Osteoporosis International最新文献

Dietary quality may be a factor in the progression of non-communicable, chronic diseases. This analysis of NHANES data demonstrates association between consumption of UPF and prevalence of osteoporosis and osteopenia in adults 50 years and older. UPF intake is an important consideration when recommending dietary patterns for optimum bone health PURPOSE: Declining bone mineral density in older adults can result in osteoporosis, leading to decreased physical function, quality of life, and increased risk of mortality. Poor dietary quality may contribute to the progression of this disease. This study explores the association between the consumption of ultra-processed foods (UPF) and the prevalence of osteoporosis and osteopenia in adults aged 50 years and older.

Method: Using regression analysis and adjusting for covariates, 24-h recall data from adults 50 years and over in four cycles of NHANES were examined for associations between prevalence of osteoporosis and intakes of UPF as a proportion of daily energy intake.

Results: Mean (SE) intake of UPF as a proportion of total daily energy ranged from 29.5% (0.3) in the lowest quintile to 76.3% (0.3) in the highest. 50.5% of women and 28.0% of men had osteopenia, 8.2% and 1.8%, respectively, had osteoporosis. Increased risk of osteopenia or osteoporosis was observed in the highest quintile of UPF intake compared to that of the lowest: OR 1.52 (95% CI 1.28, 1.79). The odds of self-reported prior fractures at hip, wrist, or spine in women increased by 1.9% for every percentage increase in proportion of UPF intake (95% CI 1.003, 1.035). Increased risk of fracture was not observed among men.

Conclusions: These findings indicate an association between osteoporosis and osteopenia and the intake of UPF as a proportion of total daily energy. Further investigation into the impact of dietary quality on osteoporosis and fracture risk is warranted, particularly in post-menopausal women.

Using data from NHANES for years 2005-2018, we examined temporal trends in osteoporosis prevalence and the proportion of undiagnosed osteoporosis in the United States of America. Our results suggested statistically significant increases in osteoporosis prevalence across several demographic groups. These findings carry profound implications for public health, given increased life expectancy and burden of chronic diseases.

Introduction: This is the first study to assess osteoporosis prevalence trends over time and the proportion of undiagnosed osteoporosis across gender, ethnicity/race, and age groups.

Methods: Observational time trend analyses were conducted using the 2005-2006, 2007-2008, 2009-2010, 2013-2014, and 2017-2018 National Health and Nutrition Examination Survey (NHANES) datasets, along with a descriptive analysis using the 2017-2018 NHANES dataset to capture the proportion of undiagnosed osteoporosis.

Results: The findings showed a statistically significant increase in osteoporosis prevalence among women, non-Hispanic Whites, and all age groups (except for individuals 80 years of age and older) during the study period. A subsequent analysis examining individuals by both gender and ethnicity/race demonstrated a statistically significant increase among Other Hispanic men and non-Hispanic White women. Additional descriptive analyses found that 69.12% of individuals with osteoporosis went undiagnosed. Specifically, 86.88% of men and 84.77% of individuals 50-59 years of age with osteoporosis went undiagnosed, representing the two highest groups.

Discussion and conclusion: The substantial and increasing prevalence among certain groups and sub-groups, along with the lack of diagnostic capture of osteoporosis, highlights existing gaps in public health efforts and care delivery infrastructure. This paper highlights high-risk groups and sub-groups that may benefit most from accelerated initiatives to reduce the burden of illness associated with osteoporosis.

Metaphyseal comminution in distal radius fracture (DRF) cases might indicate severe osteoporosis. The patients with DRFs and metaphyseal comminution showed 5.2-fold increased secondary fractures compared with those receiving combination osteoporosis therapy. High-risk DRF patients require aggressive osteoporosis management and fracture risk stratification.

Purpose: Distal radius fractures (DRFs) are common in patients with osteoporosis and associated with increased risks for subsequent fractures. Metaphyseal comminution in patients with DRFs may indicate severe osteoporosis and heightened bone fragility. However, its relationship with the risk of secondary fragility fractures remains unclear. This study aimed to evaluate the incidence of secondary fractures in patients with DRFs involving metaphyseal comminution and assess the effectiveness of osteoporosis treatment in reducing this risk.

Methods: In this retrospective cohort study, 134 patients aged ≥ 50 years underwent DRF surgery at a single institution from July 2018 to December 2022. The patients were allocated into groups by the presence (n = 45) or absence (n = 89) of metaphyseal comminution. The primary outcome was secondary fracture incidence. A multivariate Cox model was used, adjusting for age, sex, body mass index, bone mineral density, osteoporosis treatment type, and dementia.

Results: Secondary fractures were significantly more frequent in the comminution group (17.8%) than in the non-comminution group (3.4%) (p = 0.004). Metaphyseal comminution was associated with 5.2-fold increased secondary fracture risk (hazards ratio: 5.2, 95% confidence interval: 1.4-10.7, p = 0.004). The patients administered combination therapy (active vitamin D plus bisphosphonates or anabolic agents) had notably lower secondary fracture rate than did those receiving vitamin D alone (5.6% vs. 15.4%, p = 0.046).

Conclusions: Metaphyseal comminution in patient with DRFs significantly elevated secondary fracture risk; combination osteoporosis therapy might mitigate this risk. These findings underscore the need for robust osteoporosis management in high-risk patients, suggesting metaphyseal comminution should be crucial for fracture risk stratification.

A 29-year-old Spanish Caucasian man, without relevant family history, was attended in our unit due to an undiagnosed skeletal dysplasia associated with low bone mass and several fragility fractures throughout his childhood and adolescence. DXA exams throughout his life showed very low BMD values; currently, his spinal and femoral neck T-scores were - 4.3 and - 3.5, respectively. Blood and urinary tests were normal. Other relevant features included right hand and foot syndactyly, aplasia cutis, right hemibody hypoplasia, vertebral malformations, abnormal-looking humerii, and Asperger's syndrome among others. Whole exome sequencing retrieved a highly probable pathogenic variant in the PORCN gene p.(Arg296Pro) in mosaicism. PORCN mutations cause focal dermal hypoplasia (FDH), an X-linked ultra-rare ecto-mesodermal disorder characterized by several of the findings the patient presented. However, low BMD has not been classically associated with the disease. Noteworthy, PORCN is key for canonical Wnt signaling. Literature scrutiny has yielded other cases of FDH with skeletal fragility during childhood. In addition, preclinical studies with PORCN inhibitors, currently under development as an antitumoral therapy, have shown rapid detrimental effects on bone mass. Collectively, these findings indicate that FDH is probably an underrecognized monogenic cause of low bone mass due to defective Wnt signaling.

This case-control study investigated the impact of switching from bisphosphonates to denosumab, teriparatide, or romosozumab in postmenopausal osteoporosis. Romosozumab demonstrated the most significant improvements in bone mineral density, particularly in the lumbar spine and total hip, by reducing bone resorption and increasing bone formation markers.

Purpose: To investigate the impact of switching from bisphosphonates (BP) to denosumab (DMAb), teriparatide (TPTD), or romosozumab (ROMO) in postmenopausal osteoporosis.

Methods: This retrospective, case-controlled, multicenter study included 389 patients who switched from BP to DMAb, TPTD, or ROMO due to treatment inefficacy. Propensity score matching was used to align patient backgrounds, resulting in 45 patients per group. Baseline characteristics included a mean age of 73.8 years, prior BP treatment duration of 37.1 months, and bone mineral density (BMD) T-scores of -2.8 in the lumbar spine (LS), -2.5 in the total hip (TH), and -2.7 in femoral neck (FN). BMD and bone turnover markers were assessed over 12 months.

Results: Following the switch from BP, the ROMO group demonstrated a dual effect of decreased bone resorption and increased bone formation markers. The TPTD group exhibited the highest increases in both markers, while the DMAb group suppressed both. After 12 months, the ROMO group demonstrated significantly greater BMD increases in the LS (11.4%) compared to the DMAb (6.3%; p < 0.001) and TPTD (5.9%; p < 0.001) groups. Additionally, the ROMO group showed greater increases in the TH (3.3%) than TPTD group (0.8%; p < 0.01). Only the ROMO group showed a significant BMD increase in the FN (2.0%; p < 0.01 from baseline).

Conclusion: Significant BMD increases were observed in the LS for all groups, in the TH for the ROMO and DMAb groups, and in the FN for the ROMO group. ROMO showed the most substantial BMD improvements following BP therapy.

This study utilized deep learning for bone mineral density (BMD) prediction and classification using biplanar X-ray radiography (BPX) images from Huashan Hospital Medical Checkup Center. Results showed high accuracy and strong correlation with quantitative computed tomography (QCT) results. The proposed models offer potential for screening patients at a high risk of osteoporosis and reducing unnecessary radiation and costs.

Purpose: To explore the feasibility of using a hybrid deep learning framework (HDLF) to establish a model for BMD prediction and classification based on BPX images. This study aimed to establish an automated tool for screening patients at a high risk of osteoporosis.

Methods: A total of 906 BPX scans from 453 subjects were included in this study, with QCT results serving as the reference standard. The training-validation set:independent test set ratio was 4:1. The L1-L3 vertebral bodies were manually annotated by experienced radiologists, and the HDLF was established to predict BMD and diagnose abnormality based on BPX images and clinical information. The performance metrics of the models were calculated and evaluated.

Results: The $R^2$ values of the BMD prediction regression model in the independent test set based on BPX images and multimodal data (BPX images and clinical information) were 0.77 and 0.79, respectively. The Pearson correlation coefficients were 0.88 and 0.89, respectively, with P-values < 0.001. Bland-Altman analysis revealed no significant difference between the predictions of the models and QCT results. The classification model achieved the highest AUC of 0.97 based on multimodal data in the independent test set, with an accuracy of 0.93, sensitivity of 0.84, specificity of 0.96, and F1 score of 0.93.

Conclusion: This study demonstrates that deep learning neural networks applied to BPX images can accurately predict BMD and perform classification diagnoses, which can reduce the radiation risk, economic consumption, and time consumption associated with specialized BMD measurement.

Osteoporosis is often underrecognized and undertreated following periprosthetic fractures (PPF). Our study found that between 2010 and 2020, there has been no significant change in the rates of osteoporosis screening or treatment within 1 year following PPF. Orthopedic surgeons can play an integral role in helping to curtail the osteoporosis epidemic.

Purpose: Periprosthetic fractures (PPF) typically occur from low-energy mechanisms and are pathognomonic for osteoporosis. However, osteoporosis is often underrecognized and undertreated. The aim of this study was to examine trends in dual energy X-ray absorptiometry (DXA) scans and treatment of osteoporosis after PPF between 2010 and 2020.

Methods: Patients older than 40 who experienced a lower extremity PPF between 2010 and 2020 and had no prior history of osteoporosis screening or treatment were identified utilizing a large national administrative database. Rates of bone mineral density (BMD) measurement using DXA and anti-osteoporotic treatment with pharmacotherapy, or either intervention within 1 year following experiencing a PPF were determined. The rate of change for these interventions was calculated using the compounded annual growth rate (CAGR), with linear regression used to determine whether trends were statistically significant.

Results: In total, 5.7% and 3.6% of patients were screened and treated for osteoporosis, respectively. Between 2010 and 2020, there was no significant change in rates of osteoporosis screening (CAGR + 0.1%; p = 0.13), treatment (CAGR - 2.4%; p = 0.29), or either intervention (CAGR - 1.1%; p = 0.77) within 1 year following PPF. Factors associated with intervention included older age, female sex, and increased comorbidities.

Conclusion: Our study found that there has been no significant change in the rates of osteoporosis screening or treatment within 1 year following PPF. Orthopedic surgeons and allied healthcare workers can play an integral role in helping to curtail the osteoporosis epidemic.