Osteoarthritis (OA) is now understood as a heterogeneous syndrome driven by diverse biological, biomechanical, metabolic, genetic, and molecular mechanisms. This variability explains differences in disease progression and treatment response, challenging the traditional “one-size-fits-all” approach. This review highlights OA phenotyping as a key step toward precision medicine, focusing on clinical, structural, and molecular classifications that inform individualized care. A narrative review was conducted using a non-systematic search of major databases and Osteoarthritis Research Society International sources (2010–2026). Evidence was thematically synthesized across clinical, imaging, and molecular domains to characterize OA phenotypes and their potential relevance to precision medicine. Multiple OA phenotypes were identified: inflammatory, metabolic, biomechanical, cartilage–subchondral, pain-sensitization, and aging/senescence. These exhibit distinct clinical features, risk factors, and therapeutic responses. Imaging-based phenotypes (e.g., inflammatory, meniscus–cartilage, subchondral bone, atrophic, hypertrophic) and molecular endotypes (low turnover, structural damage, systemic inflammation) further refine stratification. Pain–structure discordance is notable in sensitization phenotypes and may predict poorer surgical outcomes. Joint-specific variations and emerging genomic and epigenetic insights underscore disease complexity. Advances in imaging, biomarkers, and machine learning may enable earlier detection and patient clustering, though clinical application remains limited. Phenotype- and endotype-based classification represents a critical advancement toward precision OA management. Tailored interventions based on stratification hold promise for improving outcomes; however, clinical translation remains limited by overlapping phenotypes, lack of validated biomarkers, and inconsistent results from phenotype-driven trials. Wider clinical adoption requires standardized definitions, validation across joints, and integration of multimodal diagnostic tools into routine practice.
Obesity and type 2 diabetes mellitus (T2DM) are global challenges, with obesity increasing risk of T2DM. Body mass index (BMI), the conventional measure of obesity, may not accurately predict metabolic risk, especially in Asian individuals. Evaluation of alternative anthropometric indices may offer additional approaches for risk assessment. The multicenter, cross-sectional study examined whether anthropometric indices—such as waist, hip, neck, calf, and wrist circumferences, as well as waist–hip, neck–height, and waist–calf ratios—are associated with T2DM in adults with obesity. The study included 750 adults (BMI ≥ 25 kg/m2) recruited from four endocrinology centers across India. Anthropometric and clinical data were recorded using a standardized electronic form. T2DM was present in 73
Polyetheretherketone (PEEK) has gained attention as an alternative to metallic implants in orthopaedic applications, including arthroplasty, due to its mechanical properties and biocompatibility. This review evaluates the role of PEEK in arthroplasty and other orthopaedic applications by analysing its biomechanical characteristics, surface modifications, and clinical outcomes A comprehensive literature review was conducted using PubMed, PubMed Central (PMC), Scopus, and Embase. Eligible studies included randomised controlled trials, cohort studies, preclinical research, and systematic reviews. PEEK’s elastic modulus (3–4 GPa) closely matches that of human cortical bone, potentially reducing stress shielding and enhancing osseointegration. Its inherent radiolucency improves imaging capabilities, while various surface modification techniques, including hydroxyapatite coatings and nanopatterning, have been developed to enhance bone integration. Despite positive preclinical outcomes, clinical studies are predominantly focused on short- to mid-term results, with limited long-term data on implant survivorship and complications. While PEEK shows promise in orthopaedic applications, further research is necessary to establish its clinical efficacy relative to traditional metals. Addressing the current gaps in long-term studies, regulatory challenges, and manufacturing processes will be crucial for the broader adoption of PEEK implants in orthopaedic surgery. This review highlights the ongoing evolution of PEEK in the field and suggests directions for future research.
Background: The SICOT-J, an open-access orthopedic journal affiliated with the Société Internationale de Chirurgie Orthopédique et de Traumatologie (SICOT), has been a global orthopedic research platform since 2015. This study provides a scientometric analysis of SICOT-J publications from 2015 to 2025 to evaluate research productivity, citation impact, and collaboration patterns. Methods: 542 documents published in SICOT-J and indexed in the Scopus database were analyzed using bibliometric indicators. Data on publication types, subject areas, authorship, institutional and geographic affiliations, funding disclosures, collaboration networks, and citation metrics were extracted. Microsoft Excel was used for data processing and analysis. Key indicators included citations per publication (CPP), relative citation index (RCI), and total link strength (TLS) for collaborative connections. Results: From January 1 2015, to June 30 2025, SICOT-J published 542 articles with an overall CPP of 10.29. Research articles comprised 78.6% of publications, while reviews – though fewer in number – had the highest CPP (23.38). The most frequent topics were arthroplasty (25.83%) and trauma/fractures (24.17%), with the hip and knee as the most studied anatomical regions. Only 5.17% of the articles reported external funding. Fifteen highly cited papers (≥50 citations) were mostly reviews and internationally co-authored. Conclusions: SICOT-J has demonstrated consistent publication growth and international participation, though with notable concentration in a few high-income countries. The high citation impact of reviews and collaborative works highlights the importance of strategic content development. Enhancing funding transparency, supporting underrepresented regions, and promoting emerging topics strengthen the journal’s global impact.
AIMS:Aortic regurgitation (AR) is a prevalent valvular disease. Cardiovascular magnetic resonance (CMR) imaging is emerging as an accurate and precise method for assessing AR. However, its role in guiding interventions and risk stratification for outcomes remains to be fully defined. OBJECTIVE:This systematic review and meta-analysis evaluate the predictive utility of CMR-derived AR fraction (ARF) in determining intervention timing and clinical outcomes. METHODS AND RESULTS:A systematic search identified observational studies assessing CMR-derived ARF in AR prognostication. Hazard ratios (HRs) for intervention timing, mortality, and heart failure were pooled using a random-effects model. Study heterogeneity (I² statistic) was assessed, and publication bias was evaluated using a funnel plot. A total of 1235 studies were screened, with 12 meeting the inclusion criteria. Eight studies (n = 1996 patients) were included in the meta-analysis. ARF severity thresholds ranged from 30 to 43% (mean 33.7%). Follow-up ranged from 2 to 5.1 years. The pooled HR for clinic outcomes with an ARF > 33% was 4.12 (95% CI: 2.31-7.34, P value < 0.01). The highest reported HR was 24.59, while the lowest was 1.04. Studies demonstrated that a higher ARF correlates with an increased risk of adverse outcomes, supporting CMR as a key tool for risk stratification and intervention timing. CONCLUSION:CMR-derived ARF is strongly predictive of clinical outcomes. ARF > 33% is associated with significantly increased risk, warranting its integration into clinical decision-making frameworks.
