Search Results (611)

Introduction: Anatomical gastrointestinal reconstruction following metabolic bariatric surgery (MBS) is a revisional procedure used for refractory complications, including malnutrition, intractable reflux, recurrent marginal ulcer disease, and post-bariatric hyperinsulinemic hypoglycemia (PBHH). Objective: This study aims to describe the indications, perioperative outcomes, and short-term results of laparoscopic anatomical reconstruction in a single-center series, focusing on patients with PBHH. Methods: We retrospectively reviewed 11 consecutive patients who underwent reconstruction following MBS at a single tertiary center. Perioperative outcomes, weight changes, and biochemical responses to standardized dual-modality (oral and intravenous) glucose suppression testing were analyzed. Results: Between 2018 and 2025, 11 patients completed laparoscopic anatomical reconstruction. The anatomy immediately preceding reconstruction was OAGB in nine patients (81.8%) and RYGB in two (18.2%). The indications overlapped; the most common were severe malnutrition (n = 9), marginal ulcer disease (n = 6), and PBHH (n = 4; three biochemically confirmed, one clinically diagnosed). Ten of eleven procedures (90.9%) were completed laparoscopically, with no 30-day Clavien–Dindo grade III–IV complications. Among the four PBHH patients, symptomatic resolution was achieved in all four, with residual asymptomatic biochemical hypoglycemia in one. Weight gain occurred in 10 of the 11 patients (mean 8.1 ± 4.9 kg) at a median follow-up of 7 months (IQR 3–12). Conclusions: In this preliminary series, laparoscopic anatomical reconstruction was feasible, though the small sample precludes conclusions regarding safety. Incretin hormones were not measured; the mechanistic contribution of restored foregut anatomy is inferred from prior literature rather than demonstrated here. Standardized dual-modality glucose suppression testing was central to patient selection and to documenting the biochemical response. Full article

Although new AI systems have been developed based on the integration of information from multiple sources under conditions of uncertainty, classical probabilistic models are unable to provide structured, interpretable, and reliable representations in the presence of contextual and order effects. Specifically, the fundamental principles of Kolmogorov’s assumptions underlying the modeling overlook certain common violations in real-world decision-making processes, such as non-commutativity, contextual dependence among agents, and interaction effects between information sources characterized by experiential heterogeneity. A Positive Operator-Valued Measure (POVM) formalism defined on a Hilbert space of latent states forms the basis of this article’s structured epistemic representation framework to support the reliability and interpretability of the black box in AI. The resulting model generalizes the classical epistemic quadruplet: Probability, Plausibility, Credibility, and Possibility within a single geometric framework in which three essential non-classical effect mechanisms emerge—(i) the non-commutativity of information acquisition, (ii) the contextuality arising from incompatible observational frameworks, and (iii) the interference interactions between information acquisition channels. We propose the concept of a quantum-inspired fusion operator (QI-Happenability), which introduces symmetric and antisymmetric feedback interaction terms based on the estimation of ordered residuals. An analysis of the proposed framework is then performed using real data, validating the model on the Efron et al. diabetes regression dataset (N = 442; ten standardized physiological predictors; continuous disease progression target), available in scikit-learn, which showed a 17.4% reduction in mean absolute error (MAE) compared to traditional models and significant improvements over polynomial machine learning baselines, as well as ensemble machine learning methods, within a rigorous cross-validation protocol. Contextual analysis indicates that 68% of cases violate classical bounds (CHSH inequality, p < 0.001), empirically confirming the non-classical structured representation in multi-source data. The results confirm the proposed approach as a simpler, more interpretable, and more reliable alternative to black-box models: this work demonstrates how the use of structured epistemic representations in reasoning under uncertainty preserves formal interpretability while retaining useful semantic information. By linking quantum cognition and applied AI, this work could help lay the groundwork for a new generation of interpretable and reliable decision-making systems. Full article

Anti-CD38 monoclonal antibodies have substantially improved outcomes in multiple myeloma (MM). Although daratumumab and isatuximab target the same antigen, accumulating evidence indicates that they differ in epitope recognition, biological activity, and immunomodulatory properties, suggesting these agents may not be therapeutically interchangeable. This review summarizes the molecular and immunological mechanisms underlying their distinct antitumor effects and their implications for treatment selection. Isatuximab binds near the catalytic site of CD38, resulting in potent enzymatic inhibition, enhanced antibody internalization, FOXM1 suppression, and reactive oxygen species-mediated cytotoxicity, which may preferentially target MM cells harboring 1q21 amplification. In contrast, daratumumab exerts prominent Fc-dependent immune effects, including trogocytosis-mediated downregulation of CD38 and VLA-4, suppression of cell adhesion-mediated drug resistance, and modulation of the immune microenvironment, potentially enhancing subsequent T-cell-redirecting therapies. We further discuss the relevance of these mechanistic differences to measurable residual disease, extramedullary disease, and sequencing with BCMA- and GPRC5D-directed immunotherapies. Finally, we propose a biology-guided treatment-selection model integrating genomic alterations, tumor biology, and immune remodeling to support precision medicine for patients with MM. Full article

Acute Myeloid Leukemia (AML) is a heterogeneous group of aggressive blood-related cancers that arise from the hematopoietic system, requiring specific treatments due to their genetic diversity and complexity. Artificial intelligence (AI) has emerged as a transformative technology in healthcare, with considerable potential to help manage AML. The application of AI approaches, such as Machine Learning (ML) models and Deep Learning (DL) algorithms, has been shown to aid risk stratification, diagnosis, treatment planning, and surveillance. This review highlights recent developments in AI applications for the personalized management of AML. We focus specifically on three major axes of personalization in AML: (1) the use of predictive models combining different data sources to improve prognostic assessment and guide risk-adaptive treatments; (2) prediction of treatment responses to various therapies based on data analysis; and (3) the use of AI for monitoring and adaptive trials in AML patients. Full article

Surrogate endpoints are increasingly used in chronic lymphocytic leukemia (CLL) to accelerate treatment evaluation, but their validity is context-dependent. This review examines key endpoints—progression-free survival (PFS), time to next treatment (TTNT), measurable residual disease (MRD), and quality of life (QoL)/patient-reported outcomes (PROs). PFS, while standard, is limited by competing risks and poor reflection of toxicity and patient experience. TTNT captures both efficacy and tolerability but is influenced by external factors. MRD is a strong predictor of outcomes in fixed-duration venetoclax-based regimens but less reliable in continuous therapies. QoL and PROs provide essential patient-centered insight often missed by traditional endpoints. We propose a practical framework in which endpoint selection depends on treatment type, patient characteristics, and intended use. MRD is most informative after fixed-duration therapy, TTNT in continuous treatment, and PROs in vulnerable populations. Overall, surrogate endpoints in CLL require setting-specific validation to ensure they reflect meaningful clinical benefit. Full article

Background/Objectives: Chronic total coronary occlusion (CTO) is frequently associated with persistent angina, functional limitation, and impaired health-related quality of life. Although CTO percutaneous coronary intervention (CTO-PCI) has improved technically, its clinical value is best assessed through patient-reported outcomes (PROs) and patient-centered clinical endpoints. This study evaluated the association between CTO-PCI plus optimal medical therapy (OMT) and 12-month patient-reported and clinical outcomes compared with OMT alone. Methods: This single-center, non-randomized retrospective observational cohort analysis included 251 patients with chronic coronary syndrome and angiographically confirmed CTO. Patients were managed with either a CTO-PCI + OMT strategy (n = 153) or OMT alone (n = 98). The analysis used routinely collected clinical, angiographic, echocardiographic, procedural, and follow-up data, complemented by patient-reported Seattle Angina Questionnaire (SAQ) data obtained after written informed consent. The overall SAQ assessment was considered the primary patient-reported framework, and SAQ Angina Frequency was defined as the principal symptom-specific domain for adjusted comparative analysis. Propensity-score overlap weighting was used as a sensitivity analysis to address measured baseline imbalance and treatment-selection bias. Secondary outcomes included Canadian Cardiovascular Society angina class, left ventricular ejection fraction, cumulative 12-month cardiovascular rehospitalization, and survival. Results: The complete-case SAQ population included 217 patients: 136 in the CTO-PCI + OMT group and 81 in the OMT group. Thirty-four patients lacked complete 12-month SAQ data: 24 died before SAQ reassessment, and 10 were lost to SAQ follow-up. SAQ Angina Frequency improved in both groups, from 70.81 ± 17.97 to 92.35 ± 12.37 in the CTO-PCI + OMT group and from 63.09 ± 20.10 to 83.09 ± 15.14 in the OMT group. In the multivariable ANCOVA model, CTO-PCI + OMT was associated with higher 12-month SAQ Angina Frequency compared with OMT alone (β = 7.07 points; 95% CI, 3.36–10.79; p < 0.001). This finding remained consistent in the propensity-score overlap-weighted sensitivity analysis adjusted for baseline SAQ Angina Frequency (β = 6.55 points; 95% CI, 2.39–10.70; p = 0.002). Cardiovascular rehospitalization was observed in 11 of 153 patients (7.2%) in the CTO-PCI + OMT group and in 19 of 98 patients (19.4%) in the OMT group, corresponding to lower odds of cumulative 12-month rehospitalization (OR = 0.32; 95% CI, 0.15–0.71; p = 0.005). The rehospitalization endpoint was analyzed as a cumulative binary outcome rather than as a time-to-event outcome. Overall survival estimates were 92.0% and 87.4%, respectively, with 12 deaths in each group (log-rank p = 0.225). Because only 24 deaths were recorded, the study was underpowered to evaluate mortality differences. Conclusions: In selected patients with chronic coronary syndrome and CTO, CTO-PCI + OMT was associated with greater improvement in disease-specific health status, particularly SAQ Angina Frequency, compared with OMT alone. CTO-PCI + OMT was also associated with lower cumulative 12-month cardiovascular rehospitalization, although this secondary finding should be interpreted cautiously because of the non-randomized retrospective design, modest event numbers, lack of time-to-event rehospitalization data, and potential expectation- and care-related biases. Survival analyses were underpowered and should not be interpreted as evidence of either prognostic benefit or absence of benefit. These findings support consideration of CTO-PCI as a patient-centered therapeutic option in carefully selected symptomatic patients, while acknowledging residual confounding by indication and the open-label study design. Full article

Background: Uterine fibroids are the most common benign tumors of the female reproductive system and frequently affect women’s health-related quality of life (HRQoL). The increasing use of online surveys in clinical research raises concerns regarding the comparability and reliability of data collected through different recruitment methods. This study aimed to compare the clinical and methodological comparability of data obtained from an online survey and a clinic-based survey assessing symptom severity and HRQoL among women diagnosed with uterine fibroids. Methods: A cross-sectional observational study was conducted among 167 women with confirmed uterine fibroids. The clinic-based cohort included 82 patients recruited in a gynecological outpatient clinic, while the online cohort consisted of 85 women participating through an internet-based survey. Both cohorts were assessed using identical inclusion and exclusion criteria, the same questionnaire structure, and the validated Uterine Fibroid Symptom and Health-Related Quality of Life (UFS-QoL) instrument. Symptom severity scores and HRQoL outcomes were compared descriptively and methodologically. Results: The two independently recruited cohorts showed broadly similar distributions of several demographic characteristics and patient-reported outcomes, although important differences between the source populations should be considered when interpreting these findings. Mean symptom severity scores were 48.55 ± 21.61 in the clinic-based cohort and 46.33 ± 21.40 in the online cohort, while mean HRQoL scores were 57.23 ± 22.81 and 62.50 ± 19.32, respectively. Formal comparisons revealed no significant differences in symptom severity (p = 0.506) or overall HRQoL (p = 0.110). Among the six UFS-QoL domains, only the Concern domain differed significantly between cohorts (p = 0.005), whereas all other domains showed broadly similar distributions. Separate multivariable regression models were fitted for each cohort. Although direct comparison of the models was limited by differences in variable coding, both models identified symptom severity as the strongest independent predictor of HRQoL (β = −0.715 and β = −0.752) and showed similar overall model performance (R² = 0.595 and 0.578). Regression diagnostics confirmed normality of residuals, homoscedasticity, absence of influential outliers, and low variance inflation factors in both datasets. Conclusions: Despite differences in recruitment setting and source population, similar patterns of patient-reported HRQoL and symptom severity were observed across the two independently recruited cohorts. Similarities were observed across overall HRQoL scores, symptom severity measures, and multivariable regression models, suggesting that the relationships between symptom burden and quality of life remained consistent across recruitment methods. Although differences were identified in disease-related concerns and reproductive history, these findings did not substantially alter the overall pattern of results. Taken together, the findings demonstrate that similar patterns of patient-reported HRQoL and symptom severity were observed across two independently recruited cohorts of women with uterine fibroids. These findings support the feasibility of collecting disease-specific patient-reported outcomes within uterine fibroid-specific online communities but should not be interpreted as evidence that online and clinic-based recruitment methods generate equivalent study populations. Full article

In the companion article in this issue of Current Oncology, ‘Management of AML in Older Patients: An Updated Canadian Consensus’, the authors have presented the third iteration of Canadian consensus guidelines on AML treatment in the elderly. While many aspects of AML treatment in the elderly have become better defined, some old questions remain and new questions and controversies have arisen. Here, we address three topics on which there is, at this time, no universal consensus. The first is the development and features of new risk-stratification systems specifically aimed at older, less-intensively treated patients. Several different systems now exist in parallel, potentially causing confusion amongst clinicians. The second topic is good-prognosis AML subtypes (IDH1- and NPM1-mutated AML). In the Canadian context, IDH1-mutated AML is of particular interest due to the new availability of ivosidenib in Canada. The third topic is adverse-risk AML subtypes (FLT3- and TP53-mutated AML). FLT3-mutated AML remains problematic, although it is anticipated that new drug approvals and measurable residual disease-based treatment approaches may alleviate this, at least in part. And in particular, TP53-mutated AML remains a major problem. Ongoing clinical trial enrollment is essential. Full article

Background/Objectives: Spectral flow cytometry enables the single-tube integration of all markers required for the assessment of measurable residual disease (MRD) in AML. The routine clinical use of spectral flow cytometry is challenged by the need for adequate single-stained unmixing controls. To pave the way for the clinical implementation of spectral flow cytometry, we opted to develop a multifunctional AML MRD panel, whose unmixing routine solely depends on ubiquitously available peripheral blood leukocytes (PBLs). Methods: We reconfigured our previously developed 19-color single-tube spectral MRD assay to incorporate viability, hemodilution, and leukemic stem cell (LSC) markers. In parallel, primitive markers were reassigned to non-tandem fluorochromes, resulting in a finalized 22-color panel. These fluorochromes were additionally leveraged as CD14 surrogate controls, whereas all other markers retained their dedicated fluorochromes for unmixing based on single-stained PBLs. Results: PBL-based controls enabled accurate spectral unmixing and reproducible assessment of CD16-based hemodilution and cell viability in spike-in experiments. Linear leukemia-associated immunophenotype (LAIP) detection, sensitivity, as well as intra- and inter-assay precision within predefined acceptance criteria were demonstrated in KG-1 dilution experiments using normal bone marrow (nBM). Furthermore, the 22-color assay resolved LAIPs and LSCs in patient samples with strong concordance to the 5-tube reference assay and revealed aberrant marker combinations that could not be assessed using the multi-tube design. Conclusions: This single-tube 22-color spectral flow cytometry assay may support a more clinically applicable and potentially standardizable approach to AML MRD diagnostics through a universal PBL-based unmixing strategy. Full article

Background: Quantitative PCR measurement of BCR::ABL1 is essential for monitoring molecular response and detecting relapse in chronic myeloid leukemia (CML) patients. Given the availability of multiple commercial kits for cDNA synthesis and minimal residual disease assessment, analytical accuracy and reliability are critical. This study evaluated two commercial RT and qPCR kits for BCR::ABL1 quantification and fusion transcript variant identification. Methods: Total RNA was isolated from peripheral blood, bone marrow, and external quality control samples from the UK NEQAS for Leucocyte Immunophenotyping program. cDNA synthesis was performed using two kits: AffinityScript (ASK) and RT Kit (RTK). BCR::ABL1 transcript levels were determined using the ipsogen^® BCR-ABL1 Mbcr IS-MMR Kit (IPS) and the LightMix^® bcr-abl t(9;22) M/m/µ Kit (TMB). Results were compared with UK NEQAS LI reference data. Fusion transcript variants were analyzed using nested PCR and a commercial qPCR assay. Results: Substantial variability was observed between the TMB and IPS assays, with moderate, non-significant correlation and wide limits of agreement. Established discrepancies resulted in different classifications of molecular response, and IPS results showed better concordance with external quality assessment data. ABL1 quantification revealed significantly higher copy numbers with the RTK compared to the ASK (p < 0.0001), enabling more reliable assessment of deep molecular responses. Statistical analyses indicated systematic and proportional bias between the methods. For variant detection, nested PCR demonstrated higher specificity, while the commercial assay showed limited discriminatory capability. Conclusions: Significant methodological differences may affect clinical interpretation, underscoring the importance of validation and standardization in CML molecular monitoring. Full article

Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of aggressive non-Hodgkin lymphoma and is characterized by pronounced molecular heterogeneity that is not always fully captured by standard histopathological assessment. Circulating tumor DNA (ctDNA) is increasingly regarded as a promising liquid-biopsy biomarker that enables non-invasive molecular tumor profiling, assessment of tumor burden, dynamic monitoring of treatment response, and detection of measurable/minimal residual disease (MRD). Modern analytical platforms, ranging from PCR-based assays to next-generation sequencing approaches, including CAPP-Seq and PhasED-Seq, have substantially expanded the possibilities of molecular monitoring in DLBCL. This review summarizes current data on the biological characteristics of ctDNA, contemporary methods for its analysis, concordance between ctDNA and tumor-tissue mutational profiles, and the clinical significance of baseline ctDNA levels, early molecular response, post-treatment MRD status, and molecular surveillance during remission. Special attention is given to ctDNA monitoring in patients receiving novel immunotherapies, including CAR-T cell therapy, bispecific antibodies, and antibody–drug conjugates. Emerging multi-omic approaches integrating genomic, epigenomic, and fragmentomic data are discussed as promising future directions. Key limitations of clinical implementation include insufficient standardization of preanalytical and analytical workflows, the confounding effect of clonal hematopoiesis of indeterminate potential, variability across technological platforms, and the lack of completed prospective randomized interventional studies demonstrating improved outcomes when therapy is modified according to ctDNA status. Overall, ctDNA is currently a highly informative prognostic biomarker in DLBCL; however, its full implementation as a predictive tool for treatment selection requires further harmonization, prospective validation, and confirmation in interventional clinical trials. Full article

Objective: Squamous cell carcinoma antigen (SCC-A) is a widely used biomarker for squamous cell cervical carcinoma and pretreatment elevation is associated with poor prognosis. Normalization during chemoradiation correlates with PET-CT response and survival. This study assessed the prognostic value of SCC-A normalization for biopsy-proven pathological response and survival outcomes. Materials and Methods: This retrospective single-center cohort study included patients with locally advanced or node-positive squamous cell cervical cancer treated with definitive chemoradiation at the Medical University Innsbruck between 2008 and 2023. Eligible patients had baseline SCC-A ≥ 2 ng/mL and at least two additional measurements within 42 days of treatment. SCC-A normalization was evaluated at predefined weekly time points. Associations with biopsy-assessed residual disease, PFS, and OS were assessed. Results: Of 186 screened patients, 83 met the inclusion criteria. Within 42 days, 70% achieved SCC-A normalization, with a median time of 21 days (IQR 19–32). Among predefined time points, normalization by day 28 was associated with reduced odds of residual disease (OR 0.14; 95% CI 0.04–0.44) and improved PFS (HR 0.28; 95% CI 0.12–0.63) and OS (HR 0.37; 95% CI 0.14–0.96), remaining independently significant after multivariate adjustments. Conclusions: SCC-A normalization during chemoradiation is a non-invasive independent biomarker of treatment response. Normalization within 28 days identifies patients at low risk of residual disease, progression, and death, supporting its use for early risk stratification and response monitoring for potential treatment adaptations. Full article

The assessment of consciousness has been shaped largely by research on acquired disorders of consciousness after acute or chronic brain injury, but similar problems of unreliable behavioral expression increasingly arise in neurodegenerative disease. This translational overlap is especially relevant when preserved cognition, awareness, or intentionality cannot be reliably expressed because of severe motor impairment, fluctuating arousal, cognitive decline, aphasia, apraxia, or impaired cooperation. In neurodegenerative disease, degeneration of arousal systems, large-scale brain networks, cognition, and motor pathways may similarly make observable behavior an unreliable measure of awareness. The challenge is not only to determine if a patient responds, but also to ask if residual awareness, intentionality, or covert cognition can still be detected through physiological signals. This review discusses how contemporary modalities reshape this assessment. Electroencephalography has moved from a descriptive measure of background activity to a bedside tool capable of probing event-related responses, network organization, and cortical complexity. Magnetic resonance methods reveal altered connectivity within thalamocortical and default mode network systems, while functional near-infrared spectroscopy adds a portable hemodynamic approach that may be repeated at the bedside and integrated with active paradigms. Brain–computer interfaces provide a translational step by converting neural responses into evidence of command following or, in selected patients, into communication, and artificial intelligence strengthens these approaches by extracting clinically meaningful patterns from complex neural and hemodynamic data. Additionally, autonomic measures, including heart rate variability and baroreflex indices, are considered as auxiliary physiological context for arousal and engagement, and not as direct markers of awareness. Because the most mature evidence for covert awareness and cognitive-motor dissociation comes from acquired disorders of consciousness, this review treats brain injury literature as a methodological foundation instead of as directly interchangeable evidence for neurodegenerative disease. It then examines how these approaches may be adapted to neurodegenerative contexts, especially ALS, severe dementia, Lewy body disease with fluctuating cognition, and conditions in which communication or motor output becomes unreliable. Full article

Cardiac computed tomography (CT) has evolved into a pivotal tool in precision cardiology, enabling comprehensive, non-invasive evaluation of coronary anatomy, plaque composition, vascular function, and inflammation. From calcium scoring to advanced physiological imaging, CT now integrates multiple layers of cardiovascular information within a unified diagnostic framework. Coronary artery calcium (CAC) quantification provides a robust, reproducible measure of atherosclerotic burden and refines risk estimation beyond traditional algorithms, particularly in asymptomatic individuals with an intermediate likelihood. Building upon this anatomical foundation, coronary CT angiography (CCTA) extends evaluation to the anatomical and morphological characterization of coronary artery disease (CAD), identifying both obstructive and non-obstructive plaques with high prognostic accuracy. The addition of CT-derived fractional flow reserve (FFR-CT) and stress perfusion CT (CTP) bridges anatomy and physiology, improving identification of flow-limiting stenoses and guiding revascularization decisions while reducing unnecessary invasive procedures. Beyond luminal assessment, CT-derived biomarkers such as the perivascular fat attenuation index (pFAI) have introduced a new dimension of vascular inflammation imaging, revealing residual risk even in patients without significant stenosis and suggesting novel pathways for individualized therapeutic targeting. Driven by advances in artificial intelligence and photon-counting detector technology, cardiac CT is transitioning from a purely diagnostic modality to an integrative platform for cardiovascular phenotyping. Taken as a whole, this integration of structural, functional, and biological data provides a genuinely holistic view of coronary health. In practical terms, it shifts clinical decision-making from population-based risk models toward precision-guided patient-specific strategies. Full article

Lipoprotein(a) [Lp(a)] has emerged as a major genetically determined cardiovascular risk factor that extends beyond the traditional low-density lipoprotein cholesterol (LDL-C)-centred model of atherosclerotic disease. Despite optimal LDL-C lowering, a substantial proportion of patients continue to experience cardiovascular events, highlighting the clinical relevance of residual cardiovascular risk. This review summarizes current evidence regarding the epidemiology, genetics, pathophysiology and therapeutic implications of Lp(a) in cardiovascular disease. Epidemiological, genetic, and Mendelian randomization studies consistently demonstrate an independent and likely causal association between elevated Lp(a) and atherosclerotic cardiovascular disease, ischemic stroke, calcific aortic valve stenosis, heart failure, and recurrent cardiovascular events, even in patients with well-controlled LDL-C levels. Lp(a) promotes atherosclerosis through proatherogenic, proinflammatory, and prothrombotic mechanisms, largely mediated by oxidized phospholipids and the structural homology of apolipoprotein(a) with plasminogen. Current guidelines increasingly recognize Lp(a) as a risk-enhancing factor capable of refining cardiovascular risk stratification beyond traditional algorithms, thus recommending measuring Lp(a) at least once in a lifetime in all adults. Accurate measurement and standardization of Lp(a) remain essential in clinical practice due to apo(a) isoform size variability; reporting in molar concentrations (nmol/L) is preferred as it better reflects particle number being less affected by isoform size variations and improves the reliability of cardiovascular risk stratification. Collectively, these findings support the integration of Lp(a) into precision-based cardiovascular prevention strategies and suggest a paradigm shift from an exclusively LDL-centric approach toward genetically informed risk assessment and treatment. Full article