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Objective. To evaluate the attainability of tight risk factor control targets for three diabetes risk factors and to assess the degree of polypharmacy required. Data Sources/Study Setting. National Health and Nutrition Examination Survey-III. Study Design. We simulated a strategy of “treating to targets,” exposing subjects to a battery of treatments until low-density lipoprotein (LDL)-cholesterol (100 mg/dL), hemoglobin A1c (7 percent), and blood pressure (130/80 mm Hg) targets were achieved or until all treatments had been exhausted. Regimens included five statins of increasing potency, four A1c-lowering therapies, and eight steps of antihypertensive therapy. Data Collection/Extraction Methods. We selected parameter estimates from placebo-controlled trials and meta-analyses. Principal Findings. Under ideal efficacy conditions, 77, 64, and 58 percent of subjects achieved the LDL, A1c, and blood pressure targets, respectively. Successful control depended highly on a subject's baseline number of treatments. Using the least favorable assumptions of treatment tolerance, success rates were 11–17 percentage points lower. Approximately 57 percent of subjects required five or more medication classes. Conclusions. A significant proportion of people with diabetes will fail to achieve targets despite using high doses of multiple, conventional treatments. These findings raise concerns about the feasibility and polypharmacy burden needed for tight risk factor control, and the use of measures of tight control to assess the quality of care for diabetes. [ABSTRACT FROM AUTHOR]

Context: Preventive medicine has historically favored reducing a risk factor by a small amount in the entire population rather than by a large amount in high-risk individuals. The use of multivariable risk prediction tools, however, may affect the relative merits of this strategy. Methods: This study uses risk factor data from the National Health and Nutrition Examination Survey III to simulate a population of more than 100 million Americans aged thirty or older with no history of CV disease. Three strategies that could affect CV events, CV mortality, and quality-adjusted life years were examined: (1) a population-based strategy that treats all individuals with a low- or moderate-intensity intervention (in which the low-intensity intervention represents a public health campaign with no demonstrable adverse effects), (2) a targeted strategy that treats individuals in the top 25 percent based on a single risk factor (LDL), and (3) a risk-targeted strategy that treats individuals in the top 25 percent based on overall CV risk (as predicted by a multivariable prediction tool). The efficiency of each strategy was compared while varying the intervention's intensity and associated adverse effects, and the accuracy of the risk prediction tool. Findings: The LDL-targeted strategy and the low-intensity population-based strategy were comparable for CV events prevented over five years (0.79 million and 0.75 million, respectively), as were the risk-targeted strategy and moderate-intensity population-based strategy (1.56 million and 1.87 million, respectively). The risk-targeted strategy, however, was more efficient than the moderate-intensity population-based strategy (number needed to treat [NNT] 19 vs. 62). Incorporating a small degree of treatment-related adverse effects greatly magnified the relative advantages of the risk-targeted approach over other strategies. Reducing the accuracy of the prediction tool only modestly decreased this greater efficiency. Conclusions: A population-based prevention strategy can be an excellent option if an intervention has almost no adverse effects. But if the intervention has even a small degree of disutility, a targeted approach using multivariable risk prediction can prevent more morbidity and mortality while treating many fewer people. [ABSTRACT FROM AUTHOR]

The article presents a literary review of available evidence for quality indicators (QI) that can be used to assess the prevention and management of diabetes mellitus (DM) in vulnerable elders (VE). The review included 105 articles about the prevalence and treatment of complications of DM. A description of the 10 QI which were judged by an expert panel as valid is presented, including measurement of glycated hemoglobin, improving glycemic control and foot examination. The supporting evidences for each QI are also explained.

Diabetes is a highly prevalent condition that results in substantial morbidity and premature mortality. We investigated how diabetes-associated mortality, disability, early retirement, and work absenteeism impacts workforce participation.We used the Health and Retirement Study (HRS), a national household sample of adults aged 51–61 in 1992, as a data source.We conducted cross-sectional analyses on the baseline HRS data, and longitudinal analyses using data from eight years of follow-up. We used two-part regression models to estimate the adjusted impact of diabetes on workforce participation, and then estimated the economic impact of diabetes-related losses in productivity.Diabetes is a significant predictor of lost productivity. The incremental lost income due to diabetes by 1992 was$60.0 billion over an average diabetes duration of 9.7 years. From 1992 to 2000, diabetes was responsible for$4.4 billion in lost income due to early retirement,$0.5 billion due to increased sick days,$31.7 billion due to disability, and$22.0 billion in lost income due to premature mortality, for a total of$58.6 billion dollars in lost productivity, or$7.3 billion per year.In the U.S. population of adults born between 1931 and 1941, diabetes is associated with a profound negative impact on economic productivity. By 1992, an estimated$60 billion in lost productivity was associated with diabetes; additional annual losses averaged$7.3 billion over the next eight years, totaling about$120 billion by the year 2000. Given the rising prevalence of diabetes, these costs are likely to increase substantially unless countered by better public health or medical interventions. [ABSTRACT FROM AUTHOR]