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Metabolic inflammation, or metaflammation, has emerged as a unifying mechanism linking cardiovascular and endocrine disorders. This narrative review aimed to synthesize mechanistic, clinical, and therapeutic evidence on how inflammation bridges these domains and to explore prospects for a unified therapeutic framework. We systematically searched PubMed, Scopus, and Web of Science for English-language articles published between 2010 and 2024, yielding 256 relevant articles, of which 115 were included after detailed screening. Studies addressing adipose tissue inflammation, gut microbiota dysbiosis, innate immune activation, mitochondrial dysfunction, clinical biomarkers, and anti-inflammatory therapies were analyzed. Evidence demonstrates that visceral adipose tissue (VAT) inflammation, inflammasome activation, and mitochondrial oxidative stress form shared pathogenic nodes across cardiovascular and endocrine diseases. Clinical correlates, including biomarkers such as IL-6, C-reactive protein (CRP), glycoprotein acetylation (GlycA), and exosomes, provide diagnostic and prognostic insights, while therapeutic convergence has been highlighted by sodium-glucose cotransporter 2 (SGLT2) inhibitors, glucagon-like peptide-1 (GLP-1) receptor agonists, and IL-1β-targeted interventions. Lifestyle modifications such as Mediterranean diets, microbiota-directed therapies, and intermittent fasting further reinforce dual-organ protection. Despite significant advances, limitations remain in translating multi-omics discoveries, biomarker integration, and systems pharmacology into routine practice. Current evidence underscores the need for prospective trials incorporating inflammatory phenotyping, composite cardio-endocrine outcomes, and patient-centered endpoints. Research gaps include the lack of standardized biomarkers, insufficient inclusion of diverse populations, and limited mechanistic insights from physiologically relevant models such as organ-on-chip (OoC) systems and induced pluripotent stem cell (iPSC)-derived organoids. Future studies must prioritize precision-medicine approaches and integrated care models to reduce the global burden of cardio-endocrine disease.
To develop and retrospectively validate an artificial intelligence-based decision support system (AI-DSS) for optimising prostate biopsy decisions and improving benefit-to-harm ratios. This retrospective, multicentre, multiscanner study used data from 1022 patients. An AI-DSS integrating PI-RADS scores, automated prostate-specific antigen density (PSAd), and deep-learning imaging risk scores was developed on 770 cases and validated on an independent cohort of 252 men from six UK centres. The AI-DSS performance was benchmarked against the real-world clinical decisions (reference standard) using grade selectivity, biopsy efficiency, and selective biopsy avoidance as outcome measures. Biopsy-proven detection of grade group (GG) ≥ 2 disease was the reference standard. In the validation cohort of 252 patients (mean age, 67.3 years), 137 underwent biopsy and 79 (31
BACKGROUND:Early diagnosis is crucial in improving oral cancer outcomes. Patient education materials support timely recognition and management. However, these resources are often written above recommended reading levels, beyond patients' health literacy and limiting accessibility. OBJECTIVES:To assess the readability of available patient information on oral cancer by the NHS, to evaluate three large language models (LLMs; ChatGPT, Claude and Gemini) in simplifying texts while preserving their content, and to propose an improved leaflet based on UK materials, expert review and LLM adjustment to match average UK reading levels. METHODS:Materials were collected from NHS-affiliated websites. Original and LLM-simplified texts were assessed using validated readability tools (FRES, FKGL, GFI, CLI and SMOG). Content fidelity was assessed using character 3-5-g cosine, sentence-content retention and latent semantic analysis (LSA). An expert review was applied to the proposed leaflet. RESULTS:LLM-revisions significantly improved readability across all five indices (p < 0.0001). Mean FRES of original texts was 66.4 ± 7.7, while Claude (81.6 ± 6.2) was the only model to surpass the 80 benchmark. Semantic similarity to source text remained high (LSA means 0.97 ± 0.04, 0.94 ± 0.09 and 0.96 ± 0.08; character 3-5-g cosine 0.85 ± 0.05, 0.80 ± 0.08 and 0.82 ± 0.08 for respective models). Baseline readability of the proposed leaflet was comparable to NHS materials (FRES 65.7); Claude increased this to 81.2. CONCLUSIONS:LLM-based simplification enhanced readability while preserving content fidelity. This approach can help enhance accessibility, particularly for populations disproportionately affected by oral cancer. With human oversight, it could be adopted at the policy level to standardise patient education and reduce health literacy disparities.
Introduction Three-dimensional (3D) computed tomography planning improves preoperative quantification of glenoid morphology when planning total shoulder arthroplasty, but measurement reliability across commonly used planning platforms remains uncertain. Methods A retrospective within-subject comparison of 30 shoulders was planned on four systems: Stryker Blueprint (BP), Zimmer Signature (ZS), Exactech Equinoxe (EE), and SurgiCase Materialise (MS). Measurements of retroversion and inclination were analysed to evaluate measurement variability and correlations between systems. Results Retroversion medians (IQR) were BP -6.5 (10.75), ZS -6.0 (7.0), EE -5.5 (7.0), and MS -3.5 (19.5); overall p=0.37. MS showed greater dispersion and weak correlations with other systems (ρ≈0.03-0.07). Inclination means (SD) were BP 5.93 (8.13), ZS 1.28 (7.27), EE 3.53 (7.57), MS 6.00 (5.07); overall p<0.001. All paired contrasts were significant except for BP vs. MS (-0.07, 95% CI -2.14 to 2.01; p=0.948). Inter-system inclination correlations were strong among BP, EE, and ZS (r≈0.80-0.90) and moderate to strong for MS vs. others (r≈0.57-0.75). Conclusion Platforms were not fully interchangeable. Retroversion showed no group-level bias but reduced precision, particularly for MS, while inclination was highly precise yet displayed platform-specific level differences (notably lower with ZS). Based on this, threshold-adjacent decisions (augment selection, baseplate tilt) may vary by platform. Verification of retroversion outliers and confirmation of inclination near boundaries are recommended.
Aims To determine the distribution of unhelpful pain beliefs in patients after ankle fracture surgery and investigate their impact, along with other demographic characteristics, on postoperative recovery. Methods This was an observational cohort study embedded within the Weightbearing in Ankle Fractures (WAX) trial. Adults (≥ 18 years) who underwent operative fixation of unstable ankle fractures were recruited from 23 UK hospitals two weeks post-surgery. Pain beliefs were measured at baseline using the Pain Self-Efficacy Questionnaire (PSEQ-2) and Tampa Scale of Kinesiophobia (TSK-11). Outcomes were the Olerud-Molander Ankle Score (OMAS) and EuroQol five-dimension questionnaire (EQ-5D) index at four months. Associations between pain beliefs and outcomes were examined using multivariable linear regression models adjusted for age, sex, BMI, comorbidity, occupation, and weightbearing allocation. Results Of 795 eligible patients, 561 were recruited between February 2020 and October 2021 (mean age 48 years, 64% female). At four months, higher BMI, manual labour occupation, and greater kinesiophobia (TSK-11) were associated with poorer OMAS and EQ-5D outcomes, whereas male sex and higher pain self-efficacy (PSEQ-2) predicted better outcomes. Pain beliefs accounted for roughly twice the variability in outcomes compared with other factors. The adjusted R² for the OMAS and EQ-5D models was 0.15, indicating that other unexplored factors contribute to recovery. Conclusion Unhelpful pain beliefs measured two weeks after ankle fracture surgery were consistently associated with poorer function and quality of life up to 12 months. Pain self-efficacy and fear of movement emerged as stronger predictors than most demographic or clinical factors, highlighting their value as early screening targets. These findings support the integration of biopsychosocial interventions to improve recovery following ankle fracture surgery. Cite this article: Bone Joint J 2026;108-B(3):431–438.
