Semi-Automated Nasal PAP Mask Sizing using Facial Photographs

We present a semi-automated system for sizing nasal Positive Airway Pressure (PAP) masks based upon a neural network model that was trained with facial photographs of both PAP mask users and non-users. It demonstrated an accuracy of 72% in correctly sizing a mask and 96% accuracy sizing to within 1 mask size group. The semi-automated system performed comparably to sizing from manual measurements taken from the same images which produced 89% and 100% accuracy respectively.Comment: 4 pages, 3 figures, 4 tables, IEEE Engineering Medicine and Biology Conference 201

Evaluation of the cost effectiveness of exenatide versus insulin glargine in patients with sub-optimally controlled Type 2 diabetes in the United Kingdom

<p>Abstract</p> <p>Objective</p> <p>Exenatide belongs to a new therapeutic class in the treatment of diabetes (incretin mimetics), allowing glucose-dependent glycaemic control in Type 2 diabetes. Randomised controlled trial data suggest that exenatide is as effective as insulin glargine at reducing HbA_1cin combination therapy with metformin and sulphonylureas; with reduced weight but higher incidence of adverse gastrointestinal events. The objective of this study is to evaluate the cost effectiveness of exenatide versus insulin glargine using RCT data and a previously published model of Type 2 diabetes disease progression that is based on the United Kingdom Prospective Diabetes Study; the perspective of the health-payer of the United Kingdom National Health Service.</p> <p>Methods</p> <p>The study used a discrete event simulation model designed to forecast the costs and health outcome of a cohort of 1,000 subjects aged over 40 years with sub-optimally-controlled Type 2 diabetes, following initiation of either exenatide, or insulin glargine, in addition to oral hypoglycaemic agents. Sensitivity analysis for a higher treatment discontinuation rate in exenatide patients was applied to the cohort in three different scenarios; (1) either ignored or (2) exenatide-failures excluded or (3) exenatide-failures switched to insulin glargine. Analyses were undertaken to evaluate the price sensitivity of exenatide in terms of relative cost effectiveness. Baseline cohort profiles and effectiveness data were taken from a published randomised controlled trial.</p> <p>Results</p> <p>The relative cost-effectiveness of exenatide and insulin glargine was tested under a variety of conditions, in which insulin glargine was dominant in all cases. Using the most conservative of assumptions, the cost-effectiveness ratio of exenatide vs. insulin glargine at the current UK NHS price was -£29,149/QALY (insulin glargine dominant) and thus exenatide is not cost-effective when compared with insulin glargine, at the current UK NHS price.</p> <p>Conclusion</p> <p>This study evaluated the relative cost effectiveness of insulin glargine versus exenatide in the management of Type 2 diabetes using a published model. Given no significant difference in glycaemic control and applying the additional effectiveness of exenatide over insulin glargine, with respect to weight loss, and using the current UK NHS prices, insulin glargine was found to be dominant over exenatide in all modelled scenarios. With current clinical evidence, exenatide does not appear to represent a cost-effective treatment option for patients with Type 2 diabetes when compared to insulin glargine.</p

Functional effects of polymorphisms on glucocorticoid receptor modulation of human anxiogenic substance-P gene promoter activity in primary amygdala neurones

This work was funded by The BBSRC (BB/D004659/1) the Wellcome Trust (080980/Z/06/Z) and the Medical Research Council (G0701003). Colin Hay was funded by the Chief Scientist Office, Scotland. Scott Davidson was funded by a BBSRC strategic studentship (BBS/S/2005/12001). Philip Cowie was funded by the Scottish Universities Life Sciences Alliance (SULCA).Peer reviewedPublisher PD

Switching from premixed insulin to glargine-based insulin regimen improves glycaemic control in patients with type 1 or type 2 diabetes: a retrospective primary care-based analysis

Background: Insulin glargine (glargine) and premixed insulins (premix) are alternative insulin treatments. This analysis evaluated glycaemic control in 528 patients with type 1 (n = 183) or type 2 (n = 345) diabetes, after switching from premix to a glargine-based regimen, using unselected general practice (GP) data. Methods: Data for this retrospective observational analysis were extracted from a UK GP database (The Health Improvement Network). Patients were required to have at least 12 months of available data, before and after, switching from premix to a glargine-based regimen. The principal analysis was the change in HbA1c after 12 months of treatment with glargine; secondary analyses included change in weight, bolus usage and total daily insulin dose. Inconsistent reporting of hypoglycemic episodes precludes reliable assessment of this outcome. Multivariate analyses were used to adjust for baseline characteristics and confounding variables. Results: Both cohorts showed significant reduction in mean HbA1c 12 months after the switch: by -0.67% (p < 0.001) in the type 1 cohort and by -0.53% (p < 0.001) in the type 2 cohort (adjusted data). The size of HbA1c improvement was positively correlated with baseline HbA1c; patients with a baseline HbA1c ≥ 10% had the greatest mean reduction in HbA1c, by -1.7% (p < 0.001) and -1.2% (p < 0.001), respectively. The proportion of patients receiving co-bolus prescriptions increased in the type 1 (mean 24.6% to 95.1%, p < 0.001) and type 2 (mean 16.2% to 73.9%, p < 0.001) cohorts. There was no significant change in weight in either cohort. Total mean insulin use increased in type 2 diabetes patients (from 0.67 ± 1.35 U/Kg to 0.88 ± 1.33 U/Kg, p < 0.001) with a slight decrease in type 1 diabetes patients (from 1.04 ± 2.51 U/Kg to 0.98 ± 2.58 U/Kg, p < 0.001). Conclusion: In everyday practice, patients with type 1 or type 2 diabetes inadequately controlled by premix insulins experienced significant improvement in glycaemic control over 12 months after switching to a glargine-based insulin regimen. These findings support the use of a basal-bolus glargine-based regimen in patients poorly controlled on premix.Peter Sharplin, Jason Gordon, John R Peters, Anthony P Tetlow, Andrea J Longman and Philip McEwa

Disease associated polymorphisms within the conserved ECR1 enhancer differentially regulate the tissue specific activity of the cannabinoid‐1 receptor gene promoter; implications for cannabinoid pharmacogenetics

EH was funded by Medical Research Scotland (PhD-719-2013) and GW Pharmaceuticals. AMcE was funded by BBSRC project grant (BB/N017544/1). PB and DW are funded by the Scottish Government Rural and Environment Science and Analytical Services Division to the Rowett Institute. The authors declare no conflicts of interest.Peer reviewedPublisher PD

A Transgenic Mouse Line Expressing Cre Recombinase in Undifferentiated Postmitotic Mouse Retinal Bipolar Cell Precursors

Approaches for manipulating cell type-specific gene expression during development depend on the identification of novel genetic tools. Here, we report the generation of a transgenic mouse line that utilizes Vsx2 upstream sequences to direct Cre recombinase to developing retinal bipolar cells. In contrast to the endogenous Vsx2 expression pattern, transgene expression was not detected in proliferating retinal progenitor cells and was restricted to post-mitotic bipolar cells. Cre immunolabeling was detected in rod bipolar cells and a subset of ON and OFF cone bipolar cells. Expression was first observed at postnatal day 3 and was detectable between 24 hours and 36 hours after the last S-phase of the cell cycle. The appearance of Cre-immunolabeled cells preceded the expression of bipolar cell type-specific markers such as PKCα and Cabp5 suggesting that transgene expression is initiated prior to terminal differentiation. In the presence of a constitutive conditional reporter transgene, reporter fluorescence was detected in Cre-expressing bipolar cells in the mature retina as expected, but was also observed in Cre-negative Type 2 bipolar cells and occasionally in Cre-negative photoreceptor cells. Together these findings reveal a new transgenic tool for directing gene expression to post-mitotic retinal precursors that are mostly committed to a bipolar cell fate

Comparison of 123 I-metaiodobenzylguanidine (MIBG) and 131 I-MIBG semi-quantitative scores in predicting survival in patients with stage 4 neuroblastoma: A report from the Children's Oncology Group

Background 123 I-metaiodobenzylguanidine (MIBG) scans are preferable to 131 I-MIBG for neuroblastoma imaging as they deliver less patient radiation yet have greater sensitivity in disease detection. Both 123 I-MIBG and 131 I-MIBG scans were used for disease assessments of neuroblastoma patients enrolled on Children's Oncology Group (COG) high-risk study A3973. The hypothesis was that 123 I-MIBG and 131 I-MIBG scans were sufficiently similar for clinical purposes in terms of ability to predict survival. Procedure Patients enrolled on COG A3973 with stage 4 disease who completed 123 I-MIBG or 131 I-MIBG scans at diagnosis, post-induction, post-transplant, or post-biotherapy were analyzed. The performance of the Curie score for each MIBG scan type in predicting survival was evaluated. At each time point, survival curves for 123 I-MIBG versus 131 I-MIBG were compared using the log-rank test. Results Of the 413 patients on A3973 with at least one MIBG scan, 350 were stage 4. The 5-year event-free survival (EFS) and overall survival (OS) rates were 33.4 ± 3.6% and 45.6 ± 4.0% (N = 350). At post-induction, EFS ( P  = 0.3501) and OS ( P  = 0.5337) for 123 I-MIBG versus 131 I-MIBG were not significantly different. Similarly, comparisons at the three other time points were non-significant. Conclusions We found no evidence of a statistically significant difference in outcome by type of scan. For future survival analyses of MIBG Curie scores, 123 I-MIBG and 131 I-MIBG results may be combined and analyzed overall, without adjustment for scan type. Pediatr Blood Cancer 2011;56:1041–1045. © 2011 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/83739/1/22991_ftp.pd

The Challenge of Transparency and Validation in Health Economic Decision Modelling:A View from Mount Hood

Transparency in health economic decision modelling is important for engendering confidence in the models and in the reliability of model-based cost-effectiveness analyses. The Mount Hood Diabetes Challenge Network has taken a lead in promoting transparency through validation with biennial conferences in which diabetes modelling groups meet to compare simulated outcomes of pre-specified scenarios often based on the results of pivotal clinical trials. Model registration is a potential method for promoting transparency, while also reducing the duplication of effort. An important network initiative is the ongoing construction of a diabetes model registry (https://www.mthooddiabeteschallenge.com). Following the 2012 International Society for Pharmacoeconomics and Outcomes Research and the Society of Medical Decision Making (ISPOR-SMDM) guidelines, we recommend that modelling groups provide technical and non-technical documentation sufficient to enable model reproduction, but not necessarily provide the model code. We also request that modelling groups upload documentation on the methods and outcomes of validation efforts, and run reference case simulations so that model outcomes can be compared. In this paper, we discuss conflicting definitions of transparency in health economic modelling, and describe the ongoing development of a registry of economic models for diabetes through the Mount Hood Diabetes Challenge Network, its objectives and potential further developments, and highlight the challenges in its construction and maintenance. The support of key stakeholders such as decision-making bodies and journals is key to ensuring the success of this and other registries. In the absence of public funding, the development of a network of modellers is of huge value in enhancing transparency, whether through registries or other means

The Impact of Unrelated Future Medical Costs on Economic Evaluation Outcomes for Different Models of Diabetes

Objective: This study leveraged data from 11 independent international diabetes models to evaluate the impact of unrelated future medical costs on the outcomes of health economic evaluations in diabetes mellitus. Methods: Eleven models simulated the progression of diabetes and occurrence of its complications in hypothetical cohorts of individuals with type 1 (T1D) or type 2 (T2D) diabetes over the remaining lifetime of the patients to evaluate the cost effectiveness of three hypothetical glucose improvement interventions versus a hypothetical control intervention. All models used the same set of costs associated with diabetes complications and interventions, using a United Kingdom healthcare system perspective. Standard utility/disutility values associated with diabetes-related complications were used. Unrelated future medical costs were assumed equal for all interventions and control arms. The statistical significance of changes on the total lifetime costs, incremental costs and incremental cost-effectiveness ratios (ICERs) before and after adding the unrelated future medical costs were analysed using t-test and summarized in incremental cost-effectiveness diagrams by type of diabetes. Results: The inclusion of unrelated costs increased mean total lifetime costs substantially. However, there were no significant differences between the mean incremental costs and ICERs before and after adding unrelated future medical costs. Unrelated future medical cost inclusion did not alter the original conclusions of the diabetes modelling evaluations. Conclusions: For diabetes, with many costly noncommunicable diseases already explicitly modelled as complications, and with many interventions having predominantly an effect on the improvement of quality of life, unrelated future medical costs have a small impact on the outcomes of health economic evaluations.</p