Publications by authors named "W Arend"

Purpose: Pain is a common symptom following proximal femoral fractures (PFF), however, information on its treatment in terms of agents and type of use (scheduled vs. pro re nata [PRN]) is scarce. The main objective of this study was to examine pain medication regimens according to pain intensity following PFF.

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Unlabelled: We examined incidence rates (IR) for all distal radius fracture (DRF) events based on inpatient and outpatient data from a large statutory health insurance in Germany. Of all DRF, 56% were treated as inpatients, and thus, 44% treated as outpatients. IR were higher in women than in men.

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Aims: Several instruments are used to identify depression among patients with diabetes and have been compared for their test criteria, but, not for the overlaps and differences, for example, in the sociodemographic and clinical characteristics of the individuals identified with different instruments.

Methods: We conducted a cross-sectional survey among a random sample of a statutory health insurance (SHI) (n = 1,579) with diabetes and linked it with longitudinal SHI data. Depression symptoms were identified using either the Centre for Epidemiological Studies Depression (CES-D) scale or the Patient Health Questionnaire-9 (PHQ-9), and a depressive disorder was identified with a diagnosis in SHI data, resulting in 8 possible groups.

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Unlabelled: Our study demonstrates a strong increase in utilization of inpatient health care and clear excess costs in older people in the first year after pelvic fracture, the latter even after adjustment for several confounders. Excess costs were particularly high in the first few months and mainly attributable to inpatient treatment.

Introduction: We aimed to estimate health care utilization and excess costs in patients aged minimum 60 years up to 1 year after pelvic fracture compared to a population without pelvic fracture.

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Background: Low response rates do not indicate poor representativeness of study populations if non-response occurs completely at random. A non-response analysis can help to investigate whether non-response is a potential source for bias within a study.

Methods: A cross-sectional survey among a random sample of a health insurance population with diabetes (n = 3642, 58.

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