XI. STRATEGIES FOR IMPROVING DIABETES CARE D iabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to Bode (Ed.): Medical Management of Type 1 Diabetes (1), Burant (Ed): Medical Management of Type 2 Diabetes (2), and Klingensmith (Ed): Intensive Diabetes Management (3). The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.

Standards of Medical Care in Diabetes

In 1974 an article appeared in Science magazine with the dry-sounding title “Judgment Under Uncertainty: Heuristics and Biases” by a pair of psychologists who were not well known outside their discipline of decision theory. In it Amos Tversky and Daniel Kahneman introduced the world to Prospect Theory, which mapped out how humans actually behave when faced with decisions about gains and losses, in contrast to how economists assumed that people behave. Prospect Theory turned Economics on its head by demonstrating through a series of ingenious experiments that people are much more concerned with losses than they are with gains, and that framing a choice from one perspective or the other will result in decisions that are exactly the opposite of each other, even if the outcomes are monetarily the same. Prospect Theory led cognitive psychology in a new direction that began to uncover other human biases in thinking that are probably not learned but are part of our brain’s wiring.

Thinking fast and slow.

https://www.commed.vcu.edu/Chronic_Disease/2012/cochranrvwrschbias.pdf

The Cochrane Collaboration's tool for assessing risk of bias in randomised trials

Sustained reduction in the incidence of type 2 diabetes by lifestyle intervention: follow-up of the Finnish Diabetes Prevention Study

High doses of ionizing radiation clearly produce deleterious consequences in humans, including, but not exclusively, cancer induction. At very low radiation doses the situation is much less clear, but the risks of low-dose radiation are of societal importance in relation to issues as varied as screening tests for cancer, the future of nuclear power, occupational radiation exposure, frequent-flyer risks, manned space exploration, and radiological terrorism. We review the difficulties involved in quantifying the risks of low-dose radiation and address two specific questions. First, what is the lowest dose of x- or γ-radiation for which good evidence exists of increased cancer risks in humans? The epidemiological data suggest that it is ≈10–50 mSv for an acute exposure and ≈50–100 mSv for a protracted exposure. Second, what is the most appropriate way to extrapolate such cancer risk estimates to still lower doses? Given that it is supported by experimentally grounded, quantifiable, biophysical arguments, a linear extrapolation of cancer risks from intermediate to very low doses currently appears to be the most appropriate methodology. This linearity assumption is not necessarily the most conservative approach, and it is likely that it will result in an underestimate of some radiation-induced cancer risks and an overestimate of others.

/pdf/cancer-risks-attributable-to-low-doses-of-ionizing-radiation-2n8doo68ko.pdf

Cancer risks attributable to low doses of ionizing radiation: Assessing what we really know

The spatial scan statistic proposed by Kulldorff has been applied to a wide variety of epidemiological studies for cluster detection. This scan statistic, however, uses a circular window to define the potential cluster areas and thus has difficulty in correctly detecting actual noncircular clusters. A recent proposal by Duczmal and Assuncao for detecting noncircular clusters is shown to detect a cluster of very irregular shape that is much larger than the true cluster in our experiences. We propose a flexibly shaped spatial scan statistic that can detect irregular shaped clusters within relatively small neighborhoods of each region. The performance of the proposed spatial scan statistic is compared to that of Kulldorff's circular spatial scan statistic with Monte Carlo simulation by considering several circular and noncircular hot-spot cluster models. For comparison, we also propose a new bivariate power distribution classified by the number of regions detected as the most likely cluster and the number of hot-spot regions included in the most likely cluster. The circular spatial scan statistics shows a high level of accuracy in detecting circular clusters exactly. The proposed spatial scan statistic is shown to have good usual powers plus the ability to detect the noncircular hot-spot clusters more accurately than the circular one. The proposed spatial scan statistic is shown to work well for small to moderate cluster size, up to say 30. For larger cluster sizes, the method is not practically feasible and a more efficient algorithm is needed.

/pdf/a-flexibly-shaped-spatial-scan-statistic-for-detecting-18xnows14b.pdf

A flexibly shaped spatial scan statistic for detecting clusters.

Background
To evaluate the effect of lifestyle modifications on metabolic syndrome (MetS) as assessed by its resolution and improved values for its components.

/pdf/effects-of-lifestyle-modification-on-metabolic-syndrome-a-3noehjz9jy.pdf

Effects of lifestyle modification on metabolic syndrome: a systematic review and meta-analysis.

OBJECTIVE —To evaluate the efficacy of lifestyle education for preventing type 2 diabetes in individuals at high risk by meta-analysis of randomized controlled trials, as assessed by incidence and a reduced level of plasma glucose 2 h after a 75-g oral glucose load (2-h plasma glucose).

RESEARCH DESIGN AND METHODS —Through an electronic search, 123 studies were identified. A literature search identified eight studies that met strict inclusion criterion of meta-analysis for 2-h plasma glucose and five studies for the incidence of diabetes. All were randomized controlled trials of ≥6 months with lifestyle education that included a dietary intervention. Subjects were adults diagnosed as being at high risk for type 2 diabetes. The difference in mean reduction of 2-h plasma glucose from baseline to the 1-year follow-up and relative risk (RR) of the incidence of diabetes in the lifestyle education group versus the control group were assessed. Overall estimates were calculated using a random-effects model. Those estimates were confirmed by several models, and the possibility of selection bias was examined using a funnel plot.

RESULTS —Lifestyle education intervention reduced 2-h plasma glucose by 0.84 mmol/l (95% CI 0.39–1.29) compared with the control group. The 1-year incidence of diabetes was reduced by ∼50% (RR 0.55, 95% CI 0.44–0.69) compared with the control group. Results were stable and little changed if data were analyzed by subgroups or other statistical models. Funnel plots revealed no selection bias.

CONCLUSIONS —Lifestyle education was effective for reducing both 2-h plasma glucose and RR in high-risk individuals and may be a useful tool in preventing diabetes.

/pdf/efficacy-of-lifestyle-education-to-prevent-type-2-diabetes-a-19r6gwhbsl.pdf

Efficacy of Lifestyle Education to Prevent Type 2 Diabetes: A meta-analysis of randomized controlled trials

https://www.satscan.org/papers/k-csda2003.pdf?origin=publication_detail

Power comparisons for disease clustering tests

This paper proposes a class of tests applicable to the detection of two types of disease clustering 'focused' and 'general' clustering. The former assesses the clustering of observed cases around the fixed point and the latter does not have any prior information on the centre of clustering. The proposed test for 'general' clustering is a generalization of the index for temporal clustering proposed by Tango in that it adjusts for differences in population densities and also in population distributions among categories of the counfounders such as age and sex. Simulation study shows that the proposed 'general' test outperformed the average distance method of Whittemore et al. in most of the cluster models considered.

Toshiro Tango

Papers

A flexibly shaped spatial scan statistic for detecting clusters.

Effects of lifestyle modification on metabolic syndrome: a systematic review and meta-analysis.

Efficacy of Lifestyle Education to Prevent Type 2 Diabetes: A meta-analysis of randomized controlled trials

Power comparisons for disease clustering tests

A class of tests for detecting ‘general’ and ‘focused’ clustering of rare diseases