Background and Objectives: Osteoporosis is a prevalent skeletal disorder characterized by decreased bone mass and compromised bone microarchitecture, leading to an elevated risk of fractures and significant morbidity, particularly among aging populations. Early diagnosis and personalized management are critical to reducing fracture incidence and associated healthcare burdens. Recent advances in artificial intelligence (AI) and machine learning (ML) have led to potential improvements in enhancing osteoporosis care by enabling accurate diagnostic imaging analysis, robust fracture risk prediction, and personalized therapeutic strategies. Materials and Methods: We performed a narrative review to summarize and critically evaluate the current literature on AI and ML applications in osteoporosis diagnosis and management. We searched relevant literature from inception to January 2025 to provide a comprehensive perspective, focusing on key themes, methodological approaches, and clinical implications. Results: Deep learning models, especially convolutional neural networks, facilitate rapid and accurate bone mineral density assessment from routine radiographs, expanding screening capabilities beyond conventional dual-energy X-ray absorptiometry (DXA). Machine learning algorithms harness clinical and demographic data to generate fracture risk models that often outperform traditional tools, enabling timely identification of high-risk individuals. Furthermore, AI-driven analyses of historical treatment responses coupled with real-time monitoring through wearable technologies and mobile applications allow for personalized therapeutic optimization and enhance patient engagement. Despite these promising advances, challenges remain regarding ethical considerations, data privacy, legal liability, incomplete model validation, lack of standardization, and the need for critical appraisal of real-world clinical efficacy for widespread clinical adoption. Conclusions: This narrative review indicates that AI and ML hold significant promise to revolutionize osteoporosis management by enabling early detection, precise risk stratification, and tailored interventions. However, the current evidence is heterogeneous, often lacking robust external validation and quantitative synthesis. Critical gaps include insufficient evaluation of model robustness across diverse populations, discussion of negative or conflicting results, and a comprehensive assessment of the limitations inherent in current AI evidence. Strategic efforts to validate, regulate, and critically integrate these technologies into routine clinical workflows are essential to realize their full potential and address the growing burden of osteoporosis worldwide.

Objective. Melorheostosis is a rare, non-hereditary, benign bone disease characterized by abnormal bone growth. Generally, melorheostosis develops during childhood or adolescence and progresses gradually over time. This disease represents a true challenge to the physician because of its variability due to location, extension of the affected bone, and involvement of associated soft tissue. Pain management, physical therapy, and surgery may be recommended, depending on the individual case. This review aims to get an overview of the latest evidence relating to epidemiology, clinical and radiographic characteristics, diagnosis, and possible therapeutic strategies for melorheostosis and describe our experience through a clinical case. Methods. We designed a comprehensive literature search on melorheostosis in MEDLINE (via Pubmed) up to April 2023 and reviewed reports published in international journals. Results. The purpose is to highlight the importance of a multidisciplinary approach in the management of a rare disease such as melorheostosis. We discuss the role of different physicians, including genetists, rheumatologists, physiatrists, physical therapists, and orthopedic surgeons, in providing accurate diagnoses and effective treatments. We conducted a comprehensive review of the literature on the treatment of melorheostosis to support these findings. In addition, the article presents a case study of a patient suffering from melorheostosis, focusing on difficulties in reaching a correct diagnosis and attempts towards conservative and surgical interventions. The patient underwent hip arthroplasty, and the final result was an improvement in function and a reduction in pain. Conclusions. Managing melorheostosis can be challenging, and there is no standardized treatment for this condition at the moment.

Background/Objectives: Infection with the Chikungunya virus (CHIKV) results in acute febrile diseases with severe polyarthritis, which can be followed by chronic rheumatic disease and long-term disability. To evaluate cytokine profiles in acute and chronic CHIKV infection and examine the relationship with clinical outcomes, including persistent musculoskeletal symptoms. Methods: Literature search was carried out systematically using electronic databases (PubMed, Embase, Scopus, and Google Scholar). Studies that met eligibility criteria were observational or intervention cohorts that measured levels of cytokines/chemokines in laboratory-confirmed CHIKV patients in acute (3 months) phases. Data was extracted on the study design, population, biomarkers, and clinical outcomes. As the assays were not homogeneous in terms of timing, outcome, and definitions, the findings were synthesized in narrative form using tabular representation. Results: A total of 21 studies, including 4216 participants, were incorporated. In acute CHIKV, interleukin-6 (IL-6) (reported to be elevated in 81% of studies), IL-8 (77%), TNF-α (65%), and IFN-γ (60%) were most consistently increased, alongside interferon-inducible chemokines CXCL10/IP-10 and MCP-1. Chronic-phase cohorts showed persistent elevation of IL-6 (69%), IL-8 (63%), TNF-α (58%), and IL-17 (41%), especially among patients with prolonged arthralgia or arthritis. Chronic musculoskeletal symptoms were reported in 25–65% of cases, with some persisting beyond five years. A high degree of heterogeneity was observed in assay procedures and time of sampling. Conclusions: CHIKV infection is characterized by acute inflammatory surges and, in some cases, persistent cytokine dysregulation linked to chronic arthritis. These results showed the importance of prognostic biomarkers and targeted therapy.

Background and Objectives: Individuals classified as having very high fracture risk remain vulnerable to imminent fractures even when treated with antiresorptive therapies. This meta-analysis evaluated whether initiating treatment with anabolic agents, including teriparatide, abaloparatide, and romosozumab, provides superior fracture protection in this high-risk population. Materials and Methods: A systematic review and meta-analysis of randomized controlled trials was conducted following PRISMA standards. Eligible studies included adults at very high fracture risk, defined by recent or multiple fragility fractures or markedly low bone mineral density, who received anabolic therapy as initial treatment compared with placebo or antiresorptive agents. Outcomes of interest were new vertebral, non-vertebral, hip, and clinical fractures. Effect estimates were pooled using random-effects models. Results: Six randomized trials encompassing 17,872 participants were analyzed. Initiation with anabolic therapy was associated with a marked reduction in incident vertebral fractures. The labeled pooled summary estimate for vertebral fractures was 0.43 (95% confidence interval 0.34–0.54). Significant risk reductions were also observed for clinical fractures (hazard ratio 0.62, 95% confidence interval 0.51–0.75), non-vertebral fractures (pooled effect estimate 0.71, 95% confidence interval 0.59–0.85), and hip fractures (risk ratio 0.65, 95% confidence interval 0.45–0.96). Exploratory subgroup analyses suggested greater vertebral fracture protection versus placebo and persistent benefit versus active antiresorptive comparators. Sequential therapy using an anabolic agent followed by an antiresorptive reduced spinal fracture risk by approximately half. Considerable heterogeneity was noted for vertebral fracture outcomes. Conclusions: Starting osteoporosis treatment with anabolic agents results in faster and more-pronounced fracture risk reduction across all major fracture categories in patients at very high fracture risk. These findings support a shift toward anabolic-first treatment sequencing in this particularly vulnerable group.

Background/Objectives: Abaloparatide is an osteoanabolic therapy used in patients at high risk of fracture; however, the breadth of evidence across routes, comparators, and sequential strategies has not yet been comprehensively summarized. This study aimed to evaluate the efficacy and safety of abaloparatide for reducing fractures and improving bone mineral density (BMD) in adults with osteoporosis. Methods: Following PRISMA 2020, we searched PubMed, Embase, CENTRAL, and Web of Science (2016–2024) for randomized controlled trials and comparative real-world studies. Additional meta-analyses and network meta-analyses were included as contextual evidence but not pooled to avoid double-counting. Primary outcomes were vertebral, non-vertebral, and hip fractures; secondary outcomes included percentage change in BMD and safety endpoints. Random-effects models were used; heterogeneity, influence analyses, and prediction intervals were examined. Risk of bias was assessed using RoB 2 and AMSTAR 2. Results: Nine quantitative evidence sources met the criteria. Abaloparatide reduced vertebral fractures (RR 0.13–0.21) and showed moderate reductions in non-vertebral fractures. Lumbar spine BMD increased substantially, while hip and femoral neck gains were smaller and heterogeneous. Hypercalcemia risk was consistently lower compared to teriparatide. Transdermal delivery was less effective, and sequential abaloparatide → antiresorptive therapy further reduced fractures. Serious adverse events were not increased. Conclusions: Abaloparatide provides strong vertebral protection, significant BMD improvement, and shows a favorable calcemic profile, with moderate certainty for non-vertebral effects. Evidence in men and long-term safety remains limited.

Background: Knee osteoarthritis (KOA) in people with overweight or obesity is clinically heterogeneous, reflecting mechanical loading, synovial and systemic inflammation, metabolic dysfunction, structural severity, and pain-related factors. We evaluated multidomain outcomes after semaglutide initiation and characterized clinically relevant response patterns. Methods: This retrospective, self-controlled cohort included 93 adults treated in routine rheumatology care; 88 completed a six-month follow-up. There was no untreated concurrent comparator; within-patient changes and exposure–outcome associations were therefore interpreted as non-causal. Changes in pain, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) function, anthropometry, inflammatory markers, glycated hemoglobin (HbA1c), lipids, dose exposure, and safety were evaluated. Joint multivariable models included percentage weight loss and maximum achieved dose. Exploratory K-means phenotyping integrated dose, weight loss, body mass index (BMI) decrease, visual analog scale (VAS) and WOMAC improvement, and C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and HbA1c reductions, with candidate solutions and resampling stability examined. Results: At six months, mean weight decreased by 10.88 kg, VAS pain score by 2.47 points, WOMAC total by 22.50 points, CRP by 2.67 mg/L, ESR by 7.62 mm/h, and HbA1c by 0.51 percentage points (all p < 0.001). Weight loss remained independently associated with WOMAC improvement, while achieved dose retained positive adjusted associations with pain, function, inflammatory, and metabolic changes. Exploratory clustering identified five clinically interpretable patterns along a broader response-intensity gradient, including high-burden multidomain response, high-dose concordant response, dose-modified intermediate response, inflammation-preserved response despite moderate weight loss, and dose-limited graded response. These observational coefficients and clusters cannot distinguish treatment-related effects from residual confounding or co-interventions. Conclusions: Substantial within-patient improvements were observed, but the uncontrolled design precludes causal attribution. The exploratory patterns may be compatible with contributions from baseline disease burden, dose exposure, mechanical unloading, and residual inflammatory variation; they do not establish weight-independent pharmacologic effects or validated patient subtypes. Prospective controlled, multicenter validation is required.