Association of Early Kidney Allograft Failure with Preformed IgA Antibodies to β2-Glycoprotein I

In the current immunosuppressive therapy era, vessel thrombosis is the most common cause of early graft loss after renal transplantation. The prevalence of IgA anti–β₂-glycoprotein I antibodies (IgA-aB2GPI-ab) in patients on dialysis is elevated (>30%), and these antibodies correlate with mortality and cardiovascular morbidity. To evaluate the effect of IgA-aB2GPI-ab in patients with transplants, we followed all patients transplanted from 2000 to 2002 in the Hospital 12 de Octubre prospectively for 10 years. Presence of IgA-aB2GPI-ab in pretransplant serum was examined retrospectively. Of 269 patients, 89 patients were positive for IgA-aB2GPI-ab (33%; group 1), and the remaining patients were negative (67%; group 2). Graft loss at 6 months post-transplant was significantly higher in group 1 (10 of 89 versus 3 of 180 patients in group 2; P=0.002). The most frequent cause of graft loss was thrombosis of the vessels, which was observed only in group 1 (8 of 10 versus 0 of 3 patients in group 2; P=0.04). Multivariate analysis showed that the presence of IgA-aB2GPI-ab was an independent risk factor for early graft loss (P=0.04) and delayed graft function (P=0.04). There were no significant differences regarding patient survival between the two groups. Graft survival was similar in both groups after 6 months. In conclusion, patients with pretransplant IgA-aB2GPI-ab have a high risk of early graft loss caused by thrombosis and a high risk of delayed graft function. Therefore, pretransplant IgA-aB2GPI-ab may have a detrimental effect on early clinical outcomes after renal transplantation.     

Esophagectomy with Ileocoloplasty,Last Treatment for a Leak After Laparoscopic Sleeve: “From Less to More”

Obesity Surgery - Laparoscopic sleeve gastrectomy (LSG) is increasingly playing a key role in obesity management. Such operations, however, carry complications sometimes including leaks. The...     

Bone Microarchitecture Phenotypes Identified in Older Adults Are Associated With Different Levels of Osteoporotic Fracture Risk

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).