Suboptimal inhaler medication adherence and incorrect technique are common among chronic obstructive pulmonary disease patients.

Patients with chronic obstructive pulmonary disease (COPD) are routinely prescribed one or more inhaled medications. Adherence to inhaler medications and correct inhaler device technique are crucial to successful COPD management. The goals of this study were to estimate adherence and inhaler technique in a cohort of COPD patients. This was an observational study conducted on a sample of 150 COPD patients. Medication adherence was assessed using the Medication Adherence Report Scale (MARS). Inhaler technique was assessed using standardized checklists. Clinical data were collected using a proforma. Of the 150 patients (mean age 70.3 years, 52% male), 58% reported suboptimal adherence (MARS ≤ 24). High adherence to therapy (MARS = 25) was associated with older age (p = 0.001), but not any of the other studied variables. Medication non-adherence was not associated with COPD exacerbations. Errors (≥ 1) in inhaler technique were common across all of the types of inhaler devices reportedly used by patients, with the highest proportion of errors among Turbuhaler users (83%) and the least proportion of errors among Handihaler users (50%). No clinical variables were associated with errors in inhaler technique. Suboptimal adherence and errors in inhaler technique are common among COPD patients. No clinical variables to assist in the prediction of medication non-adherence and poor inhaler technique were identifiable. Consequently, regular assessment of medication adherence and inhaler technique should be incorporated into routine clinical practice to facilitate improved health outcomes among patients with COPD.

Feasibility of a collaborative pharmacist prescribing model for patients with chronic disease(s) attending Australian general practices: a preliminary study.

BACKGROUND: Pharmacists working in general practices provide medication reviews with recommendations to general practitioners (GPs) to optimise medications. We describe a model where the pharmacist is empowered with increased responsibility to implement agreed recommendations through collaborative prescribing. AIM: To assess a collaborative pharmacist prescribing model incorporating increased pharmacist responsibility, for patients with chronic diseases in general practice. METHOD: This was a pre-test-post-test quasi experimental pilot study using a pharmacist embedded in three Australian general practices. A pharmaceutical care plan was developed with patients and their GP to identify drug related problems (DRPs). The pharmacist discussed recommendations to manage DRPs with the GP and implemented recommendations agreed by the GP and patient over the six-month study period. Outcome measures included acceptance and implementation rate of recommendations made by the pharmacist. RESULTS: The pharmacist made 135 recommendations to optimise medicine use of which 126 (93.3%) were accepted by the GP. There were 105 (83.3%) implemented by the end of the study of which the pharmacist implemented 62 (49.3%). CONCLUSION: Compared to other Australian studies using a general practice pharmacist model, this study suggested increased pharmacist responsibility through collaborative prescribing led to high acceptance and implementation rates of recommendations to manage DRPs.

A collaborative pharmacist prescribing model for patients with chronic disease(s) attending Australian general practices: Patient and general practitioner perceptions.

A collaborative pharmacist prescribing model for patients with chronic disease(s) attending Australian general practices: patient and general practitioner perceptions. Background: Pharmacists working in general practice settings are slowly emerging in Australia, with comprehensive medication reviews forming a large part of their role in optimising pharmaceutical care. In Australia, pharmacists are entirely reliant on general practitioners (GPs) accepting and implementing their recommendations to manage drug related problems (DRPs). The next step is a model where the pharmacist takes on responsibility for implementing some of their recommendations. Aim: To investigate patient and general practitioner perceptions of a collaborative model of care where the pharmacist has increased responsibility in assisting the general practitioner manage patients with chronic conditions. Method: Semi-structured, phone and face-to-face interviews were conducted with a purposive sample of patients and GPs respectively. Data were transcribed by a professional transcription service, collated using NVivo 12 Plus and analysed using Braun and Clarke's thematic analysis. Provisional codes were generated and clustered into categories, from which themes were identified. Results: Eighteen interviews were conducted (12 patients, 6 GPs). Four themes were identified from the patient interview data: pharmacist attributes; acknowledgement of the impact of the pharmacist, understanding of the GP-pharmacist collaborative model; relationships with and attitudes towards medicines and health care providers. Four themes were identified from the general practitioner interview data: pharmacist attributes; relationships with pharmacists; impressions on collaboration; impressions of the pharmacist's recommendations. Patients' and GPs' perceptions of the collaborative model of care overall were positive, acknowledging the advantages of a patient-centred, interdisciplinary approach and the potential benefits to patients. Conclusion: The GP-pharmacist collaborative model was viewed favourably by patients and GPs, with some GPs articulating the value in the pharmacist's increased responsibility as they implemented some recommendations to manage DRPs.

Cryo-EM structure of human Pol κ bound to DNA and mono-ubiquitylated PCNA.

Y-family DNA polymerase κ (Pol κ) can replicate damaged DNA templates to rescue stalled replication forks. Access of Pol κ to DNA damage sites is facilitated by its interaction with the processivity clamp PCNA and is regulated by PCNA mono-ubiquitylation. Here, we present cryo-EM reconstructions of human Pol κ bound to DNA, an incoming nucleotide, and wild type or mono-ubiquitylated PCNA (Ub-PCNA). In both reconstructions, the internal PIP-box adjacent to the Pol κ Polymerase-Associated Domain (PAD) docks the catalytic core to one PCNA protomer in an angled orientation, bending the DNA exiting the Pol κ active site through PCNA, while Pol κ C-terminal domain containing two Ubiquitin Binding Zinc Fingers (UBZs) is invisible, in agreement with disorder predictions. The ubiquitin moieties are partly flexible and extend radially away from PCNA, with the ubiquitin at the Pol κ-bound protomer appearing more rigid. Activity assays suggest that, when the internal PIP-box interaction is lost, Pol κ is retained on DNA by a secondary interaction between the UBZs and the ubiquitins flexibly conjugated to PCNA. Our data provide a structural basis for the recruitment of a Y-family TLS polymerase to sites of DNA damage.

The Role of Glycation on the Aggregation Properties of IAPP.

Epidemiological evidence shows an increased risk for developing Alzheimer's disease in people affected by diabetes, a pathology associated with increased hyperglycemia. A potential factor that could explain this link could be the role that sugars may play in both diseases under the form of glycation. Contrary to glycosylation, glycation is an enzyme-free reaction that leads to formation of toxic advanced glycation end-products (AGEs). In diabetes, the islet amyloid polypeptide (IAPP or amylin) is found to be heavily glycated and to form toxic amyloid-like aggregates, similar to those observed for the Aß peptides, often also heavily glycated, observed in Alzheimer patients. Here, we studied the effects of glycation on the structure and aggregation properties of IAPP with several biophysical techniques ranging from fluorescence to circular dichroism, mass spectrometry and atomic force microscopy. We demonstrate that glycation occurs exclusively on the N-terminal lysine leaving the only arginine (Arg11) unmodified. At variance with recent studies, we show that the dynamical interplay between glycation and aggregation affects the structure of the peptide, slows down the aggregation process and influences the aggregate morphology.

Clinical evaluation of a personalized artificial pancreas.

OBJECTIVE: An artificial pancreas (AP) that automatically regulates blood glucose would greatly improve the lives of individuals with diabetes. Such a device would prevent hypo- and hyperglycemia along with associated long- and short-term complications as well as ease some of the day-to-day burden of frequent blood glucose measurements and insulin administration. RESEARCH DESIGN AND METHODS: We conducted a pilot clinical trial evaluating an individualized, fully automated AP using commercial devices. Two trials (n = 22, n(subjects) = 17) were conducted using a multiparametric formulation of model predictive control and an insulin-on-board algorithm such that the control algorithm, or "brain," can be embedded on a chip as part of a future mobile device. The protocol evaluated the control algorithm for three main challenges: 1) normalizing glycemia from various initial glucose levels, 2) maintaining euglycemia, and 3) overcoming an unannounced meal of 30 ± 5 g carbohydrates. RESULTS: Initial glucose values ranged from 84-251 mg/dL. Blood glucose was kept in the near-normal range (80-180 mg/dL) for an average of 70% of the trial time. The low and high blood glucose indices were 0.34 and 5.1, respectively. CONCLUSIONS: These encouraging short-term results reveal the ability of a control algorithm tailored to an individual's glucose characteristics to successfully regulate glycemia, even when faced with unannounced meals or initial hyperglycemia. To our knowledge, this represents the first truly fully automated multiparametric model predictive control algorithm with insulin-on-board that does not rely on user intervention to regulate blood glucose in individuals with type 1 diabetes.

Exploring the beliefs of heart failure patients towards their heart failure medicines and self care activities.

AIM: To identify Heart Failure patients' beliefs towards their medications and how these beliefs relate to adherence. METHOD: Patients attending a multi-disciplinary, community based heart failure clinic on the Gold Coast, Australia were interviewed using a questionnaire composed of fours parts: repertory grid technique; Beliefs About Medicines Questionnaire (BMQ); Medicines Adherence Reporting Scale (MARS); demographic details. Patients were divided into those categorised as adherent (MARS score ≥ 23) and those categorised as non-adherent (MARS score < 23). Necessity beliefs scores from BMQ and the frequency of statements generated from the repertory grid portion of the questionnaire were compared between these two groups. RESULTS: Forty-three patients were interviewed with a mean age (±SD) of 64 (±17) years and thirty-six (83.7 %) were male. Thirty-seven (86.0 %) patients were categorised as adherent; the remaining six (14.0 %) as non-adherent. The 43 patients generated a total of 262 statements about their medicines. The three most common themes identified were Related to fluid (36.6 %), Helps the heart (31.7 %) and Related to weight (13.7 %). There was a significantly higher median necessity score in the adherent group compared to the non adherent group (22.0 vs. 19.5, p = 0.0272). Patients with a strong necessity score also had significantly higher self reported adherence compared to patients with a strong concerns score (21.5 vs. 18.0, p = 0.006). CONCLUSION: This study suggests that patients with heart failure possessing a strong belief in the necessity of their treatment regimen are more likely to demonstrate better adherence.

Modeling the effects of subcutaneous insulin administration and carbohydrate consumption on blood glucose.

BACKGROUND: Estimation of the magnitude and duration of effects of carbohydrate (CHO) and subcutaneously administered insulin on blood glucose (BG) is required for improved BG regulation in people with type 1 diabetes mellitus (T1DM). The goal of this study was to quantify these effects in people with T1DM using a novel protocol. METHODS: The protocol duration was 8 hours: a 1-3 U subcutaneous (SC) insulin bolus was administered and a 25-g CHO meal was consumed, with these inputs separated by 3-5 hours. The DexCom SEVEN® PLUS continuous glucose monitor was used to obtain SC glucose measurements every 5 minutes and YSI 2300 Stat Plus was used to obtain intravenous glucose measurements every 15 minutes. RESULTS: The protocol was tested on 11 subjects at Sansum Diabetes Research Institute. The intersubject parameter coefficient of variation for the best identification method was 170%. The mean percentages of output variation explained by the bolus insulin and meal models were 68 and 69%, respectively, with root mean square error of 14 and 10 mg/dl, respectively. Relationships between the model parameters and clinical parameters were observed. CONCLUSION: Separation of insulin boluses and meals in time allowed unique identification of model parameters. The wide intersubject variation in parameters supports the notion that glucose-insulin models and thus insulin delivery algorithms for people with T1DM should be personalized. This experimental protocol could be used to refine estimates of the correction factor and the insulin-to-carbohydrate ratio used by people with T1DM.

Quest for the artificial pancreas: combining technology with treatment.

The various components of the artificial pancreas puzzle are being put into place. Features such as communication, control, modeling, and learning are being realized presently. Steps have been set in motion to carry the conceptual design through simulation to clinical implementation. The challenging pieces still to be addressed include stress and exercise; as integral parts of the ultimate goal, effort has begun to shift toward overcoming the remaining hurdles to the full artificial pancreas. The artificial pancreas is close to becoming a reality, driven by technology, and the expectation that lives will be improved.

Safety constraints in an artificial pancreatic beta cell: an implementation of model predictive control with insulin on board.

BACKGROUND: Type 1 diabetes mellitus (T1DM) is characterized by the destruction of pancreatic beta cells, resulting in the inability to produce sufficient insulin to maintain normoglycemia. As a result, people with T1DM depend on exogenous insulin that is given either by multiple daily injections or by an insulin pump to control their blood glucose. A challenging task is to design the next step in T1DM therapy: a fully automated insulin delivery system consisting of an artificial pancreatic beta cell that shall provide both safe and effective therapy. The core of such a system is a control algorithm that calculates the insulin dose based on automated glucose measurements. METHODS: A model predictive control (MPC) algorithm was designed to control glycemia by controlling exogenous insulin delivery. The MPC algorithm contained a dynamic safety constraint, insulin on board (IOB), which incorporated the clinical values of correction factor and insulin-to-carbohydrate ratio along with estimated insulin action decay curves as part of the optimal control solution. RESULTS: The results emphasized the ability of the IOB constraint to significantly improve the glucose/insulin control trajectories in the presence of aggressive control actions. The simulation results indicated that 50% of the simulations conducted without the IOB constraint resulted in hypoglycemic events, compared to 10% of the simulations that included the IOB constraint. CONCLUSIONS: Achieving both efficacy and safety in an artificial pancreatic beta cell calls for an IOB safety constraint that is able to override aggressive control moves (large insulin doses), thereby minimizing the risk of hypoglycemia.

A novel adaptive basal therapy based on the value and rate of change of blood glucose.

BACKGROUND: Modern insulin pump therapy for type 1 diabetes mellitus offers the freedom to program several basal profiles that may accommodate diurnal ariability in insulin sensitivity and activity level. However, these basal profiles do not change even if a pending hypoglycemic or hyperglycemic event is foreseen. New insulin pumps could receive a direct feed of glucose values from a continuous glucose monitoring (CGM) system and could enable dynamic basal adaptation to improve glycemic control. METHOD: The proposed method is a two-step procedure. After the design of an initial basal profile, an adaptation of the basal rate is suggested as a gain multiplier based on the current CGM glucose value and its rate of change (ROC). Taking the glucose value and its ROC as axes, a two-dimensional plane is divided into a nine-zone mosaic, where each zone is given a predefined basal multiplier; for example, a basal multiplier of zero indicates a recommendation to shut off the pump. RESULTS: The proposed therapy was evaluated on 20 in silico subjects (ten adults and ten adolescents) in the Food and Drug Administration-approved UVa/Padova simulator. Compared with conventional basal therapy, the proposed basal adjustment improved the percentage of glucose levels that stayed in the range of 60-180 mg/dl for all 20 subjects. In addition, the adaptive basal therapy reduced the average blood glucose index values. CONCLUSIONS: The proposed therapy provides the flexibility to account for insulin sensitivity variations that may result from stress and/or physical activities. Because of its simplicity, the proposed method could be embedded in a chip in a future artificial pancreatic beta cell or used in a "smart" insulin pump.

Closed-loop control and advisory mode evaluation of an artificial pancreatic Beta cell: use of proportional-integral-derivative equivalent model-based controllers.

BACKGROUND: Using currently available technology, it is possible to apply modern control theory to produce a closed-loop artificial beta cell. Novel use of established control techniques would improve glycemic control, thereby reducing the complications of diabetes. Two popular controller structures, proportional-integral-derivative (PID) and model predictive control (MPC), are compared first in a theoretical sense and then in two applications. METHODS: The Bergman model is transformed for use in a PID equivalent model-based controller. The internal model control (IMC) structure, which makes explicit use of the model, is compared with the PID controller structure in the transfer function domain. An MPC controller is then developed as an optimization problem with restrictions on its tuning parameters and is shown to be equivalent to an IMC controller. The controllers are tuned for equivalent performance and evaluated in a simulation study as a closed-loop controller and in an advisory mode scenario on retrospective clinical data. RESULTS: Theoretical development shows conditions under which PID and MPC controllers produce equivalent output via IMC. The simulation study showed that the single tuning parameter for the equivalent controllers relates directly to the closed-loop speed of response and robustness, an important result considering system uncertainty. The risk metric allowed easy identification of instances of inadequate control. Results of the advisory mode simulation showed that suitable tuning produces consistently appropriate delivery recommendations. CONCLUSION: The conditions under which PID and MPC are equivalent have been derived. The MPC framework is more suitable given the extensions necessary for a fully closed-loop artificial beta cell, such as consideration of controller constraints. Formulation of the control problem in risk space is attractive, as it explicitly addresses the asymmetry of the problem; this is done easily with MPC.