology determinants. Future research must concentrate on establishing and updating the guidelines for using DHTPs.