Monitoring Of Blood Glucose Levels Research Articles

Diabetic Patients' Perspective About New Technologies Used in Managing Diabetes Mellitus in Saudi Arabia: A Cross-Sectional Study.

Background: Diabetes technologies are hardware, devices, and software that are used by people with diabetes to manage their condition, from lifestyle interventions to the monitoring of blood glucose levels. The development of these technologies is advancing, but their use in Saudi Arabia is under-researched.Objectives: To appraise the awareness of using new technological options in managing patients with diabetes and to assess the patients' satisfaction while using them.Method: This was an e-questionnaire-based cross-sectional study. The targeted population of the study was patients with diabetes in Saudi Arabia. A total of 452 respondents participated in a survey in the period between 2020 and 2021. The collected data were analyzed using descriptive statistical methods and Chi-squared tests.Results: Some 69% of participants were aware of the new technologies used in managing diabetes. There were discrepancies between the awareness and the use of new technologies. Several causes of non-use were identified; the main cause was high cost, as reported by more than half of non-users (53.2%). Other causes included non-availability and difficulty of use. Mobile health applications had the highest use rate (13.5%) among new technologies; patients reported using them mostly for blood glucose monitoring, physical activity, and nutritional programs. Patients' satisfaction was higher for modern technologies than for conventional methods.Conclusion: The results indicate that awareness of the new technologies used in managing diabetes was higher than their use. Moreover, the use of modern technologies improved the satisfaction of patients.

COVID-19 and Steroids- How well are we monitoring blood glucose levels?

Searchable abstracts of presentations at key conferences in endocrinology ISSN 1470-3947 (print) | ISSN 1479-6848 (online)

Tyrosine Hydroxylase‐Positive Neurons in the Hypothalamic Paraventricular Nucleus Modulate Blood Glucose Levels in Mice

Tyrosine hydroxylase (TH)‐positive neurons in the paraventricular nucleus of the hypothalamus (PVN), termed THPVN neurons, have emerged as key metabolic regulators. Recent studies showed that THPVN neurons are mostly Gamma‐aminobutyric acid (GABA)ergic and/or dopaminergic. Previous results from our laboratory indicate that THPVN neurons project to brainstem autonomic regulatory nuclei, such as nucleus tractus solitarius (NTS) and rostral ventrolateral medulla (RVLM). However, it is not known if THPVN neurons play a role in blood glucose regulation. We hypothesize that THPVN neurons are key regulators of blood glucose. To test our hypothesis, we used adeno‐associated virus serotype 2 (AAV2)‐mediated Cre‐recombinase driven by a rat TH promoter (AAV2‐TH‐Cre), in combination with chemogenetic approach (Designer Receptors Exclusively Activated by Designer Drugs, DREADD) to activate or inhibit THPVN neurons and continuously monitored blood glucose levels using telemetry system. hM3Dq‐LoxP (excitatory‐DREADD) and hM4Di‐LoxP (inhibitory‐DREADD) mice, 10‐14 weeks old, were bilaterally microinjected with AAV2‐TH‐Cre into the PVN. One month following AAV injection, mice were implanted with telemetry glucose transmitters (HD‐XG, DSI) to monitor blood glucose (BG) levels. To activate or inhibit THPVN neuronal activity, Clozapine‐N‐oxide (CNO, 1 mg/Kg) or vehicle were administered (i.p.) and BG was monitored by telemetry. To examine the functional role of THPVN neurons at baseline and avoid the influence of feeding on blood glucose levels, mice were fasted for 2 hours and fasting was maintained throughout the experiment. We found that activation of THPVN neurons by CNO in hM3Dq‐LoxP mice did not alter baseline blood glucose (n=5); on the other hand, inhibition of THPVN neurons by CNO in hM4Di‐LoxP mice increased baseline blood glucose levels compared with vehicle only in male mice (Male: ΔBG: 31.6 ± 8.6 mg/dL vs. 11.0 ± 6.7 mg/dL, n=4, p=0.03; Female: ΔBG: 11.0 ± 7.4 mg/dL vs. 7.3 ± 5.9 mg/dL, n=4, p=0.16). To study the functional role of THPVN neurons on whole body glucose handling, mice were fasted overnight and simultaneously injected with glucose (1 g/Kg) and either vehicle or CNO. We found that activation of THPVN neurons by CNO improved glucose clearance after glucose overload when compared with vehicle (AUC: 3133.0±109.0 vs. 6021.0±102.0, p<0.0001, n=3) in hM3Dq‐LoxP mice. In summary, our data suggest that THPVN neurons negatively regulate blood glucose possibly by their GABAergic input to downstream neural circuits. We conclude that THPVN neurons play a functional role in the regulation of glucose homeostasis; while the mechanisms remain to be determined.

Non-invasive Glucometer using Acetone Gas Sensor for Low Income Earners’ Diabetes Monitoring

A glucometer is an important device used to monitor blood glucose level of diabetes patients to prevent degenerated health conditions. The conventional glucometers are characterized by piercing of the sample site for patients’ testing. The invasive nature of these glucometers is painful to the patients and some patients are also scared at the sight of blood. To promote glucometer acceptance among patients, it is important to develop a non-invasive glucometer using acetone gas sensor with “exhaled breath” collected non-invasively as the sample for the glucometer. After the device development, exhaled breath sample of twenty subjects with age range of 20 to 55 years from a University were taken using the developed acetone sensor device. Prior to the exhaled breath sample collection, the blood glucose levels of the volunteered subjects were also determined using the conventional and proprietary invasive clinical method. To infer whether there is significant different between the mean of the results obtained from the conventional and the exhaled breath method, a t-test was carried out on the results and P values of 0.9860 and 0.9306 were obtained for fasting blood sugar and random blood sugar respectively, indicating no significant differences in the results obtained from the developed device when compared with the proprietary device. Hence, non-invasive glucometer using acetone gas sensor can be used to promote inexpensive personalized diabetes monitoring without inflicting pain on the patients. Promotion of this device could also reduce the expenses incurred on lancet and test strips, thus, making it suitable for low income earners.

A Personalized mHealth Monitoring System for Children and Adolescents with T1 Diabetes by Utilizing IoT Sensors and Assessing Physical Activities

The problem of diabetes mellitus is becoming alarming due to the increase in morbidity among children. Patients are undergoing vital insulin replacement therapy, the dose depends on the level of glucose in the blood. The glucose level prediction program, taking into account the impact of physical activity on the body, the use of mobile health capabilities will allow us to develop personalized tactics for a child patient and minimize the risks of a critical health condition. The target group of this study are children and adolescents with type 1 diabetes. This study provides an IoT based mHealth monitoring system, including sensors, medical bracelets, mobile devices with applications. The mobile healthcare application for personalized monitoring can implement the functions of more effectively targeting young users to support their own health and improve the quality of life. In addition to monitoring blood glucose levels, the effect of physical activity on the condition of patients is also taken into account. The use of the proposed method for calculating the probable change in the patient’s blood glucose level after the end of physical activity will allow the doctor to make individual recommendations for the diet before the start of physical activity and its intensity.

Physiological reconstruction of blood glucose level using CGMS-signals only

Patient with diabetes must regularly monitor blood glucose level. Drawing a blood sample is a painful and discomfort experience. Alternatively, the patient measures interstitial fluid glucose level with a sensor installed in subcutaneous tissue. Then, a model of glucose dynamics calculates blood glucose level from the sensor-measured, i.e., interstitial fluid glucose level of subcutaneous tissue. Interstitial fluid glucose level can significantly differ from blood glucose level. The sensor is either factory-calibrated, or the patient calibrates the sensor periodically by drawing blood samples, when glucose levels of both compartments are steady. In both cases, the sensor lifetime is limited up to 14 days. This is the present state of the art. With a physiological model, we would like to prolong the sensor lifetime with an adaptive approach, while requiring no additional blood sample. Prolonging sensor’s lifetime, while reducing the associated discomfort, would considerably improve patient’s quality of life. We demonstrate that it is possible to determine personalized model parameters from multiple CGMS-signals only, using an animal experiment with a hyperglycemic clamp. The experimenter injected separate glucose and insulin boluses to trigger rapid changes, on which we evaluated the ability to react to non-steady glucose levels in different compartments. With the proposed model, 70%, 80% and 95% of the calculated blood glucose levels had relative error less than or equal to 21.9%, 32.5% and 43.6% respectively. Without the model, accuracy of the sensor-estimated blood glucose level decreased to 39.4%, 49.9% and 99.0% relative errors. This confirms feasibility of the proposed method.

Analysis of Nursing Management Unstable Blood Glucose Levels in Type 2 Diabetes Mellitus Patients

Background: Diabetes Mellitus (DM) is a clinical syndrome of impaired metabolic secretion, insulin action, or both characterized by hyperglycemia. Various nursing problems can occur due to hyperglycemic conditions that are not handled properly. The instability of blood glucose levels is a major problem that occurs in uncontrolled DM patients. This condition can lead to various complications and complications so comprehensive treatment management is needed.
 Objectives: This study aims to explore and analyze the nursing management of unstable blood glucose levels in type 2 DM patients who were hospitalized.
 Methods: This study is a qualitative study using an exploratory case study method in diabetes mellitus patients type 2 who were hospitalized. The data obtained were processed and analyzed based on theories that explain the occurrence of the problem of instability in blood glucose levels and the nursing management carried out in patients with type 2 diabetes mellitus.
 Results: The results of this study indicate that the main problem in patients with type 2 diabetes mellitus is the instability of blood glucose levels which is characterized by hyperglycemia. Nursing management carried out is monitoring blood glucose level laboratory results, management of hyperglycemia, medication management, nutrition/diet management, treatment, and care education programs can reduce blood glucose levels.
 Conclusion: The problem of blood glucose instability is a priority problem in type 2 diabetes mellitus and comprehensive nursing management will determine the success of controlling blood glucose levels so that they are normal and stable.

The Behavior of Patients with Type 2 Diabetes Mellitus in Monitoring Blood Glucose Levels and Foot Care: A Cross-sectional, Community-Based Study

Hyperglycemia in patients with Diabetes Mellitus (DM) can lead to complications such as diabetic foot ulcers. Therefore, efforts are needed to prevent this chronic complication through proper foot care. This study aimed to determine the behavior of patients with type 2 diabetes mellitus (T2DM) in performing blood glucose monitoring and correct foot care. This study is a descriptive cross-sectional study, with a sample size of 125 patients with T2DM from the Community Health Center in Surabaya Indonesia. Data was collected with the use of a self-made questionnaire from May to October 2018. The variables of the study were patient characteristics, random blood glucose levels, blood glucose monitoring and foot care skills. The data analysis used was Spearman rho to determine the factors associated with foot care behaviors. Fifty-six percent (56%) of the participants have poor behavior on foot care, 36 % have moderate and only 7.2% have good. Factors that were significantly associated with foot care behavior were signs and symptoms (p = 0.023), blood glucose monitoring (p = .000), and random blood glucose levels (p = 0.040). The behaviors of patients with T2DM in blood glucose monitoring and foot care need to be improved to prevent complications from diabetic foot ulcers. Nurses must provide health education about the importance of regular foot care to patients and their families. The results of this study can be used to further improve the programs and services to prevent DM and delay the progression of chronic complications like diabetic foot ulcers at the community level.

A Single Wavelength Mid-Infrared Photoacoustic Spectroscopy for Noninvasive Glucose Detection Using Machine Learning.

According to the International Diabetes Federation, 530 million people worldwide have diabetes, with more than 6.7 million reported deaths in 2021. Monitoring blood glucose levels is essential for individuals with diabetes, and developing noninvasive monitors has been a long-standing aspiration in diabetes management. The ideal method for monitoring diabetes is to obtain the glucose concentration level with a fast, accurate, and pain-free measurement that does not require blood drawing or a surgical operation. Multiple noninvasive glucose detection techniques have been developed, including bio-impedance spectroscopy, electromagnetic sensing, and metabolic heat conformation. Nevertheless, reliability and consistency challenges were reported for these methods due to ambient temperature and environmental condition sensitivity. Among all the noninvasive glucose detection techniques, optical spectroscopy has rapidly advanced. A photoacoustic system has been developed using a single wavelength quantum cascade laser, lasing at a glucose fingerprint of 1080 cm for noninvasive glucose monitoring. The system has been examined using artificial skin phantoms, covering the normal and hyperglycemia blood glucose ranges. The detection sensitivity of the system has been improved to mg/dL using a single wavelength for the entire range of blood glucose. Machine learning has been employed to detect glucose levels using photoacoustic spectroscopy in skin samples. Ensemble machine learning models have been developed to measure glucose concentration using classification techniques. The model has achieved a 90.4% prediction accuracy with 100% of the predicted data located in zones A and B of Clarke’s error grid analysis. This finding fulfills the US Food and Drug Administration requirements for glucose monitors.

Controlled Release of Insulin Based on Temperature and Glucose Dual Responsive Biomicrocapsules.

The treatment of diabetes lies in developing novel functional carriers, which are expected to have the unique capability of monitoring blood glucose levels continuously and dispensing insulin correctly and timely. Hence, this study is proposing to create a smart self-regulated insulin delivery system according to changes in glucose concentration. Temperature and glucose dual responsive copolymer microcapsules bearing N-isopropylacrylamide and 3-acrylamidophenylboronic acid as main components were developed by bottom-spray coating technology and template method. The insulinoma β-TC6 cells were trapped in the copolymer microcapsules by use of temperature sensitivity, and then growth, proliferation, and glucose-responsive insulin secretion of microencapsulated cells were successively monitored. The copolymer microcapsules showed favorable structural stability and good biocompatibility against β-TC6 cells. Compared with free cells, the biomicrocapsules presented a more effective and safer glucose-dependent insulin release behavior. The bioactivity of secreted and released insulin did not differ between free and encapsulated β-TC6 cells. The results demonstrated that the copolymer microcapsules had a positive effect on real-time sensing of glucose and precise controlled release of insulin. The intelligent drug delivery system is supposed to mimic insulin secretion in a physiological manner, and further provide new perspectives and technical support for the development of artificial pancreas.

Association Between Snoring and Diabetes Among Pre- and Postmenopausal Women.

PurposeTo examine the relationship between diabetes and snoring frequency and determine the effect of menopause and postmenopausal years on this relationship.MethodsWe included 12,218 premenopausal and postmenopausal women from part of the baseline of the China Multi-Ethnic Cohort study (CMEC) in Chongqing province. Face-to-face questionnaires, physical examination, and biological samples were used to collect data. Logistic regression and subgroup analysis were used to explore the relationship between snoring and diabetes in women with various menopausal statuses.ResultsThe risk of diabetes increased with the snoring frequency, with adjusted odds ratios of 1.23 (95% CI:1.05–1.43) and 1.47 (95% CI:1.25–1.73) for sometimes snoring and frequent snoring, compared to non-snoring. In premenopausal and postmenopausal women, frequent snoring increased the odds of diabetes by 58% (95% CI: 7–132%) and 43% (95% CI: 20–72%), respectively, compared to non-snoring. Only in women who were ≥10 years postmenopausal had a statistical association between frequent snoring and diabetes, with a 54% (95% CI: 23–92%) increased odds of diabetes, compared to women who did not snore.ConclusionSnoring frequency is positively associated with diabetes. Women who snore frequently before and for at least ten years after menopause are at higher risk of developing diabetes. Frequent snorers and long-term postmenopausal women should monitor blood glucose levels to aid in the early detection and treatment of diabetes.

Optimal time period for blood glucose level evaluation after total knee arthroplasty in patients without diabetes: a prospective, observational study

BackgroundPostoperative hyperglycemia has been reported to be a risk factor for postoperative infection even in patients without diabetes mellitus (DM). However, there is no standard for how long blood glucose level (BGL) monitoring should be performed after total knee arthroplasty (TKA). The purpose of this study was to determine the optimal time period for BGL evaluation after TKA in patients without DM.MethodsThis prospective study included 132 knees of 110 patients who underwent TKA between March 2018 and July 2021 in our hospital. Fasting BGLs were measured preoperatively, at 9:00 PM on the day of surgery (DOS), and at 7:00 AM on postoperative days (PODs) 1, 2, and 3. Patients were divided into two groups with a preoperative hemoglobin A1c (HbA1c) cut-off value of 5.9%, and the BGLs on POD 1 were compared between the two groups.ResultsThe BGLs were significantly higher on the DOS, POD 1, and POD 2 than preoperative levels. The BGL was significantly higher on POD 1 than at any other time point. Patients with an HbA1c ≥ 5.9% had significantly higher BGLs than those with an HbA1c < 5.9% on POD 1.ConclusionsThe optimal time period for BGL evaluation after TKA in patients without DM was considered to be from postoperative to POD 2. Patients with an HbA1c ≥ 5.9% may require careful perioperative glycemic control.

Covid-19 associated mucormycosis

: Corona virus disease-2019 (COVID-19) is associated with various opportunistic, bacterial, and fungal infections. High risk groups include people with diabetes especially diabetic ketoacidosis, solid organ transplantation, long-term systemic corticosteroid use, and iron overload. Many cases of mucormycosis were reported worldwide. Mucormycosis is an invasive fungal infection with high morbidity and mortality. Early diagnosis and treatment with appropriate anti-fungals lead to improved outcomes. The aim of this study is to establish the factors associated with mucormycosis in a COVID-19 setting, like comorbidities and treatment protocols for treatment of COVID-19. The histological patterns and tissue reactions to mucormycosis also were studied. In patients with ongoing COVID-19 infection and in a post COVID-19 scenario, we studied the biopsy findings of mucormycosis in various sites like rhino-orbital, lung, gastric and trachea. Material for this study is from a tertiary care hospital in South India. Patient age ranged from 30 years to 74 years. Mean age of the patients was 51 years. Male to female ratio was 1:1.1. Tissue from sino- nasal mucosa, peri orbital tissue, exenterated eyeball, lung tissue and tissue from rare sites like gastric and tracheal mucosal lesions were also included in this study. Tissue was fixed in 10% buffered formalin. Routine Haematoxylin and Eosin(H&amp;E) stains were done. Gomori’s Methenamine silver (GMS) stains were done on all cases. Tissue was submitted for fungal cultures in all the cases.Total of twenty-three cases were diagnosed as mucormycosis based on the morphology and special stains in this analysis. Histology revealed areas of infarction in all cases with neutrophilic infiltration. Granulomatous reaction was seen in seven cases and melanin pigment was seen in two cases. 100% of patients were diabetics. There was neutrophilia in 100% of cases. Lymphopenia was seen in 85.7%, C-Reactive Protein (CRP) was elevated in 100% of cases.Ferritin was done in 14 patients and D-dimer was done in 17 patients and in all patients, these were elevated. All patients were treated with steroids according to the treatment protocol for COVID-19, Remdesivir was given in 72.7% of cases and second immunomodulator drugs like Tocilizumab in four cases and Baricitinib in one case.Mucormycosis is an emerging problem with COVID-19. It is important to carefully monitor blood glucose levels and take into account underlying medical conditions of patients before initiation of steroid therapy. Early recognition of symptoms and early diagnosis has a better outcome in patients with mucormycosis associated with COVID-19 infection.

RETRACTED ARTICLE: A novel Internet of Things (IoT)-enabled platform for patients with type 1 diabetes

Diabetic patients with type 1 diabetes (T1D) are constantly confronted with the decision of how much insulin to inject prior to each meal in order to maintain a healthy blood glucose level. As a result of recent research, it has been discovered that it is possible to construct an artificial pancreas (AP). The use of a closed-loop system, which combines an insulin pump with a continuous glucose monitor, can be beneficial for people with diabetes because it can help them manage their condition more effectively (CGM). The chronic disease diabetes with transient insulin resistance (T1D) necessitated daily insulin injections and close monitoring of blood glucose levels. T1D is characterised by insulin resistance that develops over time. Technologies for the management of type 1 diabetes, such as insulin pumps and Continuous Glucose Monitoring (CGM), have advanced significantly in the past decade, making them more effective in the management of type 1 diabetes patients. These systems may help to reduce treatment anxiety while also improving glycaemic control, according to the evidence. We describe how an attacker can cause physical harm to a victim by using their insulin pump, which is connected to the Internet, and how this can be done.

Use of a smartphone-based, interactive blood glucose management system in women with gestational diabetes mellitus: A pilot study

AimsTo determine patient satisfaction, impact on maternal and neonatal outcomes and resource utilisation of a smartphone-based, remote blood glucose level (BGL) monitoring platform with software surveillance inwomen with gestational diabetes (GDM) compared with historical controls. MethodsThis intervention study prospectively enrolled 98 women with GDM to the NET-Health smartphone-based application and compared them to 94 historical controls.The application allows automatic, real-time BGL upload to a central server for software monitoring, with automatic alerts generated for out-of-range results.Data recorded included demographics, outcomes and occasions of service (OOS). A validated satisfaction questionnaire was completed post-delivery. ResultsThe groups had comparable baseline characteristics and no significant difference in maternal and neonatal outcomes. The NET-Health application intervention reduced resource utilisation, with 1.9 fewer OOS and 37 min less clinician time – equivalent to AUD$68 saved per woman (based on clinician time only) or AUD$23 after taking into account the cost of the application. Patient satisfaction was high. ConclusionsUse of this smartphone-based application with software surveillance in women with GDM has high patient satisfaction and no differences in maternal or neonatal outcomes despite reduced resource utilisation. It is the first to demonstrate a financial benefit. Larger studies are needed.

An update on microneedle-based systems for diabetes.

Diabetes is one of the most serious chronic diseases today. Patients with diabetes need frequent insulin injections or blood sampling to monitor blood glucose levels. The microneedles are a painless transdermal drug delivery system, which has great advantages in achieving self-management. There have been a lot of researches on microneedles used in diabetes treatment. Microneedle-based treatment of diabetes has also changed from a simple and reliable system to a complex and efficient system. This review introduces microfluidic, glucose response, and other contents based on microneedles, and some challenges in the development of microneedles.

Non-Invasive Classification of Blood Glucose Level for Early Detection Diabetes Based on Photoplethysmography Signal

Monitoring systems for the early detection of diabetes are essential to avoid potential expensive medical costs. Currently, only invasive monitoring methods are commercially available. These methods have significant disadvantages as patients experience discomfort while obtaining blood samples. A non-invasive method of blood glucose level (BGL) monitoring that is painless and low-cost would address the limitations of invasive techniques. Photoplethysmography (PPG) collects a signal from a finger sensor using a photodiode, and a nearby infrared LED light. The combination of the PPG electronic circuit with artificial intelligence makes it possible to implement the classification of BGL. However, one major constraint of deep learning is the long training phase. We try to overcome this limitation and offer a concept for classifying type 2 diabetes (T2D) using a machine learning algorithm based on PPG. We gathered 400 raw datasets of BGL measured with PPG and divided these points into two classification levels, according to the National Institute for Clinical Excellence, namely, “normal” and “diabetes”. Based on the results for testing between the models, the ensemble bagged trees algorithm achieved the best results with an accuracy of 98%.

A Virtual Coach (Motibot) for Supporting Healthy Coping Strategies Among Adults With Diabetes: Proof-of-Concept Study.

BackgroundMotivation is a core component of diabetes self-management because it allows adults with diabetes mellitus (DM) to adhere to clinical recommendations. In this context, virtual coaches (VCs) have assumed a central role in supporting and treating common barriers related to adherence. However, most of them are mainly focused on medical and physical purposes, such as the monitoring of blood glucose levels or following a healthy diet.ObjectiveThis proof-of-concept study aims to evaluate the preliminary efficacy of a VC intervention for psychosocial support before and after the intervention and at follow-up. The intent of this VC is to motivate adults with type 1 DM and type 2 DM to adopt and cultivate healthy coping strategies to reduce symptoms of depression, anxiety, perceived stress, and diabetes-related emotional distress, while also improving their well-being.MethodsA total of 13 Italian adults with DM (18-51 years) interacted with a VC, called Motibot (motivational bot) using the Telegram messaging app. The interaction covered 12 sessions, each lasting 10 to 20 minutes, during which the user could dialogue with the VC by inputting text or tapping an option on their smartphone screen. Motibot is developed within the transtheoretical model of change to deliver the most appropriate psychoeducational intervention based on the user’s motivation to change.ResultsResults showed that over the 12 sessions, there were no significant changes before and after the intervention and at follow-up regarding psychosocial factors. However, most users showed a downward trend over the 3 time periods in depression and anxiety symptoms, thereby presenting good psychological well-being and no diabetes-related emotional distress. In addition, users felt motivated, involved, encouraged, emotionally understood, and stimulated by Motibot during the interaction. Indeed, the analyses of semistructured interviews, using a text mining approach, showed that most users reported a perceived reduction in anxiety, depression, and/or stress symptoms. Moreover, users indicated the usefulness of Motibot in supporting and motivating them to find a mindful moment for themselves and to reflect on their own emotions.ConclusionsMotibot was well accepted by users, particularly because of the inclusion of mindfulness practices, which motivated them to adopt healthy coping skills. To this extent, Motibot provided psychosocial support for adults with DM, particularly for those with mild and moderate symptoms, whereas those with severe symptoms may benefit more from face-to-face psychotherapy.

Monitoring of blood glucose levels, ketones and insulin bolus advice using 4SURE products and app-based technology.

With more people being diagnosed with diabetes and requiring insulin therapy as they live longer, an increasing number of individuals are needing access to blood and ketone monitoring that is simple to use and provides accurate results. Having access to a bolus advisor is equally important in order for people with diabetes to calculate accurate insulin doses based on the foods that they are eating. The use of app-based technology for healthcare purposes has increased over recent years and now includes the Diabetes:M application that can be used in conjunction with the 4SURE smart meters with no additional cost to the individual.

Swellable PVA/PVP hydrogel microneedle patches for the extraction of interstitial skin fluid toward minimally invasive monitoring of blood glucose level.

Interstitial skin fluid (ISF) is an emerging alternative source of blood samples that has attracted great interest from researchers. It is a very promising way to use microneedle patches for extracting ISF. However, the recovery of ISF still faces great challenges, such as long extraction time and low extraction volume, which may affect the analysis of biomarkers. Traditional centrifugation methods cannot completely recover ISF, which leads to inaccuracy in ISF detection. In this paper, the prepared polyvinyl alcohol/polyvinylpyrrolidone (PVA/PVP) microneedle patches had the ability to insert into the skin in a dry state; at the same time, the microneedle patches had good swelling properties and could extract ISF in a short time without any additional devices. Due to the thermal degradation of PVA, the way of gentle heating was used to recover ISF, which could greatly improve the accuracy of detection. By comparing the D-glucose content assay kit with the blood glucose concentration of rats detected using a commercial glucometer, the detection accuracy of the microneedle patches was verified. The microneedle patches can be used to sample ISF and analyze the level of biomarkers in ISF, and are expected to provide a basis for the prevention and diagnosis of clinical diseases in the future.