Objectives To determine a pooled, quantitative estimate of the length of time needed after breast or colorectal cancer screening before a survival benefit is observed.

OBJECTIVES To describe lengths of stay among nursing home decedents. DESIGN Retrospective cohort study. SETTING The Health and Retirement Study (HRS), a nationally representative survey of U.S. adults aged 50 and older. PARTICIPANTS 1,817 nursing home residents who died between 1992 and 2006. MEASUREMENTS Our primary outcome was length of stay, defined as the number of months between the nursing home admission and the date of death. Covariates included demographic, social, and clinical factors drawn from the HRS interview conducted closest to the date of nursing home admission. RESULTS The mean age of decedents was 83.3 (SD 9.0) and the majority were female (59.12%), and White (81.5%). Median and mean length of stay prior to death were 5 months (IQR 1-20) and 13.7 months (SD 18.4), respectively. Fifty-three percent died within 6 months of placement. Large differences in median length of stay were observed by gender (men, 3 months vs. women, 8 months) and net worth (highest quartile, 3 months vs. lowest quartile, 9 months) (all p<.001). These differences persisted after adjustment for age, sex, marital status, net worth, geographic region, and diagnosed chronic conditions (cancer, hypertension, diabetes, lung disease, heart disease, and stroke). CONCLUSION Nursing home lengths of stay are brief for the majority of decedents. Lengths of stay varied markedly by factors related to social support.

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BackgroundDiabetes mellitus is a potent risk factor for urinary incontinence. Previous studies of incontinence in patients with diabetes have focused on younger, healthier patients. Our objective was to characterize risk factors for urinary incontinence among frail older adults with diabetes mellitus in a real-world clinical setting.MethodsWe performed a cross-sectional analysis on enrollees at On Lok (the original Program for All-Inclusive Care of the Elderly) between October 2004 and December 2010. Enrollees were community-dwelling, nursing home-eligible older adults with diabetes mellitus (N = 447). Our outcome was urinary incontinence measures (n = 2602) assessed every 6 months as “never incontinent”, “seldom incontinent” (occurring less than once per week), or “often incontinent” (occurring more than once per week). Urinary incontinence was dichotomized (“never” versus “seldom” and “often” incontinent). We performed multivariate mixed effects logistic regression analysis with demographic (age, gender and ethnicity), geriatric (dependence on others for ambulation or transferring; cognitive impairment), diabetes-related factors (hemoglobin A1c level; use of insulin and other glucose-lowering medications; presence of renal, ophthalmologic, neurological and peripheral vascular complications), depressive symptoms and diuretic use.ResultsThe majority of participants were 75 years or older (72%), Asian (65%) and female (66%). Demographic factors independently associated with incontinence included older age (OR for age >85, 3.13, 95% CI: 2.15-4.56; Reference: Age <75) and African American or other race (OR 2.12, 95% CI: 1.14-3.93; Reference: Asian). Geriatric factors included: dependence on others for ambulation (OR 1.48, 95% CI: 1.19-1.84) and transferring (OR 2.02, 95% CI: 1.58-2.58) and being cognitively impaired (OR 1.41, 95% CI: 1.15-1.73). Diabetes-related factors associated included use of insulin (OR 2.62, 95% CI: 1.67-4.13) and oral glucose-lowering agents (OR 1.81, 95% CI: 1.33-2.45). Urinary incontinence was not associated with gender, hemoglobin A1c level or depressive symptoms.ConclusionsGeriatric factors such as the inability to ambulate or transfer independently are important predictors of urinary incontinence among frail older adults with diabetes mellitus. Clinicians should address mobility and cognitive impairment as much as diabetes-related factors in their assessment of urinary incontinence in this population.

We have developed and validated a model for describing pain over the course of labor. Our model is suited to the statistical analysis of covariance and could potentially be used to compare the effects of covariants on labor pain and the rate of change of pain.