High Risk Of Osteoporosis Research Articles

#1763 Risk factors and clinical prediction models for osteoporosis in predialysis chronic kidney disease patients

Abstract Background and Aims The research concerning osteoporosis among individuals with predialysis chronic kidney disease (CKD) has been relatively neglected in existing literature. Furthermore, the risk factors for osteoporosis in this demographic have not been adequately investigated. The objective of this study was to explore the risk factors associated with osteoporosis in predialysis CKD patients and to construct a predictive model capable of estimating the likelihood of osteoporosis in these individuals. Method A retrospective study was conducted on 326 predialysis CKD patients. Relevant clinical examination results and measurements of bone mineral density (BMD) using dual-energy X-ray absorptiometry were collected. Binary logistic regression was utilized to explore the risk factors associated with osteoporosis and to develop predictive models. Results In male predialysis CKD patients, age represents a risk factor, while 25-(OH)-Vitamin D acts as a protective factor against osteoporosis. Among female patients, age, underweight status, NBAP, and advanced CKD (G5) are significant risk factors for osteoporosis, whereas PTH serves as a protective factor. In pre-dialysis CKD patients in stages CKD1-4, age, underweight status, and NBAP are identified as risk factors for osteoporosis. For G5 predialysis patients, advanced age and NBAP pose a high risk of osteoporosis, while 25-(OH)-Vitamin D and PTH exhibit protective effects. Additionally, nomogram models illustrating the risk of osteoporosis in pre-dialysis patients of different genders and renal function stages were created. Conclusion Age, underweight, severity of renal dysfunction, NBAP, PTH, and 25-(OH)-vitamin D are strongly associated with osteoporosis in predialysis CKD patients.

The effect of fixation type on periprosthetic fractures in high-risk patients who have osteoporosis undergoing total joint arthroplasty

IntroductionMinimizing the burden of periprosthetic fractures (PFF) following total joint arthroplasty (TJA) with regard to morbidity and mortality remains an outcome of interest. Patient and surgical risk factors, including osteoporosis and fixation type, have not truly been optimized in patients undergoing TJA as a means to reduce the risk of PFF. As such, we examined: (1) What percentage of patients who underwent THA and total knee arthroplasty (TKA) met the criteria for osteoporosis screening? (2) How did the 5-year rate of PFF and fragility fracture differ in the high-risk and low-risk groups for osteoporosis between the cemented and cementless cohorts? (3) What percentage of the aforementioned patients received a dual x-ray absorptiometry (DEXA) scan before THA or TKA? MethodsWe queried an all-payer, national database from April 1, 2016 to December 31, 2021, to identify high-risk and low-risk patients who underwent TJA with a cementless or cemented fixation. High-risk patients met at least one of the following criteria: men at least 70 years old, women at least 65 years old, or patients at least 60 years old who have the following: tobacco use, alcohol abuse, body mass index <18.5, prior fragility fracture, chronic systemic corticosteroids, or genetic condition affecting sex hormones or bone mineral density. Exclusion criteria were a diagnosis of malignancy, high-energy events (motor vehicle collision), those who underwent TJA indicated for fracture, patients less than 50 years old, those who had a prior diagnosis of or treatment for osteoporosis, and a minimum follow-up of less than 2 years. ResultsThere were 384,783 patients (67.1 %) who underwent cementless TKA and 67,774 patients (11.8 %) who underwent cementless TKA who were considered high risk. Additionally, there were 62,505 patients (10.9 %) who underwent cemented THA and 58,667 patients (10.2 %) who underwent cementless THA and were considered high risk. The cementless cohort had a 5-year periprosthetic fracture risk following TKA of 7.8 % (95 % CI, 5.56 to 10.98) in comparison to 4.30 % in the cemented cohort (85 % CI, 3.98 to 4.65), P < 0.0001. The high-risk cementless cohort had a 5-year periprosthetic fracture risk following THA of 7.9 % (95 % confidence interval (CI), 6.87 to 9.19) in comparison to 7.78 % in the cemented cohort (85 % CI, 6.77 to 8.94), P < 0.0001. ConclusionThere is an increased risk of PFF at 5 years following TKA in patients at high risk for osteoporosis undergoing cementless fixation in comparison to cemented fixation. There is an increased risk of PFF at 5 years following THA in patients at high risk for osteoporosis for both cementless fixation and cemented fixation, but no clinically meaningful difference between the two groups. Addressing the shortcomings of the underutilization of bone density scans and better selecting appropriate patients for TJA based on bone quality and fracture risk can help expedite the process of improving the current state of practice.

CASE STUDY: IMPROVE BONE QUALITY AND SKELETAL MUSCLE MASS WITH A PROPER DIET AND EXERCISE FOR A PERSON AGED &gt;60 YEARS OLD

Objective: To evaluate the effects of proper dietary and exercise practice on bone mineral quality, skelet muscle and fatty mass in a person aged &gt; 60y. Subject &amp; Methods: A 60 ys- old male subject, risk of osteoporosis received the daily diet 2000Kcal, Ca 1300mg, protein 1.7mg/kg.bw, vitamin D 665IU. Endurance exercise 3 times/week x 60 minutes/ session with moderate &amp; high intensity levels; 45 minutes daily morning with moderate and light intensity, and 8 hours working at office. Heel- bone mineral density (BMD) measured by Quantitative Ultra-Sonic (QUS) instrument, skelets muscle and fat mass by Inbody 370S intrument every 6 months. The study period lasted 60 months (T60). Results: The T-score of heel bone increase from -2.4 (high risk osteoporosis) at the beginning (T0) to level of pick bone mass at T36, then maintained until T60 of intervention. The BUA (Broadband Ultrasound Attenuation), reflects the quality of the bone s’ trabecular, were also improved from 39.5dB/MHz to 108.1dB/MHz (+173.7%) from T0 to T60 respectively. The body weight, skelet-muscle &amp; fat mass were maintained quite stable during 60 months of the study. Conclusion: A proper diet and exercise restored bone quality to pick bone mass levels, maintain skeletal muscle and body fat mass in the elderly.

ASSESSING RISK FACTORS FOR OSTEOPOROSIS AND FRACTURES AT DIFFERENT SITES: LUMBAR VERTEBRAE VERSUS NECK OF FEMURS IN A LARGE COHORT. A CROSS-SECTIONAL STUDY

Osteoporosis can cause significant disability and cost to health services globally. We aim to compare risk fractures for both osteoporosis and fractures at the L1-L4 vertebrae (LV) and the neck of femurs (NOFs) in patients referred for DEXA scan in the North-West of England.Data was obtained from 31546 patients referred for DEXA scan in the North-West of England between 2004 and 2011. Demographic data was retrospectively analysed using STATA, utilising chi-squared and t-tests. Logistical models were used to report odds ratios for risk factors included in the FRAX tool looking for differences between osteoporosis and fracture risk at the LV and NOFs.In a study involving 2530 cases of LV fractures and 1363 of NOF fractures, age was significantly linked to fractures and osteoporosis at both sites, with a higher risk of osteoporosis at NOFs compared to LV. Height provided protection against fractures and osteoporosis at both sites, with a more pronounced protective effect against osteoporosis at NOFs. Weight was more protective for NOF fractures, while smoking increased osteoporosis risk with no site-specific difference. Steroids were unexpectedly protective for fractures at both sites, with no significant difference, while alcohol consumption was protective against osteoporosis at both sites and associated with increased LV fracture risk. Rheumatoid arthritis increased osteoporosis risk in NOFs and implied a higher fracture risk, though not statistically significant compared to LV. Results summarised in Table 1.Our study reveals that established osteoporosis and fracture risk factors impact distinct bony sites differently. Age and rheumatoid arthritis increase osteoporosis risk more at NOFs than LV, while height and steroids provide greater protection at NOFs. Height significantly protects LV fractures, with alcohol predicting them. Further research is needed to explore risk factors’ impact on additional bony sites and understand the observed differences’ pathophysiology.For any figures or tables, please contact the authors directly.

High content omega-3 fish oil co-treatment maintains proper bone physiology in glucocorticoid treated autoimmune mice

Despite the known side effects of glucocorticoid therapy, such as a higher risk of osteoporosis, fractures, and reduced bone density, it remains a frequently prescribed treatment for autoimmune disorders due to its strong anti-inflammatory and immunosuppressive properties. If strategies could be identified to reduce the side effects commonly associated with glucocorticoid use, it could lead to more frequent and safer use of this treatment option for autoimmune diseases. In this work, the combined effects of high content omega-3 fish oil (HCW3FO) and a synthetic glucocorticoid, methylprednisolone (MP) medication are investigated in relation to bone mineral density (BMD) reduction in arthritis prone female MRL-lpr/lpr mice. Two treatment groups were introduced to the mice when they were 4 months old: one group was given weekly injections of PBS, while the other group was given either 5 mg/kg MP or 20 mg/kg MP. Additionally, both groups were provided with the AIN93M diet, supplemented with either 4% corn oil or 4% HCW3FO daily, for a duration of 8 weeks. Prior to initiating the drug injections and dietary modifications, the mice underwent dual energy x-ray absorptiometry (DXA) scans to establish their baseline BMD values. To find out their ultimate BMD values, the mice underwent another DXA scan eight weeks later, right before being sacrificed. Over the course of eight weeks, the MP treatment did not lead to a significant reduction in BMD across various bone regions, except for the lumbar regions. Similarly, the HCW3FO treatment alone did not offer protection against BMD loss in MRL-lpr/lpr mice. However, when MP and HCW3FO were combined, it resulted in a remarkable preservation of BMD in different bone regions. This enhanced protection against BMD loss was associated with a reduced number of tartrate-resistant acid phosphatase (TRAP) positive areas and an increased number of alkaline phosphatase (ALP) positive areas in tibial sections as revealed by immunohistochemistry. Our findings provide compelling evidence that the combination of MP and HCW3FO maintains bone health in arthritis-prone MRL-lpr/lpr mice by promoting a balance between bone resorption and bone formation. Co-treatment with HCW3FO may hold promise as a potential strategy for preventing bone deterioration induced by long-term glucocorticoid therapy. Before moving on to clinical trials, more in vitro research into the mechanisms should be carried out alongside preclinical studies in mice with inflammatory diseases. QUCG-CAS-2122-2. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Detection of Pancreatic Cancer and Nutritional Support in Chronic Pancreatitis

Chronic pancreatitis (CP) is a significant risk factor for pancreatic cancer and there had been a great deal of interest in surveillance and detection of pancreatic cancer. According to presence of genetic mutation, CP can be classified into hereditary CP and sporadic CP. CP with PRSS1 gene mutation showed a high incidence of pancreatic cancer justifying screening and surveillance for those older than 40 years. But CP with other mutations and sporadic CP have relatively low incidence of pancreatic cancer and surveillance is not recommended. While computed tomography or magnetic resonance imaging is widely used for screening, endoscopic ultrasound is not recommended because of parenchymal inflammation, fibrosis, and calcification associated with CP. However, when a patient with CP has multiple risk factors for pancreatic cancer, risk of pancreatic cancer increases significantly. Patients with CP have increased risk of pancreatic cancer at five years after diagnosis; individualized screening and surveillance based on symptoms and specific circumstances should be considered. Patients with CP have a high risk of malnutrition and malnutrition is quite common. Clinicians should assess nutritional status and implement nutritional support. Nutritional support must include both macronutrients and micronutrients. Given the high risk of osteoporosis and osteopathy in CP, clinicians should consider early diagnosis, prevention, and treatment. Consultation with nutritional support team is highly recommended.

Application of machine learning algorithms to identify people with low bone density.

Osteoporosis is becoming more common worldwide, imposing a substantial burden on individuals and society. The onset of osteoporosis is subtle, early detection is challenging, and population-wide screening is infeasible. Thus, there is a need to develop a method to identify those at high risk for osteoporosis. This study aimed to develop a machine learning algorithm to effectively identify people with low bone density, using readily available demographic and blood biochemical data. Using NHANES 2017-2020 data, participants over 50 years old with complete femoral neck BMD data were selected. This cohort was randomly divided into training (70%) and test (30%) sets. Lasso regression selected variables for inclusion in six machine learning models built on the training data: logistic regression (LR), support vector machine (SVM), gradient boosting machine (GBM), naive Bayes (NB), artificial neural network (ANN) and random forest (RF). NHANES data from the 2013-2014 cycle was used as an external validation set input into the models to verify their generalizability. Model discrimination was assessed via AUC, accuracy, sensitivity, specificity, precision and F1 score. Calibration curves evaluated goodness-of-fit. Decision curves determined clinical utility. The SHAP framework analyzed variable importance. A total of 3,545 participants were included in the internal validation set of this study, of whom 1870 had normal bone density and 1,675 had low bone density Lasso regression selected 19 variables. In the test set, AUC was 0.785 (LR), 0.780 (SVM), 0.775 (GBM), 0.729 (NB), 0.771 (ANN), and 0.768 (RF). The LR model has the best discrimination and a better calibration curve fit, the best clinical net benefit for the decision curve, and it also reflects good predictive power in the external validation dataset The top variables in the LR model were: age, BMI, gender, creatine phosphokinase, total cholesterol and alkaline phosphatase. The machine learning model demonstrated effective classification of low BMD using blood biomarkers. This could aid clinical decision making for osteoporosis prevention and management.

Osteoporosis and Primary Biliary Cholangitis: A Trans-ethnic Mendelian Randomization Analysis.

Osteoporosis is a major clinical problem in many autoimmune diseases, including primary biliary cholangitis (PBC), the most common autoimmune liver disease. Osteoporosis is a major cause of fracture and related mortality. However, it remains unclear whether PBC confers a causally risk-increasing effect on osteoporosis. Herein, we aimed to investigate the causal relationship between PBC and osteoporosis and whether the relationship is independent of potential confounders. We performed bidirectional Mendelian randomization (MR) analyses to investigate the association between PBC (8021 cases and 16,489 controls) and osteoporosis in Europeans (the UK Biobank and FinnGen Consortium: 12,787 cases and 726,996 controls). The direct effect of PBC on osteoporosis was estimated using multivariable MR analyses. An independent replication was conducted in East Asians (PBC: 2495 cases and 4283 controls; osteoporosis: 9794 cases and 168,932 controls). Trans-ethnic meta-analysis was performed by pooling the MR estimates of Europeans and East Asians. Inverse-variance weighted analyses revealed that genetic liability to PBC was associated with a higher risk of osteoporosis in Europeans (OR, 1.040; 95% CI, 1.016-1.064; P = 0.001). Furthermore, the causal effect of PBC on osteoporosis persisted after adjusting for BMI, calcium, lipidemic traits, and sex hormones. The causal relationship was further validated in the East Asians (OR, 1.059; 95% CI, 1.023-1.096; P = 0.001). Trans-ethnic meta-analysis confirmed that PBC conferred increased risk on osteoporosis (OR, 1.045; 95% CI, 1.025-1.067; P = 8.17 × 10-6). Our data supports a causal effect of PBC on osteoporosis, and the causality is independent of BMI, calcium, triglycerides, and several sex hormones.

Risk Factors for Bone Fractures in Patients With Comorbid Pathology

Patients with heart failure (HF) have elevated levels of pro-inflammatory cytokines such as tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6), leading to macrophage activation, impaired microvascular function, changes in muscle contraction and fibrosis development. In addition, these proinflammatory cytokines promote bone resorption, thereby increasing the incidence of bone fractures. The aim of the study is to evaluate the effect of tumor necrosis factor-alpha receptor types 1 and 2 (TNF-α-SR1 and TNF-α-SR2) on fracture probability in individuals with osteoporosis who have concurrent chronic heart failure (HF) and type 2 diabetes mellitus (T2DM). The study was conducted on 178 women aged 50 to 65 years. Among these women, 48 were in group 1 and had both heart failure and type 2 diabetes. Group 2 included 93 patients with osteoporosis and heart failure and group 3 included 37 women with osteoporosis, heart failure and type 2 diabetes. Thirty-five postmenopausal women without any clinical and instrumental signs of cardiovascular pathology or osteoporosis were selected as the control group. The levels of TNF-α-SR1 and TNF-α-SR2 receptors in patient groups 1-3 were significantly higher (p&lt;0.01) than in the control group, as were their concentrations. In addition, it was found that the levels of both receptors were significantly higher in group 3 than in patients in groups 1 and 2. To evaluate the levels of TNF-α-SR1 and TNF-α-SR2, the data were divided into four quartiles (Q1-Q4) based on the increase in the concentrations of these markers. For TNF-α-SR2, an increasing risk gradient was observed, with the odds ratio (OR) for osteoporosis events increasing from 1.4 to 12.83, but the risk was statistically significant only for Q3-Q4. For Q4 TNF-α-SR1 levels, a significant increase in the risk of an adverse osteoporosis outcome at 36 months was also found (OR=5.25, p=0.038). In addition, the use of loop diuretics was found to be a predictor of high risk of osteoporotic fractures in patients with chronic HF (JR=6.29, 95% CI=1.45-17.26, p=0.015). Postmenopausal women with chronic HF and elevated levels of soluble TNF-α-SR1 and TNF-α-SR2 receptors are at higher risk for osteoporosis and adverse disease progression. In addition, the use of loop diuretics in these individuals is associated with an increased risk of osteoporotic fractures.

Using machine learning techniques to predict the risk of osteoporosis based on nationwide chronic disease data

Osteoporosis is a major public health concern that significantly increases the risk of fractures. The aim of this study was to develop a Machine Learning based predictive model to screen individuals at high risk of osteoporosis based on chronic disease data, thus facilitating early detection and personalized management. A total of 10,000 complete patient records of primary healthcare data in the German Disease Analyzer database (IMS HEALTH) were included, of which 1293 diagnosed with osteoporosis and 8707 without the condition. The demographic characteristics and chronic disease data, including age, gender, lipid disorder, cancer, COPD, hypertension, heart failure, CHD, diabetes, chronic kidney disease, and stroke were collected from electronic health records. Ten different machine learning algorithms were employed to construct the predictive mode. The performance of the model was further validated and the relative importance of features in the model was analyzed. Out of the ten machine learning algorithms, the Stacker model based on Logistic Regression, AdaBoost Classifier, and Gradient Boosting Classifier demonstrated superior performance. The Stacker model demonstrated excellent performance through ten-fold cross-validation on the training set and ROC curve analysis on the test set. The confusion matrix, lift curve and calibration curves indicated that the Stacker model had optimal clinical utility. Further analysis on feature importance highlighted age, gender, lipid metabolism disorders, cancer, and COPD as the top five influential variables. In this study, a predictive model for osteoporosis based on chronic disease data was developed using machine learning. The model shows great potential in early detection and risk stratification of osteoporosis, ultimately facilitating personalized prevention and management strategies.

Blood cell count-derived inflammation indices as predictors of the osteoporotic risk of postmenopausal women.

We investigated the associations between osteoporosis (OP) and systemic immune inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and platelet-to-lymphocyte ratio (PLR) in postmenopausal women. This retrospective study included 966 postmenopausal women. Logistic regression and receiver operating characteristic curve (ROC) analyses were applied to explore the relationships between SII, NLR, MLR, and PLR with the bone mineral density (BMD) and risk of OP. Logistic regression analyses showed that SII, PLR, NLR, and MLR had independent negative associations with the OP risk. The ROC curve analysis showed that SII, NLR, and MLR predicted a low BMD, with NLR having the highest predictive value (area under the curve = 0.624). SII > 504.09, PLR > 131.87, NLR > 2.02, and MLR > 0.12 correlated with a particularly high OP risk. High levels of SII, PLR, NLR, and MLR were associated with a high OP risk. In particular, NLR > 2.02 strongly predicted the risk of OP, thereby representing a valuable and convenient inflammatory marker of the OP risk.

Assessing the utility of osteoporosis self-assessment tool for Asians in patients undergoing hip surgery

ObjectivesDiagnosis and treatment of osteoporosis are instrumental in obtaining good outcomes of hip surgery. Measuring bone mineral density (BMD) using dual-energy X-ray absorptiometry (DXA) is the gold standard for diagnosing osteoporosis. However, due to limited access to DXA, there is a need for a screening tool to identify patients at a higher risk of osteoporosis. We analyzed the potential utility of the Osteoporosis Self-assessment Tool for Asians (OSTA) as a screening tool for osteoporosis. MethodsA total of 1378 female patients who underwent hip surgery at 8 institutions were analyzed. For each patient, the BMD of the proximal femoral region was measured by DXA (DXA-BMD), and the correlation with OSTA score (as a continuous variable) was assessed. Receiver operating characteristic (ROC) curve analysis was performed to assess the ability of OSTA score to predict osteoporosis. Lastly, the OSTA score was truncated to yield an integer (OSTA index) to clarify the percentage of patients with osteoporosis for each index. ResultsDXA-BMD showed a strong correlation with OSTA (r = 0.683; P < 0.001). On ROC curve analysis, the optimal OSTA score cut-off value of −5.4 was associated with 73.8% sensitivity and 80.9% specificity for diagnosis of osteoporosis (area under the curve: 0.842). A decrease in the OSTA index by 1 unit was associated with a 7.3% increase in the probability of osteoporosis. ConclusionsOSTA is a potentially useful tool for screening osteoporosis in patients undergoing hip surgery. Our findings may help identify high-risk patients who require further investigation using DXA.

The association between night shift work and osteoporosis risk in adults: A cross-sectional analysis using NHANES

PurposeThrough this study, we assess whether night shift work increases the risk of osteoporosis, and explore the effects of age, gender, or lifestyle differences. MethodsThis cross-sectional study included the collection of data from a sample of the US adults who participated in the National Health and Nutrition Examination Survey (NHANES) over a 7.3-year period (2007–2008, 2009–2010, 2017–March2020), including 4408 participants (2351[52.8%] men and 2057[47.2%] women), with an age range of 20–80 years. The primary variables, health status, nutrition, harmful lifestyle habits, and bone mineral density (BMD), were segregated, and analyzed according to different work schedules. Linear regression models were conducted to evaluate correlations of night shift work and T-scores. Associations between night shift work and osteoporosis were examined using logistic regression analyses. All regression models were stratified by gender and age ≥50 years. Osteoporosis was defined as BMD at the femoral neck or total spine equal to or less than 2.5 standard deviations below the mean for youthful people of the same gender. All data were obtained using questionnaires and examinations collected in mobile examination center (MEC) from NHANES. ResultsAfter multivariate adjustment, night shift work was related to statistically significant decreases of the total spine in T-scores of females aged ≥50 years. Furthermore, night shift work of the overall population (OR = 2.31 [95% CI, 1.03–5.18]; P = 0.043) and females aged ≥50 years (OR = 4.6 [95% CI, 1.21–17.54]; P = 0.025) was related to an increased prevalence of osteoporosis. ConclusionNight shift work correlates with a higher risk of osteoporosis in the population of the US adults, with the combined effect of age, gender, and harmful lifestyle.

Red light-emitting diode therapy minimizes the functional deleterious effects of the antiretroviral ritonavir on osteoblasts in vitro.

Long-term human immunodeficiency virus (HIV)-infected patients are considered at higher risk for osteoporosis. Among the various causes that lead these patients to lower bone health, there is the use of antiretroviral drugs (ARVs), especially protease inhibitors (PI), such as ritonavir (RTV). In this context, emerge the potential benefits of LED therapy, whose effects on bone cells are currently being extensively studied, showing a modulation in cell differentiation. However, it remains unclear if photobiostimulation might interfere with RTV effects on osteoblast differentiation. In the present study, we investigated the effects of red LED (625nm) irradiation (15 mW/cm2, 0.2J/cm2, and 8 mW/cm2, 0.12J/cm2) on osteoblast cell line MC3T3-E1 treated with RTV (2.5, 5, and 10μg/mL). Our results indicated that red LED irradiation was able to reverse, or at least minimize, the deleterious effects of RTV on the osteoblasts. Neither the ARV treatments 5 and 10μg/mL (104.4% and 95.01%) nor the LED protocols (100.3% and 105.7%) statistically altered cell viability, assessed by the MTT assay. Also, the alkaline phosphatase activity and mineralization showed a decrease in osteoblast activity followed by ARV exposure (39.3-73%), which was attenuated by LED in more than 70% with statistical significance (p < 0.05). In conclusion, photobiostimulation with red LED at 625nm was associated with improved beneficial biological effects as a potential inducer of osteogenic activity on RTV-affected cells. This is the first study that investigated the benefits of red LED irradiation over ARV-treated in vitro osteoblasts.

Daily yogurt consumption does not affect bone turnover markers in men and postmenopausal women of Caribbean Latino descent: a randomized controlled trial

BackgroundCaribbean Latino adults are at high risk for osteoporosis yet remain underrepresented in bone research. This increased risk is attributed to genetics, diet, and lifestyle known to drive inflammation and microbial dysbiosis.ObjectiveThe primary objective of this study was to determine whether consuming 5 oz of yogurt daily for 8wks improves bone turnover markers (BTMs) among Caribbean Latino adults > 50 years; and secondarily to determine the impact on the gut microbiota and markers of intestinal integrity and inflammation.MethodsFollowing a 4wk baseline period, participants were randomized to an 8wk whole fat yogurt intervention (n = 10) daily, containing only Streptococcus thermophilus and Lactobacillus bulgaricus, or to an untreated control group that did not consume yogurt (n = 10). Blood and stool samples collected at week-0 and week-8 were used to assess BTMs, inflammation, intestinal integrity biomarkers, and gut microbiota composition, short chain fatty acids (SCFAs), respectively. Data were evaluated for normality and statistical analyses were performed.ResultsParticipants were 55% women, with a mean age of 70 ± 9 years, BMI 30 ± 6 kg/m2, and serum C-reactive protein 4.8 ± 3.6 mg/L, indicating chronic low-grade inflammation. Following 8wks of yogurt intake, absolute change in BTMs did not differ significantly between groups (P = 0.06–0.78). Secondarily, absolute change in markers of inflammation, intestinal integrity, and fecal SCFAs did not differ significantly between groups (P range 0.13–1.00). Yogurt intake for 8wks was significantly associated with microbial compositional changes of rare taxa (P = 0.048); however, no significant alpha diversity changes were observed.ConclusionsIn this study, daily yogurt did not improve BTMs, inflammation, intestinal integrity, nor SCFAs. However, yogurt did influence beta diversity, or the abundance of rare taxa within the gut microbiota of the yogurt group, compared to controls. Additional research to identify dietary approaches to reduce osteoporosis risk among Caribbean Latino adults is needed.Trial registrationThis study is registered to ClinicalTrials.gov, NCT05350579 (28/04/2022).

Osteoporosis and bone health in pediatric patients with epidermolysis bullosa: A scoping review.

Nutritional compromise, low levels of vitamin D, chronic inflammation, abnormal growth, and physical inactivity affect bone metabolism and compromise long-term bone health in individuals with epidermolysis bullosa (EB). The result is a high risk for osteopenia, osteoporosis, and pathologic fractures, but this important consequence of EB has been the focus of few investigations. Our scoping review found 21 publications that assessed the current understanding and clinical practices for monitoring of osteoporosis and its treatment in EB. Recommendations summarized from 13 of these publications include early nutritional and weight assessments before 2 years of age; bloodwork every 6-12 months starting at birth; Tanner stage assessments every 6 months to detect any pubertal delay; DEXA scans starting at age 6 years with repeated scans every 1-2 years, except in mild cases; and vitamin D supplementation of 80-320 IU daily for children 0-7 years and 720 IU for patients >8 years.

The association between bone density of lumbar spines and different daily protein intake in different renal function

Background Low protein intake (LPI) has been suggested as a treatment for chronic kidney disease (CKD). However, protein intake is essential for bone health. Methods We studied the database of the National Health and Nutrition Examination Survey, 2005–2010. Basic variables, metabolic diseases, and bone density of different femoral areas were stratified into four subgroups according to different protein intake (DPI) (that is, <0.8, 0.8–1.0, 1.0–1.2, and >1.2 g/kg/day). Results Significant differences were found among all lumbar area bone mineral density (BMD) and T-scores (p < 0.0001). There was an apparent trend between a decreasing BMD in the CKD groups with increasing DPI in all single lumbar spines (L1, L2, L3, and L4) and all L spines (L1-L4). Compared with DPI (0.8–1.0 g/day/kg), higher risks of osteoporosis were noticed in the subgroup of >1.2 g/day/kg over L2 (relative risk (RR)=1.326, 95% confidence interval (CI)=1.062–1.656), subgroup >1.2 g/day/kg over L3 (RR = 1.31, 95%CI = 1.057–1.622), subgroup <0.8 g/day/kg over L4 (RR = 1.276, 95%CI = 1.015–1.605), subgroup <0.8 g/day/kg over all L spines (RR = 11.275, 95%CI = 1.051–1.548), and subgroup >1.2 g/day/kg over all L spines (RR = 0.333, 95%CI = 1.098–1.618). However, a higher risk of osteoporosis was observed only in the non-CKD group. There was an apparent trend of higher DPI coexisting with lower BMD and T scores in patients with CKD. For osteoporosis (reference:0.8–1.0 g/day/kg), lower (<0.8 g/day/kg) or higher DPI (>1.2 g/day/kg) was associated with higher risks in the non-CKD group, but not in the CKD group. Conclusions In the CKD group, LPI for renal protection was safe without threatening L spine bone density and without causing a higher risk of osteoporosis.

Performance of a preventive care programme for osteoporosis in primary care settings in Singapore during the COVID-19 pandemic

Background The Agency for Care Effectiveness of Singapore has advised primary care physicians to use osteoporosis screening tools to risk-stratify patients in the primary care setting. Objective This paper aims to report the uptake of a “Predict and Prevent” workflow for osteoporosis using risk scoring and BMD measurement in patients with chronic diseases seen in a network of primary care clinics in Singapore from 2020 to 2021. Methods A “Predict and Prevent” osteoporosis preventive care programme was implemented at a network of 11 primary care clinics. The programme included all adult patients that consulted at the clinic for a chronic condition. OSTA score was computed for each patient. All patients who consented to further fracture risk screening underwent FRAX scoring. Female patients with a high-risk OSTA score and females with diabetes with intermediate-risk OSTA score (per protocol), or those with high-risk FRAX score were recommended to undergo BMD measurement. Results Of the 6,332 adult patients with chronic diseases without baseline osteoporosis seen in the various clinics, 81.1% underwent OSTA scoring; 28.1% were intermediate risk and 7.0% were high risk. Among the per-protocol population ( n = 531), 38 (7.1%) underwent BMD testing. FRAX scoring (without BMD) was done on 939 patients (17.3%); 31.5% had a high hip fracture risk. Only 14 patients had FRAX with BMD; 57.1% had a high hip fracture risk. Conclusion A “Predict and Prevent” workflow could be implemented to screen, detect and potentially treat patients at high risk of osteoporosis. The rate of BMD measurement is low and needs to be improved.

Opportunistic screening for osteoporosis using enhanced images based on dual-energy computed tomography material decomposition: a comparison with quantitative computed tomography.

Many patients with malignant tumors require chemotherapy and radiation therapy, which can result in a decline in physical function and potentially influence bone mineral density (BMD). Furthermore, these treatments necessitate enhanced computed tomography (CT) scans for determining disease staging or treatment outcomes, and opportunistic screening with available imaging data is beneficial for patients at high risk for osteoporosis if existing imaging data can be used. The study aimed to investigate the feasibility of opportunistic screening for osteoporosis using enhanced CT based on a dual-energy CT (DECT) material decomposition technique. We prospectively enrolled 346 consecutive patients who underwent abdominal unenhanced and triphasic contrast-enhanced CT (arterial, portal venous, and delayed phases) between June 2021 and June 2022. The BMD, and the density of hydroxyapatite (HAP) on HAP-iodine images and calcium (Ca) on Ca-iodine images were measured on the L1-L3 vertebral bodies. The iodine intake was recorded. Pearson analysis was conducted to assess the correlation between iodine intake and the density values in three phases and the correlation between BMD and the densities of HAP and Ca. Furthermore, linear regression was employed for quantitative evaluation. Bland-Altman analysis was used to evaluate the agreement between calculated BMD derived from DECT (BMD-DECT) and reference BMD derived from quantitative CT (BMD-QCT). Receiver operating characteristic (ROC) analysis was applied to assess the diagnostic efficacy. The HAP and Ca density of the L1-L3 vertebral bodies did not differ significantly among the three phases of contrast-enhanced CT (F=0.001-0.049; P>0.05). Significant positive correlations were found between HAP, Ca densities, and BMD (HAP-BMD: r=0.9472, R2=0.8973; Ca-BMD: r=0.9470, R2=0.8968; all P<0.001). Bland-Altman plots showed high agreement between BMD-DECT and BMD-QCT. The area under the curve (AUC) using HAP and Ca measurements was 0.963 [95% confidence interval (CI): 0.937-0.980] and 0.964 (95% CI: 0.939-0.981), respectively, for diagnosing osteoporosis and was 0.951 (95% CI: 0.917-0.973) and 0.950 (95% CI: 0.916-0.973), respectively, for diagnosing osteopenia. The HAP and Ca density measurements generated through the material decomposition technique in DECT have good diagnostic performances in assessing BMD, which offers a new perspective for opportunistic screening of osteoporosis on contrast-enhanced CT.

A 10-Year Experience of an Integrated Geriatric Hip Fracture Treatment Protocol: Outcomes at a Minimum 2-Year Follow-Up.

Increasing incidence of fragility fractures has spurred development of protocols, largely focused on peri-operative care, with numerous proven benefits. The purpose of this investigation was to evaluate outcomes of our hip fracture treatment program regarding successful protocol implementation, compliance, effect on subsequent fracture rates, and mortality during the first decade of adoption. A retrospective review identified patients >65years old with fragility hip fractures between 2010 and 2022. The HiROC (+) cohort consisted of patients who received a "High-Risk Osteoporosis Clinic" (HiROC) referral for bone health evaluation and bisphosphonate initiation as indicated. Additional fracture rates and mortality at 3 years were calculated. Protocol implementation and compliance over the first 10years was analyzed in the four identified cohorts. A total of 1671 fragility hip fractures were identified, with 386 excluded due to insufficient follow-up, with an average age of 81.6 years and a median follow-up of 36.4 months. Of the 1280 included cases, 56% (n = 717) had a HiROC referral placed. HiROC(+) groups had lower subsequent fracture rates at two years, compared to those without referral (28% vs 13%, P < 0.0001) and those completing more steps of the protocol had lower subsequent fracture rates (28% vs 15% vs 13% vs 5%, P < 0.0001). No statistically significant difference was observed between the cohorts for anatomic site of subsequent fractures. Greater than half of all eligible patients were successfully captured by the protocol. Patients completing more steps of the protocol had lower subsequent fracture rates. Captured patients demonstrated reduced mortality rates when compared to current literature. Successful implementation of this geriatric hip fracture protocol was associated with reduced additional fractures and mortality rates. Identifying steps of process failures in the protocol can provide opportunities for increased compliance and reduction in future fracture occurrences.