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A second strength of this study is that patients enrolled in the registry did not differ in obvious ways from a random sample of fracture patients.
In Denmark, Vestergaard et al. [ 14] examined a small random sample of fracture reports registered by ICD-codes from a national database and found the accuracy of fracture reports to be as high as 97%.
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The analysis aims to identify the most likely number of these latent classes in the population, given the selected sample of fractures and the agreement data collected among the various raters.
Stratified samples of fracture fillings were collected to measure saturated hydraulic conductivity (Ks), water retention curves and basic physicochemical properties.
To illustrate this, we have described a percolation test conducted on a sample of fractured granite (natural fracture showing signs of hydrothermal circulation).
When samples of fracture-coating material were separated into fractions with different specific gravity, there was a clear indication of radionuclide association with mineral groups.
The comparability with Ray and colleagues' results is reassuring, since their study used Medicare claims data to identify fractures and also compared a sample of identified fractures with medical records.
However, hip fractures were validated using hospital admission data and a sample of other fractures (wrist/forearm and clinical spine) were confirmed by patient-reported data within a prospective cohort study including almost 3,500 patients.
Van Staa et al. (2001) reported a similar tendency, with leveling off in the very elderly, in a large sample of wrist fractures (46,947).
A suit of fifteen actual core samples free of fractures was extracted from three wells A, B and C of an actual shaly sandstone oil reservoir.
Before retrieval of registry information, a sample of 50 atypical fractures and 50 control fractures was randomly selected for reclassification.
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