Optimising health after early menopause.

The typical age at menopause is 50-51 years in high-income countries. However, early menopause is common, with around 8% of women in high-income countries and 12% of women globally experiencing menopause between the ages of 40 years and 44 years. Menopause before age 40 years (premature ovarian insufficiency) affects an additional 2-4% of women. Both early menopause and premature ovarian insufficiency can herald an increased risk of chronic disease, including osteoporosis and cardiovascular disease. People who enter menopause at younger ages might also experience distress and feel less supported than those who reach menopause at the average age. Clinical practice guidelines are available for the diagnosis and management of premature ovarian insufficiency, but there is a gap in clinical guidance for early menopause. We argue that instead of distinct age thresholds being applied, early menopause should be seen on a spectrum between premature ovarian insufficiency and menopause at the average age. This Series paper presents evidence for the short-term and long-term consequences of early menopause. We offer a practical framework for clinicians to guide diagnosis and management of early menopause, which considers the nature and severity of symptoms, age and medical history, and the individual's wishes and priorities to optimise their quality of life and short-term and long-term health. We conclude with recommendations for future research to address key gaps in the current evidence.

Variability in performance of genetic-enhanced DXA-BMD prediction models across diverse ethnic and geographic populations: A risk prediction study.

BACKGROUND: Osteoporosis is a major global health issue, weakening bones and increasing fracture risk. Dual-energy X-ray absorptiometry (DXA) is the standard for measuring bone mineral density (BMD) and diagnosing osteoporosis, but its costliness and complexity impede widespread screening adoption. Predictive modeling using genetic and clinical data offers a cost-effective alternative for assessing osteoporosis and fracture risk. This study aims to develop BMD prediction models using data from the UK Biobank (UKBB) and test their performance across different ethnic and geographical populations. METHODS AND FINDINGS: We developed BMD prediction models for the femoral neck (FNK) and lumbar spine (SPN) using both genetic variants and clinical factors (such as sex, age, height, and weight), within 17,964 British white individuals from UKBB. Models based on regression with least absolute shrinkage and selection operator (LASSO), selected based on the coefficient of determination (R2) from a model selection subset of 5,973 individuals from British white population. These models were tested on 5 UKBB test sets and 12 independent cohorts of diverse ancestries, totaling over 15,000 individuals. Furthermore, we assessed the correlation of predicted BMDs with fragility fractures risk in 10 years in a case-control set of 287,183 European white participants without DXA-BMDs in the UKBB. With single-nucleotide polymorphism (SNP) inclusion thresholds at 5×10-6 and 5×10-7, the prediction models for FNK-BMD and SPN-BMD achieved the highest R2 of 27.70% with a 95% confidence interval (CI) of [27.56%, 27.84%] and 48.28% (95% CI [48.23%, 48.34%]), respectively. Adding genetic factors improved predictions slightly, explaining an additional 2.3% variation for FNK-BMD and 3% for SPN-BMD over clinical factors alone. Survival analysis revealed that the predicted FNK-BMD and SPN-BMD were significantly associated with fragility fracture risk in the European white population (P < 0.001). The hazard ratios (HRs) of the predicted FNK-BMD and SPN-BMD were 0.83 (95% CI [0.79, 0.88], corresponding to a 1.44% difference in 10-year absolute risk) and 0.72 (95% CI [0.68, 0.76], corresponding to a 1.64% difference in 10-year absolute risk), respectively, indicating that for every increase of one standard deviation in BMD, the fracture risk will decrease by 17% and 28%, respectively. However, the model's performance declined in other ethnic groups and independent cohorts. The limitations of this study include differences in clinical factors distribution and the use of only SNPs as genetic factors. CONCLUSIONS: In this study, we observed that combining genetic and clinical factors improves BMD prediction compared to clinical factors alone. Adjusting inclusion thresholds for genetic variants (e.g., 5×10-6 or 5×10-7) rather than solely considering genome-wide association study (GWAS)-significant variants can enhance the model's explanatory power. The study highlights the need for training models on diverse populations to improve predictive performance across various ethnic and geographical groups.

The terminologies of transient, migratory, or localized osteoporosis, and bone marrow edema syndrome: a scoping review.

There is no formally defined terminology for the related entities transient osteoporosis of the hip (TOH), localized or regional migratory osteoporosis (RMO) and bone marrow edema syndrome (BMES). This study aimed to map the diversity and frequency of diagnostic terms and vocabulary utilized in the literature. A comprehensive search of electronic databases and reference lists was conducted. Publications that reported on patients with TOH, RMO, BMES, or related variants were eligible for inclusion. The terminologies were categorized based on the wording of the titles, abstracts, or texts. We included 561 publications, of which 423 were case reports, involving 2921 patients. Overall, TOH was the most commonly used term, occurring in 257 (45.8%). RMO was used in 34 (6.1%) and BMES in 57 (10.2%). The remaining used various combinations of transient, migratory, and regional in conjunction with either osteoporosis or bone marrow edema. Localized osteoporosis was not used. We identified three different terms related to pregnancy. In 76.3% of the publications, the terminology was related to osteoporosis and in 18.2% to bone marrow edema, although terminology did not correspond to actual findings. Bone marrow edema occurred as often as osteoporosis, and osteoporosis was generally ascertained by visual inspection of radiographs, seldom by bone densitometry. Many publications used osteoporosis-related terms without evidence that osteoporosis had been detected. The terminology of these closely related entities is confusing and unstandardized. The lack of formal definitions impedes accurate diagnosis, research on disease mechanisms, and effective treatment.

Screening and management of osteoporosis: a survey of knowledge, attitude, and practice among healthcare professionals in Egypt-a study by the Egyptian Academy of Bone Health.

Secondary-level healthcare professionals, mainly rheumatologists and orthopedic surgeons, were invited to participate in an online survey questionnaire to assess knowledge and compliance with osteoporosis management guidelines and strategies, as well as self-reported quality of care. About 51% of the participants admit that they do not implement specific guidelines for the management of osteoporosis in their standard practice and depend on their experience and their clinical judgments. Moreover, although a good percentage (58%) had satisfactory knowledge levels in domains on the risk of osteoporotic fractures and investigations of osteoporosis, 47.5% of the participants did not score satisfactorily in questions on pharmacotherapy, especially for those patients at high risk for fractures. INTRODUCTION: A recently published study demonstrated a treatment gap among those eligible for osteoporosis therapy in Egypt of about 82.1% in postmenopausal women and 100% in men. The current survey aimed to address some of the factors that may contribute to this wide gap. METHODS: This was a cross-sectional study of secondary care healthcare professionals (both physicians and orthopedic surgeons) who were invited to complete an online questionnaire, which gathered information about physicians' socio-demographic data, knowledge, and compliance with osteoporosis management guidelines and strategies, as well as self-reported quality of care. Additionally, a knowledge score was calculated for all the participants. RESULTS: A good percentage (58%) had a satisfactory knowledge level in domains on the risk of osteoporotic fractures and investigations of osteoporosis; however, 47.5% did not score satisfactorily in questions on pharmacotherapy, especially for those patients at high risk for fractures. CONCLUSIONS: This work has identified some of the barriers to implementing guidelines for osteoporosis and fragility fracture management. In the meantime, it highlights the urgency of intensifying efforts to develop the knowledge and attitude of the healthcare professionals dealing with this condition in Egypt.

Clinical features of fallers and non-fallers: finding best-performing combinations of physical performance measurements to discriminate physical impairments between fallers and non-fallers among older adults with and without osteoporosis.

Is osteoporosis related to worst outcomes after fall accidents? After a fall accident, there were no differences in walking and balance between individuals with/without osteoporosis. Gains in fat tissue, higher pain, and difficulty to walk were related to previous falls, regardless of osteoporosis. PURPOSE: Impairments are expected after an accidental fall in the older age; whoever, it is still unclear if patients suffering from osteoporosis are in higher risks of fall accidents and if such accidents would cause worst outcomes compared with older adults without osteoporosis. The objective of this study was to discriminate fallers and non-fallers via a combination of physical performance measurements of older adults (65 + years) with and without osteoporosis. METHODS: Older adults (n = 116) were screened for a previous fall accident and tested during (i) quiet stance; (ii) single- and dual-task walking; (iii) 8-Foot Up-and-Go; (iv) Mini BESTest; (v) 2-min step-in-place and (vi) 30-s chair stand. Evaluation of average daily pain intensity and total body fat% were obtained. RESULTS: Forty-four subjects (38%) reported a previous fall accident. There was, however, no association between osteoporosis and previous fall. Fallers had a higher daily pain intensity, higher body fat%, slower walking speed during a cognitive dual-task test and worse performance at the 8-Foot Up-and-Go test and the Mini BESTest compared to non-fallers. CONCLUSIONS: Although the presence of osteoporosis might not increase the risk of fall accidents, healthcare professionals should expect that accidental falls in older adults are associated with higher body fat%, higher daily pain intensity and problems performing daily activities such as walking.

The yield of routine laboratory examination in osteoporosis evaluation in primary care.

This study evaluated the yield of routine laboratory examination in a large population of older women in primary care. The prevalence of laboratory abnormalities was low and the clinical consequences in follow-up were limited. There was a weak association of laboratory abnormalities with osteoporosis but no association with vertebral fractures and recent fractures. PURPOSE: Most osteoporosis guidelines advice routine laboratory examination. We have investigated the yield of laboratory examinations in facture risk evaluation of elderly women in primary care. METHODS: We assessed the prevalence of laboratory abnormalities and their association with risk factors for fractures, recent fractures, low bone mineral density (BMD), and prevalent vertebral fracture in 8996 women ≥ 65 years of age participating in a primary care fracture risk screening study. In a sample of 2208 of these participants, we also evaluated the medical consequences in the medical records during a follow-up period of ≥ 1 year. RESULTS: Vitamin D deficiency (< 30 nmol/L) was present in 13% and insufficiency (< 50 nmol/L) in 43% of the study sample. The prevalence of other laboratory abnormalities (ESR, calcium, creatinine, FT4) was 4.6% in women with risk factors for fractures, 6.1% in women with low BMD (T-score ≤ - 2.5), 6.0% after a prevalent vertebral fracture, 5.2% after a recent fracture and 2.6% in the absence of important risk factors for fractures. Laboratory abnormalities other than vitamin D were associated with low BMD (OR 1.4, 95%CI 1.1-1.8) but not with prevalent vertebral fractures nor recent fractures. Low BMD was associated with renal failure (OR 2.0, 95%CI 1.3-3.4), vitamin D insufficiency (OR 1.2, 95%CI 1.0-1.3) and deficiency (OR 1.3, 95%CI 1.1-.5). In the follow-up period, 82% of the laboratory abnormalities did not result in a new diagnosis or treatment reported in the medical records. CONCLUSIONS: We identified a low prevalence of laboratory abnormalities in a primary care population of older women and the majority of these findings had no medical consequences.

Periprosthetic fractures are osteoporotic fractures: missed opportunities for osteoporosis diagnosis.

Joint replacement surgery is common in older adults, leading to increasing periprosthetic fracture (PPFx) occurrence. We reviewed all PPFx seen over a 4-year period at an academic hospital. Clinical osteoporosis could be diagnosed based on existing data in 104 (67%) at the time of PPFx. Periprosthetic fractures are generally osteoporosis-related. PURPOSE: Periprosthetic fractures (PPFx) cause morbidity, mortality, and cost. This study's purpose was to describe osteoporosis-related data available at the time of PPFx. METHODS: The electronic medical record (EMR) of PPFx patients seen over 4 years in a university orthopedic practice were reviewed. Demographic data and osteoporosis relevant parameters were collected. Prior DXA studies were reviewed, and L1 Hounsfield unit (HU) measurements were performed on CT scans obtained within 2 years before PPFx. Clinical osteoporosis was defined as prior diagnosis, prescribed osteoporosis treatment, T-score ≤ - 2.5, HU ≤ 100, or prior fracture. RESULTS: Records of 156 PPFx patients (115 F/41 M), mean (SD) age 75.4 (11.9), were reviewed. Almost all 153/156 (98%) of these fractures were femoral. Falls caused 139 (89%); 12 (8%) were spontaneous. Mean time post-arthroplasty was 7.9 (6.3) years. Prior fragility fracture(s) occurred in 72 (46%); 14 were PPFx. Osteoporosis was previously diagnosed in 45 (29%) and medications prescribed in 41 (26%). Prior to PPFx, DXA data were available in 62, mean (SD) lowest T-score was - 1.9 (0.9) and was ≤ - 2.5 in 19. CT data were available in 46; mean (SD) L1 HU was 79.0 (29.4) and was ≤ 100 in 35. Based on existing data, clinical osteoporosis could have been diagnosed in 104 (67%) at the time of PPFx. CONCLUSION: Periprosthetic fractures are osteoporosis-related. They occur in older adults, often female, and result from falls; BMD, when assessed, is low. Data available at the time of PPFx often allows osteoporosis diagnosis; this should prompt evaluation and pharmacologic treatment consideration.

Diagnosis and therapeutic approach to bone health in patients with hypopituitarism.

The results of many studies in recent years indicate a significant impact of pituitary function on bone health. The proper function of the pituitary gland has a significant impact on the growth of the skeleton and the appearance of sexual dimorphism. It is also responsible for achieving peak bone mass, which protects against the development of osteoporosis and fractures later in life. It is also liable for the proper remodeling of the skeleton, which is a physiological mechanism managing the proper mechanical resistance of bones and the possibility of its regeneration after injuries. Pituitary diseases causing hypofunction and deficiency of tropic hormones, and thus deficiency of key hormones of effector organs, have a negative impact on the skeleton, resulting in reduced bone mass and susceptibility to pathological fractures. The early appearance of pituitary dysfunction, i.e. in the pre-pubertal period, is responsible for failure to achieve peak bone mass, and thus the risk of developing osteoporosis in later years. This argues for the need for a thorough assessment of patients with hypopituitarism, not only in terms of metabolic disorders, but also in terms of bone disorders. Early and properly performed treatment may prevent patients from developing the bone complications that are so common in this pathology. The aim of this review is to discuss the physiological, pathophysiological, and clinical insights of bone involvement in pituitary disease.

Developing Cut-off Values for Low and Very Low Bone Mineral Density at the Thoracic Spine Using Quantitative Computed Tomography.

Osteoporosis is under-diagnosed while detectable by measuring bone mineral density (BMD) using quantitative computer tomography (QCT). Opportunistic screening for low BMD has previously been suggested using lumbar QCT. However, thoracic QCT also possesses this potential to develop upper and lower cut-off values for low thoracic BMD, corresponding to the current cut-offs for lumbar BMD. In participants referred with chest pain, lumbar and thoracic BMD were measured using non-contrast lumbar- and cardiac CT scans. Lumbar BMD cut-off values for very low (< 80 mg/cm3), low (80-120 mg/cm3), and normal BMD (> 120 mg/cm3) were used to assess the corresponding thoracic values. A linear regression enabled identification of new diagnostic thoracic BMD cut-off values. The 177 participants (mean age 61 [range 31-74] years, 51% women) had a lumbar BMD of 121.6 mg/cm3 (95% CI 115.9-127.3) and a thoracic BMD of 137.0 mg/cm3 (95% CI: 131.5-142.5), p < 0.001. Categorization of lumbar BMD revealed 14%, 35%, and 45% in each BMD category. When applied for the thoracic BMD measurements, 25% of participants were reclassified into a lower group. Linear regression predicted a relationship of Thoracic BMD = 0.85 * Lumbar BMD + 33.5, yielding adjusted thoracic cut-off values of < 102 and > 136 mg/cm3. Significant differences in BMD between lumbar and thoracic regions were found, but a linear relationship enabled the development of thoracic upper and lower cut-off values for low BMD in the thoracic spine. As Thoracic CT scans are frequent, these findings will strengthen the utilization of CT images for opportunistic detection of osteoporosis.

Diagnostic accuracy of chest X-ray and CT using artificial intelligence for osteoporosis: systematic review and meta-analysis.

INTRODUCTION: Artificial intelligence (AI)-based systems using chest images are potentially reliable for diagnosing osteoporosis. METHODS: We performed a systematic review and meta-analysis to assess the diagnostic accuracy of chest X-ray and computed tomography (CT) scans using AI for osteoporosis in accordance with the diagnostic test accuracy guidelines. We included any type of study investigating the diagnostic accuracy of index test for osteoporosis. We searched MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials, and IEEE Xplore Digital Library on November 8, 2023. The main outcome measures were the sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) for osteoporosis and osteopenia. We described forest plots for sensitivity, specificity, and AUC. The summary points were estimated from the bivariate random-effects models. We summarized the overall quality of evidence using the Grades of Recommendation, Assessment, Development, and Evaluation approach. RESULTS: Nine studies with 11,369 participants were included in this review. The pooled sensitivity, specificity, and AUC of chest X-rays for the diagnosis of osteoporosis were 0.83 (95% confidence interval [CI] 0.75, 0.89), 0.76 (95% CI 0.71, 0.80), and 0.86 (95% CI 0.83, 0.89), respectively (certainty of the evidence, low). The pooled sensitivity and specificity of chest CT for the diagnosis of osteoporosis and osteopenia were 0.83 (95% CI 0.69, 0.92) and 0.70 (95% CI 0.61, 0.77), respectively (certainty of the evidence, low and very low). CONCLUSIONS: This review suggests that chest X-ray with AI has a high sensitivity for the diagnosis of osteoporosis, highlighting its potential for opportunistic screening. However, the risk of bias of patient selection in most studies were high. More research with adequate participants' selection criteria for screening tool will be needed in the future.

The efficacy of nutritional screening indexes in predicting the incidence of osteosarcopenia and major osteoporotic fracture in the elderly.

INTRODUCTION: The effect of nutritional status on osteosarcopenia (OS) and major osteoporotic fracture (MOF) among the elderly is still unclear. So we aimed to compare the efficacy of the Mini-Nutrition Assessment-Short Form (MNA-sf), the Geriatric Nutritional Risk Index (GNRI) and Controlling Nutritional Status (CONUT) for predicting OS and MOF among the elderly. MATERIALS AND METHODS: A total of 409 participants were enrolled in this prospective study. Blood biochemical indexes, nutritional status, and bone- and muscle-related examinations were assessed at initial visit to the outpatient. Participants were divided into 4 groups: (1) control; (2) osteopenia/osteoporosis; (3) sarcopenia; (4) osteosarcopenia, and then followed for 5 years, recording the occurrence time of MOF. RESULTS: The frequency values of osteopenia/osteoporosis, sarcopenia, and OS, at baseline, were respectively 13.4, 16.1, and 12% among the study samples. Correlation analysis showed that nutritional status scores were associated with body mass index, handgrip strength, albumin, bone mineral density, and physical functions. According to multivariate models, poor nutritional status was significantly associated with a higher risk of OS and MOF (P < 0.05). Survival analysis showed that the MOF rate in malnutrition group was significantly higher than normal nutrition group (P < 0.05). The receiver operator characteristic curve shows that the value of MNA-sf to diagnose OS and MOF is greater (P < 0.05). CONCLUSION: The poor nutritional status was associated with a higher risk of both OS and MOF. MNA-sf showed a superior diagnostic power for OS and MOF among the elderly. Early nutrition assessments and interventions may be key strategies to prevent OS and fractures.

Associations between bone mineral density and abdominal aortic calcification: Results of a nationwide survey.

BACKGROUND AND AIMS: Vascular calcification has been linked to bone mineral density (BMD). This study aimed to investigate the association between BMD and abdominal aortic calcification (AAC). METHODS AND RESULTS: Data from the 2013-2014 National Health and Nutrition Examination Survey (NHANES) were utilized. Participants lacking BMD and AAC score data were excluded. BMD at the femoral neck was measured using dual-energy X-ray absorptiometry. AAC scores were assessed using the Kauppila scoring system, with AAC defined as a score greater than zero, and severe AAC defined as a score greater than six. Weighted multivariable regression analysis and subgroup analysis were conducted to examine the independent relationship between BMD and AAC score, AAC, and severe AAC. A total of 2965 participants were included. After adjusting for multiple covariates, BMD showed a negative association with higher AAC scores (ß = -0.17, 95% CI -0.29, -0.05, p = 0.0066). The odds of having AAC and severe AAC decreased by 9% and 16%, respectively, for every one-unit increase in BMD (AAC: odds ratio [OR] = 0.91, 95% CI 0.82, 1.00, p = 0.0431; severe AAC: OR = 0.84, 95% CI 0.71, 0.99, p = 0.0334). CONCLUSION: Low BMD is associated with higher AAC scores and an increased risk of AAC and severe AAC. Considering the detrimental impact of low BMD on cardiovascular health, individuals with AAC should be evaluated for osteopenia and osteoporosis in clinical settings.

High-sensitivity immunoassay on interdigitated electrode to detect osteoporosis biological marker.

Osteoporosis is with porous bones, which refers to a decrease in the bone mineral density and weakens the bones to become brittle. Osteoporosis often progresses without any pain or symptoms until the bone fractures. Monitoring the condition of bone regularly helps to identify the bone that weakens at its earlier stages. In general, radiological techniques have been used to measure bone mineral density, are expensive, and the procedures are complicated. Therefore, researchers are focusing on the alternative method of biomarker quantification to identify bone mineral density. This research work was focused on quantifying the osteoporosis biomarker of C-terminal telopeptide of type I collagen (CTX-I) on an interdigitated electrode (IDE) sensor. Gold nanomaterial-modified anti-CTX-I antibody was attached to silica nanomaterial-decorated IDE and then identified by CTX-I interaction. Higher immobilization of antibodies was recorded on diamond-modified IDE through gold nanoparticles, and detected CTX-I as low as 0.5 pg/mL [y = 1.5507x - 0.9043 R2 = 0.9715], determined on a linear curve at the range 0.5-3.5 ng/mL. Further, specific identification of CTX-I was confirmed by control performances with osteopontin, IL-6, and anti-IgG antibody.

Diagnosing Osteoporosis in Diabetes-A Systematic Review on BMD and Fractures.

PURPOSE OF REVIEW: Recently, the American Diabetes Association updated the 2024 guidelines for Standards of Care in Diabetes and recommend that a T-score of - 2.0 in patients with diabetes should be interpreted as equivalent to - 2.5 in people without diabetes. We aimed to evaluate the most recent findings concerning the bone mineral density (BMD)-derived T-score and risk of fractures related to osteoporosis in subjects with diabetes. RECENT FINDINGS: The dual-energy X-ray absorptiometry (DXA) scan is the golden standard for evaluating BMD. The BMD-derived T-score is central to fracture prediction and signifies both diagnosis and treatment for osteoporosis. However, the increased fracture risk in diabetes is not sufficiently explained by the T-score, complicating the identification and management of fracture risk in these patients. Recent findings agree that subjects with type 2 diabetes (T2D) have a higher T-score and higher fracture risk compared with subjects without diabetes. However, the actual number of studies evaluating the direct association of higher fracture risk at higher T-score levels is scant. Some studies support the adjustment based on the 0.5 BMD T-score difference between subjects with T2D and subjects without diabetes. However, further data from longitudinal studies is warranted to validate if the T-score treatment threshold necessitates modification to prevent fractures in subjects with diabetes.

An overview of the use of the fracture risk assessment tool (FRAX) in osteoporosis.

FRAX®, a simple-to-use fracture risk calculator, was first released in 2008 and since then has been used increasingly worldwide. By calculating the 10-year probabilities of a major osteoporotic fracture and hip fracture, it assists clinicians when deciding whether further investigation, for example a bone mineral density measurement (BMD), and/or treatment is needed to prevent future fractures. In this review, we explore the literature around osteoporosis and how FRAX has changed its management. We present the characteristics of this tool and describe the use of thresholds (diagnostic and therapeutic). We also present arguments as to why screening with FRAX should be considered. FRAX has several limitations which are described in this review. This review coincides with the release of a version, FRAXplus, which addresses some of these limitations.

Very low serum IGF-1 levels are associated with vertebral fractures in adult males with beta-thalassemia major.

PURPOSE: Patients with beta-thalassemia major (BTM) often develop several endocrine disorders due to chronic iron overload. They are also prone to osteoporosis and vertebral fractures. Plasmatic insulin-like growth factor-1 (IGF-1) levels are often low in subjects with BTM, which origin is multifactorial. The aim of this study was to evaluate a possible relationship between serum IGF-1 levels and the presence of osteoporosis and/or vertebral fractures. METHODS: We retrospectively evaluated the occurrence of vertebral fractures in 30 adult male patients affected by BTM (mean age 43.3 ± 7.9 years) with low serum IGF-1 (median value 52.4 ng/ml, 38.5-83.4). Only 6 of them (20.0%) were diagnosed with GH deficiency (GHD) after GHRH/arginine stimulation test, while 23 (76.7%) had osteoporosis and 12 (40.0%) had known vertebral fractures. All patients except one also showed at least one endocrine disorder. RESULTS: Serum IGF-1 was significantly lower in BTM patients with vertebral fractures compared to patients without vertebral fractures (U = 41.0, p = 0.005) while it was not significantly different between patients with low bone mass compared to patients without low bone mass. The diagnosis of GHD was significantly associated with lower serum IGF-1 (p = 0.001) and vertebral fractures (p = 0.002) but not with low bone mass. After ROC analysis, we found that very low IGF-1 (≤ 50.0 ng/dl) was associated with vertebral fractures (sensitivity 83.3%, specificity 75.0%) and was also predictive of GHD (sensitivity 75.0%, specificity 100.0%). CONCLUSION: Our study shows that, in male patients with BTM, serum IGF-1 ≤ 50.0 ng/dl is a marker of vertebral fractures and it is predictive of a diagnosis of GHD.

Performance of Progressive Generations of GPT on an Exam Designed for Certifying Physicians as Certified Clinical Densitometrists.

BACKGROUND: Artificial intelligence (AI) large language models (LLMs) such as ChatGPT have demonstrated the ability to pass standardized exams. These models are not trained for a specific task, but instead trained to predict sequences of text from large corpora of documents sourced from the internet. It has been shown that even models trained on this general task can pass exams in a variety of domain-specific fields, including the United States Medical Licensing Examination. We asked if large language models would perform as well on a much narrower subdomain tests designed for medical specialists. Furthermore, we wanted to better understand how progressive generations of GPT (generative pre-trained transformer) models may be evolving in the completeness and sophistication of their responses even while generational training remains general. In this study, we evaluated the performance of two versions of GPT (GPT 3 and 4) on their ability to pass the certification exam given to physicians to work as osteoporosis specialists and become a certified clinical densitometrists. The CCD exam has a possible score range of 150 to 400. To pass, you need a score of 300. METHODS: A 100-question multiple-choice practice exam was obtained from a 3rd party exam preparation website that mimics the accredited certification tests given by the ISCD (International Society for Clinical Densitometry). The exam was administered to two versions of GPT, the free version (GPT Playground) and ChatGPT+, which are based on GPT-3 and GPT-4, respectively (OpenAI, San Francisco, CA). The systems were prompted with the exam questions verbatim. If the response was purely textual and did not specify which of the multiple-choice answers to select, the authors matched the text to the closest answer. Each exam was graded and an estimated ISCD score was provided from the exam website. In addition, each response was evaluated by a rheumatologist CCD and ranked for accuracy using a 5-level scale. The two GPT versions were compared in terms of response accuracy and length. RESULTS: The average response length was 11.6 ±19 words for GPT-3 and 50.0±43.6 words for GPT-4. GPT-3 answered 62 questions correctly resulting in a failing ISCD score of 289. However, GPT-4 answered 82 questions correctly with a passing score of 342. GPT-3 scored highest on the "Overview of Low Bone Mass and Osteoporosis" category (72 % correct) while GPT-4 scored well above 80 % accuracy on all categories except "Imaging Technology in Bone Health" (65 % correct). Regarding subjective accuracy, GPT-3 answered 23 questions with nonsensical or totally wrong responses while GPT-4 had no responses in that category. CONCLUSION: If this had been an actual certification exam, GPT-4 would now have a CCD suffix to its name even after being trained using general internet knowledge. Clearly, more goes into physician training than can be captured in this exam. However, GPT algorithms may prove to be valuable physician aids in the diagnoses and monitoring of osteoporosis and other diseases.

Sarcopenia as a predictor of nutritional status and comorbidities: a cross-sectional and mendelian randomization study.

BACKGROUND: With the advancement of world population aging, age-related sarcopenia (SP) imposes enormous clinical burden on hospital. Clinical research of SP in non-geriatric wards has not been appreciated, necessitating further investigation. However, observational studies are susceptible to confounders. Mendelian randomization (MR) can effectively mitigate bias to assess causality. OBJECTIVE: To investigate the correlation between SP and comorbidities in orthopedic wards, and subsequently infer the causality, providing a theoretical basis for developing strategies in SP prevention and treatment. METHODS: Logistic regression models were employed to assess the correlation between SP and comorbidities. The MR analysis was mainly conducted with inverse variance weighted, utilizing data extracted from the UK and FinnGen biobank (Round 9). RESULTS: In the cross-sectional analysis, SP exhibited significant associations with malnutrition (P = 0.013) and some comorbidities, including osteoporosis (P = 0.014), body mass index (BMI) (P = 0.021), Charlson Comorbidity Index (CCI) (P = 0.006). The MR result also provided supporting evidence for the causality between SP and hypertension, osteoporosis and BMI. These results also withstood multiple sensitivity analyses assessing the validity of MR assumptions. CONCLUSION: The result indicated a significant association between SP and BMI, CCI, malnutrition, and osteoporosis. We highlighted that SP and comorbidities deserved more attention in non-geriatric wards, urging further comprehensive investigation.

Age-adjusted Charlson comorbidity index is associated with the risk of osteoporosis in older fall-prone men: a retrospective cohort study.

BACKGROUND: There is growing evidence linking the age-adjusted Charlson comorbidity index (aCCI), an assessment tool for multimorbidity, to fragility fracture and fracture-related postoperative complications. However, the role of multimorbidity in osteoporosis has not yet been thoroughly evaluated. We aimed to investigate the association between aCCI and the risk of osteoporosis in older adults at moderate to high risk of falling. METHODS: A total of 947 men were included from January 2015 to August 2022 in a hospital in Beijing, China. The aCCI was calculated by counting age and each comorbidity according to their weighted scores, and the participants were stratified into two groups by aCCI: low (aCCI < 5), and high (aCCI ≥5). The Kaplan Meier method was used to assess the cumulative incidence of osteoporosis by different levels of aCCI. The Cox proportional hazards regression model was used to estimate the association of aCCI with the risk of osteoporosis. Receiver operating characteristic (ROC) curve was adapted to assess the performance for aCCI in osteoporosis screening. RESULTS: At baseline, the mean age of all patients was 75.7 years, the mean BMI was 24.8 kg/m2, and 531 (56.1%) patients had high aCCI while 416 (43.9%) were having low aCCI. During a median follow-up of 6.6 years, 296 participants developed osteoporosis. Kaplan-Meier survival curves showed that participants with high aCCI had significantly higher cumulative incidence of osteoporosis compared with those had low aCCI (log-rank test: P < 0.001). When aCCI was examined as a continuous variable, the multivariable-adjusted model showed that the osteoporosis risk increased by 12.1% (HR = 1.121, 95% CI 1.041-1.206, P = 0.002) as aCCI increased by one unit. When aCCI was changed to a categorical variable, the multivariable-adjusted hazard ratios associated with different levels of aCCI [low (reference group) and high] were 1.00 and 1.557 (95% CI 1.223-1.983) for osteoporosis (P <  0.001), respectively. The aCCI (cutoff ≥5) revealed an area under ROC curve (AUC) of 0.566 (95%CI 0.527-0.605, P = 0.001) in identifying osteoporosis in older fall-prone men, with sensitivity of 64.9% and specificity of 47.9%. CONCLUSIONS: The current study indicated an association of higher aCCI with an increased risk of osteoporosis among older fall-prone men, supporting the possibility of aCCI as a marker of long-term skeletal-related adverse clinical outcomes.

Development and validation of the osteoporosis scale among the system of quality of life instruments for chronic diseases QLICD-OS (V2.0).

BACKGROUND: Quality of life of osteoporosis patients had caused widespread concern, due to high incidence and difficulty to cure. Scale specifics for osteoporosis and suitable for Chinese cultural background lacked. This study aimed to develop an osteoporosis scale in Quality of Life Instruments for Chronic Diseases system, namely QLICD-OS (V2.0). METHODS: Procedural decision-making approach of nominal group, focus group and modular approach were adopted. Our scale was developed based on experience of establishing scales at home and abroad. In this study, Quality of life measurements were performed on 127 osteoporosis patients before and after treatment to evaluate the psychometric properties. Validity was evaluated by qualitative analysis, item-domain correlation analysis, multi-scaling analysis and factor analysis; the SF-36 scale was used as criterion to carry out correlation analysis for criterion-related validity. The reliability was evaluated by the internal consistency coefficients Cronbach's α, test-retest reliability Pearson correlation r. Paired t-tests were performed on data of ​​the scale before and after treatment, with Standardized Response Mean (SRM) being calculated to evaluate the responsiveness. RESULTS: The QLICD-OS, composed of a general module (28 items) and an osteoporosis-specific module (14 items), had good content validity. Correlation analysis and factor analysis confirmed the construct, with the item having a strong correlation (most > 0.40) with its own domains/principle components, and a weak correlation (< 0.40) with other domains/principle components. Correlation coefficient between the similar domains of QLICD-OS and SF-36 showed reasonable criterion-related validity, with all coefficients r being greater than 0.40 exception of physical function of SF-36 and physical domain of QLICD-OS (0.24). Internal consistency reliability of QLICD-OS in all domains was greater than 0.7 except the specific module. The test-retest reliability coefficients (Pearson r) in all domains and overall score are higher than 0.80. Score changes after treatment were statistically significant, with SRM ranging from 0.35 to 0.79, indicating that QLICD-OS could be rated as medium responsiveness. CONCLUSION: As the first osteoporosis-specific quality of life scale developed by the modular approach in China, the QLICD-OS showed good reliability, validity and medium responsiveness, and could be used to measure quality of life in osteoporosis patients.