2-Deoxy-2-[F-18]fluoro-D-glucose Joint Uptake on Positron Emission Tomography Images: Rheumatoid Arthritis Versus Osteoarthritis

Purpose: Previous positron emission tomography (PET) studies have shown increased 2-deoxy-2-[18F]fluoro-D-glucose (FDG) uptake in joints of patients with osteoarthritis (OA) and inflamed joints of patients with rheumatoid arthritis (RA). This study compares FDG uptake in joints of RA and OA patients and FDG-uptake with clinical signs of inflammation. Procedures: FDG-PET scans of hands and wrists were performed in patients with RA and primary OA. PET data were compared with clinical data. Results: 29 % of RA joints and 6 % of OA joints showed elevated FDG-uptake. The level of uptake in PET-positive OA joints was not significantly different from that in RA joints. The majority of PET results of RA joints corresponded with clinical findings. Clinical synovitis was found some OA joints with FDG-uptake. Conclusions: FDG-uptake was observed in the majority of clinically inflamed RA joints and in a few OA joints with no significant difference in uptake level. The latter may be due to secondary synovitis

Do waiting times matter in primary care? GP visits and list sizes in England

This paper is largely motivated by the empirical observation that GP visits per person under the NHS have increased in England since the mid-1970s, while list sizes have decreased over the same period A hypothesis consistent with this observation is that larger list sizes are associated with longer waiting times, which reduce the demand for GP visits. Using a time series of repeated cross sections from 1972 to 2004, we construct a pseudopanel of synthetic individuals and find very little evidence that list sizes affect visit frequencies. While there are mild associations consistent with the waiting-time hypothesis among working-age women, there are none for men or the elderly, and no associations are robust to the cohort analysis. The demand for GP visits is most likely driven by health status, and for women, childbirth

Goods versus characteristics: revealed preference procedures for nested models

This paper compares the goods and characteristics models of the consumer within a traditional demand framework. We examine the nonparametric revealed preference conditions for the goods and characteristics models, and we develop a methodology for testing nested models of this class using nonparametric revealed preference techniques. Of primary interest is to make a comparison on the basis of predictive success, which requires that we develop a method to relate set predictions across models. This allows us to nonparametrically identify the model which best fits the data, and in doing so, to identify the value added by the characteristics structure in explaining consumer behavior. We then explore the effects of hypothetical price variation as implied by our findings in order to nonparametrically bound any comparative statics of interest. We implement these procedures on household panel data from the UK milk market. The primary result is that the better fit of the characteristics model is entirely attributable to dimension reduction