Medial tibial "spackling" to lessen chronic medial tibial soft tissue irritation.

We describe a unique, utilitarian reconstructive treatment option known as tibial "spackling" for chronic, localized medial joint line pain corresponding with progressive radiographic peripheral medial tibial bone loss beneath a well-fixed revision total knee arthroplasty tibial baseplate. It is believed that this localized pain is due to chronic irritation of the medial capsule and collateral ligament from the prominent medial edge of the tibial component. In the setting of failed nonoperative treatment, our experience with utilizing bone cement to reconstruct the medial tibial bone defect and create a smooth medial tibial surface has been successful in eliminating chronic medial soft tissue irritation.

Modeling the impact of prevention policies on future diabetes prevalence in the United States: 2010-2030.

BACKGROUND: Although diabetes is one of the most costly and rapidly increasing serious chronic diseases worldwide, the optimal mix of strategies to reduce diabetes prevalence has not been determined. METHODS: Using a dynamic model that incorporates national data on diabetes prevalence and incidence, migration, mortality rates, and intervention effectiveness, we project the effect of five hypothetical prevention policies on future US diabetes rates through 2030: 1) no diabetes prevention strategy; 2) a "high-risk" strategy, wherein adults with both impaired fasting glucose (IFG) (fasting plasma glucose of 100-124 mg/dl) and impaired glucose tolerance (IGT) (2-hour post-load glucose of 141-199 mg/dl) receive structured lifestyle intervention; 3) a "moderate-risk" strategy, wherein only adults with IFG are offered structured lifestyle intervention; 4) a "population-wide" strategy, in which the entire population is exposed to broad risk reduction policies; and 5) a "combined" strategy, involving both the moderate-risk and population-wide strategies. We assumed that the moderate- and high-risk strategies reduce the annual diabetes incidence rate in the targeted subpopulations by 12.5% through 2030 and that the population-wide approach would reduce the projected annual diabetes incidence rate by 2% in the entire US population. RESULTS: We project that by the year 2030, the combined strategy would prevent 4.6 million incident cases and 3.6 million prevalent cases, attenuating the increase in diabetes prevalence by 14%. The moderate-risk approach is projected to prevent 4.0 million incident cases, 3.1 million prevalent cases, attenuating the increase in prevalence by 12%. The high-risk and population approaches attenuate the projected prevalence increases by 5% and 3%, respectively. Even if the most effective strategy is implemented (the combined strategy), our projections indicate that the diabetes prevalence rate would increase by about 65% over the 23 years (i.e., from 12.9% in 2010 to 21.3% in 2030). CONCLUSIONS: While implementation of appropriate diabetes prevention strategies may slow the rate of increase of the prevalence of diabetes among US adults through 2030, the US diabetes prevalence rate is likely to increase dramatically over the next 20 years. Demand for health care services for people with diabetes complications and diabetes-related disability will continue to grow, and these services will need to be strengthened along with primary diabetes prevention efforts.

Small area variation in diabetes prevalence in Puerto Rico.

OBJECTIVE: To estimate the 2009 prevalence of diagnosed diabetes in Puerto Rico among adults ≥ 20 years of age in order to gain a better understanding of its geographic distribution so that policymakers can more efficiently target prevention and control programs. METHODS: A Bayesian multilevel model was fitted to the combined 2008-2010 Behavioral Risk Factor Surveillance System and 2009 United States Census data to estimate diabetes prevalence for each of the 78 municipios (counties) in Puerto Rico. RESULTS: The mean unadjusted estimate for all counties was 14.3% (range by county, 9.9%-18.0%). The average width of the confidence intervals was 6.2%. Adjusted and unadjusted estimates differed little. CONCLUSIONS: These 78 county estimates are higher on average and showed less variability (i.e., had a smaller range) than the previously published estimates of the 2008 diabetes prevalence for all United States counties (mean, 9.9%; range, 3.0%-18.2%).

Small area variation in diabetes prevalence in Puerto Rico / Variación en un área pequeña de la prevalencia de la diabetes en Puerto Rico

OBJECTIVE: To estimate the 2009 prevalence of diagnosed diabetes in Puerto Rico among adults > 20 years of age in order to gain a better understanding of its geographic distribution so that policymakers can more efficiently target prevention and control programs. METHODS: A Bayesian multilevel model was fitted to the combined 2008-2010 Behavioral Risk Factor Surveillance System and 2009 United States Census data to estimate diabetes prevalence for each of the 78 municipios (counties) in Puerto Rico. RESULTS: The mean unadjusted estimate for all counties was 14.3% (range by county, 9.9%-18.0%). The average width of the confidence intervals was 6.2%. Adjusted and unadjusted estimates differed little. CONCLUSIONS: These 78 county estimates are higher on average and showed less variability (i.e., had a smaller range) than the previously published estimates of the 2008 diabetes prevalence for all United States counties (mean, 9.9%; range, 3.0%-18.2%).

OBJETIVO: Calcular la prevalencia en el año 2009 de casos con diagnóstico de diabetes en Puerto Rico en adultos de 20 años de edad o mayores, para conocer mejor su distribución geográfica con objeto de que los responsables políticos puedan encauzar más eficientemente los programas de prevención y control. MÉTODOS: Se ajustó un modelo multinivel bayesiano a la combinación de datos del Sistema de Vigilancia de Factores de Riesgo del Comportamiento 2008-2010 y del Censo de los Estados Unidos del 2009 para calcular la prevalencia de la diabetes en cada uno de los 78 municipios de Puerto Rico. RESULTADOS: El cálculo del valor medio no ajustado para todos los municipios fue de 14,3% (intervalo por municipio de 9,9 a 18,0%). La amplitud promedio de los intervalos de confianza fue de 6,2%. Hubo poca diferencia entre los cálculos ajustados y los no ajustados. CONCLUSIONES: Los valores obtenidos mediante estos cálculos correspondientes a 78 municipios fueron por término medio más elevados y mostraron menor variabilidad (es decir, el intervalo era más pequeño) que los cálculos anteriormente publicados sobre la prevalencia de la diabetes en todos los municipios de los Estados Unidos en el 2008 (media, 9,9%; intervalo de 3,0 a 18,2%).

Bayesian Small Area Estimates of Diabetes Incidence by United States County, 2009.

In the United States, diabetes is common and costly. Programs to prevent new cases of diabetes are often carried out at the level of the county, a unit of local government. Thus, efficient targeting of such programs requires county-level estimates of diabetes incidence-the fraction of the non-diabetic population who received their diagnosis of diabetes during the past 12 months. Previously, only estimates of prevalence-the overall fraction of population who have the disease-have been available at the county level. Counties with high prevalence might or might not be the same as counties with high incidence, due to spatial variation in mortality and relocation of persons with incident diabetes to another county. Existing methods cannot be used to estimate county-level diabetes incidence, because the fraction of the population who receive a diabetes diagnosis in any year is too small. Here, we extend previously developed methods of Bayesian small-area estimation of prevalence, using diffuse priors, to estimate diabetes incidence for all U.S. counties based on data from a survey designed to yield state-level estimates. We found high incidence in the southeastern United States, the Appalachian region, and in scattered counties throughout the western U.S. Our methods might be applicable in other circumstances in which all cases of a rare condition also must be cases of a more common condition (in this analysis, "newly diagnosed cases of diabetes" and "cases of diabetes"). If appropriate data are available, our methods can be used to estimate proportion of the population with the rare condition at greater geographic specificity than the data source was designed to provide.

Projections of type 1 and type 2 diabetes burden in the U.S. population aged <20 years through 2050: dynamic modeling of incidence, mortality, and population growth.

OBJECTIVE: To forecast the number of U.S. individuals aged <20 years with type 1 diabetes mellitus (T1DM) or type 2 diabetes mellitus (T2DM) through 2050, accounting for changing demography and diabetes incidence. RESEARCH DESIGN AND METHODS: We used Markov modeling framework to generate yearly forecasts of the number of individuals in each of three states (diabetes, no diabetes, and death). We used 2001 prevalence and 2002 incidence of T1DM and T2DM from the SEARCH for Diabetes in Youth study and U.S. Census Bureau population demographic projections. Two scenarios were considered for T1DM and T2DM incidence: 1) constant incidence over time; 2) for T1DM yearly percentage increases of 3.5, 2.2, 1.8, and 2.1% by age-groups 0-4 years, 5-9 years, 10-14 years, and 15-19 years, respectively, and for T2DM a yearly 2.3% increase across all ages. RESULTS: Under scenario 1, the projected number of youth with T1DM rises from 166,018 to 203,382 and with T2DM from 20,203 to 30,111, respectively, in 2010 and 2050. Under scenario 2, the number of youth with T1DM nearly triples from 179,388 in 2010 to 587,488 in 2050 (prevalence 2.13/1,000 and 5.20/1,000 [+144% increase]), with the greatest increase in youth of minority racial/ethnic groups. The number of youth with T2DM almost quadruples from 22,820 in 2010 to 84,131 in 2050; prevalence increases from 0.27/1,000 to 0.75/1,000 (+178% increase). CONCLUSIONS: A linear increase in diabetes incidence could result in a substantial increase in the number of youth with T1DM and T2DM over the next 40 years, especially those of minority race/ethnicity.

Decreases in diabetes-free life expectancy in the U.S. and the role of obesity.

OBJECTIVE: With increasing life expectancy in the U.S., it is important to know whether a longer life expectancy means a longer healthy life span or a prolonged period of later-life morbidity. This study examines changes in lifetime without diabetes, a leading cause of morbidity in later life. RESEARCH DESIGN AND METHODS: Using demographic methods and nationally representative data, we estimated changes in diabetes-free life expectancy between 1980-1989 and 2000-2004 for adult men and women in the U.S., estimated the contribution of changes in age-specific diabetes rates, and examined the changing effects of weight status on diabetes risks. RESULTS: While life expectancy at age 18 for men and women increased between the 1980s and the 2000s, diabetes-free life expectancy at age 18 decreased by 1.7 years for men and 1.5 years for women. The proportion of 18-year-olds who would develop diabetes in their lifetimes increased by almost 50% among women and almost doubled among men. Obese individuals experienced the greatest losses in diabetes-free life expectancy during this period, estimated at 5.6 years for men and 2.5 years for women. CONCLUSIONS: Diabetes-free life expectancy decreased for both men and women between 1980-1989 and 2000-2004, and these decreases are almost entirely attributable to large increases in diabetes incidence among obese individuals.

Projection of the year 2050 burden of diabetes in the US adult population: dynamic modeling of incidence, mortality, and prediabetes prevalence.

BACKGROUND: People with diabetes can suffer from diverse complications that seriously erode quality of life. Diabetes, costing the United States more than $174 billion per year in 2007, is expected to take an increasingly large financial toll in subsequent years. Accurate projections of diabetes burden are essential to policymakers planning for future health care needs and costs. METHODS: Using data on prediabetes and diabetes prevalence in the United States, forecasted incidence, and current US Census projections of mortality and migration, the authors constructed a series of dynamic models employing systems of difference equations to project the future burden of diabetes among US adults. A three-state model partitions the US population into no diabetes, undiagnosed diabetes, and diagnosed diabetes. A four-state model divides the state of "no diabetes" into high-risk (prediabetes) and low-risk (normal glucose) states. A five-state model incorporates an intervention designed to prevent or delay diabetes in adults at high risk. RESULTS: The authors project that annual diagnosed diabetes incidence (new cases) will increase from about 8 cases per 1,000 in 2008 to about 15 in 2050. Assuming low incidence and relatively high diabetes mortality, total diabetes prevalence (diagnosed and undiagnosed cases) is projected to increase from 14% in 2010 to 21% of the US adult population by 2050. However, if recent increases in diabetes incidence continue and diabetes mortality is relatively low, prevalence will increase to 33% by 2050. A middle-ground scenario projects a prevalence of 25% to 28% by 2050. Intervention can reduce, but not eliminate, increases in diabetes prevalence. CONCLUSIONS: These projected increases are largely attributable to the aging of the US population, increasing numbers of members of higher-risk minority groups in the population, and people with diabetes living longer. Effective strategies will need to be undertaken to moderate the impact of these factors on national diabetes burden. Our analysis suggests that widespread implementation of reasonably effective preventive interventions focused on high-risk subgroups of the population can considerably reduce, but not eliminate, future increases in diabetes prevalence.

Reductions in excess mortality rates among people with diabetes by selected cause of death.

We applied Bayesian methods to estimate excess mortality rates by selected causes of death for decedents with diabetes compared to those without diabetes in North Dakota and assessed changes in the excess rate between 1992-1998 and 1999-2003. We report the probability (Pr) of a rate decrease in the age-adjusted excess rate and considered the evidence strong if the probability was 0.90 or higher. Among men with diabetes, the evidence was strong for a probable decrease in excess rate for heart disease (8.7 per 1000 to 6.5), cerebrovascular disease (1.2 per 1000 to 0.75) and arterial disease (0.24 per 1000 to 0.08). Among women with diabetes, the evidence was strong for a probable decrease in excess rates for the overall (total) rate (17.8 per 1000 to 12.6), for heart disease (6.1 per 1000 to 4.4), IHD (4.4 per 1000 to 3.1), cerebrovascular disease (1.4 per 1000 to 0.5), arterial disease (0.17 per 1000 to 0.10) and cancer (2.1 per 1000 to 1.3) as underlying cause of death. The data reflect a high likelihood that cause-specific excess mortality is decreasing for men, and especially for women, with diabetes.

Projection of diabetic retinopathy and other major eye diseases among people with diabetes mellitus: United States, 2005-2050.

OBJECTIVES: To estimate the number of people with diabetic retinopathy (DR), vision-threatening DR (VTDR), glaucoma, and cataracts among Americans 40 years or older with diagnosed diabetes mellitus for the years 2005-2050. METHODS: Using published prevalence data of DR, VTDR, glaucoma, and cataracts and data from the National Health Interview Survey and the US Census Bureau, we projected the number of Americans with diabetes with these eye conditions. RESULTS: The number of Americans 40 years or older with DR and VTDR will triple in 2050, from 5.5 million in 2005 to 16.0 million for DR and from 1.2 million in 2005 to 3.4 million for VTDR. Increases among those 65 years or older will be more pronounced (2.5 million to 9.9 million for DR and 0.5 million to 1.9 million for VTDR). The number of cataract cases among whites and blacks 40 years or older with diabetes will likely increase 235% by 2050, and the number of glaucoma cases among Hispanics with diabetes 65 years or older will increase 12-fold. CONCLUSION: Future increases in the number of Americans with diabetes will likely lead to significant increases in the number with DR, glaucoma, and cataracts. Our projections may help policy makers anticipate future demands for health care resources and possibly guide the development of targeted interventions. CLINICAL RELEVANCE: Efforts to prevent diabetes and to optimally manage diabetes and its complications are needed.

A Bayesian approach to assess heart disease mortality among persons with diabetes in the presence of missing data.

Some states' death certificate form includes a diabetes yes/no check box that enables policy makers to investigate the change in heart disease mortality rates by diabetes status. Because the check boxes are sometimes unmarked, a method accounting for missing data is needed when estimating heart disease mortality rates by diabetes status. Using North Dakota's data (1992-2003), we generate the posterior distribution of diabetes status to estimate diabetes status among those with heart disease and an unmarked check box using Monte Carlo methods. Combining this estimate with the number of death certificates with known diabetes status provides a numerator for heart disease mortality rates. Denominators for rates were estimated from the North Dakota Behavioral Risk Factor Surveillance System. Accounting for missing data, age-adjusted heart disease mortality rates (per 1,000) among women with diabetes were 8.6 during 1992-1998 and 6.7 during 1999-2003. Among men with diabetes, rates were 13.0 during 1992-1998 and 10.0 during 1999-2003. The Bayesian approach accounted for the uncertainty due to missing diabetes status as well as the uncertainty in estimating the populations with diabetes.

Effect of BMI on lifetime risk for diabetes in the U.S.

OBJECTIVE: At birth, the lifetime risk of developing diabetes is one in three, but lifetime risks across BMI categories are unknown. We estimated BMI-specific lifetime diabetes risk in the U.S. for age-, sex-, and ethnicity-specific subgroups. RESEARCH DESIGN AND METHODS: National Health Interview Survey data (n = 780,694, 1997-2004) were used to estimate age-, race-, sex-, and BMI-specific prevalence and incidence of diabetes in 2004. U.S. Census Bureau age-, race-, and sex-specific population and mortality rate estimates for 2004 were combined with two previous studies of mortality to estimate diabetes- and BMI-specific mortality rates. These estimates were used in a Markov model to project lifetime risk of diagnosed diabetes by baseline age, race, sex, and BMI. RESULTS: Lifetime diabetes risk at 18 years of age increased from 7.6 to 70.3% between underweight and very obese men and from 12.2 to 74.4% for women. The lifetime risk difference was lower at older ages. At 65 years of age, compared with normal-weight male subjects, lifetime risk differences (percent) increased from 3.7 to 23.9 percentage points between overweight and very obese men and from 8.7 to 26.7 percentage points for women. The impact of BMI on diabetes duration also decreased with age. CONCLUSIONS: Overweight and especially obesity, particularly at younger ages, substantially increases lifetime risk of diagnosed diabetes, while their impact on diabetes risk, life expectancy, and diabetes duration diminishes with age.

The evolving diabetes burden in the United States.

A diabetes epidemic emerged during the 20th century and continues unchecked into the 21st century. It has already taken an extraordinary toll on the U.S. population through its acute and chronic complications, disability, and premature death. Trend data suggest that the burden will continue to increase. Efforts to pre- vent or delay the complications of diabetes or, better yet, to prevent or delay the development of diabetes itself are urgently needed.

Lifetime risk for diabetes mellitus in the United States.

CONTEXT: Although diabetes mellitus is one of the most prevalent and costly chronic diseases in the United States, no estimates have been published of individuals' average lifetime risk of developing diabetes. OBJECTIVE: To estimate age-, sex-, and race/ethnicity-specific lifetime risk of diabetes in the cohort born in 2000 in the United States. DESIGN, SETTING, AND PARTICIPANTS: Data from the National Health Interview Survey (1984-2000) were used to estimate age-, sex-, and race/ethnicity-specific prevalence and incidence in 2000. US Census Bureau data and data from a previous study of diabetes as a cause of death were used to estimate age-, sex-, and race/ethnicity-specific mortality rates for diabetic and nondiabetic populations. MAIN OUTCOME MEASURES: Residual (remaining) lifetime risk of diabetes (from birth to 80 years in 1-year intervals), duration with diabetes, and life-years and quality-adjusted life-years lost from diabetes. RESULTS: The estimated lifetime risk of developing diabetes for individuals born in 2000 is 32.8% for males and 38.5% for females. Females have higher residual lifetime risks at all ages. The highest estimated lifetime risk for diabetes is among Hispanics (males, 45.4% and females, 52.5%). Individuals diagnosed as having diabetes have large reductions in life expectancy. For example, we estimate that if an individual is diagnosed at age 40 years, men will lose 11.6 life-years and 18.6 quality-adjusted life-years and women will lose 14.3 life-years and 22.0 quality-adjusted life-years. CONCLUSIONS: For individuals born in the United States in 2000, the lifetime probability of being diagnosed with diabetes mellitus is substantial. Primary prevention of diabetes and its complications are important public health priorities.

A dynamic Markov model for forecasting diabetes prevalence in the United States through 2050.

This study develops forecasts of the number of people with diagnosed diabetes and diagnosed diabetes prevalence in the United States through the year 2050. A Markov modeling framework is used to generate forecasts by age, race and ethnicity, and sex. The model forecasts the number of individuals in each of three states (diagnosed with diabetes, not diagnosed with diabetes, and death) in each year using inputs of estimated diagnosed diabetes prevalence and incidence; the relative risk of mortality from diabetes compared with no diabetes; and U.S. Census Bureau estimates of current population, live births, net migration, and the mortality rate of the general population. The projected number of people with diagnosed diabetes rises from 12.0 million in 2000 to 39.0 million in 2050, implying an increase in diagnosed diabetes prevalence from 4.4% in 2000 to 9.7% in 2050.