Objective. To analyze whether acute care patients with dementia are more or less likely to receive each of five aggressive medical services near the end of life, compared with patients without dementia. Data Sources. Two years of Veterans Affairs (VA) and Medicare utilization data for all 169,036 VA users nationwide age 67 and older who died between October 1, 1999 and September 30, 2001. Study Design. We performed a retrospective analysis of acute care stays discharged in the final 30 days of life. The main outcome measure was the patient's likelihood of receiving each of five aggressive services (intensive care unit [ICU] admission, ventilator, cardiac catheterization, pulmonary artery monitor, and dialysis), controlling for demographic and clinical factors in probit regressions. Principal Findings. There were 122,740 acute-stay discharges during the final 30 days of life, representing 94,100 unique patients (31,654 with dementia). In probit models comparing acute care patients with and without dementia, patients with dementia were 7.5 percentage points less likely to be admitted to the ICU (95 percent confidence interval [CI], 6.9-8.1; percent of stays with ICU admission 5 36.8 percent), 5.4 percentage points less likely to be placed on a ventilator (95 percent CI, 5.0-5.9; percent of stays with ventilator use 5 17.1 percent), 0.7 percentage points less likely to receive cardiac catheterization (95 percent CI, 0.6-0.8; percent of stays with cardiac catheterization 5 2.7 percent), 1.4 percentage points less likely to receive pulmonary artery monitoring (95 percent CI, 1.2-1.5; percent of stays with pulmonary artery monitoring 5 2.6 percent), and 0.6 percentage points less likely to receive dialysis (95 percent CI, 0.4-0.8; percent of stays with dialysis 5 4.6 percent). Conclusions. During the final 30 days of life, acute care patients with dementia are treated substantially less aggressively than patients without dementia. Further research is warranted to determine the causes and appropriateness of these patterns of care.Key Words. Acute inpatient care, end-of-life decisions, VA health care system, administrative data uses r Health Research and Educational Trust

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Using stellar population models, we predicted that the Dark Energy Survey (DES)due to its special combination of area (5000 deg.sq.) and depth (i = 24.3) -would be in the position to detect massive ( 10 11 M ) galaxies at z ∼ 4. We confront those theoretical calculations with the first ∼ 150 deg. sq. of DES data reaching nominal depth. From a catalogue containing ∼ 5 million sources, ∼ 26000 were found to have observed-frame g−r vs r−i colours within the locus predicted for z ∼ 4 massive galaxies. We further removed contamination by stars and artefacts, obtaining 606 galaxies lining up by the model selection box. We obtained their photometric redshifts and physical properties by fitting model templates spanning a wide range of star formation histories, reddening and redshift. Key to constrain the models is the addition, to the optical DES bands g, r, i, z, and Y , of near-IR J, H, K s data from the Vista Hemisphere Survey. We further applied several quality cuts to the fitting results, including goodness of fit and a unimodal redshift probability distribution. We finally select 233 candidates whose photometric redshift probability distribution function peaks around z ∼ 4, have high stellar masses (log(M * /M ) ∼ 11.7 for a Salpeter IMF) and ages around 0.1 Gyr, i.e. formation redshift around 5. These properties match those of the progenitors of the most massive galaxies in the local universe. This is an ideal sample for spectroscopic follow-up to select the fraction of galaxies which is truly at high redshift. These initial results and those at the survey completion, which we shall push to higher redshifts, will set unprecedented constraints on galaxy formation, evolution, and the re-ionisation epoch.

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Abstract-We investigated the determinants of inpatient rehabilitation costs in the Department of Veterans Affairs (VA) and examined the relationship between length of stay (LOS) and discharge costs using data from VA and community rehabilitation hospitals. We estimated regression models to identify patient characteristics associated with specialized inpatient rehabilitation costs. VA data included 3,535 patients discharged from 63 facilities in fiscal year 2001. We compared VA costs to community rehabilitation hospitals using a sample from the Uniform Data System for Medical Rehabilitation of 190,112 patients discharged in 1999 from 697 facilities. LOS was a strong predictor of cost for VA and non-VA hospitals. Functional status, measured by Functional Independence Measure (FIM) scores at admission, was statistically significant but added little explanatory value after controlling for LOS. Although FIM scores were associated with LOS, FIM scores accounted for little variance in cost after controlling for LOS. These results are most applicable to researchers conducting cost-effectiveness analyses.