Frequent Blood Glucose Monitoring Research Articles

Smart Contact Lens for Colorimetric Visualization of Glucose Levels in the Body Fluid.

Frequent blood glucose monitoring is a crucial routine for diabetic patients. Traditional invasive methods can cause discomfort and pain and even pose a risk of infection. As a result, researchers have been exploring noninvasive techniques. However, a limited number of products have been developed for the market due to their high cost. In this study, we developed a low-cost, highly accessible, and noninvasive contact lens-based glucose monitoring system. We functionalized the surface of the contact lens with boronic acid, which has a strong but reversible binding affinity to glucose. To achieve facile conjugation of boronic acid, we utilized a functional coating layer called poly(tannic acid). The functionalized contact lens binds to glucose in body fluids (e.g., tear) and releases it when soaked in an enzymatic cocktail, allowing for the glucose level to be quantified through a colorimetric assay. Importantly, the transparency and oxygen permeability of the contact lens, which are crucial for practical use, were maintained after functionalization, and the lenses showed high biocompatibility. Based on the analysis of colorimetric data generated by the smartphone application and ultraviolet-visible (UV-vis) spectra, we believe that this contact lens has a high potential to be used as a smart diagnostic tool for monitoring and managing blood glucose levels.

Effect of the AADE7 Self-Care Behaviors Framework on Diabetes Education Management in a Shared Care Model.

Diabetes self-management education (DSME) provides diabetic patients with knowledge of diabetes, requires attention and recording of dietary habits, and increases the frequency and accuracy of blood glucose monitoring. DSME also achieves better blood glucose control, thus benefiting diabetic patients and reducing the risk of diabetes complications. However, few studies have systematically examined whether DSME follows AADE 7 Self-Care Behaviors (AADE7™). Therefore, this study aimed to investigate the control effect of AADE7™-based management on laboratory test indicators of diabetic patients. The patients with diabetes who received shared care management in our hospital between June 2014 and April 2022 were analyzed retrospectively. According to the process of outpatient consultation, each patient received health education provided by diabetes education nurses and dietitians after consultation. Health education was a process from assessment to health guidance. The basic information of all patients was recorded, and AADE7™ behavior assessment and health education session were conducted through interviews. A total of 13,650 were given shared care management, requiring more than 6 follow-up visits per year, as well as health education. It was reassessed annually according to AADE standards. The impact of the patients' behavior change after the AADE7™-based management on the relevant test indicators was observed. After eight years of intervention, a total of 8319 samples were obtained after excluding the outliers. Stepwise regression analysis was performed, and the results showed that, with other conditions held constant, a greater number of days per week to follow a healthy diet, to take hypoglycemic medication as prescribed, to monitor blood glucose, and to exercise and higher education level were associated with lower levels of glycosylated hemoglobin. The change from drinking to nondrinking was associated with lower triglycerides. If low blood glucose was monitored, patients who reviewed and took immediate action showed lower levels of low-density lipoprotein, urine microalbumin, and urine microalbumin/creatinine ratio compared with those without review and immediate action. Significance tests for each term showed P value <0.05. The AADE7™ framework is a tool supporting patient-centered self-management and education. In the AADE7™ standards, successful self-management is considered as a key outcome in the care of patients with diabetes and related diseases. This tool can effectively improve patient compliance and increase the rate of blood glucose compliance rates in patients with diabetes and therefore is worthy of clinical promotion.

Neonatal Birth Weight With Daily Compared With Every-Other-Day Glucose Monitoring in Gestational Diabetes Mellitus

OBJECTIVE: To assess whether universal use of every-other-day glucose monitoring in patients with gestational diabetes mellitus (GDM) resulted in similar birth weights and medication use and was preferred by the patient compared with traditional daily glucose monitoring. METHODS: This was a noninferiority randomized controlled trial conducted at a single New York City hospital between April 2021 and May 2022. Patients with singleton pregnancies who were diagnosed with GDM after 20 weeks of gestation and had a minimum of 7 days of previous daily blood glucose testing were randomly assigned to test blood glucose values daily or every other day. The primary outcome was neonatal birth weight. We calculated a total sample size of 196 participants needed for noninferiority to be tested, assuming the mean birth weight in the every-other-day group, compared with the daily group, was no higher than the predefined noninferiority margin of 200 g (80% power and one-sided alpha of 0.05). Postrandomization characteristics, including blood glucose values and medication initiation and timing, were recorded. Satisfaction with treatment group was assessed using the validated Oxford Maternity Diabetes Treatment Satisfaction Questionnaire. RESULTS: A total of 197 patients were randomized: 98 in the daily group and 99 in the every-other-day group. Baseline characteristics were similar between groups. The mean neonatal birth weight was similar between groups (mean±SD 3,090±418 g among newborns in the daily group compared with 3,181±482 g among newborns in the every-other-day group). For the primary outcome, the every-other-day group was found to be noninferior to the daily group with an upper confidence limit for the mean difference in mean birth weight of 197 g, which was below the noninferiority margin of 200 g (P=.046). Postrandomization, there were no significant differences in the number of patients who required medication, the gestational age at which medication was started, or the type of medication used. Average fasting and postprandial glucose values were similar between groups. There was an increase in adherence to treatment group in those randomized to every-other-day blood sugars, but no difference in patient satisfaction. CONCLUSION: In patients with GDM, testing blood glucose values every other day was as effective as testing daily, without apparent effects on birth weight, medication initiation, or glucose control. Reduced frequency of blood glucose monitoring might help decrease the emotional, physical, and financial burden experienced by patients with GDM. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, NCT04857073.

Heterogeneity in glycaemic control in children and adolescents with type 1 diabetes: A latent class trajectory analysis of Danish nationwide data.

Suboptimal glycaemic control in children and adolescents with type 1 diabetes is prevalent and associated with increased risk of diabetes-related complications and mortality later in life. First, we aimed to identify distinct glycated haemoglobin (HbA1c) trajectories in children and adolescents (2-19 years) with type 1 diabetes. Second, we examined their associations with clinical and socio-demographic factors. Data were obtained from the Danish Registry of Childhood and Adolescent Diabetes (DanDiabKids) comprising all Danish children and adolescents diagnosed with type 1 diabetes from 1996 to 2019. Subgroups of distinct mean trajectories of HbA1c were identified using data-driven latent class trajectory modelling. A total of 5889 children (47% female) had HbA1c measured a median of 6 times (interquartile range 3-8) and contributing to 36,504 measurements. We identified four mean HbA1c trajectories, referred to as 'Stable but elevated HbA1c' (83%), 'Increasing HbA1c' (5%), 'Late HbA1c peak' (7%), and 'Early HbA1c peak' (5%). Compared to the 'Stable but elevated HbA1c' group, the three other groups presented rapidly deteriorating glycaemic control during late childhood or adolescence, had higher HbA1c at study entry, and included fewer pump users, higher frequency of inadequate blood glucose monitoring, more severe hypoglycaemic events, lower proportions with Danish origin, and worse educational status of parents. The groups also represented significant differences by healthcare region. Children and adolescents with type 1 diabetes experience heterogenous trajectories with different timings and magnitudes of the deterioration of HbA1c levels, although the majority follow on average a stable, yet elevated HbA1c trajectory. The causes and long-term health implications of these heterogenous trajectories need to be addressed.

SAT134 CGM Use During Pregnancy Complicated By CF-Induced Diabetes

Abstract Disclosure: A.Y. Mazori: None. E.S. Markovic: None. C.J. Levy: Advisory Board Member; Self; Dexcom, Eli Lilly &amp; Company. Research Investigator; Self; Abbott Laboratories, Insulet Corporation, Tandem Diabetes Care, Dexcom. Introduction: Glycemic control remains challenging in pregnancies complicated by diabetes mellitus. Strict glycemic targets are required to optimize maternal and neonatal outcomes, but euglycemia is hindered by fluctuating insulin sensitivity and the need for frequent blood-glucose monitoring (BGM). Consensus guidelines recommend therapeutic continuous glucose monitoring (CGM) for pregnant and nonpregnant individuals with type 1 and type 2 diabetes, but current data support therapeutic CGM use in cystic fibrosis (CF)-related diabetes (CFRD) only outside of pregnancy. We report the case of a patient with CFRD who achieved recommended glycemic targets with a therapeutic CGM during a singleton pregnancy. Methods: A case report and literature review are presented. Results: A 32-year-old nulliparous woman with CF became pregnant via frozen-embryo transfer. Prior CF complications included CFRD, pancreatic insufficiency, and recurrent pancreatitis. A therapeutic Dexcom G6 CGM and intermittent BGM were used to monitor glycemic control before and during pregnancy; sensor use exceeded 96%. Pressure-induced sensor attenuations yielded sporadic hypoglycemic values discordant with simultaneous BGM. CGM analysis for the 90 days preceding conception revealed: time in range of 63-140 mg/dL (TIR) was 90.8%, time above range (TAR) 6.3%, and time below range (TBR) 2.9%. Throughout pregnancy, TIR was 92.9%, TAR 3.4%, and TBR 3.6%; no severe hypoglycemia occurred. Daytime (6AM to midnight) and nighttime hypoglycemia were 4.6% and 2.2%, respectively. In the first trimester, TIR was 90.8%, TAR 3.7%, and TBR 5.5%. During the second trimester, the patient achieved TIR 94.2%, TAR 2.6%, and TBR 3.2%. In the third trimester, TIR was 95.7%, TAR 0.9%, and TBR 3.4%. The pregestational CFRD regimen consisted of insulin glargine 12 units and lispro 3-8 units. The basal-insulin dose was 10 units at 13 weeks’ gestation, 9 units at 27 weeks’ gestation, and 8 units at 38 weeks’ gestation. The prandial-insulin doses varied between 1.5-5 units at 13 weeks’ gestation, 0-7 units at 27 weeks’ gestation, and 0-5 units at 38 weeks’ gestation. After an uncomplicated vaginal delivery at 38 weeks and six days’ gestation, maternal fasting hypoglycemia occurred after one dose of glargine 3 units. Euglycemia was obtained without basal, prandial, or correctional insulin. The neonate experienced mild hypoglycemia that resolved with oral glucose gel and feeding. The neonate was neither macrosomic nor large for gestational age (birth weight, 3.54 kg, 71st percentile) and did not require intensive-care unit management. Both the patient and neonate were discharged on postpartum day two. Conclusion: Therapeutic CGM use in a pregnancy complicated by CFRD was effective for maternal and neonatal outcomes. Further study is warranted to examine CGM use and efficacy in this population. Presentation: Saturday, June 17, 2023

A Stacked Long Short-Term Memory Approach for Predictive Blood Glucose Monitoring in Women with Gestational Diabetes Mellitus.

Gestational diabetes mellitus (GDM) is a subtype of diabetes that develops during pregnancy. Managing blood glucose (BG) within the healthy physiological range can reduce clinical complications for women with gestational diabetes. The objectives of this study are to (1) develop benchmark glucose prediction models with long short-term memory (LSTM) recurrent neural network models using time-series data collected from the GDm-Health platform, (2) compare the prediction accuracy with published results, and (3) suggest an optimized clinical review schedule with the potential to reduce the overall number of blood tests for mothers with stable and within-range glucose measurements. A total of 190,396 BG readings from 1110 patients were used for model development, validation and testing under three different prediction schemes: 7 days of BG readings to predict the next 7 or 14 days and 14 days to predict 14 days. Our results show that the optimized BG schedule based on a 7-day observational window to predict the BG of the next 14 days achieved the accuracies of the root mean square error (RMSE) = 0.958 ± 0.007, 0.876 ± 0.003, 0.898 ± 0.003, 0.622 ± 0.003, 0.814 ± 0.009 and 0.845 ± 0.005 for the after-breakfast, after-lunch, after-dinner, before-breakfast, before-lunch and before-dinner predictions, respectively. This is the first machine learning study that suggested an optimized blood glucose monitoring frequency, which is 7 days to monitor the next 14 days based on the accuracy of blood glucose prediction. Moreover, the accuracy of our proposed model based on the fingerstick blood glucose test is on par with the prediction accuracies compared with the benchmark performance of one-hour prediction models using continuous glucose monitoring (CGM) readings. In conclusion, the stacked LSTM model is a promising approach for capturing the patterns in time-series data, resulting in accurate predictions of BG levels. Using a deep learning model with routine fingerstick glucose collection is a promising, predictable and low-cost solution for BG monitoring for women with gestational diabetes.

Efficacy of a smartphone application for helping individuals with type 2 diabetes mellitus manage their blood glucose: a protocol for factorial design trial

BackgroundChina has the largest number of individuals with type 2 diabetes mellitus (T2DM) in the world, and most lack knowledge about glycemic control and health management. This trial will examine whether a smartphone application can improve blood glucose management among individuals with T2DM.MethodsThis will be a 2-center, factorial design, equal proportional distribution, superiority trial conducted in outpatient endocrinology clinics at two tertiary hospitals in Chengdu, China. The trial will enroll smartphone-literature individuals at least 18 years old who have been diagnosed with T2DM based on glycosylated hemoglobin (HbA1c) of at least 7.0%. Individuals will be randomly assigned to receive routine care with standard education about T2DM and glycemic control (Control), routine care as well as weekly telephone reminders to self-monitor blood glucose (Reminder), routine care and a smartphone application providing information about glycemic control and health management with T2DM (App), or the combination of routine care, the smartphone application, and weekly telephone reminders (App + Reminder). After 6 months of these interventions, participants will be analyzed for the primary outcome of HbA1c as well as the secondary outcomes of blood glucose monitoring frequency, body mass index, blood pressure, knowledge about diabetes, health beliefs related to diabetes, diabetes self-management behavior, and satisfaction with the smartphone application.DiscussionThis trial will determine whether a smartphone application can improve glycemic management among Chinese with T2DM. The findings may help guide the development of effective applications in China and elsewhere.Trial registrationRegistration in the Chinese Clinical Trial Registry (ChiCTR) under registration number ChiCTR2100042297: https://www.chictr.org.cn/bin/userProject. 17 January 2021.

Identification of factors associated with fear of hypoglycemia using the capability, opportunity, motivation and behavior model in people with type 2 diabetes mellitus: a cross-sectional study.

To examined the relationship between fear of hypoglycemia and certain variables in people with type 2 diabetes mellitus (T2DM) based on the Capability, Opportunity, Motivation, and Behavior model, combined with the context unique to people with diabetes to provide a basis for developing targeted nursing interventions. In this cross-sectional study, 212 people with T2DM were recruited from February 2021 to July 2021. Data were collected using the Hypoglycaemia Fear Survey, Gold score, Patient Assessment of Chronic Illness Care (PACIC) scale and Diabetic Self-Management Attitudes Scale. Multiple linear regression analysis was performed to determine the predictors of fear of hypoglycemia using SPSS 26.0. The mean fear of hypoglycemia score was 74.88 ± 18.28 (range: 37.00-132.00). In people with T2DM, the frequency of blood glucose monitoring, the frequency of hypoglycemia in the past half-year, degree of understanding of hypoglycemia, impaired awareness of hypoglycemia, PACIC, and self-management attitude of diabetes were the influencing factors of fear of hypoglycemia (adjusted R2 = 0.560, F[21,190] = 13.800, P < 0.001). These variables explained 56.0% of the variance in the fear of hypoglycemia. The level of fear of hypoglycemia in people with T2DM was relatively high. In addition to paying attention to the disease characteristics of people with T2DM, medical staff should also pay attention to patients' own perception and handling ability of disease and hypoglycemia, attitude toward self-management behavior and external environment support, all of which have a positive effect on improving the fear of hypoglycemia in people with T2DM, optimizing the self-management level and improving quality of life.

536-P: Psycho-behavioral and Clinical Characteristics in Koreans with Type 2 Diabetes With or Without Perceived Hypoglycemia

Objective: To compare characteristics in Koreans with type 2 diabetes (T2D) with or without perceived hypoglycemia. Methods: A cross-sectional, correlational design was used. Participants 20 years or older (N=177, men= 113 [63.8%]) were recruited from a university-affiliated diabetes clinic in Korea. Groups were divided by perceived hypoglycemia or not based on the Control Problem Scale. Socio-demographics (e.g., sex, age, years with T2D), psycho-behavioral factors including diabetes self-care activity (Summary of Diabetes Self-Care Activities Questionnaire), sleep quality (Pittsburgh Sleep Quality Index), health-related quality of life (QoL; SF-12) and diabetes-related clinical factors (HbA1C, random glucose, blood pressure and lipids) were assessed. Body mass index [BMI], skeletal muscle mass [SMM], total body water (TBW), body fat mass [BFM], and fat free mass [FFM] were assessed by a body composition analyzer (InBody970, Korea). Statistical analyses were performed using SPSS (version 26.0) to compare group differences. Findings: One-third (n=67, 37.9%) perceived hypoglycemia in the past month (mean age [yr]= 59.1±12.7 vs. 62.1±12.8 and 35 participants experienced severe hypoglycemic reactions (e.g., passing out, needing help) during the past year. The hypoglycemia group reported a lower SF-12 score (88.5±14.1 vs. 96.1±15.2, p=.001), especially mental health functioning (T-score: 47.0±10.2 vs. 51.9±11.6, p=.005) and poor sleep quality needing professional counseling (n=43 [64.2%] vs. n=56 [50.9%]). Frequent monitoring of blood glucose and feet was performed while no differences for diet and exercise. The hypoglycemia group showed lower BMI (p=.018) and trend for lower SMM (p=.078), TBW (p=.086), BFM (p=.086) and FFM (p=.084). Conclusions: Perceived hypoglycemia is associated with psycho-behavioral and clinical factors. Further investigation is warranted to examine risks for hypoglycemia related to muscle and body mass decline. Disclosure E.Cha: None. Y.Shin: None. K.Joung: None. H.Kim: None. H.Kim: None. M.S.Faulkner: None. Funding National Research Foundation of Korea (HNU X-Corps)

952-P: The Accuracy and Feasibility of Continuous Glucose Monitoring in COVID-19 Non-Critically Ill Hospitalized Patients—A Pilot Study

Background: Optimal glycemic control is associated with favorable outcomes in COVID-19 hospitalized patients. Frequent capillary blood glucose (CBG) monitoring is difficult to perform. Using continuous glucose monitoring (CGM) system to assist glycemic care can reduce the exposure of healthcare personnel and PPE usage. However, data on the accuracy of CGM in this setting are limited. Objective: To evaluate the accuracy and feasibility of real-time CGM (rt-CGM) in non-ICU hospitalized adult COVID-19 patients. Methods: This is a single-center prospective study of non-ICU hospitalized adult patients with COVID-19 infection who had hyperglycemia requiring insulin therapy during admission. Medtronic Guardian Connect rt-CGM sensor and transmitter were placed on the patient’s abdomen. Paired CBG and sensor glucose values were analyzed for accuracy of CGM using mean absolute relative difference (MARD) and Clarke Error Grid Analysis (CEGA). Results: Fifteen patients were enrolled. Mean age was 48.6 ± 17.9 years. Thirteen patients (86.7%) had pre-existing diabetes. Mean HbA1c was 10.6± 3.6%. Mean duration of CGM use was 6 ± 1.2 days and mean calibration was 2.6 ± 0.7 times/day. There were 253 paired CBG and CGM measurements. The overall MARD was 9.9 ± 9.3%. The lowest MARD was observed in the CBG range of 70-180 mg/dl (9.6 ± 9.0%). The percentages of glucose readings within ±15%/15 mg/dL, ±20%/20 mg/dL, and ±30%/30 mg/dL were 80.2%, 89.7%, and 95.3%, respectively. A total of 99.2% of the data points were in zone A and B of CEGA, and none were in zone E. Percent time in range on day 1 was 57.9 ± 22.9 and improved to 64.9 ± 18.1 in the last 72 hours of sensor wear. No adverse events from the CGM were observed. CGM reduced POC testing by 30%. Conclusions: Rt-CGM use in hospitalized patients with COVID-19 infection demonstrates high accuracy and potentially improves glucose control, reduces the frequency of CBG testing, and preserves medical resources. Disclosure C.Sakjirapapong: None. S.Sirinvaravong: None. L.Preechasuk: None. N.Thongtang: None. Funding Specific League Funds (R016421005)

Blood Glucose monitoring in pregnant women with gestational diabetes mellitus

Background: Women with gestational diabetes mellitus (GDM) are more likely to develop pre-eclampsia during pregnancy, and to have the birth induced, suffer trauma to the perineum during birth, or to give birth by caesarean section.Good blood glucose control throughout pregnancy will reduce the risk of fetal macrosomia, trauma during birth (for her and her baby), induction of labor and/or caesarean section, neonatal hypoglycemia, and perinatal death. Monitoring of blood glucose levels is an important way to maintain control of sugar concentrations in the blood.However, it is not clear which is best method or frequency for monitoring blood glucose for limiting health complications for women and their babies.The purpose of this rapid literature review is to identify the most recent evidence and knowledge concerning blood glucose monitoring in pregnant women with gestational diabetes mellitus. Methods: We undertook a Rapid Literature Review focusing on articles published from 2020 to 2022 thus offering the readers access to most up-to-date evidence concerning the topic. We searched the online databases of Pubmed, EMBASE, Cochrane Library, and BMJ from January 2020 till May 15, 2022. Inclusion criteria were studies of blood glucose monitoring for pregnant women with gestational diabetes mellitus. Results: Nine papers were included in the final review. Recent evidence on frequency of blood glucose monitoring, new glucose monitoring technologies, remote monitoring technologies and reminder systems in blood glucose monitoring were summarized. Main Contribution to Evidence-Based Practice: Recommendations for frequency of blood glucose monitoring should be tailored according to pregnant women’s blood glucose management plan. Continuous glucose monitoring (CGM) should be considered for pregnant women under some specific conditions. Remote monitoring technologies or reminder systems based on smartphones, computers and tablets could be considered to improve patient’s compliance toward blood glucose monitoring.

Type 1 diabetes patient experiences and management practices during the COVID-19 pandemic in rural Uganda.

The COVID-19 pandemic has impacted various aspects of the lives of persons with chronic diseases, including type 1 diabetes (T1D). However, the diabetes care experiences and practices adopted by persons living with T1D after the declaration of the COVID-19 pandemic in Uganda have not been well documented. We investigated diabetes management practices and experiences of persons with T1D during the COVID-19 pandemic lockdown in a rural district of southwestern Uganda. Using interactive sequential explanatory mixed methods, we conducted a cross-sectional study of persons with T1D aged 18-25 years, their caregivers and health workers. Quantitative data was exclusively collected from patients with T1D using Kobo Toolbox™ and analysed with SPSS™ version26; qualitative interviews were used to elicit responses from purposively selected patients with T1D, plus caregivers and health workers that were analysed using a thematic framework approach. The study enrolled 51 (24 males) patients with T1D; diabetes duration (mean ± SD) 6.6 ± 5 years. Access to insulin syringes significantly worsened in 19.6% of participants (p = 0.03). Insulin injection frequency (p = 0.01), blood glucose monitoring (p = 0.001) and meal frequency (p = 0.0001) significantly decreased. Qualitative interviews highlighted COVID-19 restriction measures had reduced household income, frequency of clinic visits, and access to food, diabetes support and social services. Experiences and practices were consistent with decisions to prioritise survival, even with known risks around metabolic control. The online version contains supplementary material available at 10.1007/s40200-023-01222-4.

What, why and how to monitor blood glucose in critically ill patients

Critically ill patients are prone to high glycemic variations irrespective of their diabetes status. This mandates frequent blood glucose (BG) monitoring and regulation of insulin therapy. Even though the most commonly employed capillary BG monitoring is convenient and rapid, it is inaccurate and prone to high bias, overestimating BG levels in critically ill patients. The targets for BG levels have also varied in the past few years ranging from tight glucose control to a more liberal approach. Each of these has its own fallacies, while tight control increases risk of hypoglycemia, liberal BG targets make the patients prone to hyperglycemia. Moreover, the recent evidence suggests that BG indices, such as glycemic variability and time in target range, may also affect patient outcomes. In this review, we highlight the nuances associated with BG monitoring, including the various indices required to be monitored, BG targets and recent advances in BG monitoring in critically ill patients.

Patient satisfaction with access, affordability and quality of diabetes care at Mohalla Clinics in Delhi, India

Mohalla Clinics have been set up to provide curative care for minor ailments free of cost within walking distance in the urban slums, thus making primary care more accessible and affordable. Studies evaluating patient satisfaction with treatment of chronic conditions, such as diabetes, in these clinics are lacking. A survey of 400 type 2 diabetes patients was conducted, split equally between Mohalla clinics (MC) and Private clinics (PC) in Delhi. Responses were analyzed using STATA17, applying appropriate statistical tests for the data type (Chi-square test, Mann-Whitney U test, Wilcoxon signed rank test, or two-sample t test). Satisfaction level was high in both groups with no significant difference between mean satisfaction scores of MC patients and PC patients (Mean 3.79 vs. 3.85 respectively, p = 0.4). However, MC patients reported a significant improvement in their satisfaction score after switching to MC (Mean 3.79 vs. 3.3 for the previous facility, p < 0.05). Physician interaction with the patients was the most important factor in influencing the satisfaction score. Proximity to the clinic was the second most important factor for MC patients but was not as important for PC patients. Surprisingly, treatment success was considered an important factor for satisfaction level by < 10% MC and < 20% PC patients only, pointing to the need for patient education across both the groups. None of the MC patients mentioned free treatment as a contributory factor to high satisfaction, perhaps because most shifted from a government setup to MC. PC patients had more frequent follow-up visits and blood glucose monitoring, and longer consultation duration compared to MC patients, which were offset by access factors, thus not causing much difference to the satisfaction score between the two groups. Mohalla clinics are making diabetes treatment accessible and affordable for the marginalized population of Delhi, despite not being designed or fully equipped to care for chronic diseases such as diabetes that require multi-specialty care to monitor and manage multiple co-morbidities and long-term complications. Positive perception of physician interaction and convenient location of the clinics are the two major contributors to the high satisfaction patients expressed with diabetes care at these clinics.

Twice-daily injections and multiple daily injections of insulin in toddlers with type 1 diabetes: a retrospective cohort study.

Twice-daily injections and multiple daily injections of insulin in toddlers with type 1 diabetes: a retrospective cohort study.

Updated Psychosocial Surveys With Continuous Glucose Monitoring Items for Youth With Type 1 Diabetes and Their Caregivers.

We added items relevant to continuous glucose monitoring (CGM) to the Diabetes Family Conflict Scale (DFC), Diabetes Family Responsibility Questionnaire (DFR), and Blood Glucose Monitoring Communication Questionnaire (GMC) and evaluated the psychometric properties of the updated surveys. Youth with type 1 diabetes who recently started CGM and their parents completed the updated surveys and additional psychosocial surveys. Medical data were collected from self-reports and review of the medical record. Youth (N = 114, 49% adolescent girls) were aged 13.3 ± 2.7 years and had mean glycated hemoglobin (HbA1c) 7.9 ± 0.9%; 87% of them used pump therapy. The updated surveys demonstrated high internal consistency (DFC youth: α = .91, parent: α = .81; DFR youth: α = .88, parent: α = .93; and GMC youth: α = .88, parent: α = .86). Higher youth and parent DFC scores (more diabetes-specific family conflict) and GMC scores (more negative affect related to glucose monitoring) were associated with more youth and parent depressive symptoms (r = 0.28-0.60, P ≤ .003), more diabetes burden (r = 0.31-0.71, P ≤ .0009), more state anxiety (r = 0.24 to r = 0.46, P ≤ .01), and lower youth quality of life (r = -0.29 to -0.50, P ≤ .002). Higher youth and parent DFR scores (more parent involvement in diabetes management) were associated with younger youth age (youth: r = -0.76, P < .0001; parent: r = -0.81, P < .0001) and more frequent blood glucose monitoring (youth: r = 0.27, P = .003; parent: r = 0.35, P = .0002). The updated DFC, DFR, and GMC surveys maintain good psychometric properties. The addition of CGM items expands the relevance of these surveys for youth with type 1 diabetes who are using CGM and other diabetes technologies.

Relationship between Glycated Hemoglobin (HbA1c) in Adolescents with Type 1 Diabetes Mellitus (T1DM) and Parental Anxiety and Depression

IntroductionT1D is the most common chronic endocrine pathology in children. The management of type 1 diabetes requires strong diet, physical activity, lifelong insulin therapy, and proper self-monitoring of blood glucose and is usually complicated and, therefore may result in a psychosocial problem for the whole family. Metabolic control of the disease is determined by glycated haemoglobin (HbA1c), the main criterion for diabetes compensation. It is assumed that anxiety and depression symptoms negatively affect glycemic control. A correlation was observed between anxiety and depression level and glycaemic control, as well as a three-way interaction among HbA1c, frequency of blood glucose monitoring, and diabetes-related stress (Buchberger et al., 2016). Parental psychological distress was associated with higher child self-report of stress and depressive symptoms, and it had negative effects on diabetes management.ObjectivesTo evaluate the relationship between parental depression and anxiety and metabolic control of their adolescents with T1DM.MethodsThe cross-sectional study recruited adolescents with T1D (N=251) and their parents (N=251). The 7-item Generalized Anxiety Disorder (GAD-7) scale measured anxiety level. The Patient Health Questionnaire – 9 (PHQ-9) detected depressive symptoms. Glycaemic control of patients was assessed using the last glycated haemoglobin (HbA1c) values. GLM mediation analysis was performed to determine the potential mediating effect of parent’ mental health depression and anxiety on the relationship between depression and anxiety of child on the level of HbA1c.Results502 respondents were eligible for screening. Mediation analysis was performed to assess the mediating role of parent GAD-7 on the linkage between HbA1c and child GAD-7 and child PHQ-9. the results relevated that the total effect of child GAD-7 on HbA1c was significant but the total effect of child PHQ-9 was not significant. With the inclusion of the mediating variable (parent GAD-7) (Figure 1), the impact of child GAD-7 and child PHQ-9 was founding insignificant (p ≥ 0.05) but the indirect effect of child GAD-7 and child PHQ-9 on HbA1c though parent GAD-7 was found significant (p ≤ 0,01) (Table 1). This indicates that the relationship between HbA1c and child GAD-7 and PHQ-9 is fully mediated by parent GAD-7.Image:Image 2:ConclusionsGlycated haemoglobin in adolescents with Type 1 diabetes is related to adolescents’ mental health via parents’ anxiety. It means that parents’ anxiety plays more significant role in the level of glycated haemoglobin in adolescents than depression and anxiety of the adolescent.Disclosure of InterestNone Declared

Prevalence of Depression in Patients with Type 1 Diabetes between 10 and 17 Years of Age in Jordan.

The study was conducted by distributing the Center for Epidemiological Studies Depression Scale for Children (CES-DC) to adolescents with T1D seen at Jordan University Hospital between February 2019 and February 2020. Demographic, clinical, and socioeconomic data were collected using electronic clinical charts. Possible predictors of depression were assessed using logistic regression analysis. A total of 108 children were enrolled in the study with mean age of 13.7 ± 2.3 years. Fifty-eight children (53.7%) had a CES depression score less than 15, and 50 children (46.3%) had a depression score of 15 or more. The number of diabetes-related hospital admissions and the frequency of self-monitoring of blood glucose (SMBG) were significantly different between the two groups. In the multivariable analysis, both gender and SMBG frequency were statistically significant. Girls were more likely to have a depression score ≥ 15 (OR = 3.41, p = 0.025) than boys. Patients who were rarely testing blood glucose levels were more likely to have a depression score ≥ 15 compared to those who were testing regularly (OR = 36.57, p = 0.002). The prevalence of depressive symptoms is relatively high in adolescents with T1D, especially in those living in developing countries. Longer diabetes duration, higher glycated hemoglobin level, and less frequent blood glucose monitoring are associated with higher depression scores.

Path Analysis of Influencing Factors of Depression in Middle-Aged and Elderly Patients with Diabetes.

This study aimed to assess the prevalence of depression in middle-aged and elderly patients with diabetes in China, determine the risk factors of depression in these patients, and explore the internal relationship between influencing factors and depression by constructing a pathway model. Data were collected from the 2018 China Health and Retirement Longitudinal Study (CHRLS). We included 1743 patients with diabetes who were assessed using the CES-D10, which is used to measure depressive symptoms in Chinese older adults. Based on the theory of psychological stress, data were analyzed using SPSS software version 22.0 and MPLUS 8.0. A correlation analysis was used to explore the relationship between the variables and depression scores. A path model was constructed to explore the interrelationships between variables and verify the relationships between variables and depression in patients with diabetes. The prevalence of depression among patients with diabetes was 42.5%. The path analysis results showed that income, diabetes duration, sleep duration, pain distress, self-rated health, and glycemic control directly affected depression, and self-rated health had the largest effect value. With self-rated health and glycemic control as mediator variables, income, diabetes duration, sleep duration, pain distress, glycemic control, and insulin use had indirect effects on depression by influencing self-rated health. Age, frequency of blood glucose monitoring, and exercise glycemic control awareness indirectly affected depression by affecting glycemic control, self-rated health status, and depression. We found that the path analysis model could construct the interaction between the influencing factors and explore the potential interrelationship between the influencing factors and diabetes-related depression. Patients with diabetes must adhere to regular medication, maintain a healthy lifestyle, and have effective glycemic control. Diabetes depression can be effectively prevented by making psychological knowledge publicly available, providing health education, and establishing corresponding for diabetes.

Artificial intelligence for non-invasive glycaemic-events detection via ECG in a paediatric population: study protocol

PurposePaediatric Type 1 Diabetes (T1D) patients are at greater risk for developing severe hypo and hyperglycaemic events due to poor glycaemic control. To reduce the risk of adverse events, patients need to achieve the best possible glycaemic management through frequent blood glucose monitoring with finger prick or Continuous Glucose Monitoring (CGM) systems. However, several non-invasive techniques have been proposed aiming at exploiting changes in physiological parameters based on glucose levels. The overall objective of this study is to validate an artificial intelligence (AI) based algorithm to detect glycaemic events using ECG signals collected through non-invasive device.MethodsThis study will enrol T1D paediatric participants who already use CGM. Participants will wear an additional non-invasive wearable device for recording physiological data and respiratory rate. Glycaemic measurements driven through ECG variables are the main outcomes. Data collected will be used to design, develop and validate the personalised and generalized classifiers based on a deep learning (DL) AI algorithm, able to automatically detect hypoglycaemic events by using few ECG heartbeats recorded with wearable devices.ResultsData collection is expected to be completed approximately by June 2023. It is expected that sufficient data will be collected to develop and validate the AI algorithm.ConclusionThis is a validation study that will perform additional tests on a larger diabetes sample population to validate the previous pilot results that were based on four healthy adults, providing evidence on the reliability of the AI algorithm in detecting glycaemic events in paediatric diabetic patients in free-living conditions.Trial registrationClinicalTrials.gov identifier: NCT03936634. Registered on 11 March 2022, retrospectively registered, https://www.clinicaltrials.gov/ct2/show/NCT05278143?titles=AI+for+Glycemic+Events+Detection+Via+ECG+in+a+Pediatric+Population&draw=2&rank=1.