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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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Objectives

To determine the incidence of incisional hernia (IH) in the extraction incision (EI) in colorectal resection for cancer. To analyze whether the location of the incision has any relationship with the incidence of hernias and whether mesh could be useful for prevention in high-risk patients.

Methods

Retrospective review of the colon and rectal surgery database from January 2015 to December 2016. Data were classified into 2 groups, transverse (TI) and midline incision (MI), and the latter was divided into 2 subgroups (mesh [MIM] and suture [MIS]). Patients were classified using the HERNIAscore. Hernias were diagnosed by clinical and/or CT examination.

Results

A total of 182 out of 210 surgical patients were included. After a median follow-up of 13.0 months, 39 IH (21.9%) were detected, 23 of which (13.4%) were in the EI; their frequency was lower in the TI group (3.4%) and in the MIM group (5.9%) than in the MIS group (29.5%; p = 0.007). The probability of developing IH in the MIS group showed an OR = 11.7 (95%CI: 3.3-42.0) compared to the TI group and 4.3 (IC 95%: 1.1-16.3) versus the MIM group.

Conclusions

The location of the incision is relevant to avoid incisional hernias. Transverse incisions should be used as the first option. When a midline incision is needed, a prophylactic mesh could be considered in high risk patients because it is safe and associated with low morbidity.  相似文献   
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