Background: We aimed to investigate whether densitometry results and volumetric bone mineral density (vBMD) can predict vertebral fragility fractures (VFF) in postmenopausal women.Methods: We enrolled 271 postmenopausal women aged >45 years who visited our hospital for health check-ups between September 2016 and September 2017. The lumbar spine (LS) and femoral neck (FN) densitometry results and trabecular bone score (TBS) were calculated using dual energy X-ray absorptiometry. vBMD was assessed using central quantitative computed tomography (cQCT). Baseline and follow-up X-ray images were reviewed to evaluate thoracolumbar vertebral compression fractures (CFs), according to the Genant criteria.Results: At baseline, 76 patients (28.0%) had CF. Additional or progressive fractures were noted in 26 participants (9.6%) with a median follow-up of 19.5 months. The median TBS and cQCT were significantly higher in participants without baseline CF than those with baseline CF (p<0.001). During the follow-up, Kaplan–Meier analysis showed that T-scores of the LS and FN <-2.5, degraded microarchitecture based on the TBS (≤1.200), and vBMD <80 mg/cm3 was significantly associated with future osteoporotic CF. The final multivariate Cox regression analysis showed that baseline CF and low TBS and vBMD were significant risk factors for future VFF.Conclusions: Participants with baseline CF and degraded microarchitecture had higher CF predisposition. Moreover, cQCT can predict future vertebral fractures.

Aims: To compare the efficacy and safety of adding low‐dose lobeglitazone (0.25 mg/day) or standard‐dose lobeglitazone (0.5 mg/day) to patients with type 2 diabetes mellitus (T2DM) with inadequate glucose control on metformin and dipeptidyl peptidase (DPP4) inhibitor therapy. Materials and Methods: In this phase 4, multicentre, double‐blind, randomized controlled, non‐inferiority trial, patients with T2DM insufficiently controlled by metformin and DPP4 inhibitor combination therapy were randomized to receive either low‐dose or standard‐dose lobeglitazone. The primary endpoint was non‐inferiority of low‐dose lobeglitazone in terms of glycaemic control, expressed as the difference in mean glycated haemoglobin levels at week 24 relative to baseline values and compared with standard‐dose lobeglitazone, using 0.5% non‐inferiority margin. Results: At week 24, the mean glycated haemoglobin levels were 6.87 ± 0.54% and 6.68 ± 0.46% in low‐dose and standard‐dose lobeglitazone groups, respectively ( p = .031). The between‐group difference was 0.18% (95% confidence interval 0.017‐0.345), showing non‐inferiority of the low‐dose lobeglitazone. Mean body weight changes were significantly greater in the standard‐dose group (1.36 ± 2.23 kg) than in the low‐dose group (0.50 ± 1.85 kg) at week 24. The changes in HOMA‐IR, lipid profile and liver enzyme levels showed no significant difference between the groups. Overall treatment‐emergent adverse events (including weight gain, oedema and hypoglycaemia) occurred more frequently in the standard‐dose group. Conclusions: Adding low‐dose lobeglitazone to metformin and DPP4 inhibitor combination resulted in a non‐inferior glucose‐lowering outcome and fewer adverse events compared with standard‐dose lobeglitazone. Therefore, low‐dose lobeglitazone might be one option for individualized strategy in patients with T2DM.

Myungsoo Im, Doohwa Kim, Soree Ryang and Bo Hyun Kim. Int J Thyroidol 2023;16:134-8. https://doi.org/10.11106/ijt.2023.16.1.134

Parathyroid carcinoma (PC) in cases of secondary or tertiary hyperparathyroidism is relatively uncommon, and only a few case reports have described this entity. Although some papers have reported patients with one or two parathyroid malignancies, multiple PC–especially three or more–have been even more rarely reported. Herein, we report a case of secondary hyperparathyroidism due to multiple PCs in a chronic hemodialysis patient. A 54-year-old man with end-stage kidney disease was referred for hyperparathyroidism. He had been diagnosed with chronic kidney disease in 2001 and had begun hemodialysis in 2009. In laboratory tests, intact parathyroid hormone (iPTH) was markedly elevated to 1,144.1 pg/mL (normal range: 15.0–68.3 pg/mL) and serum calcium was mildly elevated to 10.56 mg/dL (normal range: 8.5–10.3 mg/dL). Ultrasonography showed hypoechoic nodules in the posterior part of both thyroid glands. All three nodules showed increased uptake on a 99mTc sestamibi scan. The patient underwent total parathyroidectomy with autotransplantation to the right forearm. Histopathology findings showed three PCs with capsular invasion and one parathyroid hyperplasia. In the immediate postoperative period, the iPTH level dropped from 1,446.8 to 82.4 pg/dL and, after 1 month, to 4.0 pg/dL. This patient needed oral calcium carbonate and active vitamin D to maintain appropriate serum calcium levels. Although multiple PCs are rare, they can cause secondary hyperparathyroidism. Therefore, clinicians should suspect multiple PCs when patients’ serum iPTH levels are exceptionally high. Additionally, since PCs could occur in multiple glands, autotransplantation of the parathyroid gland after parathyroidectomy should be done carefully.

Primary adrenal leiomyosarcoma (PAL) is an aggressive, rare tumor that is frequently diagnosed at an advanced stage. We report the case of a 65-year-old female patient with hypertension who presented with stabbing lower abdominal pain and unintentional weight loss. Abdominal computed tomography (CT) demonstrated a 10.4×8.2×8.1 cm heterogeneous left adrenal mass without biochemical evidence of hormonal hypersecretion. Retroperitoneal left adrenalectomy was performed without complications, and histopathological examination confirmed a moderately differentiated adrenal leiomyosarcoma. The patient was followed at the outpatient oncology clinic for 5 years with no evidence of recurrence. Seven years after the initial surgery, a newly detected left suprarenal mass was identified on imaging. Abdominal CT revealed a new, well-circumscribed 7.1×6.4×6.2 cm heterogeneous mass. Laparoscopic resection of the recurrent mass was performed. Pathological examination again revealed a moderately differentiated leiomyosarcoma with positive surgical margins but no lymphovascular invasion. Immunohistochemical staining was positive for smooth muscle actin, desmin, h-caldesmin, neuron-specific enolase, and synaptophysin, findings consistent with recurrent adrenal leiomyosarcoma. This case demonstrates that PAL can recur locally after prolonged disease-free intervals, underscoring the importance of extended surveillance, potentially beyond 10 years.

Background/Objectives: Type 2 diabetes (T2D) develops gradually over many years through a prolonged preclinical phase, yet traditional static risk scores often fail to capture these dynamic metabolic trajectories. We propose a longitudinal deep learning framework to predict the 10-year risk of Type 2 diabetes onset defined by comprehensive ADA criteria by modeling the physiological acceleration of routine clinical biomarkers. Methods: Utilizing an 18-year longitudinal dataset from the community-based Korean Genome and Epidemiology Study (KoGES) cohort, we selected $N=4354$ participants with complete follow-up records, ensuring high data integrity without requiring synthetic data augmentation. We constructed a 3-dimensional tensor of 21 non-invasive clinical variables spanning a 6-year observation window. To resolve the inherent precision-recall trade-offs of individual models, we developed a stacking ensemble that integrates Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) architectures via a logistic regression meta-learner. To evaluate the added value of longitudinal modeling, we compared this dynamic framework against a static XGBoost baseline that only saw the most recent data. Results: Evaluated on an independent test set ($n=874$), the ensemble significantly outperformed baseline models, achieving an overall accuracy of 0.90 (95% CI: 0.88–0.92) and an AUROC of 0.94 (95% CI: 0.93–0.95). By harmonizing LSTM’s sensitivity and GRU’s precision, the model yielded an exceptional Positive Predictive Value (PPV) of 0.97, a sensitivity of 0.80, and a specificity of 0.98. Conclusions: This framework provides a highly accurate, resource-efficient triage instrument for T2D screening, thereby reducing unnecessary clinical alerts and improving screening efficiency.