What to do with diabetes therapies when HbA1c lowering is inadequate:add, switch, or continue? A MASTERMIND study

This is the author accepted manuscript. The final version is available from BioMed Central via the DOI in this record.Background: It is unclear what to do when people with type 2 diabetes have had no or a limited glycemic response to a recently introduced medication. Intra-individual HbA1c variability can obscure true response. Some guidelines suggest stopping apparently ineffective therapy, but no studies have addressed this issue. Methods: In a retrospective cohort analysis using the UK Clinical Practice Research Datalink (CPRD), we assessed the outcome of 55,530 patients with type 2 diabetes starting their second or third non-insulin glucose lowering medication, with a baseline HbA1c >58mmol/mol (7.5%). For those with no HbA1c improvement or a limited response at 6 months (HbA1c fall <5.5mmol/mol [0.5%]) we compared HbA1c 12 months later in those who continued their treatment unchanged, switched to new treatment, or added new treatment. Results: An increase or a limited reduction in HbA1c was common, occurring in 21.9% (12,168/55,230), who had a mean HbA1c increase of 2.5mmol/mol (0.2%). After this limited response, continuing therapy was more frequent (n=9,308; 74%) than switching (n=1,177; 9%) or adding (n=2,163; 17%). Twelve months later, in those who switched medication HbA1c fell (-6.8mmol/mol [-0.6%], 95%CI -7.7, -6.0) only slightly more than those who continued unchanged (-5.1 mmol/mol [-0.5%], 95%CI -5.5, -4.8). Adding another new therapy was associated with a substantially better reduction (-12.4mmol/mol [-1.1%], 95%CI -13.1, -11.7). Propensity score matched subgroups demonstrated similar results. Conclusions: Where glucose lowering therapy does not appear effective on initial HbA1c testing, changing agents does not improve glycemic control. The initial agent should be continued with another therapy added.Medical Research Council (MRC)National Institute for Health Research (NIHR

Computer-based diabetes self-management interventions for adults with type 2 diabetes mellitus

BACKGROUND: Diabetes is one of the commonest chronic medical conditions, affecting around 347 million adults worldwide. Structured patient education programmes reduce the risk of diabetes-related complications four-fold. Internet-based self-management programmes have been shown to be effective for a number of long-term conditions, but it is unclear what are the essential or effective components of such programmes. If computer-based self-management interventions improve outcomes in type 2 diabetes, they could potentially provide a cost-effective option for reducing the burdens placed on patients and healthcare systems by this long-term condition. OBJECTIVES: To assess the effects on health status and health-related quality of life of computer-based diabetes self-management interventions for adults with type 2 diabetes mellitus. SEARCH METHODS: We searched six electronic bibliographic databases for published articles and conference proceedings and three online databases for theses (all up to November 2011). Reference lists of relevant reports and reviews were also screened. SELECTION CRITERIA: Randomised controlled trials of computer-based self-management interventions for adults with type 2 diabetes, i.e. computer-based software applications that respond to user input and aim to generate tailored content to improve one or more self-management domains through feedback, tailored advice, reinforcement and rewards, patient decision support, goal setting or reminders. DATA COLLECTION AND ANALYSIS: Two review authors independently screened the abstracts and extracted data. A taxonomy for behaviour change techniques was used to describe the active ingredients of the intervention. MAIN RESULTS: We identified 16 randomised controlled trials with 3578 participants that fitted our inclusion criteria. These studies included a wide spectrum of interventions covering clinic-based brief interventions, Internet-based interventions that could be used from home and mobile phone-based interventions. The mean age of participants was between 46 to 67 years old and mean time since diagnosis was 6 to 13 years. The duration of the interventions varied between 1 to 12 months. There were three reported deaths out of 3578 participants.Computer-based diabetes self-management interventions currently have limited effectiveness. They appear to have small benefits on glycaemic control (pooled effect on glycosylated haemoglobin A1c (HbA1c): -2.3 mmol/mol or -0.2% (95% confidence interval (CI) -0.4 to -0.1; P = 0.009; 2637 participants; 11 trials). The effect size on HbA1c was larger in the mobile phone subgroup (subgroup analysis: mean difference in HbA1c -5.5 mmol/mol or -0.5% (95% CI -0.7 to -0.3); P < 0.00001; 280 participants; three trials). Current interventions do not show adequate evidence for improving depression, health-related quality of life or weight. Four (out of 10) interventions showed beneficial effects on lipid profile.One participant withdrew because of anxiety but there were no other documented adverse effects. Two studies provided limited cost-effectiveness data - with one study suggesting costs per patient of less than $140 (in 1997) or 105 EURO and another study showed no change in health behaviour and resource utilisation. AUTHORS' CONCLUSIONS: Computer-based diabetes self-management interventions to manage type 2 diabetes appear to have a small beneficial effect on blood glucose control and the effect was larger in the mobile phone subgroup. There is no evidence to show benefits in other biological outcomes or any cognitive, behavioural or emotional outcomes

Direct and indirect control of the initiation of meiotic recombination by DNA damage checkpoint mechanisms in budding yeast

Meiotic recombination plays an essential role in the proper segregation of chromosomes at meiosis I in many sexually reproducing organisms. Meiotic recombination is initiated by the scheduled formation of genome-wide DNA double-strand breaks (DSBs). The timing of DSB formation is strictly controlled because unscheduled DSB formation is detrimental to genome integrity. Here, we investigated the role of DNA damage checkpoint mechanisms in the control of meiotic DSB formation using budding yeast. By using recombination defective mutants in which meiotic DSBs are not repaired, the effect of DNA damage checkpoint mutations on DSB formation was evaluated. The Tel1 (ATM) pathway mainly responds to unresected DSB ends, thus the sae2 mutant background in which DSB ends remain intact was employed. On the other hand, the Mec1 (ATR) pathway is primarily used when DSB ends are resected, thus the rad51 dmc1 double mutant background was employed in which highly resected DSBs accumulate. In order to separate the effect caused by unscheduled cell cycle progression, which is often associated with DNA damage checkpoint defects, we also employed the ndt80 mutation which permanently arrests the meiotic cell cycle at prophase I. In the absence of Tel1, DSB formation was reduced in larger chromosomes (IV, VII, II and XI) whereas no significant reduction was found in smaller chromosomes (III and VI). On the other hand, the absence of Rad17 (a critical component of the ATR pathway) lead to an increase in DSB formation (chromosomes VII and II were tested). We propose that, within prophase I, the Tel1 pathway facilitates DSB formation, especially in bigger chromosomes, while the Mec1 pathway negatively regulates DSB formation. We also identified prophase I exit, which is under the control of the DNA damage checkpoint machinery, to be a critical event associated with down-regulating meiotic DSB formation

Adherence to oral glucose-lowering therapies and associations with 1-year HbA_1c:A retrospective cohort analysis in a large primary care database

JOURNAL ARTICLEOBJECTIVE: The impact of taking oral glucose-lowering medicines intermittently, rather than as recommended, is unclear. We conducted a retrospective cohort study using community-acquired U.K. clinical data (Clinical Practice Research Database [CPRD] and GoDARTS database) to examine the prevalence of nonadherence to treatment for type 2 diabetes and investigate its potential impact on HbA1c reduction stratified by type of glucose-lowering medication. RESEARCH DESIGN AND METHODS: Data were extracted for patients treated between 2004 and 2014 who were newly-prescribed metformin, sulfonylurea, thiazolidinedione, or dipeptidyl peptidase-4 inhibitors and who continued to obtain prescriptions over 1 year. Cohorts were defined by prescribed medication type, and good adherence was defined as a medication possession ratio ≥0.8. Linear regression was used to determine potential associations between adherence and 1-year baseline-adjusted HbA1c reduction. RESULTS: In CPRD and GoDARTS, 13% and 15% of patients, respectively, were nonadherent. Proportions of nonadherent patients varied by the oral glucose-lowering treatment prescribed (range 8.6% [thiazolidinedione] to 18.8% [metformin]). Nonadherent, compared with adherent, patients had a smaller HbA1c reduction (0.4% [4.4mmmol/mol] and 0.46% [5.0 mmol/mol] for CPRD and GoDARTs, respectively). Difference in HbA1c response for adherent compared with nonadherent patients varied by drug (range 0.38% [4.1 mmol/mol] to 0.75% [8.2 mmol/mol] lower in adherent group). Decreasing levels of adherence were consistently associated with a smaller reduction in HbA1c. CONCLUSIONS: Reduced medication adherence for commonly used glucose-lowering therapies among patients persisting with treatment is associated with smaller HbA1c reductions compared with those taking treatment as recommended. Differences observed in HbA1c responses to glucose-lowering treatments may be explained in part by their intermittent use.A.J.F. and R.R.H. are National Institute for Health Research (NIHR) Senior Investigators and receive additional support from the Oxford NIHR Biomedical Research Centre. M.N.W. was supported by a Wellcome Trust Institutional Strategic Support Award (WT097835MF). E.R.P. holds a Wellcome Trust New Investigator award. The MASTERMIND consortium is funded by the U.K. Medical Research Council MR-K005707-1. The funder of the trial had no role in study design, data collection, data analysis, data interpretation, or writing of the report

Marine vessel wave wake: transient effects when accelerating or decelerating

It is well known that the waves generated by marine vessels, often referred to as wave wake or wash, can cause many issues when operating in sheltered waterways, including, but not limited to, erosion of shorelines and damage to maritime structures, and present a danger to other waterway users. Much research has been undertaken to understand the characteristics of these waves and their effects better, especially for high-speed vessels that operate in shallow water where particularly large and energetic waves are generated. However, in general, all previous studies have considered only steady-state conditions in which vessel speed remains constant; however, many vessel operations, particularly those of commuter ferries, in which regular passages through the transcritical zone to supercritical speeds (in terms of depth Froude number) are required. The present study describes a novel series of model-scale experiments used to quantify the waves during both acceleration and deceleration phases. Notable transient effects were found to occur during the acceleration phase that significantly increased both the height and period of the maximum wave compared to height and period of the maximum wave occurring at the corresponding steady-state speed. The wave characteristics at constant speed were used when assessing whether a particular vessel met wash criteria, and such criteria were likely significantly exceeded when a vessel accelerated to a supercritical speed, which could lead to the occurrence of wave wake issues. In an interesting finding, the study also found no such increase in wave characteristics when the same vessel decelerated back through the transcritical speed zone

Implementation of a distributed guideline-based decision support model within a patient-guidance framework

We report on new projection engine which was developed in order to implement a distributed guideline-based decision support system (DSS) within the European project MobiGuide.In this model, small portions of the guideline knowledge are projected, i.e. 'downloaded', from a central DSS server to a local DSS in the patient's mobile device, which then applies that knowledge using the mobile device’s local resources. Furthermore, the projection engine generates guideline projections which are adapted to the patient’s previously defined preferences and, implicitly, to the patient’s current context, which is embodied in the projected knowledge. We evaluated this distributed guideline application model for two complex guidelines: one for Gestational Diabetes Mellitus, and one for Atrial Fibrillation. We found that the initial specification of what we refer to as the customized guideline should be in the terms of the distributed DSS, i.e., include two levels: one for the central DSS, and one for the local DSS. In addition, we found significant differences between the customized, distributed versions of the two guidelines, indicating further research directions and possibly additional ways to analyze and characterize guidelines

Clustering by multiple long-term conditions and social care needs: a cross-sectional study among 10 026 older adults in England.

BACKGROUND   : People with multiple long-term conditions (MLTC) face health and social care challenges. This study aimed to classify people by MLTC and social care needs (SCN) into distinct clusters and quantify the association between derived clusters and care outcomes. METHODS : A cross-sectional study was conducted using the English Longitudinal Study of Ageing, including people with up to 10 MLTC. Self-reported SCN was assessed through 13 measures of difficulty with activities of daily living, 10 measures of mobility difficulties and whether health status was limiting earning capability. Latent class analysis was performed to identify clusters. Multivariable logistic regression quantified associations between derived MLTC/SCN clusters, all-cause mortality and nursing home admission. RESULTS: Our study included 9171 people at baseline with a mean age of 66.3 years; 44.5% were men. Nearly 70.8% had two or more MLTC, the most frequent being hypertension, arthritis and cardiovascular disease. We identified five distinct clusters classified as high SCN/MLTC through to low SCN/MLTC clusters. The high SCN/MLTC included mainly women aged 70-79 years who were white and educated to the upper secondary level. This cluster was significantly associated with higher nursing home admission (OR=8.71; 95% CI: 4.22 to 18). We found no association between clusters and all-cause mortality. CONCLUSIONS: We have highlighted those at risk of worse care outcomes, including nursing home admission. Distinct clusters of individuals with shared sociodemographic characteristics can help identify at-risk individuals with MLTC and SCN at primary care level

Attitudes towards the use and acceptance of eHealth technologies : a case study of older adults living with chronic pain and implications for rural healthcare

Acknowledgements The research described here is supported by the award made by the RCUK Digital Economy programme to the dot.rural Digital Economy Hub; award reference: EP/G066051/1. MC’s time writing the paper is funded by the Scottish Government’s Rural and Environmental Science and Analytical Services Division (RESAS) under Theme 8 ‘Vibrant Rural Communities’ of the Food, Land and People Programme (2011–2016). MC is also an Honorary Research Fellow at the Division of Applied Health Sciences, University of Aberdeen. The input of other members of the TOPS research team, Alastair Mort, Fiona Williams, Sophie Corbett, Phil Wilson and Paul MacNamee who contributed to be wider study and discussed preliminary findings reported here with the authors of the paper is acknowledged. We acknowledge the feedback on earlier versions of this paper provided by members of the Trans-Atlantic Rural Research Network, especially Stefanie Doebler and Carmen Hubbard. We also thank Deb Roberts for her comments.Peer reviewedPublisher PD

Prevalence and associated factors in burnout and psychological morbidity among substance misuse professionals

<p>Abstract</p> <p>Background</p> <p>Studies of psychological stress among substance misuse professionals rarely describe the nature of burnout and psychological morbidity. The main aim of this study was to determine the extent, pattern and predictors of psychological morbidity and burnout among substance misuse professionals.</p> <p>Methods</p> <p>This study was a cross-sectional mail survey of 194 clinical staff of substance misuse services in the former South Thames region of England, using the General Health Questionnaire (GHQ-12) the Maslach Burnout Inventory (MBI) as measures of psychological morbidity and burnout, respectively.</p> <p>Results</p> <p>Rates of psychological morbidity (82%: 95% CI = 76–87) and burnout (high emotional exhaustion – 33% [27–40]; high depersonalisation – 17% [12–23]; and diminished personal accomplishment – 36% [29–43]) were relatively high in the study sample. High levels of alienation and tension (job stressors) predicted emotional exhaustion and depersonalisation (burnout) but not psychological morbidity. Diminished personal accomplishment was associated with higher levels of psychological morbidity</p> <p>Conclusion</p> <p>In the sample of substance misuse professionals studied, rates of psychological morbidity and burnout were high, suggesting a higher level of vulnerability than in other health professionals. Furthermore, pathways to psychological morbidity and burnout are partially related. Therefore, targeted response is required to manage stress, burnout and psychological morbidity among substance misuse professionals. Such a response should be integral to workforce development.</p

Major depressive disorder and current psychological distress moderate the effect of polygenic risk for obesity on body mass index

We are grateful to the families who took part in GS:SFHS, the GPs and Scottish School of Primary Care for their help in recruiting them, and the whole GS team, which includes academic researchers, clinic staff, laboratory technicians, clerical workers, IT staff, statisticians and research managers. This work is supported by the Wellcome Trust through a Strategic Award, reference 104036/Z/14/Z. The Chief Scientist Office of the Scottish Government and the Scottish Funding Council provided core support for Generation Scotland. GS:SFHS was funded by a grant from the Scottish Government Health Department, Chief Scientist Office, number CZD/16/6. We acknowledge with gratitude the financial support received for this work from the Dr Mortimer and Theresa Sackler Foundation. PT, DJP, IJD and AMM are members of The University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross council Lifelong Health and Wellbeing Initiative (MR/K026992/1). Funding from the Biotechnology and Biological Sciences Research Council and Medical Research Council is gratefully acknowledged. DJM is an NRS Career Fellow, funded by the CSO. Supplementary Information accompanies the paper on the Translational Psychiatry websitePeer reviewedPublisher PD