Daily Blood Glucose Monitoring Research Articles

Health beyond biology: the extended health hypothesis and technology.

There are ethical dilemmas faced by clinicians when responding to using unregistered medical devices, such as innovative internet technologies for managing type 1 diabetes mellitus. This chronic disease significantly impacts patients' health, requiring intensive daily activities like blood glucose monitoring, insulin injections, and specific dietary recommendations. Recent technological advances, including continuous glucose monitors and insulin pumps, have been shown to improve glycemic control. Di-it Yourself Artificial Pancreas Systems are emerging open-source automated delivery methods initiated by the diabetes community, although they are not clinically evaluated and present a liability challenge for healthcare providers. To use them or not? Should parents and healthcare providers use such technology that helps, but is not proven?Having all of that in mind, we argue that the World Health Organization's (WHO) definition of health is outdated, advocating for the "Extended Health Hypothesis". This hypothesis claims that health extends beyond traditional biological boundaries to include essential functional structures like diabetes-related technology, making technology a part of a patient's health. This view aligns with the "Extended Mind Hypothesis," suggesting that health should include elements beyond organic material if they are vital to a patient's functions.In the commentary, we highlight that both naturalist and normative conceptions of health support the extended health hypothesis, emphasizing that human health is not confined to organic material. This perspective raises critical questions about whether devices like insulin pumps and continuous glucose monitors are integral to a patient's health and whether their malfunction constitutes a form of disease. Devices are considered integral to health, there is no ethical dilemma in using unregistered medical devices for managing type 1 diabetes. Finally, we call for reevaluating the definitions of health and patients, particularly for children with type 1 diabetes using advanced technologies. It asserts that the optimal use of such devices represents a new form of health, creating a health-device symbiosis that should be evaluated with the child's best interests in mind.

Family conflict: Risk factor for low adherence in adolescents with type 1 diabetes in Greek families

Introduction: Type 1 Diabetes Melitus (T1DM) treatment is demanding, due to daily blood glucose monitoring, certain diet plan, specific exercise program, multiple daily insulin injections, and management of episodes of hypo- or hyperglycemia. Family conflict may play a significant role in the adherence of adolescents with type 1 diabetes. Purpose: To evaluate Greek families’ conflicts and determine their relationship with T1DM adolescents’ adherence. Methods: A cross-sectional study was conducted from October 2021 to June 2022. Due to COVID-19 restriction, all the interviews were conducted through online survey. Three questionnaires were distributed to the adolescents. Pediatric Quality of Life Inventory tool, Diabetes Self-Management Profile and Collaborative Parent Involvement Scale for Youths Questionnaire. PeDsQL was distributed to their parents as well. Results: 59 adolescents (N=21) aged 10-19 years and their parents (N=38) participated. The mean values of PedsQL for all five factors ranged from 55.7 (Worry subcategory) to 77.8 (Treatment adherence), showing an overall moderate QoL. According to the mean values, parents’ perspectives PedsQL for all five factors ranged from 38.6 (Worry subcategory) to 77 (Treatment adherence), showing an overall moderate QoL. Mean DSMP score indicated a high level of adherence of children with diabetes mellitus to their treatment, whilst mean cooperation score indicated a high level of cooperation between parents and adolescents with T1DM and low level of FC. Bivariate analysis revealed that less FC was related to better treatment adherence in adolescents. Conclusions: T1DM management remains challenging, particularly as children grow older and move into adolescence. The family can play a significant role in T1DM management. Diabetes multidisciplinary teams should evaluate and understand family members' interactions detecting inter-family problems such as high frequency of FC. Provision of family support can improve communication between adolescents and parents and may reduce FC resulting in better T1DM treatment adherence and outcomes.

IoMT innovations in diabetes management: Predictive models using wearable data

Diabetes Mellitus (DM) represents a metabolic disorder characterized by consistently elevated blood glucose levels due to inadequate pancreatic insulin production. Type 1 DM (DM1) constitutes the insulin-dependent manifestation from disease onset. Effective DM1 management necessitates daily blood glucose monitoring, pattern recognition, and cognitive prediction of future glycemic levels to ascertain the requisite exogenous insulin dosage. Nevertheless, this methodology may prove imprecise and perilous. The advent of groundbreaking developments in information and communication technologies (ICT), encompassing Big Data, the Internet of Medical Things (IoMT), Cloud Computing, and Machine Learning algorithms (ML), has facilitated continuous DM1 management monitoring. This investigation concentrates on IoMT-based methodologies for the unbroken observation of DM1 management, thereby enabling comprehensive characterization of diabetic individuals. Integrating machine learning techniques with wearable technology may yield dependable models for forecasting short-term blood glucose concentrations. The objective of this research is to devise precise person-specific short-term prediction models, utilizing an array of features. To accomplish this, inventive modeling strategies were employed on an extensive dataset comprising glycaemia-related biological attributes gathered from a large-scale passive monitoring initiative involving 40 DM1 patients. The models produced via the Random Forest approach can predict glucose levels within a 30-minute horizon with an average error of 18.60 mg/dL for six-hour data, and 26.21 mg/dL for a 45-minute prediction horizon. These findings have also been corroborated with data from 10 Type 2 DM patients as a proof of concept, thereby demonstrating the potential of IoMT-based methodologies for continuous DM monitoring and management. The integration of innovative biological signal sensors and the application of transformative trends in ICT can offer a novel perspective on DM treatment, ensuring precise and secure glucose level management.

Three Days Compared to One Day Per Week of Self-Monitoring of Blood Glucose in Mild Gestational Diabetes: A Randomized Trial.

Background: The International Diabetes Federation estimates that 16.2% of livebirths in 2017 were affected by hyperglycemia in pregnancy, with 85.1% due to gestational diabetes mellitus (GDM). Daily blood glucose monitoring compared with alternate day testing in mild GDM is associated with similar pregnancy outcomes. Data are sparse on the ideal frequency for self-monitoring of blood glucose (SMBG) in mild GDM for glycemic control. A higher HbA1c at late pregnancy is associated with adverse pregnancy outcomes. We sought to evaluate three days compared to one day per week of four-point self-monitoring of blood glucose (SMBG) in gestational diabetes mellitus (GDM) controlled by lifestyle changes for glycemic control. Methods: This randomized trial was conducted from February–December 2018. A total of 106 women with lifestyle-controlled GDM were randomized to three days (SMBG3) or one day (SMBG1) per week of four-point (fasting and two-hours post-meal) SMBG. The primary outcome was the change in the HbA1c level at recruitment and 36-weeks gestation within and across trial arms. The student t-test was used for between-arm analyses and a paired t-test for within-arm analyses. Results: The HbA1c level through pregnancy increased significantly in both trial arms: mean increase of 0.21% ± 0.26%, p < 0.001 (SMBG3), and 0.19% ± 0.24%, p < 0.001 (SMBG1), but the 0.02% difference across trial arms was not significant (p = 0.79). Maternal weight gain (3.1 ± 2.1 kg vs. 3.3 ± 3.0 kg, p = 0.72), cesarean delivery (24/52 (48%) vs. 23/53 (43%), RR 1.06, 95% CI: 0.69–1.62, p = 0.77), neonatal birthweight (3.1 ± 0.4 kg vs. 3.0 ± 0.4 kg, p = 0.53) and neonatal intensive care unit admission (4/52 (8%) vs. 3/53 (6%), RR 1.36, 95% CI: 0.32–5.78, p = 0.68) were not significantly different for SMBG3 vs. SMBG1, respectively. Other maternal and neonatal secondary outcomes were not significantly different. Conclusion: In mild GDM, three days compared to one day per week showed a similar HbA1c levels change at 36-weeks gestation. Maternal and neonatal outcomes were also not significantly different. Less frequent monitoring of SMBG as a standard of care in mild GDM deserves further study and consideration.

Wearable transdermal microneedle patch based on photonic crystal hydrogel for glucose monitoring

Daily blood glucose monitoring is the cornerstone of diabetes management. Research efforts have been made on developing non-invasive or minimally invasive point-of-care testing system that can minimize the inconvenience of such daily test bringing to diabetes. Hereby, we develop a wearable and portable microneedle based biosensor for in situ glucose detection in an enzyme free and minimally invasive way. The photonic hydrogel film integrated inside the microneedle platform is functionalized with phenylboronic acid and displays glucose responsiveness. Presence of glucose in the chemical matrix of interstitial fluids can be distinguished with naked-eyes via the color changes of the hydrogel film. Quantification of glucose is achieved by analyzing color of hydrogel film with the facilitation of a mobile phone; thereby fast and direct diagnosis is enabled. Extraction of interstitial fluids and sensing of glucose within the psychological range was successfully demonstrated on porcine skin as human skin model. The developed microneedle platform provides a promising tool for detecting other health related analytes in an enzyme-free way with minimal invasiveness.

Profiles of Depressive Symptoms and Diabetes Distress in Preadolescents With Type 1 Diabetes

ObjectivesDiabetes distress and depressive symptoms are common psychosocial concerns for people with diabetes. These are related, yet distinct, mood states, which have each been related to diabetes management and glycated hemoglobin (A1C) among adolescents and adults with diabetes. However, they have not been examined concurrently in preadolescents with type 1 diabetes. Understanding the overlaps and distinctions between diabetes distress and depressive symptoms in youth would help guide decisions about psychosocial screening in diabetes clinical practice. In this study, we aimed to categorize preadolescents based on clinical cutoffs of concurrently administered measures of depressive symptoms and diabetes distress, and identify clinical and demographic characteristics of each group. MethodsOne hundred eighty youth (age range, 9 to 13 years; age [mean ± standard deviation], 11.3±1.3 years; 55% female; 56% Caucasian; mean A1C, 8.4±1.6% [68 mmol/mol]) completed measures of diabetes distress, depressive symptoms and quality of life. Daily blood glucose monitoring frequency was calculated from meter download. A1C values were obtained from electronic medical records. ResultsDepressive symptoms and diabetes distress each significantly correlated with A1C and quality of life. Although most (69%) participants had no clinically significant elevations in either diabetes distress or depressive symptoms, 14% had elevated depressive symptoms only and 17% had elevated distress without concurrent elevated depressive symptoms. Groups differed based on A1C, quality of life and insurance status. ConclusionsRoutine assessment of both depressive symptoms and diabetes distress may help to identify preadolescents with type 1 diabetes who require psychosocial support.

204-OR: Advancing Our Understanding of the Relationships between Diabetes Distress and Depressive Symptoms with Biobehavioral Variables in Adolescents with Diabetes

In adolescents with diabetes, associations of depressive symptoms and diabetes distress (DD) with self-care behaviors and glycemic control vary considerably across studies, yet in adults, DD is a stronger predictor than depressive symptoms. This secondary data analysis compared the strength of the association of DD and depressive symptoms on bio-behavioral (HbA1c and average daily blood glucose monitoring checks [BGM]) and perceived global health among adolescents with diabetes. Results: Data from 119 adolescents (75% T1D; diabetes duration of 4.8±4.5 years; HbA1c 8.7 ±2.3%; 62% female; mean age of 15.8±2.1 years; 36% Hispanic, 31% white) screened in clinic were analyzed. Teens completed the 2-item DD Scale (DDS2), the PHQ-9, and PROMIS Pediatric Global Health (PGH). Demographics, HbA1c, and BGM were obtained from medical chart review. Of the 119, 6% had severe depression (PHQ &amp;gt;10) and 22% had moderate to severe DD. DD was significantly correlated with HbA1c and BGM (r=.27, -.32;p=.004, .002; respectively); and both DD and PHQ were significantly correlated with the PGH (r=.43, -.57;ps&amp;lt;.001; respectively). In the regression models that included both DD and PHQ along with demographic and clinical covariates, DD was a significant predictor of HbA1c (ß= .31, partial r=.27, p=.004) and BGM (ß= -.24, partial r=-.23, p=.03). PHQ was not a significant predictor of either, but was a significant predictor of PGH (ß=-.6, partial r=-.47, p&amp;lt;.001). Type of diabetes was not a significant covariate. Conclusion: DD had stronger associations with diabetes biobehavioral variables than depressive symptoms. Considering the outcomes are diabetes-specific, this is not surprising. However, it shows that simply screening for depression may miss an important aspect of the psychosocial health of adolescents with diabetes. Appropriate intervention should follow positive screens of DD to improve adolescents’ diabetes-related variables. Disclosure H. Abujaradeh: None. J.J. Wong: None. K.K. Hood: Consultant; Self; Lilly Diabetes. Research Support; Self; Dexcom, Inc. Speaker's Bureau; Self; Johnson &amp; Johnson Diabetes Institute.

Factors associated with disordered eating behaviours in adolescents with Type 1 diabetes.

To assess the occurrence of disordered eating behaviours in teenagers with Type 1 diabetes and to compare characteristics according to level of disordered eating behaviours. In this cross-sectional study, we collected adolescents' demographic and diabetes management data by parent-youth interview and chart review. Teenagers completed psychosocial surveys, including the Diabetes Eating Problem Survey-Revised (DEPS-R), a diabetes-specific measure of disordered eating behaviours. We categorized teenagers according to level of disordered eating behaviours: low, DEPS-R score <10; moderate, DEPS-R score 10-19; and high, DEPS-R score ≥20. The 178 teenagers (48% girls) were aged 14.9±1.3 years, with diabetes duration of 7.4±3.7 years. Most (59%) had low, 26% had moderate, and 15% had high levels of disordered eating behaviours. Several biomedical and psychosocial characteristics differed by level of disordered eating behaviours. There were more girls in the moderate (62%) and high (65%) than in the low level of disordered eating behaviours group (37%; P=0.003) and more obese teenagers in the moderate (13%) and high (27%) groups than in the low group (4%; P=0.0003). Frequency of daily blood glucose monitoring decreased (P=0.0006) and HbA1c level increased (P=0.01) with greater level of disordered eating behaviours. A greater level of disordered eating behaviours was also associated with poorer treatment adherence, more negative affect regarding blood glucose monitoring, poorer quality of life, and more depressive symptoms (all P<0.0001), along with more diabetes-specific family conflict (P=0.01). Identifying teenagers with Type 1 diabetes who have moderate and high levels of disordered eating behaviours may prevent progression to eating disorders and substantial morbidity by directing support and intervention efforts to those in need.

Effects of a Web-Based Self-Management Program on the Behavior and Blood Glucose Levels of Women with Gestational Diabetes Mellitus.

Background:Women diagnosed with gestational diabetes mellitus suffer from anxiety and depression, which make controlling blood glucose levels difficult.Introduction:This quasi-experimental study uses a nonequivalent control group pretest-posttest design to investigate the effects of a web-based self-care program on self-care behaviors, anxiety, depression, and blood glucose in patients with gestational diabetes mellitus.Methods:The subjects of the study were outpatients being treated in the Department of Endocrinology at Hospital G, located in Seoul near University C, from July 15, 2015, to December 31, 2016. The experimental and control groups contained 22 participants each. The experimental group received a 12-week web-based program and one session of nutrition education; the control group received nutrition education. Using the SPSS program, pre-post changes in blood glucose, anxiety, depression, and self-care behaviors were examined between the two groups by a repeated-measures ANOVA.Results:After the 12 weeks intervention, self-care behaviors increased in both groups, and blood glucose monitoring increased in the experimental group (p = 0.001). Anxiety in the experimental group decreased by 5.1 points but increased by 1.0 point in the control group (p = 0.048). Depression increased in both groups. Glycated hemoglobin (HbA1C) levels decreased in the experimental group but increased in the control group (p = 0.001).Discussion:In addition to reducing HbA1C and anxiety, the web-based self-care program was effective in increasing the frequency of daily blood glucose monitoring in patients with gestational diabetes mellitus.Conclusions:This study will be helpful in informing an anxiety intervention program, blood glucose control, and healthy self-care behaviors in women with gestational diabetes mellitus.

Sleep habits in adolescents with type 1 diabetes: Variability in sleep duration linked with glycemic control.

To describe adolescents' sleep on school and weekend nights using multiple methods and to examine the links between sleep variability, quality, and duration with diabetes indicators. Adolescents with type 1 diabetes (N = 65, mean age = 15.0, 52.3% female, mean HbA1c = 8.9% or 74 mmol/mol) wore an actigraph and kept daily diaries recording sleep, activities, and blood glucose monitoring (BGM) habits for at least 7 days. Average daily BGM and blood glucose (BG) levels were obtained through glucometer downloads. HbA1c was obtained as part of clinic visits. Adolescents completed a sleep quality questionnaire (Pittsburgh sleep quality index [PSQI]), and adolescents and caregivers reported on adherence to diabetes treatment. Adolescents reported a mean PSQI global score of 5.37, which is above the clinical cutoff for poor sleep quality. Actigraphy data revealed that mean adolescent total sleep time was 6:54 (h:min), and participants slept more on weekend nights than on school nights (P < .001). Additionally, variability in sleep duration was significantly related to HbA1c, frequency of BGM, and average BG. Total sleep time and self-reported sleep quality were not significantly associated with adherence or glycemic control. Few adolescents with type 1 diabetes met recommendations for sleep duration, and many reported poor sleep quality. We identified significant associations between variability in sleep duration with poorer glycemic control and less frequent BGM, supporting the need to consider sleep patterns as a modifiable factor that may affect adherence and glycemic control.

Association between depressive symptoms and dietary intake in patients with type 1 diabetes

AimsDepressive mood negatively affects self-care practices, and thereby increases the risk of long-term complications. Not much is known about the association between depressive symptoms and dietary intake in patients with type 1 diabetes, a population with high risk of cardiovascular disease. MethodsSubjects (n = 976, 41% men, age 48 ± 14 years) were participants in the Finnish Diabetic Nephropathy Study. Depressive symptomatology was assessed with the Beck Depression Inventory (BDI). Dietary patterns were derived from food frequency questionnaire-entries by exploratory factor analysis. Energy and macronutrient intakes were calculated from food records. In the same record, participants also reported the results of their daily blood glucose monitoring. Associations between BDI score and self-care variables were analysed using generalized linear regression. For macronutrients, a substitution model was applied. ResultsTwo dietary patterns (“Fish and vegetables”, and “Traditional”) negatively associated with the BDI score. Instead, an increase in the “Sweet” pattern score was positively associated with depressive symptomatology. Of the macronutrients, favouring protein over carbohydrates or fats associated with lower depression scores. Higher blood glucose self-monitoring frequency and higher variability of the measurements were positively associated with the BDI score. However, no association was observed between depressive symptoms and the mean of the blood glucose measurements. ConclusionsDepressive symptoms are reflected in the dietary intake and the self-monitoring of blood glucose, in type 1 diabetes. Whether depression, via compromised self-care practices, negatively affect long-term outcomes in this patient group has to be the subject of future studies.

Drug-Induced Falsely Low A1C: Report of a Case Series From a Diabetes Clinic.

A1C is a universally used blood test to assess glycemic control during the previous 2–3 months in patients with diabetes (1). It is used to monitor long-term glycemic control and assess patients’ response to therapy and is a quality-assessment tool for diabetes care in the United Kingdom and throughout the world (2). Hence, it is important that any condition that can affect the true value of A1C be considered in clinical practice. We report here a case series of patients attending our adult secondary care diabetes clinic, all of whom were noted to have considerably lower A1C levels than what would be expected from their daily blood glucose monitoring results. The cause for the falsely low A1C in each case was found to be drug-induced hemolysis, most commonly due to sulfasalazine use. When A1C is inaccurate, fructosamine levels can be another way of monitoring average glycemic control, particularly in patients taking drugs that cause drug-induced hemolysis (1,3). In some patients, A1C can be falsely low. Any condition that shortens the life span of red blood cells, and therefore the length of time hemoglobin is exposed to glucose in the bloodstream, can falsely lower A1C. Examples include hemolytic anemias, hemoglobinopathies, splenomegaly, blood loss, blood transfusions, chronic liver or kidney disease, and some drugs (4,5). Drugs that cause subtle hemolysis without anemia may interfere with the accuracy of A1C measurement (6). Reported examples of such drugs include dapsone, sulfasalazine, ribavirin, and antiretroviral drugs (4). There are few data from randomized, controlled studies on the subject of drug-induced hemolysis causing falsely low A1C levels; thus, there is little information about the prevalence of this phenomenon. There are, however, several case reports. The first, reported in 1979 from Kesson et al. (6), described a case of dapsone-induced hemolysis …

Factors Associated With Diabetes-Specific Health-Related Quality of Life in Youth With Type 1 Diabetes: The Global TEENs Study.

Our objective was to characterize diabetes-specific health-related quality of life (D-HRQOL) in a global sample of youth and young adults with type 1 diabetes (T1D) and to identify the main factors associated with quality of life. The TEENs study was an international, cross-sectional study of youth, 8-25 years of age, with T1D. Participants (N = 5,887) were seen in clinical sites in 20 countries across 5 continents enrolled for 3 predetermined age groups: 8-12, 13-18, and 19-25 years of age. To assess D-HRQOL, participants completed the PedsQL Diabetes Module 3.0 and were interviewed about family-related factors. Specifics about treatment regimen and self-management behaviors were collected from medical records. Across all age groups, females reported significantly lower D-HRQOL than did males. The 19-25-year age group reported the lowest D-HRQOL. Multivariate linear regression analyses revealed that D-HRQOL was significantly related to HbA1c; the lower the HbA1c, the better the D-HRQOL. Three diabetes-management behaviors were significantly related to better D-HRQOL: advanced methods used to measure food intake; more frequent daily blood glucose monitoring; and more days per week that youth had ≥30 min of physical activity. In all three age groups, the lower the HbA1c, the better the D-HRQOL, underscoring the strong association between better D-HRQOL and optimal glycemic control in a global sample of youth and young adults. Three diabetes-management behaviors were also related to optimal glycemic control, which represent potentially modifiable factors for clinical interventions to improve D-HRQOL as well as glycemic control.

Disparities in recommended preventive care usage among persons living with diabetes in the Appalachian region

ObjectiveTo examine disparities in the receipt of preventive care recommended by the American Diabetes Association (ADA) between Appalachian and non-Appalachian counties and within Appalachian counties.Research design and methodsBehavioral Risk Factor...

An Adult Health Care-Based Pediatric to Adult Transition Program for Emerging Adults With Type 1 Diabetes.

Purpose The purpose of the study was to evaluate an adult health care program model for emerging adults with type 1 diabetes transitioning from pediatric to adult care. Methods Evaluation of the Pediatric to Adult Diabetes Transition Clinic at the University of Pennsylvania included a cohort of 72 emerging adults with type 1 diabetes, ages 18 to 25 years. Data were extracted from transfer summaries and the electronic medical record, including sociodemographic, clinical, and follow-up characteristics. Pre- and postprogram assessment at 6 months included mean daily blood glucose monitoring frequency (BGMF) and glycemic control (A1C). Paired t tests were used to examine change in outcomes from baseline to 6 months, and multiple linear regression was utilized to adjust outcomes for baseline A1C or BGMF, sex, diabetes duration, race, and insulin regimen. Open-ended survey responses were used to assess acceptability amongst participants. Results From baseline to 6 months, mean A1C decreased by 0.7% (8 mmol/mol), and BGMF increased by 1 check per day. Eighty-eight percent of participants attended ≥2 visits in 6 months, and the program was rated highly by participants and providers (pediatric and adult). Conclusions This study highlights the promise of an adult health care program model for pediatric to adult diabetes transition.

Frequency of mealtime insulin bolus predicts glycated hemoglobin in youths with type 1 diabetes.

Within pediatric diabetes management, two electronic measures of adherence exist: frequency of daily blood glucose monitoring (BGM) and the BOLUS score, a measure of frequency of mealtime insulin bolusing. Past research has demonstrated that the BOLUS score is superior to daily BGM in predicting youths' glycated hemoglobin (HbA1c) in a cross-sectional study. We present data comparing the two adherence measures in predicting HbA1c using a prospective, longitudinal design. Blood glucose meter data and insulin pump records were collected from a clinical database of 175 youths with type 1 diabetes (mean age, 11.7 ± 3.6 years at baseline). Youths' HbA1c levels occurring at the download time and at 3, 6, 9, and 12 months post-downloads were also collected. We calculated youths' mean BGM and BOLUS score using a standardized protocol. Intraclass correlations (ICCs) revealed significant absolute equivalence between youths' predicted HbA1c values using BOLUS and BGM scores and future actual HbA1c values up to 12 months post-download. However, the ICCs of BOLUS scores with future HbA1c values were consistently higher than those of the BGM scores. Also, the predictions of the BOLUS scores were significantly more accurate (P ≤ 0.002) than those of the BGM scores based on the root mean squared error of predictions. In a prospective, longitudinal design, youths' BOLUS scores were superior to youths' daily BGM in predicting future values of HbA1c. Calculating a BOLUS score versus BGM can help researchers and clinicians achieve a better prediction of youths' HbA1c.

Children’s and adolescent’s self - assessment of metabolic control versus professional judgment: a cross-sectional retrospective and prospective cohort study

BackgroundMorbidity and mortality in T1DM depend on metabolic control, which is assessed by HbA1c measurements every 3–4 months. Patients’ self-perception of glycemic control depends on daily blood glucose monitoring. Little is known about the congruence of patients’ and professionals’ perception of metabolic control in T1DM.ObjectiveTo assess the actual patients’ self-perception and objective assessment (HbA1c) of metabolic control in T1DM children and adolescents and to investigate the possible factors involved in any difference.MethodsPatients with T1DM aged 8 – 18 years were recruited in a cross-sectional, retrospective and prospective cohort study. Data collection consisted of clinical details, measured HbA1c, self-monitored blood glucose values and questionnaires assessing self and professionals’ judgment of metabolic control.Results91 patients participated. Mean HbA1c was 8.03%. HbA1c was higher in patients with a diabetes duration > 2 years (p = 0.025) and in patients of lower socioeconomic level (p = 0.032). No significant correlation was found for self-perception of metabolic control in well and poorly controlled patients. We found a trend towards false-positive memory of the last HbA1c in patients with a HbA1c > 8.5% (p = 0.069) but no difference in patients’ knowledge on target HbA1c between well and poorly controlled patients.ConclusionsT1DM patients are aware of a target HbA1c representing good metabolic control. Ill controlled patients appear to have a poorer recollection of their HbA1c. Self-perception of actual metabolic control is similar in well and poorly controlled T1DM children and adolescents. Therefore, professionals should pay special attention that ill controlled T1DM patients perceive their HbA1c correctly.

Acute hepatitis B outbreaks in 2 skilled nursing facilities and possible sources of transmission: North Carolina, 2009-2010.

Acute hepatitis B virus (HBV) infections have been reported in long-term care facilities (LTCFs), primarily associated with infection control breaks during assisted blood glucose monitoring. We investigated HBV outbreaks that occurred in separate skilled nursing facilities (SNFs) to determine factors associated with transmission. Outbreak investigation with case-control studies. Two SNFs (facilities A and B) in Durham, North Carolina, during 2009-2010. Residents with acute HBV infection and controls randomly selected from HBV-susceptible residents during the outbreak period. After initial cases were identified, screening was offered to all residents, with repeat testing 3 months later for HBV-susceptible residents. Molecular testing was performed to assess viral relatedness. Infection control practices were observed. Case-control studies were conducted to evaluate associations between exposures and acute HBV infection in each facility. Six acute HBV cases were identified in each SNF. Viral phylogenetic analysis revealed a high degree of HBV relatedness within, but not between, facilities. No evaluated exposures were significantly associated with acute HBV infection in facility A; those associated with infection in facility B (all odds ratios >20) included injections, hospital or emergency room visits, and daily blood glucose monitoring. Observations revealed absence of trained infection control staff at facility A and suboptimal hand hygiene practices during blood glucose monitoring and insulin injections at facility B. These outbreaks underscore the vulnerability of LTCF residents to acute HBV infection, the importance of surveillance and prompt investigation of incident cases, and the need for improved infection control education to prevent transmission.

Frequency of Mealtime Insulin Bolus as a Proxy Measure of Adherence for Children and Youths with Type 1 Diabetes Mellitus

Electronic measures of adherence can be superior to patient report. In type 1 diabetes, frequency of blood glucose monitoring (BGM), as measured by patients' home blood glucose meters, has already been identified as a valid proxy of adherence. We present methodology to calculate adherence using insulin pump records and evaluate the reliability and validity of this methodology. Blood glucose meter data, insulin pump records, and corresponding hemoglobin A1c (HbA1c) levels were randomly gathered from clinical and research databases for 100 children and youths (referred to hereafter as youths) with type 1 diabetes (mean±SD age, 12.7±4.6 years). Youths' mean frequency of daily BGM was calculated. Additionally, we calculated a mean mealtime insulin bolus score (BOLUS): youths received 1 point each for a bolus between 0600 and 1000 h, 1100 and 1500 h, and 1600 and 2200 h (maximum of 1 point/meal or 3 points/day). Simple correlations between youths' HbA1c level, age, frequency of BGM, and insulin BOLUS scores were all significant. Partial correlations and multiple regression analyses revealed that insulin BOLUS scores better explain variations in HbA1c levels than the electronically recorded frequency of daily blood glucose measures. Our procedures for calculating insulin BOLUS scores using insulin pump records demonstrate better concurrent validity with youths' HbA1c levels than that of the frequency of BGM with youths' HbA1c levels. Our analyses have shown that insulin bolus scoring was superior to the frequency of BGM in predicting youths' HbA1c levels.

Noninvasive blood glucose monitoring during oral intake of different sugars with optical coherence tomography in human subjects

The potential of OCT applied to noninvasive blood glucose monitoring has attracted significant efforts. In this work we investigated the feasibility of OCT in monitoring blood glucose during oral intake of different sugars in humans. Five groups of experiments were performed, in which different sugars were used. The OCT signal slope (OCTSS) changed with variation of blood glucose concentration (BGC). A good correlation between OCTSS and BGC was observed in these experiments. The averaged correlation coefficients R between OCTSS and BGC are 0.900, 0.836, 0.895 and 0.884, corresponding to oral administration of glucose, fructose, sucrose and mixed sugar, respectively. Our studies demonstrated the capability and accuracy of the OCT system in monitoring BGC noninvasively and it could become a powerful tool in daily blood glucose monitoring for patients.