Diabetes and COVID-19 : Disease-Management-People

Association Between Diabetes Mellitus Education and Self-Management Pre- and Post-COVID-19

PurposeThis study explored the association between diabetes education and self-management during different COVID-19 periods.DesignCross-sectional study.SettingKorea Community Health Survey (2019, 2021, and 2022) and the data from Korea Centers for Disease Control and Prevention Agency.Participants78, 860 individuals with diabetes who participated in the 2019, 2021, and 2022 KCHS.MeasureDiabetes education was categorized according to whether individuals received education on how to manage the disease. Diabetes self-management was assessed using self-checking and screening of HbA1c levels.AnalysisMultiple logistic regression analysis and a subgroup analysis examined the regional impact of COVID-19 on this association.ResultsParticipants who received education before and after COVID-19 were more likely to self-manage their diabetes than those without education (pre-COVID-19 aOR = 2.11, post-COVID-19, 2022 aOR = 2.04, and post-COVID-19, 2021 aOR = 1.94). Those in regions with lower COVID-19 incidence had slightly higher self-management rates (pre-COVID-19 aOR = 2.37; post-COVID-19 2022 aOR = 2.33; post-COVID-19 2021 aOR = 2.02) compared to participants in high-incidence regions (pre-COVID-19 aOR = 1.96; post COVID-19 2021 aOR = 1.89 and post COVID-19 2022 aOR = 1.89).ConclusionsDiabetes education has a positive impact on self-management, which is especially important during public health crises such as the COVID-19 pandemic.

Progress in the management of type 2 diabetes mellitus: a narrative review of telerehabilitation and wearable devices

Type 2 diabetes mellitus (T2DM) management demands innovative strategies that address its complex nature. Telerehabilitation and conventional rehabilitation, which utilize wearable devices, represent promising avenues in this regard. This narrative review synthesizes the current literature to comprehensively compare these modalities in terms of accessibility, monitoring mechanisms, patient adherence, cost-effectiveness, and social support. Telerehabilitation offers unparalleled convenience, real-time monitoring, and personalized feedback through wearables, thereby fostering greater patient engagement and adherence compared to conventional rehabilitation. However, conventional rehabilitation provides face-to-face interactions, immediate feedback, and a more personalized touch, albeit with logistical challenges and higher costs. This review emphasizes the significance of patient preferences, technological access, and healthcare infrastructure in selecting the appropriate approach. It also calls for further research into long-term outcomes, cost-effectiveness, and the optimal integration of wearable technology in diabetes management programs. Ultimately, both telerehabilitation and conventional rehabilitation demonstrate considerable potential in empowering individuals with T2DM, underlining the imperative for tailored and patient-centric interventions in diabetes care. The review also stresses the significance of integrating patient preferences and their level of comfort with technology when deciding on treatment approaches. It also takes into account the diverse socioeconomic contexts and healthcare infrastructures globally, which can affect the viability and efficacy of both telerehabilitation and conventional rehabilitation. Moreover, the integration of wearable technology in diabetes management programs holds promise for enhancing self-management capabilities and promoting healthier lifestyles. However, it is essential to tackle prospective discrepancies in access to these technologies and ensure fair distribution. Looking forward, ongoing research efforts should focus on justifying long-term outcomes, optimizing cost-effectiveness, and refining implementation strategies to maximize the benefits of both modalities.

Reevaluating diabetes and COVID-19 outcomes using national-level data

PURPOSE

Using a US nationally representative survey of adults, we aimed to evaluate the association between prevalent diabetes and the uptake of COVID-19 testing, rate of positive testing and symptom severity.

METHODS

Data were sourced from the 2020-2021 National Health Interview Survey. COVID-19 outcomes were defined as: (1) test uptake (2) test positivity (3) diagnosis of COVID-19 and (4) severe disease symptoms with a positive COVID-19 test result. We compared the prevalence of COVID-19 outcomes by diabetes status and examined their associations using multivariate adjusted logistic and ordered logistic regression models.

RESULTS

The prevalence of test uptake and test positivity were 50.7 % and 9.4 % in the US population, respectively. 10.3 % were diagnosed with COVID-19 infection by health professionals. There were no statistically significant differences in the outcomes by diabetes status. However, individuals with diabetes were more likely to have severe symptoms. In adjusted regression model, we found no significant associations of diagnosed diabetes with all outcomes.

CONCLUSIONS

Our findings contrast with prior evidence derived from hospitalized patients. Researchers and policy makers are encouraged to review the properties of data sources and their impact on public health recommendations, particularly in response to future pandemics.

Impact of Long-Term Non-Communicable Diseases on SARS-COV-2 Hospitalized Patients Supported by Radiological Imaging in Southern Pakistan

COVID-19 patients with already existing chronic medical conditions are more likely to develop severe complications and, ultimately, a higher risk of mortality. This study analyzes the impacts of pre-existing chronic illnesses such as diabetes (DM), hypertension, and cardiovascular diseases (CVDs) on COVID-19 cases by using radiological chest imaging. The data of laboratory-confirmed COVID-19-infected hospitalized patients were analyzed from March 2020 to December 2020. Chest X-ray images were included to further identify the differences in X-ray patterns of patients with co-morbid conditions and without any co-morbidity. The Pearson chi-square test checks the significance of the association between co-morbidities and mortality. The magnitude and dimension of the association were calibrated by the odds ratio (OR) at a 95% confidence interval (95% CI) over the patients' status (mortality and discharged cases). A univariate binary logistic regression model was applied to examine the impact of co-morbidities on death cases independently. A multivariate binary logistic regression model was applied for the adjusted effects of possible confounders. For the sensitivity analysis of the model, receiver operating characteristic (ROC) was applied. Patients with different comorbidities, including diabetes (OR = 33.4, 95% CI: 20.31-54.78, p < 0.001), cardiovascular conditions (OR = 24.14, 95% CI: 10.18-57.73, p < 0.001), and hypertension (OR = 16.9, 95% CI: 10.20-27.33, p < 0.001), showed strong and significant associations. The opacities present in various zones of the lungs clearly show that COVID-19 patients with chronic illnesses such as diabetes, hypertension, cardiovascular disease, and obesity experience significantly worse outcomes, as evidenced by chest X-rays showing increased pneumonia and deterioration. Therefore, stringent precautions and a global public health campaign are crucial to reducing mortality in these high-risk groups.

Trends in prescription days and intervals between physician visits and their impact on glycemic control before and during the COVID-19 pandemic in Japan

We assessed trends in glycemic control among individuals with diabetes before and during the coronavirus disease 2019 pandemic. We used two databases to investigate changes in prescription days and the interval between physician visits and their impact on glycemic control among individuals with diabetes in Japan between 2017 and 2020. The analysis using the JMDC database indicated that prescription days were extended by approximately 20 days in 2020 compared to other years. The analysis using the Japan diabetes comprehensive database project based on an advanced electronic medical record system database revealed that intervals between physician visits were extended by approximately 7 days in 2020 compared to other years and glycemic control did not materially change in 2020. These results suggest that the prescription days increased with the spread of coronavirus disease 2019 in patients with diabetes, but the impact of the coronavirus disease 2019 pandemic on glycemic control appeared to be small.

Improvements in mental health associated with increased electronic communication and deterioration in physical health in adults aged 50+ during the COVID-19 pandemic

Background

Previous studies have documented changes in physical health, mental health and social parameters during COVID-19. At the same time, there are no comprehensive analyses of these parameters designed as longitudinal studies on large-scale older populations before and during the pandemic.

Objective

This longitudinal study aims to provide a quantitative analysis of the COVID-19 impact on the physical, mental, and social parameters in adults aged 50 and older before, in the early stages, and during the COVID-19 pandemic.

Methods

The data for this study were collected from three waves of the Survey of Health, Ageing and Retirement in Europe (SHARE), a supranational longitudinal database: pre-COVID (October 2019-March 2020), early-COVID (June-September 2020), and during-COVID (June-August 2021). The sample included 31,526 individuals, compared across the three-time points through nonparametric group comparison tests.

Results

Physical health was subjectively rated as poorer in the during-COVID wave compared to the pre-COVID wave. Additionally, the number of illnesses or health conditions reported in the during-COVID wave was significantly higher than in the pre-COVID wave, with the biggest increases registered for cardiovascular diseases. The results also show that employment and overall social contact decreased while loneliness increased over time. Unexpectedly, mental health issues, such as sadness or depression and trouble sleeping, decreased significantly in the COVID waves compared to the pre-COVID wave. The analysis of two additional pre-COVID waves (2015, 2017) revealed that poorer pre-COVID mental health reflected in high values of sadness or depression and trouble sleeping was not an isolated peak but represented a typical baseline. The positive influence on the individuals' mental health during COVID-19 was found to be electronic communication, which showed higher values than face-to-face communication and lowered the odds of sadness or depression.

Conclusion

Future policies should thus consider the positive impact of electronic contacts on mental health to promote overall health in adults aged 50 and older.

The prognostic significance of insulin resistance in COVID-19: a review

Objectives

Emerging publications indicate that diabetes predisposes patients with COVID-19 to more severe complications, which is partly attributed to inflammatory condition. In the current review, we reviewed recent published literature to provide evidence on the role of insulin resistance (IR) in diabetes, the association between diabetes and COVID-19 severity and mortality, the impact of COVID-19 infection on incident new-onset diabetes, mechanisms responsible for IR in COVID-19 patients, and the predictive value of different surrogates of IR in COVID-19.

Method

The literature search performs to find out studies that have assessed the association between IR surrogates and morbidity and mortality in patients with COVID-19.

Results

We showed that there is a bulk of evidence in support of the fact that diabetes is a potent risk factor for enhanced morbidity and mortality in COVID-19 patients. COVID-19 patients with diabetes are more prone to remarkable dysglycemia compared to those without diabetes, which is associated with an unfavourable prognosis. Furthermore, SARS-COV2 can make patients predispose to IR and diabetes via activating ISR, affecting RAAS signaling pathway, provoking inflammation, and changing the expression of PPARɣ and SREBP-1. Additionally, higher IR is associated with increased morbidity and mortality in COVID-19 patients and different surrogates of IR can be utilized as a prognostic biomarker for COVID-19 patients.

Conclusion

Different surrogates of IR can be utilized as predictors of COVID-19 complications and death.

Cardioprotective effects of vaccination in hospitalized patients with COVID-19

COVID-19 vaccination has been shown to prevent and reduce the severity of COVID-19 disease. The aim of this study was to explore the cardioprotective effect of COVID-19 vaccination in hospitalized COVID-19 patients. In this retrospective, single-center cohort study, we included hospitalized COVID-19 patients with confirmed vaccination status from July 2021 to February 2022. We assessed outcomes such as acute cardiac events and cardiac biomarker levels through clinical and laboratory data. Our analysis covered 167 patients (69% male, mean age 58 years, 42% being fully vaccinated). After adjustment for confounders, vaccinated hospitalized COVID-19 patients displayed a reduced relative risk for acute cardiac events (RR: 0.33, 95% CI [0.07; 0.75]) and showed diminished troponin T levels (Cohen's d: - 0.52, 95% CI [- 1.01; - 0.14]), compared to their non-vaccinated peers. Type 2 diabetes (OR: 2.99, 95% CI [1.22; 7.35]) and existing cardiac diseases (OR: 4.31, 95% CI [1.83; 10.74]) were identified as significant risk factors for the emergence of acute cardiac events. Our findings suggest that COVID-19 vaccination may confer both direct and indirect cardioprotective effects in hospitalized COVID-19 patients.

Clinical Characteristics and Analysis of Associated Risk Factors in Patients with Severe and Non-Severe COVID-19 Infection

Objective

Our aim was to highlight the clinical characteristics and determine the risk factors associated with severe and non-severe COVID-19 infection.

Study Method

A retrospective review was conducted on clinical data obtained from patients with COVID-19 infection, admitted to the emergency department between November 2022 and January 2023. Total of 1684 participants were categorized into severe (312 cases,18.53%) and non-severe (1,372 cases,81.47%) cohorts. Logistic regression was utilized for multivariate analysis, with a P-value less than 0.05 signifying a significant difference between the groups.

Results

The study consisted of 952 males (56.53%) and 732 females (43.47%) participants. The age distribution ranged from 18 to 93 years in both cohorts. There were statistically significant differences between the clinical symptoms of the severe and non-severe cohorts (P < 0.05). According to the multivariate statistical analysis, patients with more pronounced clinical manifestations had significantly elevated values related to age(P < 0.05), diabetes(P < 0.01), hypertension(P < 0.01), C-reactive protein (CRP) (P < 0.05), and lactate dehydrogenase (LDH) (P < 0.01) as compared to those presenting with milder symptoms.

Conclusion

The primary clinical presentations in both the cohorts were mostly similar. Predominant factors contributing to the severity of COVID-19 infection were age, diabetes, hypertension, elevated CRP levels, and increased LDH.

Risk prediction for severe COVID-19 progressing to critical illness and death in the ICU and efficacy analysis of using traditional Chinese medicine

To reveal the key factors influencing the progression of severe COVID-19 to critical illness and death in the intensive care unit (ICU) and to accurately predict the risk, as well as to validate the efficacy of treatment using traditional Chinese medicine (TCM), thus providing valuable recommendations for the clinical management of patients. A total of 189 patients with COVID-19 in 25 ICUs in Chongqing, China, were enrolled, and 16 eventually died. Statistical models shown that factors influencing the progression of COVID-19 to critical illness include the severity of illness at diagnosis, the mode of respiratory support, and the use of TCM. Risk factors for death include a history of metabolic disease, the use of antiviral drugs and TCM, and invasive endotracheal intubation. The area under curve of the noncollinearity model predicted the risk of progression to critical illness and the risk of death reached 0.847 and 0.876, respectively. The use of TCM is an independent protective factor for the prevention of the progression of severe COVID-19, while uncorrectable hypoxemia and invasive respiratory support are independent risk factors, and antiviral drugs can help reduce mortality. The multifactorial prediction model can assess the risk of critical illness and death in ICU COVID-19 patients, and inform clinicians in choosing the treatment options and medications.

Exploring Disease Management Experiences of Individuals with Type 2 Diabetes During the COVID-19 Pandemic: A Qualitative Study

The aim of this study was to investigate the impact of COVID-19 infection on disease management among individuals with type 2 diabetes and to explore their perspectives on COVID-19. This descriptive qualitative study included patients with diabetes, with a sample of 15 patients meeting the study criteria. The data were analyzed using code groups, which were then further categorized into main themes and subthemes. The main themes were: initial contact with the SARS-CoV-2 that is associated with COVID-19 illness changes in diabetes self-management behaviors; attempt at maintaining diabetes selfmanagement behaviors; and problems with accessing diabetes care. The study findings revealed several significant insights. Individuals with diabetes exhibited a fear of contracting SARS-CoV-2, which led to reduced levels of exercise and difficulties in managing blood sugar levels and insulin adjustments. Moreover, due to anxiety about COVID-19 infection, they postponed health check-ups, resulting in experiencing diabetes-related complications.

Cardiac Complications and COVID-19: A Review of Life-threatening Co-morbidities

The novel 2019 coronavirus disease (COVID-19) was first reported in the last days of December 2019 in Wuhan, China. The presence of certain co-morbidities, including cardiovascular diseases (CVDs), are the basis for worse outcomes in patients with COVID-19. Relevant English-language literature was searched and retrieved from the Google Scholar search engine and PubMed database up to 2023 using COVID-19, SARS-CoV-2, Heart failure, Myocardial infarction, and Arrhythmia and Cardiac complication as keywords. Increased hemodynamic load, ischemia-related dysfunction, ventricular remodeling, excessive neurohumoral stimulation, abnormal myocyte calcium cycling, and excessive or insufficient extracellular matrix proliferation are associated with heart failure (HF) in COVID-19 patients. Inflammatory reaction due to the excessive release of inflammatory cytokines, leads to myocardial infarction (MI) in these patients. The virus can induce heart arrhythmia through cardiac complications, hypoxia, decreased heart hemodynamics, and remarkable inflammatory markers. Moreover, studies have linked cardiac complications in COVID-19 with poor outcomes, extended hospitalization time, and increased mortality rate. Patients with COVID-19 and CVDs are at higher mortality risk and they should be given high priority when receiving the treatment and intensive care during hospitalization.

The impact of impaired insulin regulation on severity of SARS-CoV-2 infection: a 2-year retrospective single-center analysis

Background

The COVID-19 pandemic has caused an international healthcare crisis and produced a large healthcare burden. Diabetes mellitus (DM) is a common disease that can be controlled via pharmacologic agents; however, many patients have poor glycemic control, leading to disease-related complications. DM has been reported in the literature to be associated with increasing morbidity and mortality in COVID-19 patients. The authors aim to assess the associations between glucose homoeostasis and COVID-19 disease severity and mortality.

Methods

A retrospective chart review of patients ages 18-100 years of age admitted with COVID-19 between January 2020 and December 2021 was performed. The primary outcome was COVID-19 mortality with respect to haemoglobin A1C levels of less than 5.7%, 5.7-6.4%, and 6.5% and greater. Disease severity was determined by degree of supplemental oxygen requirements (ambient air, low-flow nasal cannula, high-flow nasal cannula, non-invasive mechanical ventilation, and invasive mechanical ventilation). COVID-19 mortality and severity were also compared to blood glucose levels on admission as grouped by less than 200 mg/dl and greater than or equal to 200 mg/dl.

Results

A total of 1156 patients were included in the final analysis. There was a statistically significant association between diabetic status and mortality (P=0.0002). Statistical significance was also noted between admission blood glucose ≥200 mg/dl and mortality (P=0.0058) and respiratory disease severity (P=0.0381). A multivariate logistic regression for predicting mortality showed increasing haemoglobin A1C was associated with increased mortality (odds ratio 1.72 with 95% CI of 1.122-2.635).

Conclusions

In our 2-year retrospective analysis, there was an association between a diagnosis of DM and COVID-19-related mortality. Hyperglycaemia on admission was found to be statistically significant with mortality in patients diagnosed with COVID-19. Glucose homoeostasis and insulin dysregulation likely play a contributing factor to COVID-19 disease severity and mortality.

Medical and social factors influencing the utilization of healthcare services among older adults in Israel during the COVID-19 lockdown

Background

The corona virus disease 2019 (COVID-19) pandemic significantly impacted older adults. However, most older communities focused on the medical issues. The aims of this study were to identify the medical and social factors linked with the usage of medical services during the COVID-19 lockdown in Israel.

Methods

The study was conducted Over two periods of time from February to April in 2019 (P1), before the COVID-19 and from February to April in 2020 (P2), during the first lockdown. The study was conducted on people aged 65 and older in Israel. The variable statistics were analyzed using frequency tabulation, cross-tabulation frequencies, and t-tests. Two hierarchical logistic regressions were conducted over four steps for each period.

Results

The participants (n = 102,303) comprised 64.5% female (65,946) and 35.5% male (36,357) (mean age 80.5, SD- 7.46). It was found that participants who had not subscribed to the supportive community services were 7.47 times more likely to access medical services in P1 and 12.417 times more likely to access medical services during the lockdown. This variable was also found to be a strong predictor in the final model. The most significant variable for predicting the participants' needs during P2 was their previous needs in P1. Other social variables were living in assisted living home and living in community settlements. The presence of 12 diseases in this study did not predict service demand.

Conclusion

Community support reduces medical service demands during disasters and provides services for older adults. During pandemics, however, social services need to be expanded and made more easily accessible to older adults.

A Transformer-Based Model Trained on Large Scale Claims Data for Prediction of Severe COVID-19 Disease Progression

In situations like the COVID-19 pandemic, healthcare systems are under enormous pressure as they can rapidly collapse under the burden of the crisis. Machine learning (ML) based risk models could lift the burden by identifying patients with a high risk of severe disease progression. Electronic Health Records (EHRs) provide crucial sources of information to develop these models because they rely on routinely collected healthcare data. However, EHR data is challenging for training ML models because it contains irregularly timestamped diagnosis, prescription, and procedure codes. For such data, transformer-based models are promising. We extended the previously published Med-BERT model by including age, sex, medications, quantitative clinical measures, and state information. After pre-training on approximately 988 million EHRs from 3.5 million patients, we developed models to predict Acute Respiratory Manifestations (ARM) risk using the medical history of 80,211 COVID-19 patients. Compared to Random Forests, XGBoost, and RETAIN, our transformer-based models more accurately forecast the risk of developing ARM after COVID-19 infection. We used Integrated Gradients and Bayesian networks to understand the link between the essential features of our model. Finally, we evaluated adapting our model to Austrian in-patient data. Our study highlights the promise of predictive transformer-based models for precision medicine.

Correlations between serum leptin levels and classical biomarkers in SARS-CoV-2 infection, in critically ill patients

BACKGROUND

Altered levels of some blood markers might be linked with the degree of severity and mortality of patients with SARS-CoV-2 infection. This study aimed to find out if there are correlations between serum leptin levels and classical biomarkers.

MATERIALS AND METHODS

We present a single-center observational cohort study on SARS-CoV-2 infected patients. The study was conducted at Infectious Diseases Clinic of Academic Emergency Hospital Sibiu, from May through November 2020. In this study, we retrospectively analyzed 54 patients, all with confirmed SARS-CoV-2 infection.

RESULTS

Our results revealed that there is a negative correlation between serum leptin and Interleukin-6 levels and a positive correlation between serum leptin and blood glucose levels. A positive correlation between ferritin and lactate dehydrogenase levels was also observed. No correlation was found between leptin and other biomarkers such as ferritin, neutrophil/lymphocyte ratio, lactate dehydrogenase, C-reactive protein, fibrinogen, erythrocyte sedimentation rate, or D-dimer.

CONCLUSIONS

Further studies need to be conducted to investigate the role of leptin in SARS-CoV-2 infection. The results of this research could contribute to the introduction of the determination of serum leptin levels in the routine evaluation of patients with critical illness.

Prevalence and impact of diabetes mellitus in hospitalized COVID-19 patients in a Tunisian Center: a cross-sectional study

Background

The outbreak of the coronavirus disease 2019 (COVID-19) has become an evolving worldwide health crisis. With the rising prevalence of diabetes mellitus has come an increasing awareness of their impacts on infectious diseases, and the risk for postinfection complications and mortality from critical infections.

Objective

The objective of this study was to evaluate the prevalence and impact of diabetes mellitus on the severity and mortality of COVID-19.

Methods

Data of laboratory-confirmed hospitalized patients at the COVID-19 unit between September 2020 and August 2021 were analyzed, in a cross-sectional study. The population was classified into two groups: COVID-19 patients with and without diabetes. Primary outcomes were the overall length of hospital stay, the admission to the ICU, and death. The association between diabetes and death was assessed in a Cox proportional hazards model.

Results

A total of 866 patients were included. There were 270 (31.2%) patients with diabetes. Diabetic patients were more likely to have hypertension (58.1 vs. 33.4%), cardiovascular disease (18.5 vs. 10.4%), and dyslipidaemia (17.8 vs. 7.2). Overall, 263 patients died, among them only 86 in the diabetic group (P=0.523). Patients with diabetes had a higher risk of developing complications (P<0.001). Multivariate Cox regression analysis showed that diabetes was not significantly associated with death [HR (95% CI): 1.253 (0.963-1.631)].

Conclusion

Diabetes was associated with a greater risk of complications in patients with COVID-19. Special attention to diabetic patients during treatment must be given to avoid these complications.

COVID-19 resilience index in European Union countries based on their risk and readiness scale

Addressing risks and pandemics at a country level is a complex task that requires transdisciplinary approaches. The paper aims to identify groups of the European Union countries characterized by a similar COVID-19 Resilience Index (CRI). Developed in the paper CRI index reflects the countries' COVID-19 risk and their readiness for a crisis situation, including a pandemic. Moreover, the study detects the factors that significantly differentiate the distinguished groups. According to our research, Bulgaria, Hungary, Malta, and Poland have the lowest COVID-19 Resilience Index score, with Croatia, Greece, Czechia, and Slovakia following close. At the same time, Ireland and Scandinavian countries occupy the top of the leader board, followed by Luxemburg. The Kruskal-Wallis test results indicate four COVID-19 risk indicators that significantly differentiate the countries in the first year of the COVID-19 pandemic. Among the significant factors are not only COVID-19-related factors, i.e., the changes in residential human mobility, the stringency of anti-COVID-19 policy, but also strictly environmental factors, namely pollution and material footprint. It indicates that the most critical global environmental issues might be crucial in the phase of a future pandemic. Moreover, we detect eight readiness factors that significantly differentiate the analysed country groups. Among the significant factors are the economic indicators such as GDP per capita and labour markets, the governance indicators such as Rule of Law, Access to Information, Implementation and Adaptability measures, and social indicators such as Tertiary Attainment and Research, Innovation, and Infrastructure.

A nonlinear mathematical model on the Covid-19 transmission pattern among diabetic and non-diabetic population

In this paper, a three tier mathematical model describing the interactions between susceptible population, Covid-19 infected, diabetic population and Covid-19 infected, non diabetic population is proposed. Basic properties of such a dynamic model, namely, non negativity, boundedness of solutions, existence of disease-free and disease equilibria are studied and sufficient conditions are obtained. Basic reproduction number for the system is derived. Sufficient conditions on functionals and parameters of the system are obtained for the local as well as global stability of equilibria, thus, establishing the conditions for eventual prevalence of disease free or disease environment, as the case may be. The stability aspects are discussed in the context of basic reproduction number and vice versa. An important contribution of this article is that a novel technique is presented to estimate some key, influencing parameters of the system so that a pre-specified, assumed equilibrium state is approached eventually. This enables the society to prepare itself with the help of these key, influencing parameters so estimated. Several examples are provided to illustrate the results established and simulations are provided to visualize the examples.

Comprehensive analysis of clinical data for COVID-19 outcome estimation with machine learning models

COVID-19 is a global threat for the healthcare systems due to the rapid spread of the pathogen that causes it. In such situation, the clinicians must take important decisions, in an environment where medical resources can be insufficient. In this task, the computer-aided diagnosis systems can be very useful not only in the task of supporting the clinical decisions but also to perform relevant analyses, allowing them to understand better the disease and the factors that can identify the high risk patients. For those purposes, in this work, we use several machine learning algorithms to estimate the outcome of COVID-19 patients given their clinical information. Particularly, we perform 2 different studies: the first one estimates whether the patient is at low or at high risk of death whereas the second estimates if the patient needs hospitalization or not. The results of the analyses of this work show the most relevant features for each studied scenario, as well as the classification performance of the considered machine learning models. In particular, the XGBoost algorithm is able to estimate the need for hospitalization of a patient with an AUC-ROC of 0 . 8415 ± 0 . 0217 while it can also estimate the risk of death with an AUC-ROC of 0 . 7992 ± 0 . 0104 . Results have demonstrated the great potential of the proposal to determine those patients that need a greater amount of medical resources for being at a higher risk. This provides the healthcare services with a tool to better manage their resources.

In situ electrospun aloe-nanofiber membrane for chronic wound healing

Alleviating excessive inflammation while accelerating chronic wound healing to prevent wound infection has remained challenging, especially during the coronavirus disease 2019 (COVID-19) pandemic caused by SARS-CoV-2 when patients experienced difficulties with receive appropriate healthcare. We addressed this issue by developing handheld electrospun aloe-nanofiber membranes (ANFMs) with convenient, environmentally friendly properties and a therapeutic capacity for wound closure. Our results showed that ANFMs fabricated with high molecular weight polyvinyl alcohol (PVA) to form fibers during electrospinning had uniform fibrous architecture and a porous structure. Given the value of aloe gel in accelerating wound healing, liquid extracts from ANFMs significantly downregulated the expression of the pro-inflammatory genes, interleukin-6 (IL-6) and inducible nitric oxide synthase (iNOS), and markedly suppress the generation of reactive oxygen species (ROS) induced by lipopolysaccharide in RAW264.7 macrophages. These results indicated the excellent antioxidant and anti-inflammatory effects of ANFMs. After implantation into a mouse diabetic wound model for 12 days in situ, ANFMs notably expedited chronic wound healing via promoting angiogenesis and enhancing cell viability. Our ANFMs generated by handheld electrospinning in situ healed chronic wounds offer a convenient and promising alternative for patients to heal their own wounds under variable conditions.

COVID-19: Diabetes Perspective-Pathophysiology and Management

Recent evidence relating to the impact of COVID-19 on people with diabetes is limited but continues to emerge. COVID-19 pneumonia is a newly identified illness spreading rapidly throughout the world and causes many disabilities and fatal deaths. Over the ensuing 2 years, the indirect effects of the pandemic on healthcare delivery have become prominent, along with the lingering effects of the virus on those directly infected. Diabetes is a commonly identified risk factor that contributes not only to the severity and mortality of COVID-19 patients, but also to the associated complications, including acute respiratory distress syndrome (ARDS) and multi-organ failure. Diabetic patients are highly affected due to increased viral entry into the cells and decreased immunity. Several hypotheses to explain the increased incidence and severity of COVID-19 infection in people with diabetes have been proposed and explained in detail recently. On the other hand, 20-50% of COVID-19 patients reported new-onset hyperglycemia without diabetes and new-onset diabetes, suggesting the two-way interactions between COVID-19 and diabetes. A systematic review is required to confirm diabetes as a complication in those patients diagnosed with COVID-19. Diabetes and diabetes-related complications in COVID-19 patients are primarily due to the acute illness caused during the SARS-CoV-2 infection followed by the release of glucocorticoids, catecholamines, and pro-inflammatory cytokines, which have been shown to drive hyperglycemia positively. This review provides brief insights into the potential mechanisms linking COVID-19 and diabetes, and presents clinical management recommendations for better handling of the disease.

Analyzing the Effectiveness of mHealth to Manage Diabetes Mellitus Among Adults Over 50: A Systematic Literature Review

Purpose

A total of 537 million suffered from diabetes mellitus in 2021, and the aging of the population will not abate this number in the future. Diabetes predisposes people to ailments and doubles the risk of COVID-19 mortality. mHealth has shown promise to help manage diabetes. The aim of this review is to objectively analyze research from the last 2.5 years to assess effectiveness where mHealth has been used as an intervention to help manage diabetes in older patients. We also analyzed patient satisfaction, quality, and barriers to adoption of mHealth to manage diabetes.

Patients and Methods

No human subjects were involved in this review. We queried four research databases for mHealth to manage diabetes in older adults. We conducted the review based on the Kruse Protocol for writing as systematic review and we reported our findings in accordance with PRISMA (2020).

Results

Thirty research articles from 11 countries were analyzed. Five interventions of mHealth were identified. Of these mHealth Short Message service (SMS) helped change behavior and encouraged self-care. mHealth SMS coupled with telemedicine for coaching showed positive effects on weight loss, BMI, diet, exercise, HbA1C, disease awareness, blood pressure, cholesterol, medication adherence, and foot care.

Conclusion

mHealth SMS coupled with telemedicine for coaching shows the greatest promise for educating, changing behavior, and realizing positive outcomes across a broad spectrum of health factors. The largest drawback is the cost of acquiring equipment and training users.

The metabolic control and laboratory evaluation in patients with type 2 diabetes during the COVID-19 pandemic and the impact of telemedicine: a single-center experience

Objective: The study aimed to evaluate the metabolic control during the COVID-19 pandemic in subjects with type 2 diabetes mellitus (T2DM) and whether care through telemedicine significantly impacted it.

Material and methods: This was a retrospective study for which three time-periods were prespecified: the COVID-19 pandemic period, pre-COVID-19 period, and before pre-COVID-19. The following information were collected: anthropometric and laboratory parameters (glycated hemoglobin (HbA1c), blood glucose, lipid profile, creatinine, eGFR, etc.), self-measured blood glucose (SMBG), blood pressure (BP), diabetes therapy, number of on-site and of telemedicine consultations. The mean values of all available measurements for HbA1c, SMBG, BP, weight, and body mass index (BMI) were calculated.

Results: During the COVID-19 pandemic, the HbA1c values increased (6.78±0.77% to 6.96±0.87%, p<0.0001; + 0.18±0.67%), despite treatment intensification (p<0.01), while BMI and total cholesterol values slightly decreased (32.01±5.5 kg/m2 to 31.7±5.4 kg/m2, p<0.0001, and 178.1±40.8 mg/dl to 170.5±38.4 mg/dl, p<0.05). The deterioration of glycemic control (to HbA1c >7%) were rather seen in males (to 7.01±0.92%, p<0.0001), patients from rural areas (to 7.08±0.96%, p<0.001) and younger than 65 y.o. (to 7.05±0.82%, p<0.001). More male patients had a mean HbA1c increase of >0.5% during the COVID-19 pandemic (32.3% vs 21.5%, p<0.05). Patients who received more diabetes care visits through telemedicine had a more attenuated increase in HbA1c (6.79±0.80% to 6.90±0.83%, p<0.05 vs 6.76±0.72% to 7.08±0.92%, p<0.0001).

Conclusions: The glycemic control slightly deteriorated during the COVID-19 pandemic (but with overall HbA1c within target), with certain patient categories being more affected. Diabetes care though telemedicine allowed the maintenance of the metabolic control.

A review of the effectiveness of telemedicine in glycemic control in diabetes mellitus patients

This review aimed to evaluate the effectiveness of telemedicine as an intervention for patients with diabetes mellitus, considering blood glucose levels as the primary outcome. A comprehensive literature search was performed using the PubMed, Embase, Web of Science, and EBSCO databases. This narrative review covered randomized controlled trials published in English. The process of selecting studies adhered to the preferred reporting items for systematic reviews and meta-analyses guidelines. Nine studies were selected, and their data were analyzed and summarized. Five of the nine reviewed studies found that telemedicine counseling was effective in decreasing glycated hemoglobin A (HbA1c) levels in the blood. Due to methodological limitations, one study could not report HbA1c results, and two studies reported that telemedicine counseling did not lead to any significant changes in HbA1c levels. One study found that while HbA1c levels did not show a marked decrease, patients' treatment adherence and quality of life improved when telemedicine was combined with health counseling. Moreover, six studies found that telemedicine counseling was more effective than traditional counseling regarding secondary outcomes. The overall findings of this review suggest that telemedicine counseling is more effective than conventional counseling in achieving decreased blood glucose levels in patients with diabetes mellitus while increasing their treatment adherence and improving their quality of life.

Risks of Severe COVID-19 Outcomes Among Patients With Diabetic Polyneuropathy in the United States

CONTEXT

Diabetic neuropathy (DN) affects more than 50% of diabetic patients who are also likely to have compromised immune system and respiratory function, both of which can make them susceptible to the SARS-CoV-2 virus.

OBJECTIVE

To assess the risk of severe COVID-19 illness among adults with DN, compared with those with no DN and those with no diabetes.

SETTING

The analysis utilized electronic health records from 55 US health care organizations in the TriNetX research database.

DESIGN

A retrospective cohort study.

PARTICIPANTS

The analysis included 882 650 adults diagnosed with COVID-19 in January 2020 to June 2021, including 16 641 with DN, 81 329 with diabetes with no neuropathy, and 784 680 with no diabetes.

OUTCOME MEASURES

The presence of health care utilization (admissions to emergency department, hospital, intensive care unit), 30-day mortality, clinical presentation (cough, fever, hypoxemia, dyspnea, or acute respiratory distress syndrome), and diagnostic test results after being infected affected by COVID-19.

RESULTS

The DN cohort was 1.19 to 2.47 times more likely than the non-DN cohorts to utilize care resources, receive critical care, and have higher 30-day mortality rates. Patients with DN also showed increased risk (1.13-2.18 times) of severe symptoms, such as hypoxemia, dyspnea, and acute respiratory distress syndrome.

CONCLUSIONS

Patients with DN had a significantly greater risk of developing severe COVID-19-related complications than those with no DN. It is critical for the public health community to continue preventive measures, such as social distancing, wearing masks, and vaccination, to reduce infection rates, particularly in higher risk groups, such as those with DN.

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.

Investigation of COVID-19 fear, treatment compliance, and metabolic control of patients with type 2 diabetes mellitus during the pandemic

AIMS

This study was carried out to investigate fear levels, treatment compliance, and metabolic control of type II Diabetes Mellitus patients during the COVID-19 pandemic.

METHODS

The study employed a single-center, observational design and was conducted between January and April 2021. The study consisted of 303 patients who attended the internal medicine outpatient clinic of a university hospital in Turkey. For data collection, the Patient Identification Form, COVID-19 Fear Scale, and the Type II Diabetes Treatment Compliance Scale were used. The study complied with the Helsinki Declaration criteria. IBM SPSS v25.0 statistics package program was used for data analysis.

RESULTS

The mean age of the patients was 45.8 ± 7.5 years, the mean duration of illness was 8.2 ± 3.6 years. Moreover, 40.6% of patients presented with poor levels of treatment compliance. In addition, the mean FCV-19S score of the patients was 29.1 ± 3.05. It was noticeable that those with high mean scores of FCV-19S had poor compliance with treatment and metabolic control during the pandemic (p &lt; 0.05).

PRACTICE IMPLICATIONS

Fear of COVID-19 negatively affects treatment compliance and metabolic control of type II diabetes patients. The patients avoided attending their regular follow-ups at the hospital due to fear of contracting COVID-19. In order to reduce the fear of COVID-19 it is paramount to maintain optimum metabolic control and treatment compliance.

Impact of the COVID-19 Pandemic on Diabetes Care for Adults With Type 2 Diabetes in Ontario, Canada

OBJECTIVES

The COVID-19 pandemic and related public health prevention measures have led to a disruption of the delivery of routine care and may have had an impact on the quality of diabetes care. Our aim in this study was to evaluate the extent to which structure, process and outcome quality measures in diabetes care changed in the first 6 months of the pandemic compared with previous periods.

METHODS

A before-and-after observational study was conducted of all community-living Ontario residents >20 years of age and living with diabetes. The patients were divided into 3 cohorts: a pandemic cohort, alive March to September 2020 (n=1,393,404); reference cohort 1, alive March to September 2019 (n=1,415,490); and reference cohort 2, alive September 2019 to February 2020 (n=1,444,000). Outcome measures were in-person/virtual visits to general practitioners and specialists, eye examinations, glycated hemoglobin (A1C) and low-density lipoprotein (LDL) testing, filled prescriptions, and admissions to emergency departments (EDs) and hospitals for acute and chronic diabetes complications.

RESULTS

The probability of an in-person visit to a general practitioner decreased by 47% (95% confidence interval [CI], 47% to 47%) in the pandemic period compared with both previous periods. The probability of having an eye exam was lower by 43% (95% CI, 44% to 43%), an A1C test by 28% (95% CI, 29% to 28%) and an LDL test by 31% (95% CI, 31% to 31%) in the pandemic period compared with the same 6-month period the year before. There were very small decreases in drug prescriptions and decreases of 18% and 16% in ED and hospital visits for complications.

CONCLUSIONS

We observed disruptions to both structure and process measures of diabetes care in Ontario during the first wave of the pandemic.

Multimodal Diabetes Empowerment for Older Adults with Diabetes

Systematically improving empowerment is not easy when operating a diabetes program for older adults. This study aimed to develop and test the feasibility of the diabetes empowerment (Dia-Empower) program for older adults with type 2 diabetes. A non-randomized controlled study with a matched sampling design was conducted. Community-dwelling older adults with diabetes were allocated to either the Dia-Empower program group or a control group. Changes in the primary (diabetes self-care and empowerment) and secondary outcomes (body composition and physical function) were compared between the groups. The scores for diabetes self-care and empowerment were significantly higher in the experimental group than in the control group. Changes in skeletal muscle mass and body fat ratio were significantly different between the groups. Handgrip strength and shoulder flexibility positively changed in the experimental group. The Dia-Empower program was feasible for older adults with diabetes in the community. In the future, it is necessary to study the long-term effects of the program and its effects on blood sugar control.

COVID-19 and diabetes in children

This review describes the impact of coronavirus disease 2019 (COVID-19) in children and adolescents, investigating changes in diabetes presentation during the COVID-19 pandemic, possible links between severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection and diabetes, and mechanisms of pancreatic β-cell destruction. Although glycemic control in individuals with already known diabetes mellitus did not worsen during the pandemic, there was a worrying increase in diabetic ketoacidosis in children with new-onset diabetes, probably due to containment measures and delayed access to emergency departments. Moreover, new evidence suggests that SARS-CoV-2 has the capacity to directly and indirectly induce pancreatic β-cell destruction, and the risk of newly diagnosed diabetes after COVID-19 increased in both children and adults. While long-term studies continue to follow children with SARS-CoV-2 infection, this review discusses available findings on the relationship between COVID-19 and diabetes. It is important to emphasize the need to maintain close links between families of children with chronic conditions and their pediatricians, as well as to promote early access to healthcare services, in order to reduce dangerous delays in diabetes diagnosis and prevent diabetic ketoacidosis.

Holistic care of patients with diabetic foot ulcers during the COVID-19 era: integration of Henderson's Need Theory

The COVID-19 pandemic has inhibited the practice of diabetic foot ulcer care, particularly in the community. Comprehensive theory-based nursing care is needed to prevent further complications. Unfortunately, a study combining theory with nursing care in diabetic foot ulcer care has not been explored. When caring for patients with diabetic foot ulcers, who are also at increased risk of severe complications from COVID-19, it is important to take a holistic view of the patient and consider all of their needs and the factors affecting them. Henderson's Need Theory and the 14 basic needs contained within it was chosen to be integrated in the care of patients with diabetic foot ulcers during the pandemic, with the hope that the findings will help nurses to optimise care in both hospital-based and community practice.

Analysis of potential risk factors associated with COVID-19 and hospitalization

Coronavirus disease 2019 (COVID-19) was found to cause complications in certain groups of people, leading to hospitalization. Several factors have been linked to this, such as gender, age, comorbidity, and race. Understanding the precise reasons for the COVID-19-induced complications might help in designing strategies to minimize hospitalization. A retrospective, cross-sectional observational study was conducted for patients in a COVID-19-designated specialty hospital after obtaining ethical clearance. Patients' demographic and clinical characteristics, such as age, gender, race, vaccinated status, complications, comorbidities, and medications, were retrieved from the hospital medical database. The data were statistically analyzed to determine the association between the predictors and the outcomes of COVID-19. An odds ratio (both unadjusted and adjusted) analysis was carried out to determine the risk factors for hospitalization [non-intensive care (non-ICU) and intensive care (ICU)] due to COVID-19. The data from the study indicated that the majority of patients hospitalized due to COVID-19 were male (>55%), aged > 60 years (>40%), married (>80%), and unvaccinated (>71%). The common symptoms, complications, comorbidities, and medications were fever, pneumonia, hypertension, and prednisolone, respectively. Male gender, patients older than 60 years, unemployed, unvaccinated, complicated, and comorbid patients had an odds ratio of more than 2 and were found to be significantly (p < 0.05) higher in ICU admission. In addition, administration of prednisolone and remdesivir was found to significantly reduce (p < 0.05) the odds ratio in ICU patients. The analysis of the data suggested that male gender, age above 60 years, and unvaccinated with comorbidities increased the complications and resulted in hospitalization, including ICU admission. Hypertension and type 2 diabetes associated with obesity as metabolic syndrome could be considered one of the major risk factors. Preventive strategies need to be directed toward these risk factors to reduce the complications, as well as hospitalization to defeat the COVID-19 pandemic.

THE EFFECT OF ANXIETY LEVELS OF TYPE 2 DIABETES MELLITUS PATIENTS ON THEIR TREATMENT ADHERENCE IN THE COVID-19 PANDEMIC PERIOD

This study was conducted to investigate the effects of the anxiety levels of Diabetes Mellitus (DM) patients on their treatment adherence in the COVID-19 pandemic period. The sample of this descriptive and cross-sectional study consisted of 313 DM patients who presented to the internal medicine outpatient clinic between 01.01.2021 and 01.02.2021. The data were collected using a Personal Information Form, the Coronavirus Anxiety Scale (CAS), and the Morisky Medication Adherence Scale (MMAS-8). Descriptive statistics, Mann-Whitney U test, Kruskal-Wallis test and Spearman’s correlation test were used to analyze the data. The mean CAS score of the DM patients was 7.89±3.87, while their mean total MMAS-8 score was 4.06±1.56. It was determined that the patients who were using oral antidiabetic medications, those adhering to their medication and diet treatment, and those who were not COVID-19 had higher levels of anxiety. There was a negative significant relationship between the MMAS-8 and CAS scores of the patients (p

Identifying factors associated with COVID-19 related deaths during the first wave of the pandemic in Europe

Aim

To clarify the high variability in COVID-19-related deaths during the first wave of the pandemic, we conducted a modeling study using publicly available data.

Materials and methods

We used 13 population- and country-specific variables to predict the number of population-standardized COVID-19-related deaths in 43 European countries using generalized linear models: the test-standardized number of SARS-CoV-2-cases, population density, life expectancy, severity of governmental responses, influenza-vaccination coverage in the elderly, vitamin D status, smoking and diabetes prevalence, cardiovascular disease death rate, number of hospital beds, gross domestic product, human development index and percentage of people older than 65 years.

Results

We found that test-standardized number of SARS-CoV-2-cases and flu vaccination coverage in the elderly were the most important predictors, together with vitamin D status, gross domestic product, population density and government response severity explaining roughly two-thirds of the variation in COVID-19 related deaths. The latter variable was positively, but only weakly associated with the outcome, i.e., deaths were higher in countries with more severe government response. Higher flu vaccination coverage and low vitamin D status were associated with more COVID-19 related deaths. Most other predictors appeared to be negligible.

Conclusion

Adequate vitamin D levels are important, while flu-vaccination in the elderly and stronger government response were putative aggravating factors of COVID-19 related deaths. These results may inform protection strategies against future infectious disease outbreaks.

[COVID-19 and Bipolar Affective Disorder: Subjective Changes in Lifestyle Variables During the First Lockdown During the COVID-19 Pandemic in Austria]

INTRODUCTION

The COVID-19 pandemic with its protective measures (e. g. lockdown) had far-reaching effects on everyone's well-being. The aim of this study was to examine lifestyle variables during the first Austrian lockdown in patients with bipolar disorder in comparison to a healthy control group and to assess subjective changes caused by the pandemic.

METHOD

At the beginning of April 2020, an online survey of n=75 participants (35 people with bipolar disorder and 40 healthy controls) with standardized questionnaires (Beck Depression Inventory-2, Food Craving Inventory, Altman Self Rating Mania Scale) as well as non-standardized COVID-19-specific questions on the subject of "Psychological stress and effects of the COVID-19 pandemic in bipolar disorder" was created and distributed via LimeSurvey.

RESULTS

Both groups reported a negative impact on their mental health. The participants with bipolar disorder showed significantly higher values in the Beck Depression Inventory-2 score (p<0,001), in emotional distress due to social distancing (p=0,003) and significantly lower values in muscle-strengthening exercise (p=0,039) and in sport units (p=0,003) compared to the control group. In addition, patients with bipolar disorder smoked more often than individuals of the control group. People with bipolar disorder were 42,9% more likely to report they were less efficient during the pandemic, and 22,9% experienced weight gain compared to before the pandemic. The control group, on the other hand, was less efficient at 17,5% and 5,0% reported weight gain. However, a comparison with pre-pandemic data showed a decrease in food craving in both groups.

CONCLUSION

This study provided first evidence of self-reported adverse effects on mental stress and lifestyle in people with bipolar disorder at the beginning of the COVID-19 pandemic. Psychiatric care and early interventions for patients with bipolar disorder would be particularly important in times of crisis in order to help maintain a healthy lifestyle and thus counteract unfavourable developments.

From Survey Results to a Decision-Making Matrix for Strategic Planning in Healthcare: The Case of Clinical Pathways

Background: It is a well-known fact that the information obtained from a survey can be used in a healthcare organizational analysis; however, it is very difficult to compare the different results found in the literature to each other, even through the use of metanalysis, as the methodology is often not consistent. Methods: Data from a survey analyzing the organizational and managerial responses adopted in pathology-specific clinical pathways (CPs) during the first two waves of the COVID-19 pandemic were used for constructing a decisional matrix, a tool called SPRIS system, consisting of four different sheets. The first sheet reports the results of the survey and, using a streetlight color system, identifies strengths and weaknesses; the second one, by assigning a priority score, establishes the priority of intervention on each of the strengths and weaknesses identified; the third sheet reports the subjective items of the questionnaire in order to identify threats and opportunities and their probability of happening; in the last sheet, a SWOT Analysis is used to calculate the performance index of the whole organization. Results: The SPRIS system, applied to data concerning the adaptation of four CPs to the COVID-19 pandemic, showed that, whereas all the CPs had a good performance index, some concerns remained unsolved and need be addressed. Conclusions: The SPRIS system showed to be an easily constructed tool that is able to give an overview of the organization analyzed by the survey and to produce an index that can be used in a direct quality comparison between different services or organizations.

Factors Influencing the Utilization of Diabetes Complication Tests Under the COVID-19 Pandemic: Machine Learning Approach

OBJECTIVE

There are still not enough studies on the prediction of non-utilization of a complication test or a glycated hemoglobin test for preventing diabetes complications by using large-scale community-based big data. This study identified the ratio of not taking a diabetes complication test (fundus examination and microprotein urination test) among adult diabetic patients over 19 years using a national survey conducted in South Korea and developed a model for predicting the probability of not taking a diabetes complication test based on it.

METHODS

This study analyzed 25,811 subjects who responded that they had been diagnosed with diabetes by a doctor in the 2020 Community Health Survey. Outcome variables were defined as the utilization of the microprotein urination test and the fundus examination during the past year. This study developed a model for predicting the utilization of a diabetes complication test using logistic regression analysis and nomogram to understand the relationship of predictive factors on the utilization of a diabetes complication test.

RESULTS

The results of this study confirmed that age, education level, the recognition of own blood glucose level, current diabetes treatment, diabetes management education, not conducting the glycated hemoglobin test in the past year, smoking, single-person household, subjectively good health, and living in the rural area were independently related to the non-utilization of diabetes complication test after the COVID-19 pandemic.

CONCLUSION

Additional longitudinal studies are required to confirm the causality of the non-utilization of diabetes complication screening tests.

Influence of the COVID-19 pandemic on overall physician visits and telemedicine use among patients with type 1 or type 2 diabetes in Japan

BackgroundRegular visits with healthcare professionals are important for preventing serious complications in patients with diabetes. The purpose of this retrospective cohort study was to clarify whether there was any suppression of physician visits among patients with diabetes during the spread of COVID-19, in Japan and to assess whether telemedicine contributed to continued visits.MethodsWe used the JMDC Claims database which contains the monthly claims reported from July 2018 to May 2020 and included 4595 (type 1) and 123,686 (type 2) patients with diabetes.Using a difference-in-differences analysis, we estimated the changes in the monthly numbers of physician visits or telemedicine per 100 patients in April and May 2020 compared with the same months in 2019.ResultsFor patients with type 1 diabetes, the estimates for total overall physician visits were -2.53 (95% CI, -4.63 to 0.44) in April and -8.80 (-10.85 to -6.74) in May; those for telemedicine visits were 0.71 (0.47 to 0.96) in April and 0.54 (0.32 to 0.76) in May. For patients with type 2 diabetes, the estimates for overall physician visits were -2.50 (-2.95 to -2.04) in April and -3.74 (-4.16 to -3.32) in May; those for telemedicine visits were 1.13 (1.07 to 1.20) in April and 0.73 (0.68 to 0.78) in May.ConclusionsThe COVID-19 pandemic was associated with suppression of physician visits and a slight increase in the utilisation of telemedicine among patients with diabetes during April and May 2020.

Efficacy of BAINS Circuit in Treating Critically Ill Hypoxemic COVID-19 Patients During the Second Wave of the Pandemic in India

BACKGROUND

The COVID-19 pandemic has encouraged doctors to look for novel ways of treating patients with respiratory failure due to the limited availability of ventilators and highflow nasal cannula. The study aims to assess the efficacy of using the Bains circuit as an alternative to HFNC and NIV as life-saving tools in patients with respiratory failure during the second wave of the COVID-19 pandemic in India.

METHODS

This is a prospective interventional study carried out in the intensive care unit of Shri B.M Patil Medical College Hospital and Research Centre, Vijayapur, India, from May 2021 to June 2021. All patients (n=90) with respiratory failure not responding to therapy with an oxygen mask were included. Patients were placed on Bain circuits, one end connected to a non-invasive ventilation mask fitted to the face of the patients, and the other end connected to a central oxygen port. Patients' vital parameters were assessed on an hourly basis. The blood gas analyses were done before and after using Bains.

RESULTS

The study showed diabetes (33.4%), hypertension (22.2%), and diabetes with hypertension (11.1%) as comorbid factors among the ICU admitted patients. The results from the arterial blood gas analyses showed a statistically significant increase in Sp02 (%) and a decrease in respiratory rate (cycles/min) in the patients after being kept on Bains (p<0.05). Further, it showed that 72% of ICU patients with 70-79% Sp02 had a recovery by using Bains. The overall outcome of ICU admitted COVID-19 patients on Bains showed that 38.9% of patients improved and were shifted to 02/NRBM masks.

CONCLUSION

The study highlights a novel concept of using the Bains circuit as an effective alternative to HFNC and NIV for oxygenation in critically ill COVID-19 patients during scarcity of NIV and HFNC at the peak of the pandemic.

Breakdown of Diabetic Foot Ulcer Care during the First Year of the Pandemic in Poland: A Retrospective National Cohort Study

The COVID-19 pandemic revealed a breakdown of the system of DFU patient care. This retrospective national cohort study analyses the epidemiological status of DFU patients in relation to urgent and elective hospitalizations, amputation rates, and deaths in Poland from 2017 to 2019, and during 2020 when the COVID-19 pandemic began. The data were obtained from national medical records gathered by the National Health Fund (NHF). Discharge diagnoses were categorized according to ICD-10 and ICD-9 codes. Analysis of the data showed a statistically significant decrease in elective hospital admissions (from 29.6% to 26.3%, p = 0.001). There was a decrease in the percentage of hospitalizations related to limb-salvage procedures (from 79.4% to 71.3%, p = 0.001). The opposite tendency was observed among urgent hospital admissions (from 67.0% to 73.2%, p = 0.01), which was related to a significant increase in the number of minor amputations (from 3146 to 4269, p = 0.017). This rise was in parallel with the increase in the percentage of patients who died during hospitalization due to DFU (from 3.9% to 4.8%, p = 0.03). The number of deaths has not changed significantly (from 590.7 to 668.0, p = 0.26). The results of the conducted analyses confirm the negative tendencies in the medical care of patients with DFU during the first year of the pandemic in Poland. Changes in therapy schemes and stronger patient support following this period are necessary to avoid further complications in patients with DFU.

COVID-19: A systematic review and update on prevention, diagnosis, and treatment

Since the rapid onset of the COVID-19 or SARS-CoV-2 pandemic in the world in 2019, extensive studies have been conducted to unveil the behavior and emission pattern of the virus in order to determine the best ways to diagnosis of virus and thereof formulate effective drugs or vaccines to combat the disease. The emergence of novel diagnostic and therapeutic techniques considering the multiplicity of reports from one side and contradictions in assessments from the other side necessitates instantaneous updates on the progress of clinical investigations. There is also growing public anxiety from time to time mutation of COVID-19, as reflected in considerable mortality and transmission, respectively, from delta and Omicron variants. We comprehensively review and summarize different aspects of prevention, diagnosis, and treatment of COVID-19. First, biological characteristics of COVID-19 were explained from diagnosis standpoint. Thereafter, the preclinical animal models of COVID-19 were discussed to frame the symptoms and clinical effects of COVID-19 from patient to patient with treatment strategies and in-silico/computational biology. Finally, the opportunities and challenges of nanoscience/nanotechnology in identification, diagnosis, and treatment of COVID-19 were discussed. This review covers almost all SARS-CoV-2-related topics extensively to deepen the understanding of the latest achievements (last updated on January 11, 2022).

An exploration of factors characterising unusual spatial clusters of COVID-19 cases in the East Midlands region, UK: A geospatial analysis of ambulance 999 data

Complex interactions between physical landscapes and social factors increase vulnerability to emerging infections and their sequelae. Relative vulnerability to severe illness and/or death (VSID) depends on risk and extent of exposure to a virus and underlying health susceptibility. Identifying vulnerable communities and the regions they inhabit in real time is essential for effective rapid response to a new pandemic, such as COVID-19. In the period between first confirmed cases and the introduction of widespread community testing, ambulance records of suspected severe illness from COVID-19 could be used to identify vulnerable communities and regions and rapidly appraise factors that may explain VSID. We analyse the spatial distribution of more than 10,000 suspected severe COVID-19 cases using records of provisional diagnoses made by trained paramedics attending medical emergencies. We identify 13 clusters of severe illness likely related to COVID-19 occurring in the East Midlands of the UK and present an in-depth analysis of those clusters, including urban and rural dynamics, the physical characteristics of landscapes, and socio-economic conditions. Our findings suggest that the dynamics of VSID vary depending on wider geographic location. Vulnerable communities and regions occur in more deprived urban centres as well as more affluent peri-urban and rural areas. This methodology could contribute to the development of a rapid national response to support vulnerable communities during emerging pandemics in real time to save lives.

Using bioinformatics and systems biology to discover common pathogenetic processes between sarcoidosis and COVID-19

The coronavirus disease (COVID-19) pandemic caused by SARS-CoV-2 is ongoing. Individuals with sarcoidosis tend to develop severe COVID-19; however, the underlying pathological mechanisms remain elusive. To determine common transcriptional signatures and pathways between sarcoidosis and COVID-19, we investigated the whole-genome transcriptome of peripheral blood mononuclear cells (PBMCs) from patients with COVID-19 and sarcoidosis and conducted bioinformatic analysis, including gene ontology and pathway enrichment, protein-protein interaction (PPI) network, and gene regulatory network (GRN) construction. We identified 33 abnormally expressed genes that were common between COVID-19 and sarcoidosis. Functional enrichment analysis showed that these differentially expressed genes were associated with cytokine production involved in the immune response and T cell cytokine production. We identified several hub genes from the PPI network encoded by the common genes. These hub genes have high diagnostic potential for COVID-19 and sarcoidosis and can be potential biomarkers. Moreover, GRN analysis identified important microRNAs and transcription factors that regulate the common genes. This study provides a novel characterization of the transcriptional signatures and biological processes commonly dysregulated in sarcoidosis and COVID-19 and identified several critical regulators and biomarkers. This study highlights a potential pathological association between COVID-19 and sarcoidosis, establishing a theoretical basis for future clinical trials.

Pfizer-BioNTech vaccine effectiveness against Sars-Cov-2 infection: Findings from a large observational study in Israel

Development of an effective vaccine against Covid-19 is crucial to reducing infection. mRNA BNT162b2, developed and manufactured by Pfizer-BioNTech, was one of the first FDA-approved vaccinations reporting high efficacy (95%) and minimal side effects. Evaluating effectiveness of BNT162b2 in a general population has been made possible after the implementation of a nation-wide vaccination program in Israel. This retrospective cohort study was carried out in Maccabi HealthCare services, Israel among 1.6 million members aged 16 and over. The population was divided into those who were at least seven days post- second vaccination and those who had not been vaccinated. Number of days till the end of the study or Covid-19 infection, Covid-19-related hospitalization and mortality was calculated for each participant between 18.1.2021 to 25.4.2021. Participants who had reached day eight after second vaccination during the study period could contribute days to both groups. Vaccine efficacy (VE) was calculated using a conditional Poisson model, controlling for age group, gender, hypertension, diabetes and obesity, fitted within clusters defined by geographical statistical area and calendar week. BNT162b2 was found effective for the total population group for infection, hospitalization and mortality, with adjusted VE of 93·0% (CI:92·6-93·4%), 93·4% (CI:91·9-94·7%) and 91·1% (CI:86·5-94·1%) respectively. VE for infection was lower for participants aged 75 and over, and for those with hypertension, diabetes and obesity. This study strengthens the evidence that the Pfizer-BioNTech vaccination is effective in preventing infection, hospitalization and mortality.

Euglycemic Diabetic Ketoacidosis in a Pregnant Woman With Severe COVID-19: A Case Report

Euglycemic diabetic ketoacidosis (DKA) of pregnancy is an uncommon but serious condition that poses a substantial risk to the fetus. The physiological state of pregnancy itself predisposes women to ketosis and ketoacidosis, which can be further exacerbated by acute stressors such as infection. In this article, we describe a case of a pregnant woman with gestational diabetes and coronavirus disease 2019 (COVID-19) requiring mechanical ventilation who developed euglycemic DKA during her hospital course. Despite treating the patient with standard DKA protocol, fetal heart monitoring was non-reassuring and, hence, a cesarean section was performed. Postoperatively, her DKA resolved; however, she was maintained on supportive ventilation for continued management of her severe COVID-19 infection. In light of the ongoing pandemic, it is essential that healthcare teams closely monitor pregnant women presenting with COVID-19 infection for early signs of euglycemic DKA so that treatment may be initiated early and feto-maternal complications are avoided.

COVID-19 Pandemic and Periodontal Practice: The Immunological, Clinical, and Economic Points of View

The recent global health problem, COVID-19, has had far-reaching impacts on lifestyles. Although many effective WHO-approved vaccines have been produced that have reduced the spread and severity of the disease, it appears to persist in humans for a long time and possibly forever as everyday it turns out to have new mutations. COVID-19 involves the lungs and other organs primarily through cytokine storms, which have been implicated in many other inflammatory disorders, including periodontal diseases. COVID-19 is in a close association with dental and periodontal practice from two respects: first, repeated mandatory lockdowns have reduced patient referrals to dentists and limited the dental and periodontal procedures to emergency treatments, whereas it is important to recognize the oral manifestations of COVID-19 as well as the influence of oral and periodontal disease on the severity of COVID-19. Second, dentistry is one of the high-risk professions in terms of close contact with unmasked individuals, necessitating redefining the principles of infection control. The pressures of the economic recession on patients as well as dentists add to the difficulty of resuming elective dental services. Therefore, this study is divided into two parts corresponding to what mentioned above: the first part examines the clinical and immunological associations between COVID-19 and periodontal and oral diseases, and the second part delineates the measures needed to control the disease transmission in dental clinics as well as the economic impact of the pandemic era on dental services.