ObjectivesThe aim of this study was to investigate the impact of adrenal venous sampling (AVS) lateralization cutoffs on surgical outcomes.Patients and MethodsCosyntropin-stimulated AVS was used to guide surgical management of 377 patients with primary aldosteronism (PA) who were evaluated 6 months after surgery.Main Outcome MeasuresThe proportion of patients that achieved clinical benefit and complete biochemical success based on the AVS aldosterone lateralization index (LI) was determined.ResultsClinical benefit was achieved in 29 of 47 patients with an LI between 2 and 4, in 66 of 101 with an LI between 4 and 10, and in 158 of 203 with an LI > 10 (P < 0.01 for trend). Complete biochemical success was achieved in 27 of 42 with an LI between 2 and 4, in 60 of 76 with an LI between 4 and 10, and in 127 of 155 with an LI > 10 (P = 0.024 for trend). After adjustment for confounders and using those patients with an LI between 2 and 4 as a reference, a clinical benefit was associated only with those with an LI > 10 (OR, 2.30; 95% CI, 1.03 to 5.16), whereas complete biochemical success was associated with those with an LI between 4 and 10 (OR, 2.83; 95% CI, 1.14 to 7.01) or LI > 10 (OR, 3.55; 95% CI, 1.47 to 8.55).ConclusionsDifference of clinical outcome was relatively small when strict LI diagnostic threshold was used; biochemical cure was sufficiently achieved when an LI > 4 was used. Our study by standardized outcome measures validated that an LI > 4 may be appropriate for determining unilateral disease in PA.

FALLING is a major health concern among elderly people because it increases the incidence of fractures and causes a deterioration in mobility. It is reported that one in three people over 65 years of age fall at least once per year and that half of elderly people over 80 years of age experience at least one fall per year [1][2][3]. Moreover, the severity of fall-related complications increases with aging. Fractures are one of the most serious fall-related injuries and can lead to a loss of independence through disability and fear of falling. The reduction in mobility and independence is a serious issue in aging societies because it often results in admission to a hospital or nursing home and can potentially result in premature death. Additionally, diabetes mellitus (DM) is known to be associated with an Department of Medicine, Diabetes, Metabolism and Endocrinology, Matsuyama Red Cross Hospital, Japan Abstract. Diabetes mellitus is associated with an increased risk of falls, which increases the incidence of osteoporotic fractures and accordingly decreases quality of life. However, the association between fall risk and diabetic complications is not completely understood. Therefore, the aim of this study was to examine the association between fall risk and osteoporotic fractures in patients with type 2 diabetes mellitus (T2DM). We enrolled 194 Japanese patients with T2DM and assessed their fall risk using a brief interview form that included five items covering physical and social aspects of functioning and environmental factors. We examined the associations between fall risk and the presence of diabetic complications, such as neuropathy, retinopathy, nephropathy, cardiovascular disease, cerebrovascular disease, peripheral artery disease (PAD), and osteoporotic fractures (including any fracture and vertebral fractures only). In the multivariate logistic regression analysis, a longer history of T2DM, the presence of neuropathy and PAD, and a history of any fractures were significantly and positively associated with the risk of falls. On the other hand, a lower body mass index, the presence of neuropathy, and the risk of falls were independently and positively associated with the risk of any fracture. When fractures were limited to vertebral fractures only, the association with the risk of falls remained significant. We found that the risk of falls and osteoporotic fractures were associated in patients with T2DM and that a brief screening test of the risk of falls was useful for assessing the risk of osteoporotic fractures.Key words: Fall, Osteoporosis, Fracture, Neuropathy, Type 2 diabetes mellitus increased risk of falling [4][5][6]. Therefore, it is no less important to assess the risk of falls in diabetic patients than it is in their non-diabetic counterparts. Osteoporosis has been recognized as one of the complications of DM. Accumulating evidence shows that patients with DM have an increased risk of osteoporotic fractures independently of their bone mineral density (BMD) [7][8][9]. Several meta-analyses ha...

Advanced glycation end products (AGEs) cause bone fragility due to deterioration in bone quality. We previously reported that AGE3 induced apoptosis and inhibited differentiation via increased transforming growth factor (TGF)-β signaling in osteoblastic cells. Additionally, we demonstrated that AGE3 increased apoptosis and sclerostin expression and decreased receptor activator of nuclear factor-κB ligand (RANKL) expression in osteocyte-like cells. However, it remains unclear whether TGF-β signaling is involved in the effects of AGEs on apoptosis and the expression of sclerostin and RANKL in osteocytes. Effects of AGE3 on apoptosis of mouse osteocyte-like MLO-Y4-A2 cells were examined by DNA fragmentation ELISA. Expression of TGF-β, sclerostin, and RANKL was evaluated using real-time PCR, Western blotting, and ELISA kits. To block TGF-β signaling, we used SD208, a TGF-β type I receptor kinase inhibitor. AGE3 (200 µg/mL) significantly increased apoptosis and mRNA expression of Sost, the gene encoding sclerostin, and decreased Rankl mRNA expression in MLO-Y4-A2 cells. AGE3 significantly increased the expression of TGF-β. Co-incubation of SD208 with AGE3 significantly rescued AGE3-induced apoptosis in a dose-dependent manner. Moreover, SD208 restored AGE3-increased mRNA and protein expression of sclerostin. In contrast, SD208 did not affect AGE3-decreased mRNA and protein expression of RANKL. These findings suggest that AGE3 increases apoptosis and sclerostin expression through increasing TGF-β expression in osteocytes, and that AGE3 decreases RANKL expression independent of TGF-β signaling.

Primary aldosteronism (PA) is associated with an increased risk of cardiometabolic diseases, especially in unilateral subtype. Despite its high prevalence, the case detection rate of PA is limited, partly because of no clinical models available in general practice to identify patients highly suspicious of unilateral subtype of PA, who should be referred to specialized centers. The aim of this retrospective cross-sectional study was to develop a predictive model for subtype diagnosis of PA based on machine learning methods using clinical data available in general practice. Overall, 91 patients with unilateral and 138 patients with bilateral PA were randomly assigned to the training and test cohorts. Four supervised machine learning classifiers; logistic regression, support vector machines, random forests (RF), and gradient boosting decision trees, were used to develop predictive models from 21 clinical variables. The accuracy and the area under the receiver operating characteristic curve (AUC) for predicting of subtype diagnosis of PA in the test cohort were compared among the optimized classifiers. Of the four classifiers, the accuracy and AUC were highest in RF, with 95.7% and 0.990, respectively. Serum potassium, plasma aldosterone, and serum sodium levels were highlighted as important variables in this model. For feature-selected RF with the three variables, the accuracy and AUC were 89.1% and 0.950, respectively. With an independent external PA cohort, we confirmed a similar accuracy for feature-selected RF (accuracy: 85.1%). Machine learning models developed using blood test can help predict subtype diagnosis of PA in general practice.

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