Background/Objectives: Atrial fibrillation (AF) is a significant contributor to ischemic stroke; however, existing thromboembolic risk scores exhibit only moderate predictive accuracy. Lipoprotein(a) (Lp(a)), a genetically determined lipoprotein characterized by proatherogenic and prothrombotic properties, may play a role in cardioembolic events in AF. Nonetheless, its clinical relevance in this context remains ambiguous. The goal of this systematic review and meta-analysis was to look at the differences in circulating Lp(a) levels between AF patients who had an ischemic stroke and those who did not, as well as to see if Lp(a) could help figure out who is at risk of thromboembolic events. Methods: A thorough search was performed in PubMed/MEDLINE, Embase, Scopus, Web of Science, and CENTRAL until September 2025, in accordance with PRISMA 2020 and Cochrane Handbook guidelines. Eligible studies encompassed adults with AF and accessible data on Lp(a) concentrations, contrasting individuals with and without ischemic stroke. Results: Five observational studies involving 20,678 atrial fibrillation patients (3104 with ischemic stroke) were incorporated. The pooled analysis revealed markedly elevated Lp(a) concentrations in stroke patients relative to non-stroke controls (MD = 2.42 mg/dL; 95% CI 0.68–4.16; p = 0.007). Conclusions: While Lp(a) testing is not presently endorsed in AF guidelines, our results indicate a possible correlation with ischemic stroke risk. Nonetheless, these findings must be regarded with caution owing to significant heterogeneity, the predominance of Chinese cohorts, and the exceedingly low certainty of evidence as per GRADE assessment. Additional extensive, multi-ethnic, and rigorously designed prospective studies are necessary to ascertain whether Lp(a) constitutes an independent risk factor for ischemic stroke in atrial fibrillation.

Background/Objectives: The most prevalent prolonged cardiac arrhythmia and a significant global health burden is atrial fibrillation (AF). Although its connection to AF is still unknown, lipoprotein(a) (Lp(a)), a genetically determined lipoprotein with pro-inflammatory and pro-atherogenic characteristics, has been linked to cardiovascular disease. The purpose of this study was to measure and assess the relationship between circulating Lp(a) levels and AF. Methods: In compliance with the PRISMA 2020 guidelines, a systematic review and meta-analysis were carried out using a protocol that was preregistered in PROSPERO (CRD420251153244). Comprehensive searches of PubMed/MEDLINE, Embase, Web of Science, Scopus, the Cochrane Library, and Google Scholar up until September 2025 were used to find observational studies comparing circulating Lp(a) levels in adults with and without AF. Results: Circulating Lp(a) concentrations were significantly higher in AF patients than in controls across 10 studies (pooled MD = 2.81; 95%CI: 1.58–4.05; p < 0.0001). In the subgroup analysis by geographical setting, studies conducted in Asia and studies from Europe/USA exhibited a statistically significant effect. Despite the extreme heterogeneity (I² = 99%), sensitivity analyses verified that the overall effect was stable. Conclusions: Our pooled analysis revealed a statistically significant association between Lp(a) and AF; however, the certainty of the evidence was rated as very low according to the GRADE methodology. To elucidate causality, enhance risk stratification, and investigate whether Lp(a)-lowering tactics could alter AF risk, large, prospective, multi-ethnic studies with standardized biomarker assessment are needed.

Dimensional and transdiagnostic models have become central to contemporary efforts to move psychiatric nosology beyond DSM/ICD categories. This shift reflects persistent limitations of categorical syndromes as final biological targets, including within-diagnosis heterogeneity, cross-diagnostic comorbidity, developmental instability, and incomplete alignment with underlying mechanisms. This article examines a central unresolved problem in this transition: when, if ever, a descriptive or predictive psychiatric dimension can be interpreted as a candidate disease axis. We conducted a conceptual synthesis of major dimensional and transdiagnostic frameworks, including Research Domain Criteria (RDoC), Hierarchical Taxonomy of Psychopathology (HiTOP), the general psychopathology factor, cross-disorder genomic models, clinical staging approaches, and data-driven subtyping. The analysis separates three levels of inference that are often conflated in psychiatric research: descriptive structure, predictive utility, and disease-level biological validity. The synthesis identifies a recurrent inferential error in which reproducible factors, clusters, or classifiers are prematurely treated as evidence of disease architecture. Such constructs may describe real covariance patterns or improve prognostic prediction without establishing biological validity. We propose an eight-domain hierarchical framework for promotion to candidate disease-axis status, organized into four core gatekeepers—replication across cohorts, ascertainment, and methods, developmental coherence, incremental prognostic value beyond diagnosis and nonspecific severity, and discriminability from nonspecific severity—and four supporting/disciplining domains: cross-level convergence, mechanistic constraint, clinical leverage, and explicit falsifiability/boundary conditions. On this basis, middle-level transdiagnostic spectra and selected cross-disorder genomic liabilities appear more defensible as candidate disease axes than highly global or weakly specified constructs. Psychiatry was justified in turning toward dimensional models, but dimensionality alone does not confer biological validity. The key task is not to choose between categories and dimensions, but to define the evidential thresholds under which dimensional constructs warrant ontological promotion.