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Prevalence of osteoporosis is more than 50% in older adults, yet current clinical methods for diagnosis that rely on areal bone mineral density (aBMD) fail to detect most individuals who have a fragility fracture. Bone fragility can manifest in different forms, and a “one-size-fits-all” approach to diagnosis and management of osteoporosis may not be suitable. High-resolution peripheral quantitative computed tomography (HR-pQCT) provides additive information by capturing information about volumetric density and microarchitecture, but interpretation is challenging because of the complex interactions between the numerous properties measured. In this study, we propose that there are common combinations of bone properties, referred to as phenotypes, that are predisposed to different levels of fracture risk. Using HR-pQCT data from a multinational cohort (n = 5873, 71% female) between 40 and 96 years of age, we employed fuzzy c-means clustering, an unsupervised machine-learning method, to identify phenotypes of bone microarchitecture. Three clusters were identified, and using partial correlation analysis of HR-pQCT parameters, we characterized the clusters as low density, low volume, and healthy bone phenotypes. Most males were associated with the healthy bone phenotype, whereas females were more often associated with the low volume or low density bone phenotypes. Each phenotype had a significantly different cumulative hazard of major osteoporotic fracture (MOF) and of any incident osteoporotic fracture (p < 0.05). After adjustment for covariates (cohort, sex, and age), the low density followed by the low volume phenotype had the highest association with MOF (hazard ratio = 2.96 and 2.35, respectively), and significant associations were maintained when additionally adjusted for femoral neck aBMD (hazard ratio = 1.69 and 1.90, respectively). Further, within each phenotype, different imaging biomarkers of fracture were identified. These findings suggest that osteoporotic fracture risk is associated with bone phenotypes that capture key features of bone deterioration that are not distinguishable by aBMD. © 2021 American Society for Bone and Mineral Research (ASBMR).  相似文献   
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Abstract

Objectives: This study examined word use as an indicator of interpersonal positive reframing in daily conversations of couples coping with breast cancer and as a predictor of stress.

Design: The Electronically Activated Recorder (EAR) and Linguistic Inquiry and Word Count (LIWC) were used to examine naturally occurring word use conceptually linked to positive reframing (positive emotion, negative emotion, and cognitive processing words).

Sample: Fifty-two couples coping with breast cancer.

Methods: Couples wore the EAR, a device participants wear, that audio-recorded over one weekend (>16,000 sound files), and completed self-reports of positive reframing (COPE) and stress (Perceived Stress Scale). LIWC, a software program, measured word use.

Findings: Both partners’ word use (i.e., positive emotion and cognitive processing words) was associated with their own reported positive reframing, and spouses’ word use was also indicative of patients’ positive reframing. Results also revealed that, in general, words indicating positive reframing predicted lower levels of stress.

Conclusions: Findings supported the hypothesis that partners—and particularly spouses of breast cancer patients—may assist each other’s coping by positively reframing the cancer experience and other negative experiences in conversation.  相似文献   
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