Bone Loss after Solid Organ Transplantation: A Review of Organ-Specific Considerations.

This review article investigates solid organ transplantation-induced osteoporosis, a critical yet often overlooked issue, emphasizing its significance in post-transplant care. The initial sections provide a comprehensive understanding of the prevalence and multifactorial pathogenesis of transplantation osteoporosis, including factors such as deteriorating post-transplantation health, hormonal changes, and the impact of immunosuppressive medications. Furthermore, the review is dedicated to organ-specific considerations in transplantation osteoporosis, with separate analyses for kidney, liver, heart, and lung transplantations. Each section elucidates the unique challenges and management strategies pertinent to transplantation osteoporosis in relation to each organ type, highlighting the necessity of an organ-specific approach to fully understand the diverse manifestations and implications of transplantation osteoporosis. This review underscores the importance of this topic in transplant medicine, aiming to enhance awareness and knowledge among clinicians and researchers. By comprehensively examining transplantation osteoporosis, this study contributes to the development of improved management and care strategies, ultimately leading to improved patient outcomes in this vulnerable group. This detailed review serves as an essential resource for those involved in the complex multidisciplinary care of transplant recipients.

Protein Signatures of Parathyroid Adenoma according to Tumor Volume and Functionality.

BACKGRUOUND: Parathyroid adenoma (PA) is a common endocrine disease linked to multiple complications, but the pathophysiology of the disease remains incompletely understood. The study aimed to identify the key regulator proteins and pathways of PA according to functionality and volume through quantitative proteomic analyses. METHODS: We conducted a retrospective study of 15 formalin-fixed, paraffin-embedded PA samples from tertiary hospitals in South Korea. Proteins were extracted, digested, and the resulting peptides were analyzed using liquid chromatography-tandem mass spectrometry. Pearson correlation analysis was employed to identify proteins significantly correlated with clinical variables. Canonical pathways and transcription factors were analyzed using Ingenuity Pathway Analysis. RESULTS: The median age of the participants was 52 years, and 60.0% were female. Among the 8,153 protein groups analyzed, 496 showed significant positive correlations with adenoma volume, while 431 proteins were significantly correlated with parathyroid hormone (PTH) levels. The proteins SLC12A9, LGALS3, and CARM1 were positively correlated with adenoma volume, while HSP90AB2P, HLA-DRA, and SCD5 showed negative correlations. DCPS, IRF2BPL, and FAM98A were the main proteins that exhibited positive correlations with PTH levels, and SLITRK4, LAP3, and AP4E1 had negative correlations. Canonical pathway analysis demonstrated that the RAN and sirtuin signaling pathways were positively correlated with both PTH levels and adenoma volume, while epithelial adherence junction pathways had negative correlations. CONCLUSION: Our study identified pivotal proteins and pathways associated with PA, offering potential therapeutic targets. These findings accentuate the importance of proteomics in understanding disease pathophysiology and the need for further research.

A CT-based Deep Learning Model for Predicting Subsequent Fracture Risk in Patients with Hip Fracture.

Background Patients have the highest risk of subsequent fractures in the first few years after an initial fracture, yet models to predict short-term subsequent risk have not been developed. Purpose To develop and validate a deep learning prediction model for subsequent fracture risk using digitally reconstructed radiographs from hip CT in patients with recent hip fractures. Materials and Methods This retrospective study included adult patients who underwent three-dimensional hip CT due to a fracture from January 2004 to December 2020. Two-dimensional frontal, lateral, and axial digitally reconstructed radiographs were generated and assembled to construct an ensemble model. DenseNet modules were used to calculate risk probability based on extracted image features and fracture-free probability plots were output. Model performance was assessed using the C index and area under the receiver operating characteristic curve (AUC) and compared with other models using the paired t test. Results The training and validation set included 1012 patients (mean age, 74.5 years ± 13.3 [SD]; 706 female, 113 subsequent fracture) and the test set included 468 patients (mean age, 75.9 years ± 14.0; 335 female, 22 subsequent fractures). In the test set, the ensemble model had a higher C index (0.73) for predicting subsequent fractures than that of other image-based models (C index range, 0.59-0.70 for five of six models; P value range, < .001 to < .05). The ensemble model achieved AUCs of 0.74, 0.74, and 0.73 at the 2-, 3-, and 5-year follow-ups, respectively; higher than that of most other image-based models at 2 years (AUC range, 0.57-0.71 for five of six models; P value range, < .001 to < .05) and 3 years (AUC range, 0.55-0.72 for four of six models; P value range, < .001 to < .05). Moreover, the AUCs achieved by the ensemble model were higher than that of a clinical model that included known risk factors (2-, 3-, and 5-year AUCs of 0.58, 0.64, and 0.70, respectively; P < .001 for all). Conclusion In patients with recent hip fractures, the ensemble deep learning model using digital reconstructed radiographs from hip CT showed good performance for predicting subsequent fractures in the short term. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Li and Jaremko in this issue.

A machine learning-assisted system to predict thyrotoxicosis using patients' heart rate monitoring data: a retrospective cohort study.

Previous studies have shown a correlation between resting heart rate (HR) measured by wearable devices and serum free thyroxine concentration in patients with thyroid dysfunction. We have developed a machine learning (ML)-assisted system that uses HR data collected from wearable devices to predict the occurrence of thyrotoxicosis in patients. HR monitoring data were collected using a wearable device for a period of 4 months in 175 patients with thyroid dysfunction. During this period, 3 or 4 thyroid function tests (TFTs) were performed on each patient at intervals of at least one month. The HR data collected during the 10 days prior to each TFT were paired with the corresponding TFT results, resulting in a total of 662 pairs of data. Our ML-assisted system predicted thyrotoxicosis of a patient at a given time point based on HR data and their HR-TFT data pair at another time point. Our ML-assisted system divided the 662 cases into either thyrotoxicosis and non-thyrotoxicosis and the performance was calculated based on the TFT results. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of our system for predicting thyrotoxicosis were 86.14%, 85.92%, 52.41%, and 97.18%, respectively. When subclinical thyrotoxicosis was excluded from the analysis, the sensitivity, specificity, PPV, and NPV of our system for predicting thyrotoxicosis were 86.14%, 98.28%, 94.57%, and 95.32%, respectively. Our ML-assisted system used the change in mean, relative standard deviation, skewness, and kurtosis of HR while sleeping, and the Jensen-Shannon divergence of sleep HR and TFT distribution as major parameters for predicting thyrotoxicosis. Our ML-assisted system has demonstrated reasonably accurate predictions of thyrotoxicosis in patients with thyroid dysfunction, and the accuracy could be further improved by gathering more data. This predictive system has the potential to monitor the thyroid function status of patients with thyroid dysfunction by collecting heart rate data, and to determine the optimal timing for blood tests and treatment intervention.

Sodium-Glucose Cotransporter 2 Inhibitors vs Incretin-Based Drugs and Risk of Fractures for Type 2 Diabetes.

Importance: Postmenopausal individuals with type 2 diabetes are susceptible to fractures due to the interaction of elevated blood glucose levels and a deficiency of the hormone estrogen. Despite continued concerns of fracture risks associated with sodium-glucose cotransporter 2 inhibitors (SGLT2i), existing evidence in this high-risk population is lacking. Objective: To assess the risk of fractures associated with SGLT2i vs incretin-based drugs of dipeptidyl-peptidase 4 inhibitors (DPP4i) and glucagon-like peptide 1 receptor agonists (GLP1RA), separately, in postmenopausal individuals with type 2 diabetes. Design, Setting, and Participants: This active-comparator, new-user cohort study used nationwide claims data of Korea and took place from January 1, 2013, to December 31, 2020. Postmenopausal individuals (aged ≥45 years) with type 2 diabetes were included. Exposures: New users of SGLT2i or comparator drugs. Main Outcomes and Measures: The primary outcome was overall fractures, comprising vertebral, hip, humerus, and distal radius fractures. Patients were followed up from the day after drug initiation until the earliest of outcome occurrence, drug discontinuation (90-day grace period) or switch, death, or end of the study period. After propensity score fine stratification, hazard ratios (HRs) with 95% CIs were estimated using weighted Cox models. Results: Among 37 530 (mean [SD] age, 60.6 [9.7] years) and 332 004 (mean [SD] age, 60.6 [9.9] years) new users of SGLT2i and DPP4i, respectively, a lower rate of incident overall fractures was presented with SGLT2i vs DPP4i (weighted HR, 0.78; 95% CI, 0.72-0.84). Among 111 835 (mean [SD] age, 61.4 [9.8] years) and 8177 (mean [SD] age, 61.1 [10.3] years) new users of SGLT2i and GLP1RA, respectively, no association with an increased risk of overall fractures was presented with SGLT2i vs GLP1RA (weighted HR, 0.92; 95% CI, 0.68-1.24). Results from several subgroup and sensitivity analyses presented consistent results from main analysis. Conclusions and relevance: This population-based cohort study suggests that SGLT2i was not associated with an increased rate of incident fractures compared with DPP4i and GLP1RA, separately, among postmenopausal individuals with type 2 diabetes.

Development and validation of common data model-based fracture prediction model using machine learning algorithm.

The need for an accurate country-specific real-world-based fracture prediction model is increasing. Thus, we developed scoring systems for osteoporotic fractures from hospital-based cohorts and validated them in an independent cohort in Korea. The model includes history of fracture, age, lumbar spine and total hip T-score, and cardiovascular disease. PURPOSE: Osteoporotic fractures are substantial health and economic burden. Therefore, the need for an accurate real-world-based fracture prediction model is increasing. We aimed to develop and validate an accurate and user-friendly model to predict major osteoporotic and hip fractures using a common data model database. METHODS: The study included 20,107 and 13,353 participants aged ≥ 50 years with data on bone mineral density using dual-energy X-ray absorptiometry from the CDM database between 2008 and 2011 from the discovery and validation cohort, respectively. The main outcomes were major osteoporotic and hip fracture events. DeepHit and Cox proportional hazard models were used to identify predictors of fractures and to build scoring systems, respectively. RESULTS: The mean age was 64.5 years, and 84.3% were women. During a mean of 7.6 years of follow-up, 1990 major osteoporotic and 309 hip fracture events were observed. In the final scoring model, history of fracture, age, lumbar spine T-score, total hip T-score, and cardiovascular disease were selected as predictors for major osteoporotic fractures. For hip fractures, history of fracture, age, total hip T-score, cerebrovascular disease, and diabetes mellitus were selected. Harrell's C-index for osteoporotic and hip fractures were 0.789 and 0.860 in the discovery cohort and 0.762 and 0.773 in the validation cohort, respectively. The estimated 10-year risks of major osteoporotic and hip fractures were 2.0%, 0.2% at score 0 and 68.8%, 18.8% at their maximum scores, respectively. CONCLUSION: We developed scoring systems for osteoporotic fractures from hospital-based cohorts and validated them in an independent cohort. These simple scoring models may help predict fracture risks in real-world practice.

Chronic airway disease as a major risk factor for fractures in osteopenic women: Nationwide cohort study.

Introduction: The study aimed to demonstrate the risk factors for fractures and to develop prediction models for major osteoporotic and hip fractures in osteopenic patients using the nationwide cohort study in South Korea. Methods: The study was a retrospective nationwide study using the national screening program for transitional ages from the National Health Insurance Services database in Korea from 2008 to 2019. Primary outcomes were incident fracture events of major osteoporotic and hip fractures. Major osteoporotic and hip fracture events were defined as diagnostic and procedural codes. Patients were followed until the fragility fractures, death, or 2019, whichever came first. Results: All participants were 66-year-old females, with a mean body mass index was 25.0 ± 3.1 kg/m2. During a median follow-up of 10.5 years, 26.9% and 6.7% of participants experienced major osteoporotic and hip fractures. In multivariate analysis, a history of fracture, chronic airway disease, falls, diabetes mellitus and cerebrovascular diseases were significant risk factors for major osteoporotic (hazard ratio [HR] 2.35 for a history of fracture; 1.17 for chronic airway disease; 1.10 for falls; 1.12 for diabetes mellitus; 1.11 for cerebrovascular disease) and hip fractures (HR 1.75 for a history of fracture; 1.54 for diabetes mellitus; 1.27 for cerebrovascular disease; 1.17 for fall; 1.15 for chronic airway disease). The performances of the prediction models were area under the receiver operating curve of 0.73 and 0.75 for major osteoporotic and hip fractures. Conclusion: The study presented prediction models of major osteoporotic and hip fractures for osteopenia patients using simple clinical features.

Fracture Liaison Service in Korea: 2022 Position Statement of the Korean Society for Bone and Mineral Research.

Osteoporosis and osteoporotic fractures cause socioeconomic concerns, and medical system and policies appear insufficient to prepare for these issues in Korea, where the older adult population is rapidly increasing. Many countries around the world are already responding to osteoporosis and osteoporotic fractures by adopting fracture liaison service (FLS), and such an attempt has only begun in Korea. In this article, we introduce the operation methods for institutions implementing FLS and characteristics of services, and activities of the FLS Committee for FLS implementation in the Korean Society for Bone and Mineral Research. In addition, we hope that the current position statement will contribute to the implementation of FLS in Korea and impel policy changes to enable a multidisciplinary and integrated FLS operated under the medical system.

In-depth proteomic signature of parathyroid carcinoma.

OBJECTIVE: Diagnosing parathyroid carcinoma (PC) is complicated and controversial that early diagnosis and intervention are often difficult. Therefore, we aimed to elucidate the protein signatures of PC through quantitative proteomic analyses to aid in the early and accurate diagnosis of PC. DESIGN: We conducted a retrospective cohort study. METHODS: We performed liquid chromatography with tandem mass spectrometry using formalin-fixed paraffin-embedded samples. For the analyses, 23 PC and 15 parathyroid adenoma (PA) tissues were collected from 6 tertiary hospitals in South Korea. RESULTS: The mean age of the patients was 52 years, and 63% were women. Proteomic expression profiling revealed 304 differentially expressed proteins (DEPs) with a cut-off of P < .05 and fold change >1.5. Among DEPs, we identified a set of 5 proteins that can discriminate PC from PA: carbonic anhydrase 4 (CA4), alpha/beta hydrolase domain-containing protein 14B (ABHD14B), laminin subunit beta-2 (LAMB2), CD44 antigen (CD44), and alpha-1-acid glycoprotein 1 (ORM1) that exhibited the highest area under the curve of 0.991 in neural network model. The nuclear percentage of CA4 and LAMB2 in immunohistochemistry was significantly lower in PC tissue than in the PA (CA4: 2.77 ± 1.96%, 26.2 ± 3.45%, P < .001; LAMB2: 6.86 ± 3.46%, 38.54 ± 4.13%, P < .001). The most enriched canonical pathways in PC included glycoprotein-6 signaling and mammalian target of rapamycin (mTOR). CONCLUSIONS: We identified key proteins differentially expressed between PC and PA using proteomic analyses of parathyroid neoplasms. These findings may help to diagnose PC accurately and elucidate potential therapeutic targets.

Risk of fracture in neuromyelitis optica spectrum disorder and multiple sclerosis: a nationwide cohort study in South Korea.

PURPOSE: Interest in fractures in patients with multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) has considerably increased in the last decade. However, few studies have compared the incidence of fractures between patients with MS and NMOSD using a nationwide database. This study aimed to evaluate the differences in the risk of fracture between patients with NMOSD and MS compared to that in healthy controls using cohort data from a Korean nationwide database. METHODS: In this retrospective cohort study, data from the National Health Insurance Service (NHIS) database from January 2010 to December 2017 were analyzed. A total of 1,217/1,329 patients with MS/NMOSD free of fractures at the index date were included. Matched controls were selected based on age, sex, and the presence of hypertension, diabetes mellitus, and dyslipidemia. The mean follow-up durations after the index date were 4.40/4.08 years for patients with MS/NMOSD and 4.73/4.28 for their matched controls. RESULTS: The adjusted hazard ratios (aHRs) with 95% confidence intervals of any, hip, and vertebral fractures were 1.81 (1.43-2.28), 3.36 (1.81-6.24), and 2.01 (1.42-2.99) times higher for patients with MS than for controls, respectively, and they were 1.85 (1.47-2.34), 3.82 (2.05-7.11), and 2.84 (1.92-4.21) times higher for patients with NMOSD than for controls, respectively. No significant differences were observed in the incidence of fractures between the MS and NMOSD groups. Patients with MS/NMOSD had a 1.8-fold higher risk of fracture than matched controls, and the risk of hip fracture was especially high (3- to 4-fold higher). CONCLUSIONS: Clinicians need to regularly assess patients with MS/NMOSD for the risk of fractures and take preventative measures to reduce it.

Residual risks of comorbidities after parathyroidectomy in a nationwide cohort of patients with primary hyperparathyroidism.

PURPOSE: Primary hyperparathyroidism (PHPT) is a common endocrine disorder with increasing incidence, while epidemiologic data in Asian population has been lacking. Therefore, we aimed to identify the incidence, prognosis, and prognostic factors of PHPT patients who underwent parathyroidectomy in Korea. METHODS: In this retrospective nationwide cohort, patients with PHPT were defined as those with diagnostic codes of PHPT and procedural codes for parathyroidectomy, excluding chronic renal failure or secondary hyperparathyroidism based on National Health Insurance Services database in Korea in 2002-2018. Main primary outcomes were all-cause mortality, cardiovascular, and cerebrovascular events. RESULTS: A total of 5561 patients were diagnosed with PHPT and had parathyroidectomy. The mean age was 54.5 years, and 71.8% were women. The age-standardized incidence was 10.1/100,000 person-year in 2018, rising from 1.7/100,000 person-year in 2002. During a mean of 5.9 years, history of cardiovascular disease, mood disorder, and genitourinary stone had increased risks of mortality with hazard ratios (HRs) of 1.59 (95% confidence interval [CI] 1.10-2.29), 1.43 (CI 1.14-1.80), and 1.40 (CI 1.09-1.80), respectively. History of hypertension, cerebrovascular disease, diabetes mellitus, and mood disorder were risk factors for cardiovascular events with HRs of 1.42 (CI 1.22-1.66), 1.29 (CI 1.05-1.58), 1.22 (CI 1.07-1.40), and 1.14 (CI 1.00-1.29), respectively. Mood disorder was a significant risk factor for cerebrovascular events (HR 1.30, CI 1.11-1.52). CONCLUSION: The incidence of PHPT patients who underwent parathyroidectomy has been rising in Korea as reported in other countries. Patients with complications, especially mood disorder, had increased cardiovascular and cerebrovascular events and mortality risks.

Fracture risk in Parkinson's disease according to its severity and duration.

Fracture risk was elevated in Parkinson's disease (PD) patients compared with controls in this nationwide study. Among PD patients, the risk of fracture increased linearly with PD severity, whereas no difference in fracture risk was observed according to PD duration. INTRODUCTION: Parkinson's disease (PD) is reported to be associated with a high risk of fractures. Several studies found an association between severity and duration of PD and falls or bone mineral density, but those factors have not been considered in most previous research. The aim of this study was to determine the fracture risk in PD patients according to their disease severity and duration. METHODS: This population-based, retrospective cohort study used data from the Korean National Health Insurance Service database. The study population included 10,333 patients with prevalent PD and 6,501,464 comparison cohort. Fracture risks according to the prevalence, severity, and duration of PD were evaluated using Cox proportional hazard methods. RESULTS: Fracture risk was elevated in PD patients at all sites compared with controls (adjusted hazard ratio [aHR] 1.49, 95% confidence interval [CI] 1.44-1.56 for any fracture). When comparing fracture sites, hip fractures showed the largest risk increase in PD patients (aHR 2.16, 95% CI 1.95-2.38). Among PD patients, the risk of any fracture increased linearly with PD severity and was highest in patients with severe disease (aHR 1.65, 95% CI 1.53-1.79 compared with controls). Meanwhile, no significant association was observed between PD duration and fracture risk. CONCLUSIONS: The prevalence of PD was related to an increased risk of fractures in this nationwide study, and PD severity was linearly associated with fracture risk. PD prevalence and severity should be considered when evaluating the risk factors of fracture in clinical practice.

Development of a Spine X-Ray-Based Fracture Prediction Model Using a Deep Learning Algorithm.

BACKGRUOUND: Since image-based fracture prediction models using deep learning are lacking, we aimed to develop an X-ray-based fracture prediction model using deep learning with longitudinal data. METHODS: This study included 1,595 participants aged 50 to 75 years with at least two lumbosacral radiographs without baseline fractures from 2010 to 2015 at Seoul National University Hospital. Positive and negative cases were defined according to whether vertebral fractures developed during follow-up. The cases were divided into training (n=1,416) and test (n=179) sets. A convolutional neural network (CNN)-based prediction algorithm, DeepSurv, was trained with images and baseline clinical information (age, sex, body mass index, glucocorticoid use, and secondary osteoporosis). The concordance index (C-index) was used to compare performance between DeepSurv and the Fracture Risk Assessment Tool (FRAX) and Cox proportional hazard (CoxPH) models. RESULTS: Of the total participants, 1,188 (74.4%) were women, and the mean age was 60.5 years. During a mean follow-up period of 40.7 months, vertebral fractures occurred in 7.5% (120/1,595) of participants. In the test set, when DeepSurv learned with images and clinical features, it showed higher performance than FRAX and CoxPH in terms of C-index values (DeepSurv, 0.612; 95% confidence interval [CI], 0.571 to 0.653; FRAX, 0.547; CoxPH, 0.594; 95% CI, 0.552 to 0.555). Notably, the DeepSurv method without clinical features had a higher C-index (0.614; 95% CI, 0.572 to 0.656) than that of FRAX in women. CONCLUSION: DeepSurv, a CNN-based prediction algorithm using baseline image and clinical information, outperformed the FRAX and CoxPH models in predicting osteoporotic fracture from spine radiographs in a longitudinal cohort.

Effect of Denosumab on the Change of Osteoclast Precursors Compared to Zoledronate Treatment in Postmenopausal Women with Osteoporosis.

BACKGROUND: A rapid increase in bone turnover and bone loss has been observed in response to the discontinuation of denosumab. It led to an acute increase in the fracture risk, similar to that observed in the untreated patients. We aimed to investigate the effect of denosumab on osteoclast (OC) precursor cells compared to that of zoledronate. METHODS: The study compared the effects of denosumab (60 mg/24-week) and zoledronate (5 mg/48-week) over 48 weeks in postmenopausal women with osteoporosis. From patients' peripheral mononuclear cells, CD14+/CD11b+/vitronectin receptor (VNR)- and CD14+/CD11b+/VNR+ cells were isolated using fluorescent-activated cell sorting, representing early and late OC precursors, respectively. The primary endpoint was the changes in OC precursors after 48 weeks of treatment. RESULTS: Among the 23 patients, 11 were assigned to the denosumab group and 12 to the zoledronate group (mean age, 69 years). After 48 weeks, the changes in OC precursors were similar between and within the groups. Serum C-terminal telopeptide of type I collagen levels were inversely correlated with OC precursor levels after denosumab treatment (r=-0.72, P<0.001). Lumbar spine, femur neck, and total hip bone mineral density (BMD) increased in both groups. Lumbar spine BMD increased more significantly in the denosumab group than in the zoledronate group. CONCLUSIONS: Denosumab and zoledronate treatments induced similar changes in OC precursors. During denosumab treatment, old age and suppressed bone turnover were associated with increased OC precursor cell populations. Further validation studies with prospective designs are required.

Effect of Vitamin D Supplementation on Risk of Fractures and Falls According to Dosage and Interval: A Meta-Analysis.

BACKGROUND: Although recent studies comparing various dosages and intervals of vitamin D supplementation have been published, it is yet to be elucidated whether there is an appropriate dose or interval to provide benefit regarding fracture risk. We aimed to assess the published evidence available to date regarding the putative beneficial effects of vitamin D supplements on fractures and falls according to various dosages and intervals. METHODS: We performed a meta-analysis of randomized controlled studies reporting associations between vitamin D supplementation and the risks of fractures and falls in PubMed, EMBASE, and Cochrane library. Studies with supplements of ergocalciferol or calcitriol, those with a number of event ≤10, or those with a follow-up duration of less than 6 months were also excluded. RESULTS: Thirty-two studies were included in the final analysis. Vitamin D supplementation with daily dose of 800 to 1,000 mg was associated with lower risks of osteoporotic fracture and fall (pooled relative risk [RR], 0.87; 95% confidence interval [CI], 0.78 to 0.97 and RR, 0.91; 95% CI, 0.85 to 0.98), while studies with <800 or >1,000 mg/day did not. Also, among intervals, daily administration of vitamin D was associated with the reduced risk of falls, while intermittent dose was not. Also, patients with vitamin D deficiency showed a significant risk reduction of falls after vitamin D supplementation. CONCLUSION: Daily vitamin D dose of 800 to 1,000 IU was the most probable way to reduce the fracture and fall risk. Further studies designed with various regimens and targeted vitamin D levels are required to elucidate the benefits of vitamin D supplements.

Association of androgen excess and bone mineral density in women with classical congenital adrenal hyperplasia with 21-hydroxylase deficiency.

The relationship between androgen excess and bone health in patients with congenital adrenal hyperplasia (CAH) with 21-hydroxylase (21-OH) deficiency is not fully understood. This study demonstrated positive correlations between androgen hormones and bone mineral density (BMD) in CAH women with 21-OH deficiency. PURPOSE: This study aims to assess BMD and its association with androgen excess in women with CAH. METHODS: We enrolled 92 women with CAH with 21-OH deficiency and retrospectively reviewed their clinical features, hormone concentrations, body composition, glucocorticoid (GC) dose, and BMD. RESULTS: BMD was not different according to the subtypes of CAH. BMD at the lumbar spine was lower in women with CAH with regular menstruation than those with irregular menstruation (1.081 vs. 1.165 g/cm2, P < 0.05). BMD was lower in women with CAH with 17-hydroxyprogesterone (17-OHP) < 10 ng/mL than in those with ≥ 10 ng/mL (lumbar spine, 1.019 vs. 1.150 g/cm2; femur neck, 0.806 vs. 0.899 g/cm2; total hip, 0.795 vs. 0.943 g/cm2; all P < 0.05). After adjusting for age and BMI in correlation analyses, testosterone concentrations were positively correlated with lumbar spine, femur neck, and total hip BMD (r = 0.46, r = 0.38, and r = 0.35, respectively; all P < 0.05), while 17-OHP was positively correlated with lumbar spine BMD (r = 0.38, P < 0.01). In subgroup analysis, 17-OHP was positively correlated with BMD (lumbar spine, r = 0.22; femur neck, r = 0.22; total hip, r = 0.24; all P < 0.05) only in the group with a total cumulative dose of GC ≥ 156.0 g/m2. CONCLUSION: Androgen excess may have a protective effect on BMD in women with classic CAH and high cumulative doses of GC.

Determinants of Short-Term Weight Gain Following Surgical Treatment for Craniopharyngioma in Adults.

OBJECTIVE: Craniopharyngiomas (CPs) are associated with hypothalamic damage that causes hypothalamic obesity, however, the mechanisms underlying CP-related postoperative weight gain remain debatable. This study aimed to elucidate whether the major determinant of postoperative weight gain in patients with CP is hypothalamic injury or steroid replacement therapy. METHODS: We included 48 adult patients with CP (age ≥18 years) who underwent transsphenoidal surgery between 2010 and 2018 in a single tertiary center, and whose body weight was measured pre- and postoperatively (<120 days after the surgery). We recruited 144 age- and body mass index-matched patients with non-functioning pituitary adenoma (NFPA) as controls. RESULTS: Patients with CP experienced greater postoperative weight gain than patients with NFPA (3.0±5.1 vs. 0.1±3.6 kg, p<0.001). The prevalence of postoperative steroid use was significantly higher in patients with CP than in those with NFPA (89.6% vs. 34.0%, p<0.001). Steroid replacement therapy and CP were associated with postoperative weight gain after adjusting for covariates in overall patients (p=0.032 and 0.007, respectively). In subgroup analysis with postoperative steroid users, weight gain was significantly greater in patients with CP (n=43, 0.96±0.25 kg/month) than in patients with NFPA (n=49, 0.26±0.23 kg/month) even after adjusting for the daily steroid dose (p=0.048). CONCLUSION: Patients with CP experience greater postoperative weight gain than those with NFPA. Hypothalamic damage itself as well as steroid replacement may contribute to the postoperative weight gain in patients with CP.

Skeletal effects of combined bisphosphonates treatment and parathyroidectomy in osteoporotic patients with primary hyperparathyroidism.

INTRODUCTION: Bone loss caused by primary hyperparathyroidism (PHPT) is an indication for parathyroidectomy (PTX). However, whether adding bisphosphonates would be superior to PTX alone to increase bone mass remains unclear. We thus aimed to compare the skeletal effects of the combination treatment of bisphosphonates and PTX with PTX alone. MATERIALS AND METHODS: In this retrospective analysis, bone mineral density (BMD) changes after 1 year of combination treatment and PTX alone were compared. We also analyzed the correlation between changes in serum biochemical parameters and BMD after 1 year of treatment in both groups. RESULTS: The baseline characteristics of patients treated with PTX alone (n = 24) and combination treatment (n = 26) were comparable. BMD significantly increased after 1 year of treatment in both groups (all p < 0.001), and the increase in BMD at the femur neck was higher in the PTX alone group than in the combination group (p = 0.011). There was a decreasing trend in serum alkaline phosphatase (ALP) levels in PTX alone compared to the combination treatment group (p = 0.053). In the study cohort, lower BMD and higher ALP levels at baseline were associated with higher 1-year BMD changes at all sites. Interestingly, a significant association was found between changes in ALP and BMD at the femur neck in the PTX alone group (p = 0.003), but abolished in the combination group (p = 0.946). CONCLUSIONS: There is no additional benefit of BMD in combination treatment with bisphosphonates and PTX over PTX alone in osteoporotic patients with PHPT. Combined bisphosphonate treatment might interfere with the increase in bone mass caused by PTX.