Pregnancy planning in patients with rheumatic diseases (RD) is a multifaceted public health issue that includes complex strategies targeting underlying disease activity and reproductive potential. Patients with autoimmune diseases, including those with systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), Sjögren syndrome, systemic sclerosis (SSc), and spondyloarthritis, present with heightened risks of adverse maternal and fetal outcomes, including miscarriage, fetal growth restriction, preeclampsia, preterm birth, and increased utilization of assisted reproductive technologies. Available evidence suggests that conception during sustained disease remission, alongside tailored drug therapies, enhances maternal-fetal outcomes. Critical determinants of obstetric prognosis include disease-specific activity indices, serologic markers, organ involvement, and prior gonadotoxic exposures which compromise ovarian reserve. Structured preconception counseling that integrates contraception strategies, fertility preservation, ovarian reserve assessment, and multidisciplinary follow-up is essential to mitigate these risks. Current management paradigms advocate the continuation of pregnancy-compatible disease-modifying antirheumatic drugs (DMARDs), while strictly avoiding teratogenic therapies. Despite these advances, substantial unmet needs exist in early risk stratification, patient education, and systematic integration of reproductive health counselling into routine RD management. This review synthesizes contemporary evidence, delineates existing gaps, and provides a strategic framework for optimizing pregnancy planning and reproductive outcomes in women with RDs. The review addresses the key domains, including preconception risk stratification, disease-specific considerations, fertility assessment, ovarian reserve evaluation, and optimization of drug therapies. A multidisciplinary, treat-to-target approach is essential to improve pregnancy outcomes and long-term maternal health in this high-risk population.
Rheumatic diseases (RDs) are chronic immune-mediated disorders associated with disproportionately increased cardiovascular morbidity and mortality. Accelerated atherogenesis in these diseases is driven by persistent systemic inflammation, autoantibody-mediated endothelial injury, oxidative stress, and dysregulated lipid metabolism, resulting in premature vascular remodeling manifested by increased carotid intima–media thickness, arterial stiffness, impaired flow-mediated dilation, and coronary artery calcification. This review synthesizes evidence regarding subclinical atherosclerosis and cardiometabolic risk across common RDs. In rheumatoid arthritis and systemic lupus erythematosus, vascular alterations correlate with inflammatory burden, disease duration, autoantibody profiles, renal involvement, and glucocorticoid exposure. Emerging biomarkers—including apolipoprotein B48, FIB-4 index, asymmetric dimethylarginine, and adhesion molecules—provide incremental prognostic value beyond traditional lipid parameters. Advanced imaging modalities, such as ^18F-sodium fluoride PET/CT and vascular elastography, enhance early detection of arterial calcification and stiffness. Growing evidence in primary Sjögren syndrome, Behçet disease, systemic sclerosis, and ankylosing spondylitis similarly confirms increased subclinical atherosclerosis and endothelial dysfunction. Importantly, tight disease control and targeted immunomodulatory therapies—including methotrexate, biologic agents, antimalarials, and cytokine-directed treatments—are associated with improved vascular and metabolic profiles and attenuation of disease progression. Subclinical atherosclerosis represents a critical interface between autoimmunity and cardiovascular disease in RDs. Early vascular assessment integrated with disease-specific and metabolic risk stratification is essential to implement precision-based cardiovascular prevention in this high-risk population.
Rheumatic diseases encompass diverse immune-mediated disorders that compromise musculoskeletal and systemic functions, often resulting in persistent disability. Hand muscle weakness is an early and clinically meaningful manifestation across rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and systemic sclerosis (SSc). Reduced handgrip strength (HGS) is an integrative measure that reflects systemic inflammation, neuromuscular involvement, and functional deterioration, providing critical insight into disease progression. The current review aims to overview available evidence on HGS testing in rheumatic diseases, with a focus on measurement devices, clinical and prognostic significance, and perspectives for its integration into disease monitoring and patient management. HGS is a sensitive marker of muscular function and frailty. Advances in mechanical and digital dynamometry, wearable devices, and smartphone-integrated systems enable precise and remote assessments. Reduced HGS correlates with higher disease burden and impaired quality of life. Despite its growing applicability, heterogeneity in testing procedures and inter-device variability underscore the need for standardized protocols and device-specific reference values. Advances in wearable sensors, digital dynamometry, and AI-supported telerehabilitation hold promise for integrating HGS into personalized disease monitoring.
Pregnancy raises the risk of maternal and fetal complications in systemic lupus erythematosus (SLE) patients due to physiological and immunological changes, with infections standing out as a significant concern. It is important to conduct a comprehensive examination of the structure and trends in the scientific literature of this field. This bibliometric study analyzed publications on SLE-related infections during pregnancy using the Scopus database. The search was conducted on January 15, 2026, using the keywords “Systemic Lupus Erythematosus”, “Pregnancy”, and “Infection” in the title, abstract, and keyword fields. The analysis included an examination of publication distribution and trends over time using linear regression. Data on countries, authors, institutions, funding sources, journals, document types, and keywords of the articles were collected. A total of 994 publications were included in the analysis. The annual number of publications increased significantly over the years and the publication output peaked in 2024 (n = 73) (R² = 0.664, p < 0.001). In total, 71 countries contributed to the literature, with 28 classified as main active countries (≥ 1
BACKGROUND:The integration of artificial intelligence, specifically large language models, into editorial processes, is gaining interest due to its potential to streamline manuscript assessments, particularly regarding ethical and transparency reporting in public health journals. This study aims to evaluate the capability and limitations of ChatGPT-4.0 in accurately detecting missing ethical and transparency statements in research articles published in high-ranked (Q1) versus low-ranked (Q4) public health journals. METHODS:Articles from top-tier (Q1) and low-tier (Q4) public health journals were analyzed using ChatGPT-4.0 for the presence of essential ethical components, including ethics approval, informed consent, animal ethics, conflicts of interest, funding notes, and open data sharing statements. Performance metrics such as sensitivity, recall, and precision were calculated. RESULTS:ChatGPT exhibited high sensitivity and recall across all evaluated components, accurately identifying all missing ethics statements. However, precision varied significantly between categories, with notably high precision for data availability statements (0.96) and significantly lower precision for funding statements (0.16). A comparative analysis between Q1 and Q4 journals showed a marked increase in missing ethics statements in the Q4 group, particularly for open data sharing statements (4 vs. 50 cases), ethics approval (2 vs. 5 cases), and informed consent statements (3 vs. 8 cases). CONCLUSION:ChatGPT-4.0 in preliminary screening shows considerable promise, providing high accuracy in identifying missing ethics statements. However, limitations regarding precision highlight the necessity for additional human checks. A balanced integration of artificial intelligence and human judgment is recommended to enhance editorial checks and maintain ethical standards in public health publishing.
