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Echocardiography enhanced prediction of first cardiovascular events in this referral-based elderly cohort. Its role in risk stratification for primary prevention of these events in the community warrants further investigations.

The case definition, community incidence, and characteristics of atypical femoral shaft fractures (FSFs) are poorly understood. This retrospective study utilized electronic medical records and radiograph review among women !50 years of age and men !65 years of age from January 1996 to June 2009 at Kaiser Permanente Northwest to describe the incidence rates and characteristics of subgroups of femur fractures. Fractures were categorized based on the American Society for Bone and Mineral Research (ASBMR) as atypical fracture major features (AFMs) (low force, shaft location, transverse or short oblique, noncomminuted) and AFMs with additional minor radiograph features (AFMms) (beaking, cortical thickening, or stress fracture). There were 5034 fractures in the study. The incidence rates of FSFs (without atypical features) and AFMs appeared flat (cumulative incidence: 18.2 per 100,000 person-years, 95% CI ¼ 16.0-20.7; 5.9 per 100,000 person-years, 95% CI ¼ 4.6-7.4; respectively) with 1,271,575 person-years observed. The proportion of AFMs that were AFMms increased over time. Thirty percent of AFMs had any dispensing of a bisphosphonate prior to the fracture, compared to 15.8% of the non-atypical FSFs. Years of oral glucocorticosteroid dispensing appeared highest in AFM and AFMm fractures. Those with AFMs only were older and had a lower frequency of bisphosphonate dispensing compared to those with AFMms. We conclude that rates of FSFs, with and without atypia, were low and stable over 13.5 years. Patients with only AFMs appear to be different from those with AFMms; it may be that only the latter group is atypical. There appear to be multiple associated risk factors for AFMm fractures. ß

OBJECTIVE—Weight loss in type 2 diabetes is undisputedly important, and data from community settings are limited. We evaluated weight change and resulting glycemic and blood pressure control in type 2 diabetic patients at an HMO. RESEARCH DESIGN AND METHODS—Using electronic medical records, this retrospective cohort study identified 2,574 patients aged 21–75 years who received a new diagnosis of type 2 diabetes between 1997 and 2002. We estimated 3-year weight trajectories using growth curve analyses, grouped similar trajectories into four categories using cluster analysis, compared category characteristics, and predicted year-4 above-goal A1C and blood pressure by group. RESULTS—The weight-trajectory groups were defined as higher stable weight (n = 418; 16.2%), lower stable weight (n = 1,542; 59.9%), weight gain (n = 300; 11.7%), and weight loss (n = 314; 12.2%). The latter had a mean weight loss of 10.7 kg (−9.8%; P < 0.001) by 18 months, with near-complete regain by 36 months. After adjusting for age, sex, baseline control, and related medication use, those with higher stable weight, lower stable weight, or weight-gain patterns were more likely than those who lost weight to have above-goal A1C (odds ratio [OR] 1.66 [95% CI 1.12–2.47], 1.52 [1.08–2.14], and 1.77 [1.15–2.72], respectively). Those with higher stable weight or weight-gain patterns were more likely than those who lost weight to have above-goal blood pressure (1.83 [1.31–2.57] and 1.47 [1.03–2.10], respectively). CONCLUSIONS—A weight-loss pattern after new diagnosis of type 2 diabetes predicted improved glycemic and blood pressure control despite weight regain. The initial period postdiagnosis may be a critical time to apply weight-loss treatments to improve risk factor control.

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