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.
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.
Obesity is a global health crisis affecting developing nations, including India. The management of obesity continues to evolve with newer drugs, metabolic and bariatric surgery and endoscopic interventions, requiring family physicians and specialists to adapt their clinical practice accordingly. There is an urgent need for a standardized algorithm to diagnose, stage, and treat obesity. The Endocrine Society of India (ESI) and the Obesity Surgeons Society of India (OSSI) appointed a steering committee to develop an evidence-based algorithm for managing patients with obesity in India. This was put to vote by 80 specialists (38 from OSSI and 42 from ESI) in a physical meeting. A proposed stage-wise algorithm based on Edmonton Obesity Staging System, Asian definition of obesity, and resources in India, received 100
