Glycated hemoglobin, type 2 diabetes, and poor diabetes control are positively associated with impulsivity changes in aged individuals with overweight or obesity and metabolic syndrome.

Impulsivity has been proposed to have an impact on glycemic dysregulation. However, it remains uncertain whether an unfavorable glycemic status could also contribute to an increase in impulsivity levels. This study aims to analyze associations of baseline and time-varying glycemic status with 3-year time-varying impulsivity in older adults at high risk of cardiovascular disease. A 3-year prospective cohort design was conducted within the PREDIMED-Plus-Cognition substudy. The total population includes 487 participants (mean age = 65.2 years; female = 50.5%) with overweight or obesity and metabolic syndrome. Insulin resistance (HOMA-IR), glycated hemoglobin (HbA1c), presence of type 2 diabetes mellitus, and type 2 diabetes control were evaluated. Impulsivity was measured using the Impulsive Behavior Scale questionnaire and various cognitive measurements. Impulsivity z-scores were generated to obtain Global, Trait, and Behavioral Impulsivity domains. Linear mixed models were used to study the longitudinal associations across baseline, 1-year, and 3-year follow-up visits. HOMA-IR was not significantly related to impulsivity. Participants with higher HbA1c levels, type 2 diabetes, and poor control of diabetes showed positive associations with the Global Impulsivity domain over time, and those with higher HbA1c levels were further related to increases in the Trait and Behavioral Impulsivity domains over the follow-up visits. These results suggest a potential positive feedback loop between impulsivity and glycemic-related dysregulation.

Sex differences in association of joint glycemic, blood pressure and lipid control and two-year risk of falls among older adults with diabetes.

AIMS: To characterize the risk of falls among males and females by joint glycemic, blood pressure (BP) and cholesterol control among older adults (≥65 years) with diagnosed diabetes in USA. METHODS: Using longitudinal data from the Health and Retirement Study (2006-2019), we studied the association of joint glycemic (HbA1c < 7.5 %), BP (systolic <140 and diastolic <90 mmHg) and cholesterol (total < 200 mg/dL) control with two-year risk of falls. We estimated risk ratios (RR) to describe the associations for joint ABC control and independent biomarker control by sex, using modified Poisson regressions after adjusting for known individual and household risk factors. RESULTS: The analytic sample consisted of 4509 observations from 2829 older adults (54.7 % female) with a mean age of 72.2 (SD: 6.6) years and duration of diabetes of 9.9 years. Joint ABC control was not associated with risk of falls among females but was associated with lower risk among males (0.91 [95%CI: 0.81-1.02]). Furthermore, achievement of glycemic control (0.85 [95%CI: 0.73-0.98]) and BP control (0.89 [95%CI: 0.79-1.01]) were associated with lower risk but cholesterol control (1.15 [95%CI: 0.99, 1.34]) was associated with higher risk of falls among males. CONCLUSIONS: Joint achievement of glycemic, BP and cholesterol targets may prevent falls among older males. Future studies among people with diabetes should consider biomarker control as a preventive factor for falls.

Exploring the self-efficacy of patients with diabetes: its role as a predictor of diabetes management and well-being.

Background: Self-efficacy is a popular psychological concept that refers to an individual's perception or belief in his ability to perform specific actions. This study aimed to assess the predictive value of self-efficacy, measured using the Self-Efficacy for Managing Chronic Disease 6-Item Scale (SEM6S) questionnaire, for diabetes management and overall well-being in patients with diabetes. Subject and methods: An anonymous online cross-sectional study was conducted to evaluate the self-efficacy of diabetic patients in the Asser region of Saudi Arabia. The participants were requested to upload their most recent glycated hemoglobin A1C (HbA1C) measurements taken in the last three months, which helped in the accurate categorization of their diabetes as either controlled or uncontrolled. We used the valid Arabic version of the SEM6S and WHO-5 well-being questionnaires to assess patient self-efficacy and well-being. Results: A cohort of 342 patients was enrolled in the study, 67.25% were married, their mean age was 43.17 ± 17.61 years, and 52.69% had university-level or higher education. Among the participants, 46.0% exhibited well-being, while 24.9% reported poor well-being, including 9.4% who were identified as experiencing depression. The mean scores of self-efficacy and well-being were significantly higher among those with controlled diabetes versus uncontrolled diabetes (40.86 ± 13.26 vs. 36.48 ± 13.26) and (67.35 ± 21.22 vs. 60.93 ± 25.05), respectively. The predictors of glycemic control were self-efficacy [Odds ratio (OR)=1.03 (95%CI, 1.01-1.06, P=0.002], having other chronic diseases [OR=3.25 (95%CI), P<0.001], having type 1 diabetes [OR=7.16, 95%CI, P=0.005], being Saudi [OR=7.67, (95%CI, P=0.027], working in a public sector [OR=0.15, (95%CI, 0.05-0.44), P=0.005], being unemployed [OR=0.19, (95%CI, 0.06-0.59), P=0.005], being a smoker [OR=0.44, 95%CI, 0.19-0.98, P=0.048], and duration of diabetes between 6-10 years [OR= 0.33, 95%CI, 0.11-0.95), P=0.043] or more than 10 years OR=0.32, 95%CI, 0.12-0.86), P=0.026]. The main determinants of well-being were having self-efficacy [OR=1.07 (95%CI, 1.04-1.09), P = 0.0001], having public health insurance [OR=4.36 (95%CI, P=0.015], and education level (read and write) [OR=0.13 (95%CI,.02-.70), P=0.021]. Conclusions: The study reveals that non-modifiable and modifiable factors, including self-efficacy, play a crucial role in diabetes control. The study recommends providing targeted educational interventions, using different social media platforms, psychosocial support programs, and inclusive healthcare policies to improve diabetes control and mental well-being among diabetic patients.

The Effect of Type-2 Diabetes Mellitus on Sleep Architecture and Sleep Apnea Severity in Patients With Obstructive Sleep Apnea Syndrome.

INTRODUCTION: Obstructive sleep apnea syndrome (OSAS) is a severe condition that is characterized by recurrent partial or complete breathing interruptions during sleep, leading to insulin resistance, microvascular complications, and cardiovascular complications. It is of great importance to know the impact of type 2 diabetes mellitus (DM), which is prevalent in the world and in our country, Turkey, leads to significant mortality and morbidity, significantly affects the quality of life, and requires continuous follow-up, on sleep in patients with OSAS and to raise awareness on this issue. In this study, we aimed to determine the effects of diabetes on sleep duration and sleep architecture in patients with OSAS and to investigate the relationship between OSAS severity and DM control. METHODS: Fifty diabetic and 42 non-diabetic patients diagnosed with OSAS at the Sleep Disorders Center of Süreyyapasa Chest Diseases and Thoracic Surgery Training and Research Hospital, Istanbul, Turkey, between October 2022 and March 2023 were included in the study. Polysomnographic and biochemical parameters of the two groups were compared. The effect of OSAS severity and sleep architecture on diabetes control was investigated. RESULTS: No significant difference was found between diabetic and non-diabetic patients in terms of total sleep duration, sleep efficiency, and sleep latency, whereas REM (rapid eye movement) latency was prolonged and REM sleep duration and percentage were significantly lower in diabetic patients. The severity of OSAS was found to be greater in diabetic patients and they spent significantly more time below 90% saturation during sleep. No correlation was found between the groups in the glycated hemoglobin (HbA1c) parameter, which we examined in terms of diabetes control, sleep architecture, and OSAS severity. CONCLUSION: The presence of diabetes aggravates the severity of OSAS, prolongs the transition to REM sleep, and leads to a decrease in REM duration. Sleep is essential for both mental and physical well-being. In this regard, it is of utmost importance to examine diabetic patients for OSAS and to perform polysomnography in appropriate patients.

Turkish Validity and Reliability of Comprehensive Diabetes Self-Management Scale.

Objectives: A self-care approach is very important in diabetes management. In this study, it was aimed to make the Turkish validity and reliability of the Comprehensive Diabetes Self-Management Scale (CDSMS), which examines the behaviors of diabetes patients. Methods: The study is of methodological type. CDSMS, which was translated into Turkish from its original version and tested for language validity, was first included in the pilot application and then in the main study. The validity of the scale was evaluated by the Cronbach's alpha coefficient. Then, a Receiver Operating Characteristic (ROC) analysis was performed to determine the cut off score. Results: The mean age of the study participants was 57.10 ± 11.20 years and the mean disease duration was 9.96 ± 7.79 years. The internal consistency of CDSMS was 0.73, which was measured using Cronbach's alpha. After the ROC analysis, the optimal cut-point score of CDSMS to predict good glycemic control was determined as 21.17 points. Conclusion: With this study, it was found that the Turkish version of CDSMS is valid and reliable for use in the Turkish population. It is thought that CDSMS will be beneficial to physicians working in the clinic in terms of showing the disease management skills of diabetic patients.

Short- and Long-Term Effects on Glucose Control of Nonadherence to Insulin Therapy in People With Type 2 Diabetes An In Silico Study.

BACKGROUND: Strict adherence to multiple daily insulin (MDI) therapy is a cornerstone for the achievement of good glucose control in people with advanced type 2 diabetes (T2D). Here, we aim to in silico assess glucose control in T2D subjects with poor adherence to MDI therapy. METHODS: We tuned the Padova T2D Simulator, originally describing early-stage T2D physiology, around advanced T2D people. One hundred in silico advanced T2D subjects were generated and equipped with optimal MDI therapy: specifically, basal and bolus insulin amounts and injection times were individualized for each subject by applying titration algorithms that iteratively update insulin dose based on glucose deviation from its target. Then, the effect of nonadhering to MDI therapy was assessed using standard glucose control metrics calculated in two 6-month 3-meal/day in silico scenarios: in Scenario 1, subjects received the optimal basal and prandial insulin bolus at each meal; in Scenario 2, subjects received optimal basal insulin and randomly delayed or skipped the prandial insulin bolus in 3 lunches during working days and 1 dinner during weekends. RESULTS: A statistically significant degradation was found in all glucose control outcome metrics in Scenario 2 versus Scenario 1: e.g., percent time above 180 mg/dL increased by 22.2% and glucose management index by 0.2%. CONCLUSIONS: Impaired adherence to MDI therapy in T2D leads to glucose control deteriorations in both short and long terms. Interestingly, short-term hyperglycemia seems being contrasted by residual endogenous insulin secretion, which statistically increased by 3-fold after delayed/skipped insulin boluses compared with optimal ones.

Association between Diabetes and Levels of Micronutrients in Qatar-A Case-Control Study.

OBJECTIVE: The objectives of this study were to investigate associations between micronutrient levels and diabetes and to explore the association in individuals with controlled and uncontrolled diabetes. METHODS: A case-control study, matched on age and gender, was performed on participants with (cases) and without diabetes (controls), who were Qatari or long-term residents (≥15 years of residence). Participants with diabetes were divided into those with controlled and uncontrolled diabetes using an HbA1c cutoff of 7%. Levels of micronutrients were measured from serum and categorized into normal and abnormal levels. RESULTS: A total of 1118 participants (374 cases and 744 controls) were included with a mean age of 41.7 years (SD 9.9), of whom 53.9% were female. Of those with diabetes, 229 had controlled diabetes and 145 had uncontrolled diabetes. Compared to those without diabetes, participants with diabetes had significantly lower mean magnesium (0.80 mmol/L (SD 0.07) vs. 0.84 mmol/L (SD 0.06), respectively, p < 0.001). Lower magnesium and iron were observed in participants with uncontrolled compared to participants with controlled diabetes. After multivariable logistic regression, diabetes was associated with hypomagnesemia (OR 3.2, 95% CI 3.4-213.9) and low iron (OR 1.49, 95% CI 1.03-2.15). Uncontrolled diabetes showed stronger odds of association with hypomagnesemia (OR 5.57, 95% CI 3.65-8.52). CONCLUSION: In an affluent setting in the MENA region, diabetes was associated with low magnesium and low iron, and this association was stronger in individuals with uncontrolled diabetes.

Attachment in close relationships and glycemic outcomes in children with type 1 diabetes.

BACKGROUND: Our aim was to determine whether child attachment to parents, parent attachment style, and morning cortisol levels were related to diabetes outcomes measured by average glycated hemoglobin (HbA1c), HbA1c variability over 4 years and time in range (TIR) in children with type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS: 101 children with T1D and one of their parents were assessed at baseline for child attachment (Child Attachment Interview; CAI) and parent attachment (Relationship Structures Questionnaire; ECR-RS). Serum samples were collected for cortisol measurements before the interviews. HbA1c levels were measured during a 4-year follow-up period at regular 3-monthly visits, and data for TIR were exported from blood glucose measuring devices. Multivariate linear regression models were constructed to identify independent predictors of glycemic outcomes. RESULTS: More girls than boys exhibited secure attachment to their mothers. The results of the regression models showed that securely attached girls (CAI) had higher average HbA1c than did insecurely attached girls (B = -0.64, p = 0.03). In boys, the more insecure the parent's attachment style, the worse the child's glycemic outcome: the higher the average Hb1Ac (B = 0.51, p = 0.005), the higher the HbA1c variability (B = 0.017, p = 0.011), and the lower the TIR (B = -8.543, p = 0.002). CONCLUSIONS: Attachment in close relationships is associated with glycemic outcomes in children with T1D, and we observed significant differences between sexes. A sex- and attachment-specific approach is recommended when treating children with less favorable glycemic outcomes. Special attention and tailored support should be offered to securely attached girls in transferring responsibility for diabetes care and at least to male children of insecurely attached parents to prevent suboptimal glycemic control. Further studies in larger samples and more daily cortisol measurements may help us better understand the links between stress response, attachment and T1D.

Disparities in Diabetes Care: Differences Between Rural and Urban Patients Within a Large Health System.

PURPOSE: We sought to ascertain factors associated with the quality of diabetes care, comparing rural vs urban diabetic patients in a large health care system. METHODS: We conducted a retrospective cohort study assessing patients' attainment of the D5 metric, a diabetes care metric having 5 components (no tobacco use, glycated hemoglobin [A1c] level less than 8%, blood pressure less than 140/90 mm Hg, low-density lipoprotein cholesterol level at goal or statin prescribed, and aspirin use consistent with clinical recommendations). Covariates included age, sex, race, adjusted clinical group (ACG) score as a marker of complexity, insurance type, primary care clinician type, and health care use data. RESULTS: The study cohort consisted of 45,279 patients with diabetes, 54.4% of whom resided in rural locations. The D5 composite metric was met in 39.9% of rural patients and 43.2% of urban patients (P <.001). Rural patients were significantly less likely to have attained all metric goals than urban counterparts (adjusted odds ratio [AOR] = 0.93; 95% CI, 0.88-0.97). The rural group had fewer outpatient visits (mean number of visits = 3.2 vs 3.9, P <.001) and less often had an endocrinology visit (5.5% vs 9.3%, P <.001) during the 1-year study period. Patients with an endocrinology visit were less likely to have met the D5 metric (AOR = 0.80; 95% CI, 0.73-0.86), whereas the more outpatient visits patients had, the greater their likelihood of attainment (AOR per visit = 1.03; 95% CI, 1.03-1.04). CONCLUSIONS: Rural patients had worse diabetes quality outcomes than their urban counterparts, even after adjustment for other contributing factors and despite being part of the same integrated health system. Lower visit frequency and less specialty involvement in the rural setting are possible contributing factors.

Individual patient-centered target-driven intervention to improve clinical outcomes of diabetes, health literacy, and self-care practices in Nepal: A randomized controlled trial.

Purpose: To examine the effectiveness of a culturally and linguistically appropriate, patient-centered, target-driven lifestyle intervention with video education training in improving clinical outcomes, health literacy, and diabetic self-care practices in newly diagnosed patients in Nepal. Methods: A total of 110 participants with newly and consequently diagnosed Type 2 were randomly allocated into intervention (mean age = 45 ± 9.7 years) and control (mean age = 47 ± 12.5 years) groups. Intervention group participants were trained on a culturally and linguistically appropriate diabetic video education program and were given a customized dietary and physical activity plan with specific targets to practice at home. Participants' compliance was monitored weekly via telephone calls. Both groups received the usual treatment from their doctor and were followed up after three months. Outcome measures included changes in: i. diabetic health literacy, diet, and physical activity measured using self-reported questionnaires; and ii. blood glucose (glycated hemoglobin, HbA1c), cholesterol, blood pressure, body mass index, and visual acuity. Clinical outcome measures were blinded from randomization and intervention allocation. Results: After three months, HbA1c decreased to 6.1% from the baseline value of 7.2% in the intervention group compared to 6.6% in the control group from the baseline value of 7.1% (p <0.05). The intervention group had mean total cholesterol and low-density lipoprotein of 174 and 95.5 mg/dL, which were significantly lower than 186 and 107.5 mg/dL in the control group. Daily white rice consumption decreased by 36.5% in the intervention vs. 4% in the control group (p <0.05). After three months, the intervention group participants exercised more than the control group (p <0.05). All intervention group participants self-initiated retinal screening checks since the baseline visit among which 13% showed early diabetic retinopathy signs compared to 0% in the control group. Health literacy improvement in the intervention group was found to be sustained after three months too. Conclusions: A culturally appropriate, target-driven lifestyle intervention with video education training is effective in improving clinical outcomes, health literacy, and self-care practice in newly diagnosed diabetic patients in Nepal, i.e., at a time period when effective diabetes control is vital to prevent further complications. The training intervention could be rolled out nationwide in order to reduce the risk of diabetic-related complications and improve people's quality of life and productivity.

Comprehensive Study of a Diabetes Mellitus Mathematical Model Using Numerical Methods with Stability and Parametric Analysis.

Diabetes is sweeping the world as a silent epidemic, posing a growing threat to public health. Modeling diabetes is an effective method to monitor the increasing prevalence of diabetes and develop cost-effective strategies that control the incidence of diabetes and its complications. This paper focuses on a mathematical model known as the diabetes complication (DC) model. The DC model is analyzed using different numerical methods to monitor the diabetic population over time. This is by analyzing the model using five different numerical methods. Furthermore, the effect of the time step size and the various parameters affecting the diabetic situation is examined. The DC model is dependent on some parameters whose values play a vital role in the convergence of the model. Thus, parametric analysis was implemented and later discussed in this paper. Essentially, the Runge-Kutta (RK) method provides the highest accuracy. Moreover, Adam-Moulton's method also provides good results. Ultimately, a comprehensive understanding of the development of diabetes complications after diagnosis is provided in this paper. The results can be used to understand how to improve the overall public health of a country, as governments ought to develop effective strategic initiatives for the screening and treatment of diabetes.

Predictive factors in treatment response of malignant external otitis.

PURPOSE: To evaluate the prevalence and impact of various predictive factors including diabetes control in malignant external otitis (MEO) treatment response. METHODS: In a cross-sectional study on MEO patients, we defined treatment response with three indices; ESR level decrease, hospitalization period, and systemic antifungal drug usage. The impact of diabetes control and other predictive factors on these indices have been evaluated. RESULTS: Overall, 164 patients with a mean age of 67.8 ± 9.7 years were included. Cranial nerve involvement was present in 56 patients. Nine patients had immunodeficiency. 19.5% of cases had leukocytosis. Diabetes mellitus was present in 156 patients, suffering for an average of 13.9 ± 8.6 years. The overall mean hemoglobin A1C (HbA1c) level was 8.3% (4.4-12.8%), and the mean fasting blood sugar was 146.4 mg/dl (63-292 mg/dl). 29.3% of patients had good diabetes control before admission (HbA1c < 7%), 54.9% had poor control (7% < HbA1c < 10%) and 15.9% had very poor glycemic control (HbA1c > 10%). The predictive role for the following factors were not statistically significant: age, gender, comorbidities, diabetes, diabetes management method used before and during hospitalization, diabetes duration, leukocytosis, immunodeficiency, fasting blood sugar level, HbA1c level, glycemic control index, and insulin amount. However, CRP level with a mean value of 34.3 mg/L showed a significant correlation with ESR decrease, hospitalization period, and antifungal drug usage. CONCLUSION: CRP level could be used as a predictor for the hospitalization period, the need for systemic antifungal and ESR level decrease. It would be helpful to check the CRP level at the time of diagnosis to predict the hospitalization period and the necessity of systemic antifungal management to adjust the treatment strategy.

Impact of Anaemia on HbA1c Interpretation Among Normogylcaemic Individuals With Diabetes Mellitus: A Clinical Laboratory Observational Study.

BACKGROUND AND AIM: Over the past decades, glycosylated haemoglobin (HbA1c) has been a gold standard for monitoring diabetes control over a long period, relative to blood glucose level (BGL) which measures short-term results. It is speculated that anaemia and factors that induce haemolysis may cause falsely elevated HbA1c leading to 'false positive' interpretations. This study aimed to investigate how anaemia impacts HbA1c. METHODS: This was a pathology-based observational pilot study using archived data of diabetic subjects monitored with both BGL and HbA1c in regional New South Wales (NSW), Australia. A total of 28,487 cases of blood glucose results were pooled and those with HbA1c and anaemia results were evaluated for correlation with the BGL results. Data collection was limited to de-identified information from the laboratory information system, hence details on the ethnicity and medical history were unavailable. Descriptive frequencies and Pearson correlations were performed. RESULTS: In the pooled data, 53.36% of individuals were females, and 50.54% had BGL ≥5.6 mmol/L. In the pilot dataset, the majority (64.86%) were males, 18.92% with BGL ≤5.6 mmol/L and 67.57% had HbA1c (≥6.5%). In the entire dataset, BGL was moderately and positively correlated with HbA1c (r = 0.6), whereas in the subset of individuals with normo-BGL and anaemia, the correlation was negative (r = -0.2). DISCUSSION: This pilot investigation observed a pertinent issue, which is a negative correlation between glycaemia and HbA1c in patients with anaemia. HbA1c was falsely increased despite normal blood glucose levels in individuals with anaemia. This advances the speculation that anaemia falsely increases HbA1c. Therefore, caution is necessary while interpreting HbA1c results for patients with anaemia, and new methods for interpretation are required.

Plasma Prostaglandin E2 Metabolite Levels Predict Type 2 Diabetes Status and One-Year Therapeutic Response Independent of Clinical Markers of Inflammation.

Over half of patients with type 2 diabetes (T2D) are unable to achieve blood glucose targets despite therapeutic compliance, significantly increasing their risk of long-term complications. Discovering ways to identify and properly treat these individuals is a critical problem in the field. The arachidonic acid metabolite, prostaglandin E2 (PGE2), has shown great promise as a biomarker of ß-cell dysfunction in T2D. PGE2 synthesis, secretion, and downstream signaling are all upregulated in pancreatic islets isolated from T2D mice and human organ donors. In these islets, preventing ß-cell PGE2 signaling via a prostaglandin EP3 receptor antagonist significantly improves their glucose-stimulated and hormone-potentiated insulin secretion response. In this clinical cohort study, 167 participants, 35 non-diabetic, and 132 with T2D, were recruited from the University of Wisconsin Hospital and Clinics. At enrollment, a standard set of demographic, biometric, and clinical measurements were performed to quantify obesity status and glucose control. C reactive protein was measured to exclude acute inflammation/illness, and white cell count (WBC), erythrocyte sedimentation rate (ESR), and fasting triglycerides were used as markers of systemic inflammation. Finally, a plasma sample for research was used to determine circulating PGE2 metabolite (PGEM) levels. At baseline, PGEM levels were not correlated with WBC and triglycerides, only weakly correlated with ESR, and were the strongest predictor of T2D disease status. One year after enrollment, blood glucose management was assessed by chart review, with a clinically-relevant change in hemoglobin A1c (HbA1c) defined as ≥0.5%. PGEM levels were strongly predictive of therapeutic response, independent of age, obesity, glucose control, and systemic inflammation at enrollment. Our results provide strong support for future research in this area.

Time in range: new parameter to evaluate blood glucose control.

Continuous glucose monitoring became more common in everyday clinical practice. New parameters have been created as a standard for assessing the degree of control for people with diabetes and can be used more clearly than glycated haemoglobin. The new parameter time in range represents a significant benefit not only for diabetologists, but also an important tool to help the patients in their daily lives with diabetes.

Evaluating the Impact of the COVID-19 Pandemic on Monthly Trends in Primary Care.

Introduction As the COVID-19 pandemic progressed, multiple barriers arose for patients and providers in the primary care setting. Despite the attempt to utilize telemedicine to overcome barriers, visits remained lower than pre-pandemic levels. This raises concern for preventative medicine and chronic disease management. Methods This study aimed to evaluate the impact of the pandemic in primary care by utilizing two years of data from a family medicine clinic. Data obtained from the electronic medical record for March 2019 through February 2020 and March 2020 through February 2021 were used to evaluate monthly trends from the year before the pandemic and the first year of the pandemic in the following six categories: hypertension control, diabetes control, lipid profile screening, breast cancer screening, colorectal cancer screening, and cervical cancer screening. Results The paired t-tests found a significant difference in the averages between the two years for all categories except hypertension control. The results for chi-square demonstrated a significant difference in four months for cervical cancer screening, five months for hypertension control and colorectal cancer screening, nine months for diabetes control and lipid profile screening, and 10 months for breast cancer screening. Conclusion These results show a profound impact of the pandemic on both preventative medicine and chronic disease management. This study had a large sample size but is not generalizable to the entire population. These results can help guide quality improvement measures going forward. However, further research is necessary to better understand the full extent of COVID-19's impact on primary care.

Diabetes Treatment and Mental Illness: A Call for an Integrated Health Care System in Underserved Semi-Rural Malaysia.

Diabetes mellitus (DM) management imposes a tremendous psychological burden on patients. The study investigates the association between DM treatment with blood glucose (BG) control and common mental health conditions. A cross-sectional study was conducted among 1821 individuals with DM in a community-based survey conducted in 2013. Information on respondents' sociodemographic, mental health, DM treatment, and BG levels was collected. Multinomial logistic regression was employed to examine the association of diabetes treatment with controlled BG levels (<11.1 mmol/L) (42.5%, n = 774) or uncontrolled BG levels (34.3%, n = 625) compared with those not undergoing treatment (23.2%, n = 422) on depression anxiety, and stress. Having DM treatment and controlled BG was associated with high depressive symptoms (Relative Risk Ratio, RRR: 2.42; 95% CI 1.33−4.41) and high anxiety symptoms (1.66; 1.08−2.56) but not with perceived stress. However, treated DM with uncontrolled BG was associated with anxiety (high: 1.64; 1.05−2.56; low: 2.59; 1.10−6.09) but not depression or perceived stress. Our results suggest that being treated for DM, regardless of glucose control status, was associated with anxiety symptoms, whereas being treated with controlled BG was associated with high depressive symptoms. This situation highlights the need for integrative, multidisciplinary care for DM patients with mental health comorbidities.

A software interface for in silico testing of type 2 diabetes treatments.

BACKGROUND AND OBJECTIVE: The increasing incidence of diabetes continuously stimulates the research on new antidiabetic drugs. Computer simulation can save time and costs, alleviating the need of animal trials and providing useful information for optimal experiment design and drug dosing. We recently presented a type 2 diabetes (T2D) simulator as tool for in silico testing of new molecules and guiding treatment optimization. Here we present a user-friendly interface aimed to increase the usability of the simulator. METHOD: The simulator, based on a large-scale glucose, insulin, and C-peptide model and equipped with 100 virtual subjects well describing system dynamics in a real T2D population, is extended to incorporate pharmacokinetics/pharmacodynamics (PK/PD) of a drug of interest. A graphical interface is developed on top of the simulator, allowing an easy design of in silico experiments: specifically, it is possible to select the population size to test, design the experiment (crossover or parallel), its duration and the sampling grid, choose glucose and insulin doses, and define treatment PK/PD and dose administered. The simulator also provides the outcome metrics requested by the user, and performs statistical comparisons among treatments and/or placebo. RESULTS: To illustrate the potential of the simulator, we provided a case study using metformin and liraglutide. Literature-based PK/PD models of metformin and liraglutide have been incorporated in the simulator, by modulating key drug-sensitive model parameters. An in silico placebo-controlled trial has been done by simulating a three-arm meal tolerance test with subjects receiving placebo, metformin 850 mg, liraglutide 1.80 mg, respectively. The obtained results are in agreement with the clinical evidences, in terms of main glucose, insulin, and C-peptide outcome metrics. CONCLUSIONS: We developed a user-friendly software interface for the T2D simulator to support the design and test of new antidiabetic drugs and treatments. This increases the simulator usability, making it suitable also for users who have low experience with computer programming.

Effects of internet-based interventions on improvement of glycemic control and self-management in older adults with diabetes: Systematic review and meta-analysis.

PURPOSE: To assess and summarize the effects of internet-based interventions on diabetes control and self-management of older adults with diabetes. METHODS: PubMed, Web of Science and three Chinese databases were searched to identified articles published in until December 2021. Clinical trials if they covered the effects of internet-based interventions on diabetes control and self-management of older adults with diabetes were included. All data analysis were performed by Review Manager 5.3. RESULTS: Sixteen studies with a total of 5604 participants met the inclusion criteria. Our primary outcomes included HbA1c control and self-management. (1) HbA1c control: results indicated statistically difference and high heterogeneity [Q = 112.9, df = 8, p < 0.001, I2 = 93%], in the subgroup analysis of studies in China, results showed a significant influence of internet-based interventions on HbA1c control [Q = 21.31, df = 5, p = 0.03, I2 = 77%]; (2) self-management: in the subgroup analysis of study duration ≤ 6 months [Q = 84.62, df = 2, p < 0.001, I2 = 98%]. CONCLUSION: Internet-based interventions are promising on diabetes control and self-management of older adults with diabetes, but still preliminary due to the heterogeneity of intervention components and the limited number of higher methodological quality trials. AVAILABILITY OF DATA AND MATERIAL: Applicable.