When is diabetes distress clinically meaningful?: establishing cut points for the Diabetes Distress Scale.

ObjectiveTo identify the pattern of relationships between the 17-item Diabetes Distress Scale (DDS17) and diabetes variables to establish scale cut points for high distress among patients with type 2 diabetes.Research design and methodsRecruited were 506 study 1 and 392 study 2 adults with type 2 diabetes from community medical groups. Multiple regression equations associated the DDS17, a 17-item scale that yields a mean-item score, with HbA(1c), diabetes self-efficacy, diet, and physical activity. Associations also were undertaken for the two-item DDS (DDS2) screener. Analyses included control variables, linear, and quadratic (curvilinear) DDS terms.ResultsSignificant quadratic effects occurred between the DDS17 and each diabetes variable, with increases in distress associated with poorer outcomes: study 1 HbA(1c) (P < 0.02), self-efficacy (P < 0.001), diet (P < 0.001), physical activity (P < 0.04); study 2 HbA(1c) (P < 0.03), self-efficacy (P < 0.004), diet (P < 0.04), physical activity (P = NS). Substantive curvilinear associations with all four variables in both studies began at unexpectedly low levels of DDS17: the slope increased linearly between scores 1 and 2, was more muted between 2 and 3, and reached a maximum between 3 and 4. This suggested three patient subgroups: little or no distress, <2.0; moderate distress, 2.0-2.9; high distress, ≥3.0. Parallel findings occurred for the DDS2.ConclusionsIn two samples of type 2 diabetic patients we found a consistent pattern of curvilinear relationships between the DDS and HbA(1c), diabetes self-efficacy, diet, and physical activity. The shape of these relationships suggests cut points for three patient groups: little or no, moderate, and high distress

Environmental attitudes among university students In New Zealand and Australia

This paper develops a causal model of environmental attitudes using measures of the dominant social paradigm (DSP) of western industrial societies. Two components of the DSP framework beliefs in economic growth and anthropocentrism are examined regards to environmental attitudes using a sample of university students from Australia and New Zealand. The results indicate that one&rsquo;s belief in the DSP has a negative effect on environmental attitudes and perception of change necessary ameliorate degradation of the environment. Thus, while public policy favors increasing awareness of and interest in the environment, policy instruments may remain ineffective in producing lasting change if the components of the DSP remain unchanged. It is argued that public policy ought to be directed at changing the DSP so that its negativeeffects will be minimized.<br /

Exploring the role of the patient–physician relationship on insulin adherence and clinical outcomes in type 2 diabetes: Insights from the MOSAIc study

BackgroundThe 2‐year prospective MOSAIc (Multinational Observational Study assessing Insulin use: understanding the challenges associated with progression of therapy) study is investigating whether patient‐, physician‐, and health system‐related factors affect outcomes in patients with type 2 diabetes (T2D). This baseline subanalysis investigated how aspects of the patient–physician relationship are associated with diabetes‐related distress, insulin adherence, and glycemic control.MethodsPatients with T2D taking insulin for ≥3 months were recruited at primary care and specialty practice sites in 18 countries. Physicians provided usual care. Clinical history and most recent HbA1c values were collected; patients were surveyed regarding their perception of physician interactions, diabetes‐related distress level, and insulin adherence.ResultsThe analysis population comprised 4341 patients. Four (of six) domains showed a significant relationship with total diabetes‐related distress (P < 0.01). Poor insulin adherence was associated with greater diabetes‐related distress (adjusted odds ratio [aOR] 1.14; 95% confidence interval [CI] 1.06–1.22), higher Discrimination (aOR 1.13; 95% CI 1.02–1.27) and Hurried Communication (aOR 1.35; 95% CI 1.20–1.53) scores, and a lower Explained Results score (aOR 0.86; 95% CI 0.77–0.97). Poor insulin adherence was associated with a 0.43% increase in HbA1c, whereas a 1‐unit increase in total diabetes‐related distress and Hurried Communication scores was associated with a 0.171% and 0.145% increase in HbA1c, respectively.ConclusionsPatients distressed about living with T2D, and dissatisfied with aspects of their interactions with physicians, exhibited poor insulin adherence. Perceived physician inattention and lack of engagement (and diabetes‐related distress) directly affect insulin adherence and glycemic control.背景为期2年的前瞻性MOSAIc(Multinational Observational Study assessing Insulin use: understanding the challenges associated with progression of therapy,评估胰岛素使用情况的多国观察性研究:了解治疗进展带来的挑战)研究调查了患者‐、医生‐、医疗卫生系统‐相关因素是否会对2型糖尿病患者的临床结局产生影响。这项基线亚组分析调查了患者‐医生关系对糖尿病相关的不适、胰岛素依从性以及血糖控制可造成何种影响。方法在18个国家的初级保健以及专业医疗机构中招募胰岛素使用时间≥ 3个月的2型糖尿病患者。医生提供了常规的医疗护理。收集临床病史以及最近的HbA1c值;调查患者对医患之间关系的看法、与糖尿病相关的不适程度以及胰岛素依从性。结果分析人群包含了4341名患者。(在6个领域中)有4个方面与总的糖尿病相关不适之间具有显著的相关性(P < 0.01)。胰岛素依从性差与较高的糖尿病相关不适(校正过的优势比[aOR]为1.14;95%置信区间[CI]为1.06‐1.22)、较高的歧视(aOR为1.13;95% CI为1.02‐1.27)和仓促沟通(aOR为1.35;95% CI为1.20‐1.53)得分以及更低的解释病情得分(aOR为0.86;95% CI为0.77‐0.97)相关。胰岛素依从性差可导致HbA1c升高0.43%,然而总的糖尿病相关不适以及仓促沟通得分每增加1个单位就可以导致HbA1c分别升高0.171%与0.145%。结论患者感到苦恼的是2型糖尿病影响到了他们的生活,对于与医生的交流感到不够满意,而且表现为胰岛素依从性差。患者觉得医生不关心自己、缺乏交流(以及糖尿病本身造成的相关痛苦)会直接影响到胰岛素依从性以及血糖控制。HighlightsPatient perceptions of the quality of their interactions with their physicians have a significant association with total diabetes‐related distress. Diabetes‐related distress and patient–physician interactions have a significant independent association with insulin adherence and HbA1c level.This study delineates specific aspects of the patient–physician interaction that are linked to diabetes‐related distress, insulin adherence behavior, and glycemic control.Path analysis showing associations between patient–physician interactions, diabetes‐related distress, insulin adherence, and HbA1c level. The model is not adjusted for baseline covariates and shows only those factors with at least one significant interaction. Parameter coefficients in the path analysis are shown.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137500/1/jdb12443.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137500/2/jdb12443_am.pd

Improved patient-reported outcomes with iGlarLixi versus premix BIAsp 30 in people with type 2 diabetes in the SoliMix trial

AIM: To assess patient‐reported outcomes (PROs) in the SoliMix trial, which compared the efficacy and safety of iGlarLixi versus BIAsp 30 in people with type 2 diabetes (T2D). MATERIALS AND METHODS: SoliMix (EudraCT: 2017‐003370‐13), a 26‐week, open‐label study, randomized (1:1) 887 adults with T2D and HbA1c ≥7.5%‐≤10.0% (≥58‐≤86 mmol/mol) on basal insulin plus oral antihyperglycaemic drugs (OADs) to once‐daily iGlarLixi or twice‐daily premix insulin, BIAsp 30. PROs were assessed using the Treatment‐Related Impact Measure Diabetes (TRIM‐D) and Global Treatment Effectiveness Evaluation (GTEE) questionnaires. RESULTS: Over 26 weeks, iGlarLixi showed greater improvement from baseline versus BIAsp 30 in total TRIM‐D score (least squares mean difference [95% confidence interval]: 5.08 [3.69, 6.47]; effect size: 0.32) and in each TRIM‐D domain, with the greatest differences seen in diabetes management (8.47 [6.11, 10.84]) and treatment burden (6.95 [4.83, 9.07]). GTEE scores showed a greater proportion of participants and physicians rated a complete or marked improvement of diabetes control with iGlarLixi (80.5%, 82.8%) versus BIAsp 30 (63.3%, 65.1%) at week 26. Post hoc analyses showed that after adjusting for HbA1c, body weight and hypoglycaemia outcomes, iGlarLixi continued to show greater improvements in TRIM‐D total scores versus BIAsp 30. CONCLUSIONS: In addition to better glycaemic control, weight benefit and less hypoglycaemia, once‐daily iGlarLixi provided improved diabetes management, treatment burden and perceived effectiveness versus twice‐daily premix BIAsp 30, further supporting iGlarLixi as an advanced treatment option in people with suboptimally controlled T2D on basal insulin plus OADs

Optimizing postprandial glucose management in adults with insulin-requiring diabetes: Report and recommendations

Faster-acting insulins, new noninsulin drug classes, more flexible insulin-delivery systems, and improved continuous glucose monitoring devices offer unprecedented opportunities to improve postprandial glucose (PPG) management and overall care for adults with insulin-treated diabetes. These developments led the Endocrine Society to convene a working panel of diabetes experts in December 2018 to assess the current state of PPG management, identify innovative ways to improve self-management and quality of life, and align best practices to current and emerging treatment and monitoring options. Drawing on current research and collective clinical experience, we considered the following issues for the ∼200 million adults worldwide with type 1 and insulin-requiring type 2 diabetes: (i) the role of PPG management in reducing the risk of diabetes complications; (ii) barriers preventing effective PPG management; (iii) strategies to reduce PPG excursions and improve patient quality of life; and (iv) education and clinical tools to support endocrinologists in improving PPG management. We concluded that managing PPG to minimize or prevent diabetes-related complications will require elucidating fundamental questions about optimal ways to quantify and clinically assess the metabolic dysregulation and consequences of the abnormal postprandial state in diabetes and recommend research strategies to address these questions. We also identified practical strategies and tools that are already available to reduce barriers to effective PPG management, optimize use of new and emerging clinical tools, and improve patient self-management and quality of life

The value of episodic, intensive blood glucose monitoring in non-insulin treated persons with type 2 diabetes: Design of the Structured Testing Program (STeP) Study, a cluster-randomised, clinical trial [NCT00674986]

<p>Abstract</p> <p>Background</p> <p>The value and utility of self-monitoring of blood glucose (SMBG) in non-insulin treated T2DM has yet to be clearly determined. Findings from studies in this population have been inconsistent, due mainly to design differences and limitations, including the prescribed frequency and timing of SMBG, role of the patient and physician in responding to SMBG results, inclusion criteria that may contribute to untoward floor effects, subject compliance, and cross-arm contamination. We have designed an SMBG intervention study that attempts to address these issues.</p> <p>Methods/design</p> <p>The Structured Testing Program (STeP) study is a 12-month, cluster-randomised, multi-centre clinical trial to evaluate whether poorly controlled (HbA1c ≥ 7.5%), non-insulin treated T2DM patients will benefit from a comprehensive, integrated physician/patient intervention using structured SMBG in US primary care practices. Thirty-four practices will be recruited and randomly assigned to an active control group (ACG) that receives enhanced usual care or to an enhanced usual care group plus structured SMBG (STG). A total of 504 patients will be enrolled; eligible patients at each site will be randomly selected using a defined protocol. Anticipated attrition of 20% will yield a sample size of at least 204 per arm, which will provide a 90% power to detect a difference of at least 0.5% in change from baseline in HbA1c values, assuming a common standard deviation of 1.5%. Differences in timing and degree of treatment intensification, cost effectiveness, and changes in patient self-management behaviours, mood, and quality of life (QOL) over time will also be assessed. Analysis of change in HbA1c and other dependent variables over time will be performed using both intent-to-treat and per protocol analyses. Trial results will be available in 2010.</p> <p>Discussion</p> <p>The intervention and trial design builds upon previous research by emphasizing appropriate and collaborative use of SMBG by both patients and physicians. Utilization of per protocol and intent-to-treat analyses facilitates a comprehensive assessment of the intervention. Use of practice site cluster-randomisation reduces the potential for intervention contamination, and inclusion criteria (HbA1c ≥ 7.5%) reduces the possibility of floor effects. Inclusion of multiple dependent variables allows us to assess the broader impact of the intervention, including changes in patient and physician attitudes and behaviours.</p> <p>Trial Registration</p> <p>Current Controlled Trials NCT00674986.</p

Ebola virus disease in West Africa — the first 9 Months of the epidemic and forward projections

BACKGROUND On March 23, 2014, the World Health Organization (WHO) was notified of an outbreak of Ebola virus disease (EVD) in Guinea. On August 8, the WHO declared the epidemic to be a "public health emergency of international concern." METHODS By September 14, 2014, a total of 4507 probable and confirmed cases, including 2296 deaths from EVD (Zaire species) had been reported from five countries in West Africa - Guinea, Liberia, Nigeria, Senegal, and Sierra Leone. We analyzed a detailed subset of data on 3343 confirmed and 667 probable Ebola cases collected in Guinea, Liberia, Nigeria, and Sierra Leone as of September 14. RESULTS The majority of patients are 15 to 44 years of age (49.9% male), and we estimate that the case fatality rate is 70.8% (95% confidence interval [CI], 69 to 73) among persons with known clinical outcome of infection. The course of infection, including signs and symptoms, incubation period (11.4 days), and serial interval (15.3 days), is similar to that reported in previous outbreaks of EVD. On the basis of the initial periods of exponential growth, the estimated basic reproduction numbers (R-0) are 1.71 (95% CI, 1.44 to 2.01) for Guinea, 1.83 (95% CI, 1.72 to 1.94) for Liberia, and 2.02 (95% CI, 1.79 to 2.26) for Sierra Leone. The estimated current reproduction numbers (R) are 1.81 (95% CI, 1.60 to 2.03) for Guinea, 1.51 (95% CI, 1.41 to 1.60) for Liberia, and 1.38 (95% CI, 1.27 to 1.51) for Sierra Leone; the corresponding doubling times are 15.7 days (95% CI, 12.9 to 20.3) for Guinea, 23.6 days (95% CI, 20.2 to 28.2) for Liberia, and 30.2 days (95% CI, 23.6 to 42.3) for Sierra Leone. Assuming no change in the control measures for this epidemic, by November 2, 2014, the cumulative reported numbers of confirmed and probable cases are predicted to be 5740 in Guinea, 9890 in Liberia, and 5000 in Sierra Leone, exceeding 20,000 in total. CONCLUSIONS These data indicate that without drastic improvements in control measures, the numbers of cases of and deaths from EVD are expected to continue increasing from hundreds to thousands per week in the coming months

A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings

BackgroundA composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data.MethodsWe assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low-glucose and low-glucose hypoglycemia; very high-glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation.ResultsThe analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals.ConclusionThe GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments

Self-monitoring of blood glucose in noninsulin-using type 2 diabetic patients: right answer, but wrong question: self-monitoring of blood glucose can be clinically valuable for noninsulin users.

Given the importance of glycemic control in the development of diabetes complications, the plethora of tools now available to monitor the day-to-day trends in glycemia is remarkable. In this regard, self-monitoring of blood glucose (SMBG) has been considered a key component of patient management. Arguably, there remains almost universal agreement that SMBG should be available to all diabetic patients regardless of current treatment strategy. However, recently there have been reports that have challenged the current paradigm that all patients should use SMBG and concluded that SMBG for type 2 diabetic patients not on insulin may not be beneficial on glycemic control and must be weighed against the expense and inconvenience. In the counterpoint narrative following the contribution by Malanda et al., Drs. Polonsky and Fisher provide a compelling argument suggesting that while it is evident that implementing SMBG in unstructured ways without training patients and clinicians is likely to be a waste of resources, there are effective and powerful ways to use structured SMBG in insulin-naïve type 2 diabetic patients. -William T. Cefalu, MD Editor in Chief, Diabetes Care