Challenging the 50-50 rule for the basal-bolus insulin ratio in patients with type 2 diabetes who maintain stable glycaemic control.

BACKGROUND: For patients using basal-bolus insulin therapy, it is widespread clinical practice to aim for a 50-50 ratio between basal and total daily bolus. However, this practice was based on a small study of individuals without diabetes. To assess the rule in real-world practice, we retrospectively analyzed patients on basal-bolus therapy that was adjusted at least weekly by an artificial intelligence-driven titration within the d-Nav® Insulin Management Technology. MATERIALS AND METHODS: We obtained de-identified data from the Diabetes Centre of Ulster Hospital for patients with four inclusion criteria: type 2 Diabetes (T2D), on d-Nav >6 months, on basal-bolus insulin therapy >80% of the time (based on insulin analogs), and no gap in data >3 months. RESULTS: We assembled a cohort of 306 patients, followed by the d-Nav service for 3.4 ± 1.8 years (mean ± SD), corresponding to about 180 autonomous insulin dose titrations and about 5000 autonomous individual dose recommendations per patient. After an initial run-in period, mean glycated hemoglobin (HbA1c) values in the cohort were maintained close to 7%. Surprisingly, in just over three-quarters of the cohort, the average basal insulin fraction was <50%; in half of the cohort average basal insulin fraction <41.2%; and in one-quarter the basal insulin fraction was <33.6%. Further, the basal insulin fraction did not remain static over time. In half of the patients, the basal insulin fraction varied by ≥1.9×; and, in 25% of the patients, ≥2.5×. CONCLUSION: Our data show that a 50-50 ratio of basal-to-bolus insulin does not generally apply to patients with T2D who successfully maintain stable glycemia. Therefore, the 50-50 ratio should not serve as an ongoing treatment guide. Moreover, our results emphasize the importance of at least weekly insulin titrations.

Adherence to metformin in adults with type 2 diabetes: a combined method approach.

BACKGROUND: Medication adherence, one of the most important aspects in the process of optimal medicines use, is unfortunately still a major challenge in modern healthcare, and further research is required into how adherence can be assessed and optimised. The aim of this study was to use a combined method approach of self-report and dried blood spot (DBS) sampling coupled with population pharmacokinetic (PopPK) modelling, to assess adherence to metformin in adult patients with type 2 diabetes. Further aims were to assess metformin exposure levels in patients, determine factors associated with non-adherence with prescribed metformin, and to explore the relationship between adherence and therapeutic outcomes. METHODS: A combined method approach was used to evaluate metformin adherence in patients with type 2 diabetes who had been prescribed metformin for a minimum period of 6 months. Patients were recruited from consultant-led diabetic outpatient clinics at three hospitals in Northern Ireland, UK. Data collection involved self-reported questionnaires [Medication Adherence Report Scale (MARS), Beliefs about Medicines Questionnaire and Centre for Epidemiologic Studies Depression Scale], direct measurement of metformin concentration in DBS samples, and researcher-led patient interviews. The DBS sampling approach was coupled with population pharmacokinetic (PopPK) modelling, which took account of patient characteristics, metformin dosage and type of formulation prescribed (immediate or sustained release). RESULTS: The proportion of patients considered to be adherent to their prescribed metformin, derived from self-reported MARS scores and metformin concentration in DBS samples, was 61.2% (74 out of 121 patients). The majority (n = 103, 85.1%) of recruited patients had metformin exposure levels that fell within the therapeutic range. However, 17 patients (14.1%) had low exposure to metformin and one patient (0.8%) had undetectable metformin level in their blood sample (non-exposure). Metformin self-administration and use of a purchased adherence pill box significantly increased the probability of a patient being classified as adherent based on logistic regression analysis. Both HbA1c and random glucose levels (representing poor glycaemic control) in the present research were, however, not statistically linked to non-adherence to metformin (P > 0.05). CONCLUSIONS: A significant proportion of participating patients were not fully adherent with their therapy. DBS sampling together with the use of a published PopPK model was a useful, novel, direct, objective approach to estimate levels of adherence in adult patients with type 2 diabetes (61.2%).

Exploring patient information needs in type 2 diabetes: A cross sectional study of questions.

This study set out to analyze questions about type 2 diabetes mellitus (T2DM) from patients and the public. The aim was to better understand people's information needs by starting with what they do not know, discovered through their own questions, rather than starting with what we know about T2DM and subsequently finding ways to communicate that information to people affected by or at risk of the disease. One hundred and sixty-four questions were collected from 120 patients attending outpatient diabetes clinics and 300 questions from 100 members of the public through the Amazon Mechanical Turk crowdsourcing platform. Twenty-three general and diabetes-specific topics and five phases of disease progression were identified; these were used to manually categorize the questions. Analyses were performed to determine which topics, if any, were significant predictors of a question's being asked by a patient or the public, and similarly for questions from a woman or a man. Further analysis identified the individual topics that were assigned significantly more often to the crowdsourced or clinic questions. These were Causes (CI: [-0.07, -0.03], p < .001), Risk Factors ([-0.08, -0.03], p < .001), Prevention ([-0.06, -0.02], p < .001), Diagnosis ([-0.05, -0.02], p < .001), and Distribution of a Disease in a Population ([-0.05,-0.01], p = .0016) for the crowdsourced questions and Treatment ([0.03, 0.01], p = .0019), Disease Complications ([0.02, 0.07], p < .001), and Psychosocial ([0.05, 0.1], p < .001) for the clinic questions. No highly significant gender-specific topics emerged in our study, but questions about Weight were more likely to come from women and Psychosocial questions from men. There were significantly more crowdsourced questions about the time Prior to any Diagnosis ([(-0.11, -0.04], p = .0013) and significantly more clinic questions about Health Maintenance and Prevention after diagnosis ([0.07. 0.17], p < .001). A descriptive analysis pointed to the value provided by the specificity of questions, their potential to disclose emotions behind questions, and the as-yet unrecognized information needs they can reveal. Large-scale collection of questions from patients across the spectrum of T2DM progression and from the public-a significant percentage of whom are likely to be as yet undiagnosed-is expected to yield further valuable insights.

Temporary Reductions in Insulin Requirements Are Associated with Hypoglycemia in Type 2 Diabetes.

Background: In patients with type 2 diabetes, insulin therapy necessitates regular and frequent dosage titration to overcome variations in insulin requirements. The goal of this study was to evaluate changes in insulin requirements, using data from a technology-based insulin-titration service. Methods: To keep glycemia stable, the service adjusts and records insulin dosage at least weekly. Therefore, insulin dosage closely tracks insulin requirement. Events of considerable and persistent decrease in insulin requirements were identified by reductions in total daily dose (TDD) of insulin ≥25%. Periods ended when a persistent increase in TDD of insulin has started. The average frequency of hypoglycemia was expressed as any glucose reading <54 mg/dL (both inside or outside periods of decrease in insulin dosage) divided by the total number of months for each patient. Results: Patients (n = 246) were followed for 2.8 ± 0.9 years. Reductions of TDD of insulin were experienced by 70.3% of the patients, occurred 0.8 ± 0.5 times per year, lasted 10.0 ± 7.7 weeks, and insulin requirements declined by 39.9% ± 12.6%. The frequency of hypoglycemia (<54 mg/dL) was low, at 0.5 ± 0.6 per month, and the difference in frequencies in biphasic/premixed and basal-bolus insulin regimens was not statistically significant. Hypoglycemia was 6.5 times more prevalent during reductions in TDD of insulin. Conclusions: Sizeable changes in insulin requirements occur over time, which demand persistent and frequent titration to preserve treatment safety.

Impact of an educational DVD on anxiety and glycaemic control in women diagnosed with gestational diabetes mellitus (GDM): A randomised controlled trial.

AIMS: The diagnosis of gestational diabetes mellitus (GDM) during pregnancy can lead to anxiety. This study evaluated the impact of an innovative patient-centred educational DVD on anxiety and glycaemic control in women newly diagnosed with GDM. METHODS: 150 multi-ethnic women, aged 19-44years, from three UK hospitals were randomised to either usual care plus DVD (DVD group, n=77) or usual care alone (control group, n=73) at GDM diagnosis. Primary outcomes were anxiety (State-Trait Anxiety Inventory) and mean 1-h postprandial capillary self-monitored blood glucose for all meals, on day prior to follow-up. RESULTS: No significant difference between the DVD and control group were reported, for anxiety (37.7±11.7 vs 36.2±10.9; mean difference after adjustment for covariates (95% CI) 2.5 (-0.8, 5.9) or for mean 1-h postprandial glucose for all meals (6.9±0.9 vs 7.0±1.2mmol/L; -0.2 (-0.5, 0.2). However, the DVD group had significantly lower postprandial breakfast glucose compared to the control group (6.8±1.2 vs 7.4±1.9mmol/L; -0.5 (-1.1, -<0.1; p=0.04). CONCLUSIONS: The results in this trial did not highlight any differences between those who received the intervention and those who received usual care. It is possible that women already felt supported by their frequent attendance at specialist clinics for monitoring and advice. Healthcare professional and family support are key elements to empowering women with GDM and require further consideration in future interventions. Nonetheless, educational resources such as this will be beneficial to help support women given the current resource and time implications of the year on year rises in the incidence of gestational diabetes.

Soliciting and Responding to Patients' Questions about Diabetes Through Online Sources.

When patients cannot get answers from health professionals or retain the information given, increasingly they search online for answers, with limited success. Researchers from the United States, Ireland, and the United Kingdom explored this problem for patients with type 2 diabetes mellitus (T2DM). In 2014, patients attending an outpatient clinic (UK) were asked to submit questions about diabetes. Ten questions judged representative of different types of patient concerns were selected by the researchers and submitted to search engines within trusted and vetted websites in the United States, Ireland, and the United Kingdom. Two researchers independently assessed if answers could be found in the three top-ranked documents returned at each website. The 2014 search was repeated in June, 2016, examining the two top-ranked documents returned. One hundred and sixty-four questions were collected from 120 patients during 12 outpatient clinics. Most patients had T2DM (95%). Most questions were about diabetes (N = 155) with the remainder related to clinic operation (N = 9). Of the questions on diabetes, 152 were about T2DM. The 2014 assessment found no adequate answers to the questions in 90 documents (10 questions, 3 websites, 3 top documents). In the 2016 assessment, 1 document out of 60 (10 questions, 3 websites, 2 top documents) provided an adequate answer relating to 1 of the 10 questions. Available online sources of information do not provide answers to questions from patients with diabetes. Our results highlight the urgent need to develop novel ways of providing answers to patient questions about T2DM.

A novel approach to optimise glycaemic control in insulin users.

Insulin therapy has been available for almost a century. However, its success rate is still disappointing where the majority of users sustain harmfully elevated glycated haemoglobin (HbA1c) levels. The key element essential for effective and safe insulin therapy is frequent dosage titration to overcome constant variations in insulin requirements. In reality, dosage titration is done sporadically during clinic visits. A scalable solution to this problem is being reviewed. A diabetes nurses service improves glycaemic control without overburdening the health system. The service relies on a handheld device, which provides patients with an insulin dose recommendation for each injection while using the device to monitor glucose. Similar to the approach providers use during clinical encounters, the device analyses stored glucose trends and constantly titrates insulin dosage without care providers' supervision. In this report, we describe the logic behind the technology by providing examples from users.

Preconception counselling resource for women with diabetes.

Women with diabetes need to plan for pregnancy if they are to reduce their risk of poor pregnancy outcome. While care providers have focused on setting up specialist pre-pregnancy planning clinics to help women prepare for pregnancy, the majority of women do not attend, entering pregnancy unprepared. A major barrier to accessing this care, and a consequence of poor preconception counselling, is a lack of knowledge as to the need to plan and the reasons why. This project addressed an urgent need to raise awareness of the importance of planning for pregnancy among women with diabetes and among the healthcare professionals (HCPs) caring for them. Focus groups with the target groups informed the development of a preconception counselling resource for women with diabetes. Originally produced as a DVD (Diabetes UK funding), this resource has been embedded in routine care in Northern Ireland (NI) since 2010. A subsequent service evaluation of pregnancy planning indicators undertaken across all five antenatal-metabolic clinics in NI indicated that women who viewed the resource were better prepared for pregnancy. In order to increase the positive impact of the resource and to ensure longer term sustainability the DVD was converted to a website, http://www.womenwithdiabetes.net (Public Health Agency NI funding). The evaluation also highlighted that women with type 2 diabetes were a hard to reach group. As these women are often cared for outside of specialist clinics, it is pertinent that all HCPs caring for women with diabetes are aware of the importance of preconception counselling. Funding also supported the development of an e-learning continuing professional development (CPD) resource within the website. The e-learning resource has since been embedded into existing CPD programmes and is an important tool to ensure that all HCPs caring for women with diabetes are empowered to provide preconception counselling at every opportunity.

A retrospective audit of type 2 diabetes patients prescribed liraglutide in real-life clinical practice.

BACKGROUND: In phase 3 trials, the once-daily human glucagon-like peptide-1 analog liraglutide provided effective glycemic control with low rates of hypoglycemia, weight loss, and reduced systolic blood pressure (SBP) in patients with type 2 diabetes. Through a retrospective clinical audit, the authors aimed to assess the clinical effectiveness of liraglutide, from initiation to first hospital visit, when prescribed at a center in Northern Ireland. METHODS: Patients attending Ulster Hospital who were prescribed liraglutide (June 2009-September 2010) and assessed both at baseline and first post-initiation visit were included in the analysis. The primary endpoint was change in glycated hemoglobin (HbA1c) from baseline. Weight, blood pressure, and frequency of hypoglycemic events were also assessed. RESULTS: Data from 193 patients are reported (baseline HbA1c 9.0%, mean age 55.8 years, diabetes duration 8.8 years, 66.8% male). Average time to first visit after initiation was 13.5 weeks, at which point 174 patients (90.2%) were prescribed 1.2 mg liraglutide. Mean change in HbA1c from initiation to first visit was -0.9%, while mean body weight change was -2.4 kg and change in SBP was -2.0 mmHg. Transient gastrointestinal side effects were experienced by 11.9% of patients. The number of patients experiencing minor hypoglycemic events was low (5.7%) and no major events were reported. CONCLUSION: Data from clinical studies translate into clinical practice: liraglutide provided improved glycemic control after 13.5 weeks of treatment, accompanied by weight loss and low incidence of hypoglycemia.

Pregnancy planning and diabetes: a qualitative exploration of women's attitudes toward preconception care.

INTRODUCTION: Seeking preconception care is recognized as an important health behavior for women with preexisting diabetes. Yet many women with diabetes do not seek care or advice until after they are pregnant, and many enter pregnancy with suboptimal glycemic control. This study explored the attitudes about pregnancy and preconception care seeking in a group of nonpregnant women with type 1 diabetes mellitus. METHODS: In-depth semistructured interviews were completed with 14 nonpregnant women with type 1 diabetes. RESULTS: Analysis of the interview data revealed 4 main themes: 1) the emotional complexity of childbearing decisions, 2) preferences for information related to pregnancy, 3) the importance of being known by your health professional, and 4) frustrations with the medical model of care. DISCUSSION: These findings raise questions about how preconception care should be provided to women with diabetes and highlight the pivotal importance of supportive, familiar relationships between health professionals and women with diabetes in the provision of individualized care and advice. By improving the quality of relationships and communication between health care providers and patients, we will be better able to provide care and advice that is perceived as relevant to the individual, whatever her stage of family planning.

An intensive insulinotherapy mobile phone application built on artificial intelligence techniques.

BACKGROUND: Software to help control diabetes is currently an embryonic market with the main activity to date focused mainly on the development of noncomputerized solutions, such as cardboard calculators or computerized solutions that use "flat" computer models, which are applied to each person without taking into account their individual lifestyles. The development of true, mobile device-driven health applications has been hindered by the lack of tools available in the past and the sheer lack of mobile devices on the market. This has now changed, however, with the availability of pocket personal computer handsets. METHOD: This article describes a solution in the form of an intelligent neural network running on mobile devices, allowing people with diabetes access to it regardless of their location. Utilizing an easy to learn and use multipanel user interface, people with diabetes can run the software in real time via an easy to use graphical user interface. The neural network consists of four neurons. The first is glucose. If the user's current glucose level is within the target range, the glucose weight is then multiplied by zero. If the glucose level is high, then there will be a positive value multiplied to the weight, resulting in a positive amount of insulin to be injected. If the user's glucose level is low, then the weights will be multiplied by a negative value, resulting in a decrease in the overall insulin dose. RESULTS: A minifeasibility trial was carried out at a local hospital under a consultant endocrinologist in Belfast. The short study ran for 2 weeks with six patients. The main objectives were to investigate the user interface, test the remote sending of data over a 3G network to a centralized server at the university, and record patient data for further proofing of the neural network. We also received useful feedback regarding the user interface and the feasibility of handing real-world patients a new mobile phone. Results of this short trial confirmed to a large degree that our approach (which also can be known as intensive insulinotherapy) has value and perhaps that our neural network approach has implications for future intelligent insulin pumps. CONCLUSIONS: Currently, there is no software available to tell people with diabetes how much insulin to inject in accordance with their lifestyle and individual inputs, which leads to adjustments in software predictions on the amount of insulin to inject. We have taken initial steps to supplement the knowledge and skills of health care professionals in controlling insulin levels on a daily basis using a mobile device for people who are less able to manage their disease, especially children and young adults.

Feature selection and classification model construction on type 2 diabetic patients' data.

OBJECTIVE: Diabetes affects between 2% and 4% of the global population (up to 10% in the over 65 age group), and its avoidance and effective treatment are undoubtedly crucial public health and health economics issues in the 21st century. The aim of this research was to identify significant factors influencing diabetes control, by applying feature selection to a working patient management system to assist with ranking, classification and knowledge discovery. The classification models can be used to determine individuals in the population with poor diabetes control status based on physiological and examination factors. METHODS: The diabetic patients' information was collected by Ulster Community and Hospitals Trust (UCHT) from year 2000 to 2004 as part of clinical management. In order to discover key predictors and latent knowledge, data mining techniques were applied. To improve computational efficiency, a feature selection technique, feature selection via supervised model construction (FSSMC), an optimisation of ReliefF, was used to rank the important attributes affecting diabetic control. After selecting suitable features, three complementary classification techniques (Naïve Bayes, IB1 and C4.5) were applied to the data to predict how well the patients' condition was controlled. RESULTS: FSSMC identified patients' 'age', 'diagnosis duration', the need for 'insulin treatment', 'random blood glucose' measurement and 'diet treatment' as the most important factors influencing blood glucose control. Using the reduced features, a best predictive accuracy of 95% and sensitivity of 98% was achieved. The influence of factors, such as 'type of care' delivered, the use of 'home monitoring', and the importance of 'smoking' on outcome can contribute to domain knowledge in diabetes control. CONCLUSION: In the care of patients with diabetes, the more important factors identified: patients' 'age', 'diagnosis duration' and 'family history', are beyond the control of physicians. Treatment methods such as 'insulin', 'diet' and 'tablets' (a variety of oral medicines) may be controlled. However lifestyle indicators such as 'body mass index' and 'smoking status' are also important and may be controlled by the patient. This further underlines the need for public health education to aid awareness and prevention. More subtle data interactions need to be better understood and data mining can contribute to the clinical evidence base. The research confirms and to a lesser extent challenges current thinking. Whilst fully appreciating the requirement for clinical verification and interpretation, this work supports the use of data mining as an exploratory tool, particularly as the domain is suffering from a data explosion due to enhanced monitoring and the (potential) storage of this data in the electronic health record. FSSMC has proved a useful feature estimator for large data sets, where processing efficiency is an important factor.

Implementing autonomy in a diabetes management system.

We have developed a speech-based telemedicine system which enables patients with hypertension and type 2 diabetes mellitus to send frequent, home-monitored health data via the telephone to the point of care. The decision support module in the system was tested using data from a cohort of 10 patients generated over a two-year period. Results from the tests indicate that the system is effective in providing personalized feedback to the patient and in generating alerts for the clinical user. The work suggests that this method of care delivery is practical, informative, and may improve the efficiency of chronic health-care delivery by reducing costs and improving patient-physician communication between hospital visits.