Osteoporosis International最新文献

This study examined the underuse of bone mineral density (BMD) testing in Cushing's syndrome patients, using a US insurance claims database. Despite osteoporosis risks, only 6.40% of 53,101 patients received BMD testing. The study underscores significant care gaps, particularly among males and older adults, necessitating improved screening efforts.

Background: Cushing syndrome (CS) is caused by long-term exposure to elevated glucocorticoid levels, primarily due to chronic steroid use, though it can also result from pituitary tumors. This condition leads to significant bone mineral density (BMD) loss and a heightened risk of osteoporosis. Despite guidelines for BMD testing in at-risk patients, osteoporosis has remained underdiagnosed in CS. The prevalence of BMD measurement in this group in the US continues to be unknown, indicating a gap in care.

Methods: We conducted a retrospective study using data from the PearlDiver Patient Records Database (2010-2020). Patients diagnosed with Cushing's syndrome who underwent BMD testing were included, while those with prior osteoporosis diagnoses were excluded. We analyzed patient demographics, comorbidities, and outcomes using t-tests, chi-squared tests, and logistic regression with significance set at p < 0.001.

Results: Among 53,101 identified Cushing's syndrome patients, only 6.40% underwent bone mineral density (BMD) testing within two years of diagnosis. Females were significantly more likely to be tested (7.85% vs. 2.58%; p < 0.001), and those tested were younger (mean age: 62.79 vs. 65.21 years; p < 0.001). The Midwest region had the highest testing rate at 7.1%, and patients with commercial insurance had the highest testing frequency at 7.5%. Factors associated with reduced BMD testing included male gender (OR = 0.31; p < 0.001), older age (OR = 0.96; p < 0.001), and higher Elixhauser Comorbidity Index (ECI) scores (OR = 0.89; p < 0.001). Conversely, obesity (OR = 1.51; p < 0.001) and chronic kidney disease (OR = 1.38; p < 0.001) increased the likelihood of testing. Among those tested, 12.56% were diagnosed with osteoporosis, with older age and tobacco use significantly increasing the odds of diagnosis.

Conclusion: Despite guideline recommendations, only 6.40% of patients with Cushing's syndrome underwent BMD screening. Among those screened, 12.56% were diagnosed with osteoporosis.. These findings highlight the need for improved adherence to screening guidelines, particularly for high-risk populations, to better manage and prevent osteoporosis in Cushing's syndrome patients.

The prevalence of osteoporosis in individuals with type 1 diabetes (T1D) was investigated. Based on IOF/ADA recommendations, 36% had indications for anti-osteoporotic therapy. We propose that postmenopausal women and men with T1D and age > 50 years are screened for osteoporosis.

Purpose: Type 1 diabetes is associated with an increased fracture risk and a lowering of the threshold for osteoporosis treatment has been recommended to be increased from a bone mineral density of a T-score ≤ - 2.5 to a T-score ≤ - 2.0. In this study, we aimed to investigate the prevalence and risk factors for osteoporosis in type 1 diabetes using the classic diagnostic criteria defined by WHO and the novel T-score cutoff of - 2.0 proposed by the ADA.

Methods: In a cross-sectional study, data were collected from the type 1 diabetes clinic at Steno Diabetes Center Aarhus, Aarhus University Hospital, where active attenders in the clinic were offered screening for osteoporosis using DXA of the lumbar spine and hip in the time period 2020-2022.

Results: A total of 764 individuals with type 1 diabetes had a DXA and of these, 25.5% had osteoporosis based on a vertebral fracture or T-score ≤ - 2.5, and 36% met ADA-treatment criteria with a vertebral fracture or T-score ≤ - 2.0. In multivariate analysis increasing age (OR = 1.3, 95% CI 1.0; 1.7) and a family history of osteoporosis (OR = 1.9, 95% CI 1.2; 3.0) were associated with an increased risk of osteoporosis, whereas an increase in BMI was associated with a decreased risk of osteoporosis (OR = 0.87, 95% CI 0.82; 0.92).

Conclusion: The present study finds that a high proportion of individuals with type 1 diabetes have osteoporosis, and an even higher proportion meet the treatment criteria proposed by the ADA, and thus, early detection and treatment of osteoporosis may reduce the apparent increased fracture risk in type 1 diabetes.

Objective: Vascular calcification shares many features with skeletal mineralisation and shares an inverse relationship with osteoporosis (skeletal de-mineralisation). However, medications that reduce bone loss (anti-resorptives) have had inconsistent effects on extra-skeletal mineralisation (i.e. vascular and valvular calcification). As such, this paper aims to synthesise existing literature examining the effect of anti-resorptive treatments on extra-skeletal (vascular and valvular) calcification across populations.

Methods: Medline and Embase were searched (inception to October 2024) for studies that assessed the association between anti-resorptive medication use and vascular/valvular calcification. Pooled standardised mean differences (SMDs) with 95% confidence intervals (CI) were calculated for all outcomes, using random-effects model. Leave-one-out sensitivity analyses were performed for internal validity.

Results: Of 4071 articles screened, 33 were included in the review, and 15 (2344 participants) had data available for meta-analysis. Anti-resorptive use was associated with non-significant, small magnitude improvements in abdominal aortic calcification (decreased value), coronary artery calcification (decreased value) and ejection fraction (increased value) but significant small reduction in aortic valve area (representing less calcification on the valve) with standardised mean difference of - 0.45 (95% confidence interval (CI) - 0.99; 0.08, I² = 84%), - 1.19 (95% CI - 2.92; 0.55, I² = 91%), - 0.67 (95% CI - 1.72; 0.38, I² = 94%), 0.26 (95% CI - 0.14; 0.66, I² = 62%) and 0.56 (95% CI 0.07; 1.06, I² = 76%), respectively.

Conclusion: The significance of small positive effect of anti-resorptives on aortic stenosis is clinically uncertain. Despite strong biological links between vascular calcification and skeletal mineralisation, anti-resorptives do not appear to have a strong favourable influence on extra-skeletal mineralisation. This suggests that mechanisms that link vascular calcification with osteoporosis may be acting in pathways not influenced by anti-resorptives. This systematic review and meta-analysis summarises the effect of anti-resorptives on vascular and valvular calcification. There is a small, positive effect of anti-resorptives on aortic stenosis, though this is of uncertain clinical importance.

Purpose: Ankle fractures, ranking as one of the very common osteoporotic fractures, pose a substantial socioeconomic burden. We aimed to investigate the incidence of elderly ankle fractures, refracture risks, and mortality rates in South Korea.

Methods: Utilizing the Korean National Health Insurance Service (NHIS) registry from January 2006 to December 2022, individuals over 50 years with ankle fractures were identified. Osteoporotic ankle fractures were defined using admission diagnoses, procedural codes, and cast-related codes. Incidence rates, refracture rates, and one-year mortality rates were analyzed with standardization adjusted for gender and age distribution.

Results: From 2006 to 2022, annual ankle fracture incidence rose from 193.90 to 278.83 per 100,000 person-years. Women exhibited 1.93 times higher incidence than men, with a notable increase in women. Most common in ages 60 to 69, ankle fracture rates increased until 2019 and after 2020 but decreased between 2019 and 2020. The one-year ankle refracture rates and osteoporotic refracture rates increased from 3.55% and 4.56% in 2007 to 9.32% and 10.37% in 2021, respectively. The one-year mortality rate after ankle fractures decreased from 2.10% in 2007 to 1.49% in 2021.

Conclusion: This study offers insights into the epidemiology of osteoporotic ankle fractures in South Korea, revealing increasing incidence, gender differences, age-related patterns, and trends in refracture and mortality rates over the study period. This study examines the incidence, refracture risk, and mortality of osteoporotic ankle fractures in South Korea using a nationwide dataset (2006-2022). The incidence of ankle fractures increased significantly, especially in women, and refracture rates also rose, highlighting an unmet need for better osteoporosis management.

Our study focused on predicting thoracolumbar osteoporotic vertebral fractures through radiomic analysis of non-fractured thoracic vertebrae using conventional chest CT. Four types of radiomics models were developed and showed acceptable prediction performance. Radiomics models incorporating both cortical-appendicular and trabecular bone may have superior performance compared to those using either feature set individually. The RAD score models based on thoracic vertebral combinations achieved comparable performance with lumbar bone mineral density (BMD) measurements.

Purpose: To develop and validate radiomics models based on chest CT for predicting the risk of thoracolumbar osteoporotic vertebral fractures (OVFs).

Methods: A total of 494 patients (including 198 patients with thoracolumbar OVFs) who underwent conventional chest CT scans were included in this retrospective analysis and were divided into training set 1 (n = 334) and validation set 1 (n = 160). Radiomics features (RFs) were extracted from each thoracic vertebral level on chest CT images. Four types of radiomics models (trabecular RFs, cortical-appendicular RFs, mixed RFs, and RAD score) were constructed and compared. Additionally, RAD score models based on trabecular and cortical-appendicular bone of different vertebral combinations (T1-T6, T7-T12, and top 3 vertebrae) were performed, respectively. A subset of patients with available bone mineral density (BMD) data formed training set 2 (n = 199) and validation set 2 (n = 88). We combined RAD score of different vertebral combinations with lumbar BMD for predicting thoracolumbar OVFs, and further adjusted for age. Predictive performance was evaluated using the area under the receiver operating characteristic curve (AUC).

Results: Among the radiomics models, the RAD score model based on trabecular and cortical-appendicular bone achieved highest AUC at the most vertebral levels. The RAD score model of top 3 (T5 + T8 + T10) vertebrae achieved higher AUC (0.813) than T7-T12 (AUC = 0.780) with a statistically significant difference (P = 0.02) and T1-T6 (AUC = 0.772) without a statistically significant difference (P = 0.062). Prior to adjusting for age, both RAD score models (AUCs 0.774-0.807) and RAD score + BMD models (AUCs 0.771-0.800) demonstrated slightly superior performance compared to BMD (AUC = 0.736) alone in predicting OVFs, although the differences were not statistically significant (P > 0.05). Following adjustment for age, our RAD score models, which utilized different vertebral combinations (AUCs 0.784-0.804), were found to be comparable to lumbar BMD (AUC = 0.785) in predicting OVFs (P > 0.05).

Conclusion: Radiomics analysis based on conventional chest CT can provide valuable information for predicting thoracolumbar OVFs. Radiomics models incorporating both cortical-appendicular and trabecular bone may have superior performance c

Less is known about recovery from hip fracture in men. We found differences in 25-hydroxyvitamin D and bone biomarkers between men and women during the year after hip fracture, underscoring the importance of vitamin D assessment in older men and pharmaceutical treatment to reduce bone resorption after hip fracture.

Purpose: Less is known about recovery from hip fracture in men compared to women. We examined differences between men and women in 25-hydroxyvitamin D (25OHD) and bone turnover markers, and associations with bone mineral density (BMD) and physical function, during the year after a hip fracture.

Methods: Community-dwelling, ambulatory adults aged 65 years and over (157 men and 154 women) enrolled in the Baltimore Hip Studies 7th cohort were included. We analyzed 25OHD, C-terminal telopeptide (β-CTX-I), procollagen type I N-terminal propeptide (PINP), PTH, and femoral neck BMD at baseline, 2, 6, and 12 months after hip fracture, and short physical performance battery (SPPB) at 2, 6, and 12 months.

Results: During admission for hip fracture, median 25OHD levels were 15.2 ng/mL (IQR 10.0) in men compared with 23.9 ng/mL (IQR 13.4) in women and remained lower in men at 2, 6, and 12 months (all p < 0.001). β-CTX-I was higher in men on admission, and at 2 and 6 months (all p < 0.05), and PINP was higher in men at 6 months (p = 0.04), with no significant differences between men and women in PTH. Higher 25OHD and PINP concentrations in women only and lower β-CTX-I and PTH concentrations in both sexes were associated with greater BMD. Higher 25OHD concentrations were associated with higher SPPB scores in both sexes.

Conclusions: These findings underscore the importance of vitamin D assessment in older men and missed opportunities in both sexes for vitamin D supplementation and pharmaceutical treatment to reduce bone resorption after hip fracture.

This study presents an innovative ensemble machine learning model integrating genomic and clinical data to enhance the prediction of major osteoporotic fractures in older men. The Super Learner (SL) model achieved superior performance (AUC = 0.76, accuracy = 95.6%, sensitivity = 94.5%, specificity = 96.1%) compared to individual models. Ensemble machine learning improves fracture prediction accuracy, demonstrating the potential for personalized osteoporosis management.

Purpose: Existing fracture risk models have limitations in their accuracy and in integrating genomic data. This study developed and validated an innovative ensemble machine learning (ML) model that combines multiple algorithms and integrates clinical, lifestyle, skeletal, and genomic data to enhance prediction for major osteoporotic fractures (MOF) in older men.

Methods: This study analyzed data from 5130 participants in the Osteoporotic Fractures in Men cohort Study. The model incorporated 1103 individual genome-wide significant variants and conventional risk factors of MOF. The participants were randomly divided into training (80%) and testing (20%) sets. Seven ML algorithms were combined using the SL ensemble method with tenfold cross-validation MOF prediction. Model performance was evaluated on the testing set using the area under the curve (AUC), the area under the precision-recall curve, calibration, accuracy, sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and reclassification metrics. SL model performances were evaluated by comparison with baseline models and subgroup analyses by race.

Results: The SL model demonstrated the best performance with an AUC of 0.76, accuracy of 95.6%, sensitivity of 94.5%, specificity of 96.1%, NPV of 95.1%, and PPV of 94.7%. Among the individual ML, gradient boosting performed optimally. The SL model outperformed baseline models, and it also achieved accuracies of 93.1% for Whites and 91.6% for Minorities, outperforming single ML in subgroup analysis.

Conclusion: The ensemble learning approach significantly improved fracture prediction accuracy and model performance compared to individual ML. Integrating genomic and phenotypic data via the SL approach represents a promising advancement for personalized osteoporosis management.

This study investigated whether osteoporosis impacts reoperation or periprosthetic fracture after total ankle arthroplasty. Findings showed no significant difference in reoperation or fracture rates between patients with or without osteoporosis, suggesting osteoporosis may not be a major risk factor for these outcomes.

Background: This study examines the association between osteoporosis and postoperative periprosthetic fracture or reoperation after primary total ankle arthroplasty (TAA) to guide surgical decision-making.

Methods: The United States TriNetX network identified adults undergoing primary TAA. Patients were split per the presence or absence of osteoporosis. The primary outcome was the risk ratio (RR) with 95% confidence intervals (CI) of reoperation within 3 years of primary TAA. Secondary outcome included the RR with 95% CI for postoperative periprosthetic fractures after primary TAA.

Results: There were 270 patients per cohort. There was no statistically significant difference in the likelihood of reoperation in the osteoporosis cohort as compared to the non-osteoporosis cohort through 3 years (5.9% versus 5.6%; p = 0.853). There was also no statistically significant difference in the likelihood of postoperative periprosthetic fractures in the osteoporosis cohort as compared to the non-osteoporosis cohort (6.3% versus 4.1%; p = 0.244).

Conclusion: These findings suggest that osteoporosis may not be a meaningful risk factor for reoperation or postoperative periprosthetic fracture after primary TAA.