Search

In this study, a turn-on paper-based optical analytical system with a rapid, sensitive and quantitative response for glucose was developed. The luminescence sensing material, crystalline iridium(III)-Zn(II) coordination polymers, or Ir-Zne, was grown electrochemically on stainless steel mesh and then deposited on filter paper. This sensing substrate was subsequently built up under glucose oxidase encapsulated in hydrogel and then immobilized on egg membrane with the layer-by-layer method. Once the glucose solution was dropped onto the paper, the oxygen content was depleted simultaneously with a concomitant increase in the phosphorescence of Ir-Zne. The detection limit for glucose was 0.05 mM. The linear dynamic range for the determination of glucose was 0.05-8.0 mM with a correlation coefficient ( R 2) of 0.9956 (y=68.11 [glucose]−14.72). The response time was about 0.12 s, and the sample volume was less than 5 μL. The effects of mesh size, buffer concentration, pH, enzyme concentration, temperature, and interference, and the stability of the biosensor, have also been studied in detail. Finally, the biosensor was successfully applied to the determination of glucose in human serum. [ABSTRACT FROM AUTHOR]

Objectives: Diabetes is a significant public health concern in India, with Kerala being labeled as the diabetes capital of the country. The study aims to evaluate the prevalence, treatment, and management of diabetes to examine the unmet need for care to propose cost-effective strategies. Design: A cross-sectional study was conducted on a geographically defined cohort population in Ernakulam. Sample: This paper presents diabetes data of adults ≥30 years enrolled from the community cohort. The interviews were conducted with 997 participants at their residence. Measurement: Random blood glucose was assessed for each participant using a finger prick test. Results: The overall prevalence of diabetes was 30.1%, of which 4.1% of participants had undiagnosed diabetes. Among those with diabetes, 86.3% were aware of their diagnosis; among those aware, 86.5% were on treatment. Among those on treatment for diabetes, 54% achieved controlled blood sugar. Conclusion: The challenge in diabetes management is controlling the blood glucose levels of people who adhere to treatment. Younger employed females from lower-income quartiles have the highest risk. The study also raises questions about quality and strategies for medication compliance. The findings inspire future research on care needs, policies, and program responses to reduce the diabetes disease burden. [ABSTRACT FROM AUTHOR]

Real‐time continuous glucose monitors using subcutaneous needle‐type sensors continue to develop. The limitations of currently available systems, however, include time lag behind changes in blood glucose, the invasive nature of such systems, and in some cases, their accuracy. Non‐invasive techniques have been developed, but, to date, no commercial device has been successful. A key research priority for people with Type 1 diabetes identified by the James Lind Alliance was to identify ways of monitoring blood glucose constantly and accurately using a discrete device, invasive or non‐invasive. Integration of such a sensor is important in the development of a closed‐loop system and the technology must be rapid, selective and acceptable for continuous use by individuals. The present review provides an update on existing continuous glucose‐sensing technologies, and an overview of emergent techniques, including their accuracy and limitations. What's new?: One of 10 key research priorities identified by the James Lind Alliance Type 1 diabetes Priority Setting Partnership was to investigate whether it is possible to monitor blood sugar levels constantly and accurately with a discrete device (non‐invasive or invasive).This paper provides an overview of the latest glucose‐sensing techniques, currently marketed products and their accuracy.To date, no device based on a non‐invasive technique has successfully reached the commercial market. We review the technological challenges faced, clinical impact and future directions in continuous glucose monitoring. [ABSTRACT FROM AUTHOR]

Closed-loop insulin delivery system, also known as artificial pancreas (AP), provides the blood glucose control in diabetic patients, enabling the automatic blood-sugar management and reducing the risks and improving the lives of people with diabetes. A new three-compartmental model of glucose-insulin interaction for AP is presented and tested in this paper. The glucose and insulin 'spaces' are split into a plasma compartment and interstitial fluids compartment, respectively. The model includes an additional subcutaneous compartment and provides three explicit delays and three parameters influencing the regulatory system and correlating with the physiopathology of the patients. Two delays are related with hepatic glucose production and insulin secretion; the third delay represents the lag time in the absorption of exogenous insulin in subcutaneous tissue. The parameters regulate the system dynamics acting on the glucose utilization and the insulin secretion. The clinical data (including information on food ingestion and exogenous insulin injection) from five case studies of Type 1 diabetics are presented and used to validate the mathematical model. After training the parameters for each case study, the model well simulates the glucose level during a 4-day test. The estimated values are physiologically meaningful and provide a further insight on the subject's dysfunctions and on the state of the disease. The results have been also compared with a parallel simulation carried out by implementing a previous two-compartmental model. The proposed algorithm produces a lower sum of the squared error between the simulated and the measured glucose concentrations over time. [ABSTRACT FROM AUTHOR]

Objective Randomized trials provide evidence that intensive lifestyle interventions leading to dietary and physical activity change can delay or prevent Type 2 diabetes. Translational studies have assessed the impact of interventions based on, but less intensive than, trial protocols delivered in community settings with high-risk populations. The aim of this review was to synthesize evidence from translational studies of any design to assess the impact of interventions delivered outside large randomized trials. Methods Medical and scientific databases were searched using specified inclusion and exclusion criteria. Studies were included that used a tested diabetes preventive study protocol with an adult population at risk from Type 2 diabetes. Included papers were quality assessed and data extracted using recommended methods. Results From an initial 793 papers, 19 papers reporting 17 studies were included. Translational studies from a range of settings utilized a variety of methods. All were based on the US Diabetes Prevention Programme protocol or the Finnish Diabetes Prevention Study, with modifications that increased feasibility and access. The main outcome that was reported in all studies was weight change. Weight loss, which occurred in all but one study, was greater in intervention arms than in control subjects. No consistent differences were found in blood glucose or waist circumference. Conclusions Translational studies based on the intensive diabetes prevention programmes showed that there is potential for less intensive interventions both to be feasible and to have an impact on future progression to diabetes in at-risk individuals. [ABSTRACT FROM AUTHOR]

Objective There is an increased risk of physical health comorbidities in people with a mental illness. This paper examines the metabolic syndrome parameters for the general population, indigenous Australians and people with a mental illness, and compares them to a sample of predominantly indigenous adults with mental health problems. Design A longitudinal (24 month) audit of patient medical records was conducted between February 2011 and March 2013. Setting The Kimberley Mental Health and Drug Service in Broome, Western Australia. Participants Largely indigenous adults with a mental illness. Sample numbers increased from 56 at baseline (80% indigenous) to 136 at 18 months (70% indigenous). Main outcome measures Waist circumference, blood pressure, fasting lipids, and fasting blood glucose. Results Preliminary assessment of the data indicates a high percentage of abnormalities at baseline and at the 18 month period on all four parameters, yet not all patients were assessed on a regular basis. Conclusions Abnormalities in metabolic profiles consistent with the non-Indigenous mental health population were found. There are considerable challenges to implementing regular monitoring of physical and metabolic profiles of indigenous people in rural and remote communities. [ABSTRACT FROM AUTHOR]

Aims This paper aims to investigate whether intraepidermal nerve-fibre density ( IENFD) may be used as a marker of the course of neuropathy in patients with Type 2 diabetes mellitus. Methods Skin biopsies from the distal leg were serially evaluated in a group of 30 patients with Type 2 diabetes mellitus (median age 60 years, 17 men) with a short duration of diabetes (< 3 years) and good glucose control, and in 23 age- and sex-matched controls. The time intervals between biopsies were > 2 years (median 33.8 months). Eighteen patients with Type 2 diabetes mellitus had symptoms or signs of distal symmetrical diabetic polyneuropathy, 12 had no neuropathy. Results At first skin biopsy, IENFD was normal in all controls and in patients without neuropathy (mean 9.5 and 7.9 fibres/mm, respectively) compared with abnormal IENFD in 77.8% in patients with polyneuropathy (mean 3.4 fibres/mm). The annual rate of intraepidermal nerve-fibre ( IENF) loss expressed as a percentage of the first IENFD value in patients with diabetic polyneuropathy was significantly higher [mean ( se), 11.95 (3.82)%] compared with controls [1.92 (1.81)%, P < 0.001] and similar to patients without polyneuropathy [12.16 (4.38)%]. The rate of IENF loss did not correlate with degree of glucose control. Conclusions The annual rate of IENF loss in patients with Type 2 diabetes mellitus was several times higher than that of healthy participants, irrespective of the presence of signs or symptoms of diabetic polyneuropathy at initial evaluation. The change in IENFD is not linear and should be expressed as a proportion of initial IENFD to serve as a marker of the course of diabetic neuropathy. [ABSTRACT FROM AUTHOR]

Aims To investigate the extent of and factors associated with adherence to Type 2 diabetes medication. Methods The CINAHL, Embase, International Pharmaceutical Abstracts, Medline, PubMed and Psych INFO databases were searched for the period January 2004 to July 2013. Papers were included in the present review if they reported the prevalence of adherence (the percentage of the study population that is classified as adherent) to Type 2 diabetes medication and used validated adherence measures with a defined cut-off point to indicate adherence. Reported factors were classified as potential predictors if the studies that examined that particular variable reported consistent findings. Results Of the 27 studies included in the present review, the prevalence of adherence ranged from 38.5 to 93.1%. Only six out of 27 studies (22.2%) reported prevalence of adherence of ≥ 80% among their study population. Depression and medication cost were found to be consistent and potentially modifiable predictors for diabetes medication-taking behaviour. The associations between adherence and other factors were inconsistent among the reviewed studies. Conclusions Adherence to diabetes medication remains an ongoing problem. This review has highlighted the urgent need to develop consensus about what constitutes good adherence in diabetes. Further research is needed to clarify modifiable factors, in addition to depression and medication cost, that influence adherence and may provide a focus for targeted interventions to promote adherence, optimize diabetes control and limit the progression of diabetes. [ABSTRACT FROM AUTHOR]

In this paper the relationship between blood glucose concentration and palm perspiration rate is studied as a non-invasive method. A glucose concentration range from 83 mg/dl to 116.5 mg/dl is examined. An artificial neural network (ANN) trained by the Levenberg–Marquardt algorithm is developed to detect the performance indices based on the one- and two-input variables. A data set for 72 volunteers is used for this study. Data of 36 volunteers are used for training the ANN and data of 36 volunteers were reserved for testing. Results of the study are acceptable with an error of 8.38% for the Elman neural network and 8.77% for the multilayer neural network. Therefore, the palm perspiration rate may be used as a good indicator for detecting glucose concentration in blood. This non-invasive method has advantages such as time saving, cost etc. over other methods and it is painless. The results of clinical experiments, follow-up methods and other applications are presented. [ABSTRACT FROM AUTHOR]