Citations

Background: Rupture at tendon repair sites in animal models impedes the study of healing. To address this, we investigated “safe incisions” – strategic partial transections to prevent rupture under excessive force. We hypothesized these would act as mechanical “fuses,” reducing repair site tension. Objectives: This in vitro biomechanical study optimized safe incision spacing to enhance tendon construct strength and minimize gap formation in a turkey flexor tendon model. Materials and Methods: Forty turkey flexor tendons were divided into five groups ( n = 8): Repaired without incisions, intact with 5 mm incisions, repaired with 5 mm incisions, intact with 10 mm incisions, and repaired with 10 mm incisions. Repairs used a modified Pennington suture. Safe incisions (opposing hemi-transections) with 5 mm or 10 mm longitudinal spacing were created proximally. Tendons were tested to failure at 1 mm/s, recording force-elongation, failure mode, gap formation (>2 mm at 10% strain), stiffness, and repair site elongation. Results: Repaired tendons without incisions (Group 1) showed 100% repair site failure (46.5 ± 10.96 N). With 5 mm safe incisions (Group 3), no repair site failures occurred (incision failure at 18.11 ± 10.96 N). 10 mm incisions (Group 5) offered partial protection (25% repair failure at 37.48 ± 11.35 N). Group 1 had higher gap formation (75% vs. 0% in Group 3, P < 0.01), stiffness, and repair site elongation than Groups 3 and 5. Gap formation force was similar for Group 1 (25.76 ± 9.18 N) and Group 5 (25.04 ± 12.21 N). Conclusions: In this in vitro model, 5 mm spaced safe incisions effectively shifted failure away from the repair and limited gap formation by reducing stiffness. 10 mm incisions provided partial protection. Strategically placed safe incisions show potential to protect tendon repairs from immediate rupture by enabling controlled lengthening at a weaker site. However, tendinopathy risk and clinical relevance require in vivo studies.

Brugada Syndrome (BrS) is a rare but clinically significant inherited arrhythmia disorder characterized by a type 1 ECG pattern and an increased risk of sudden cardiac death (SCD). Since its first description in 1992, BrS has been the subject of intensive investigation, yet risk stratification remains one of its greatest challenges. While survivors of cardiac arrest and patients with documented ventricular fibrillation (VF) are clear candidates for implantable cardioverter-defibrillators (ICDs), predicting risk in asymptomatic or intermediate-risk individuals is less straightforward. Over the past two decades, multiple risk scores have been developed—including the Sieira, Shanghai, BRUGADA-RISK, and PAT—each integrating combinations of clinical, ECG, electrophysiological study (EPS), and genetic data. Performance metrics vary, with C-statistics ranging from 0.70 to 0.82 in derivation cohorts, but external validation has often been limited. Importantly, current ESC and AHA/ACC guidelines only endorse syncope and EPS inducibility as validated predictors, reflecting the cautious stance of expert panels in the face of heterogeneous data. Nonetheless, the emergence of structured risk models has improved our ability to stratify intermediate-risk patients and stimulated further innovation. Looking ahead, opportunities lie in integrating artificial intelligence applied to raw ECG waveforms, wearable technology for dynamic monitoring, advanced cardiac imaging biomarkers, and polygenic risk scores. Multinational collaboration and federated learning will be essential to overcome statistical fragility and ensure global applicability. Ultimately, BrS risk scores should be considered decision-support tools that enrich but do not replace clinical judgment. Shared decision-making remains central, particularly in asymptomatic patients where ICD implantation is not a clear-cut choice.

Introduction Mitral regurgitation (MR) is a common valvular disease associated with complications such as pulmonary hypertension, atrial fibrillation, and heart failure. However, its full impact on the cardiovascular system, especially on right heart function, is not yet fully understood. Understanding this relationship is important because the right ventricle (RV) is critical for maintaining cardiovascular function. Dysfunction of the RV, which may be contributed by conditions like MR, is strongly associated with poor clinical outcomes. Despite its importance, comprehensively studying MR's effect on the RV has been challenging due to the complex, interdependent nature of cardiovascular dynamics, limited patient data, and the difficulty in synthesizing disparate information to clarify the left heart-right heart connection. Methods The primary goal of this study is to investigate the effects of MR on cardiovascular hemodynamics and RV function by integrating 3D models of the left heart with a closed-loop 0D models of the entire cardiovascular system. We further conduct detailed analyses using patient-specific models to explore how various system modifications impact the RV, providing insights into the nuanced effects of MR on the right heart. Results and Discussion This analysis provides several clinically relevant insights. First, progressive MR markedly increases RV afterload and predisposes the RV to dysfunction, even when intrinsic RV contractility is preserved or enhanced. Second, MR-specific severity indices and left-heart metrics alone fail to capture the true burden on the right heart; RV impairment can progress despite stable or only modestly changing MR descriptors. Finally, these findings highlight the need to incorporate direct assessment of RV structure and function into the evaluation of MR, as RV vulnerability plays a critical role in determining patient risk and guiding management decisions.

Cardiac rehabilitation is strongly recommended in secondary cardiovascular prevention. In patients after coronary artery bypass grafting, this intervention is suggested to reduce mortality, morbidity, and disability. In addition, rehabilitation programs improve quality of life and cardiorespiratory fitness. Modern cardiac rehabilitation programs include structured exercise training, education, nutritional counseling, psychosocial support, and management of cardiovascular risk factors, each tailored to the specific needs of post-coronary artery bypass grafting patients who often face a high burden of comorbidities and surgical recovery challenges. For these reasons, cardiac rehabilitation should be regarded as standard of care. Evidence supports early cardiac rehabilitation initiation and individualized multidisciplinary plans, which have shown to improve exercise capacity, health-related quality of life, and medication adherence. Long-term follow-up is essential, as studies have demonstrated a clear association between sustained cardiac rehabilitation engagement and decreased rates of rehospitalization and all-cause mortality. Therefore, this comprehensive review presents recent advances and updates on the management of patients after coronary artery bypass grafting during cardiac rehabilitation, with a focus on the core components and long-term follow-up.

Background Artificial intelligence (AI)–enabled electrocardiography has emerged as a tool for detecting cardiac dysfunction. The prognostic relevance of AI‐enabled electrocardiography–derived diastolic dysfunction (DD) in patients undergoing transcatheter aortic valve replacement had not been assessed. Methods We analyzed 3197 patients undergoing transcatheter aortic valve replacement for severe aortic stenosis between 2010 and 2023 with baseline 12‐lead ECGs processed by a validated AI model to classify diastolic function (grades 0–3). Multivariable Cox models and nested model comparisons assessed associations with all‐cause mortality, including a prespecified analysis in patients with indeterminate echocardiographic grading. Trajectories were defined by change in AI‐enabled electrocardiography DD grade (<2 versus ≥2) from baseline to 30‐day or 1‐year follow‐up. Results At baseline, 21% had grade 3, 57% had grade 2, 8% had grade 1, and 14% had grade 0 AI‐enabled electrocardiography DD. Higher grades were associated with adverse cardiac remodeling and comorbidities. Over a median follow‐up of 3.4 years, grade 3 AI‐enabled electrocardiography DD independently predicted mortality (hazard ratio [HR], 1.80 [95% CI, 1.47–2.20]; P <0.001). AI‐enabled electrocardiography DD improved prognostic discrimination beyond clinical and echocardiographic measures (ΔHarrell concordance statistic, 0.016; Δ χ 2 =57; P <0.001). Among 1259 patients with indeterminate echocardiographic grading, AI‐enabled electrocardiography added prognostic value (ΔHarrell concordance statistic, 0.02; Δ χ 2 =13; P =0.006). Worsening or persistently high‐risk trajectories were associated with increased mortality (HRs, 1.45–1.80; all P <0.05). Conclusions AI‐enabled electrocardiography–derived DD independently predicts mortality after transcatheter aortic valve replacement, adds value beyond echocardiographic grading, and enables dynamic risk stratification through longitudinal tracking.

Background Fenestrated and branched endovascular aneurysm repair can be complicated by branch vessel occlusion in the absence of structural stenosis. We hypothesized that computational flow simulation could identify adverse hemodynamic features associated with postfenestrated and branched endovascular aneurysm repair branch occlusion. Methods Patients undergoing 4‐vessel fenestrated and branched endovascular aneurysm repair for Extent II to IV thoracoabdominal aortic aneurysms were retrospectively reviewed. Branches that occluded without identifiable kinking or stenosis on computed tomography were included, along with an equal cohort of anatomy‐matched patent controls. Patient‐specific pulsatile rigid‐wall simulations were performed using SimVascular with individualized geometries and boundary conditions. Abnormal time‐averaged wall shear stress (TAWSS) was defined as <10 or >70 dynes/cm 2 . Results Nine patients (36 target vessels) experienced 10 branch occlusions. Postoperative pressure and flow did not differ significantly between occluded and patent renal or mesenteric branches. However, occluded renal and mesenteric branches demonstrated significantly larger postoperative areas of abnormal TAWSS compared with controls (renal: 14.5% versus 5.9%, P =0.003; mesenteric: 17.7% versus 9.9%, P =0.035). Logistic generalized estimating equation modeling showed abnormal TAWSS to be a significant predictor of renal branch occlusion ( P =0.0085). Model estimates suggested occlusion probabilities of 1.1%, 31%, and 94% at 0%, 10%, and 20% abnormal TAWSS surface area, respectively. A cluster‐bootstrapped receiver operating characteristic curve (area under the curve, 0.876) identified a >10.2% threshold that correctly classified 92% of renal occlusions. Abnormal TAWSS frequently localized to distal stent–artery interfaces. Conclusions Elevated abnormal TAWSS within stented renal branches is associated with subsequent branch occlusion after fenestrated and branched endovascular aneurysm repair. Computational flow simulation‐derived TAWSS thresholds may help identify high‐risk branches before failure, warranting prospective validation.

Complex bidirectional interactions between the nervous and cardiovascular systems are integrated through the heart–brain axis, a physiological pathway that governs both neural regulation of cardiovascular function and cardiovascular influences on brain health. Emerging evidence indicates that even in the absence of overt disease, subclinical changes in the heart, aortic arch, and extracranial arteries contribute to brain injury and cognitive vulnerability. This review synthesizes current knowledge on how subclinical heart–brain axis dysfunction affects brain structure and function, highlighting the roles of central and autonomic neural pathways as well as hormonal signaling in driving neurological decline. Key biomarkers linked to silent brain injury, cognitive decline, and dementia are discussed, emphasizing their potential for early risk stratification and as targets for preventive interventions. We also outline mechanistic pathways connecting subclinical heart–brain axis dysfunction to adverse brain outcomes, identify major gaps in current evidence, and propose priorities for future research and clinical trials aimed at early detection and risk reduction to preserve brain health.

INTRODUCTION Recent work has identified unique cognitive profiles for early‐onset Alzheimer's disease (EOAD) relative to late‐onset Alzheimer's disease (LOAD), however, examination has been limited in determining whether the association between age and cognitive severity at presentation also differs across conditions. METHODS A series of linear spline regression models was conducted across baseline cognitive data from 325 EOAD and 314 LOAD participants, after accounting for education, sex, and apolipoprotein ε4 status. RESULTS Significant differences existed in the relationship between baseline age and cognitive performance between EOAD and LOAD samples for Processing Speed/Attention, Executive Functioning, and Episodic Immediate Memory. Younger participants from both EOAD and LOAD groups performed disproportionately worse on non‐amnestic cognitive domains, with this occurring to a greater extent in EOAD than LOAD. DISCUSSION In the age of disease‐modifying treatments, results highlight the importance of assessing for cognitive declines in individuals starting much earlier than age 65. Highlights Early‐onset Alzheimer's disease (EOAD) and late‐onset Alzheimer's disease (LOAD) participants each displayed cognitive impairments relative to same‐aged peers across most domains. Both groups displayed positive relationships between impairment among non‐amnestic cognitive domains and baseline age. This relationship displayed a significantly greater effect in EOAD than LOAD, with domains of Processing Speed/Attention and Executive Functioning skills being the most pronounced. Of those participants developing AD, age displayed a disproportionate impact on their symptom onset.

BACKGROUND: Myocardial flow reserve (MFR), measured by positron emission tomography (PET) myocardial perfusion imaging, provides valuable information on epicardial coronary disease, diffuse atherosclerosis, and microvascular function. Despite its routine use, the prognostic efficacy of 13 N-ammonia PET MFR remains unconfirmed in larger multicenter cohorts of patients with suspected or known coronary artery disease. METHODS: We considered patients from 5 sites in the REFINE PET (Registry of Flow and Perfusion Imaging for Artificial Intelligence with PET) registry who underwent 13 N-ammonia PET myocardial perfusion imaging for coronary artery disease. Clinical and imaging data were collected at the time of myocardial perfusion imaging. MFR was quantified as the ratio of stress to rest myocardial blood flow, using QPET software (Cedars-Sinai Medical Center, Los Angeles, CA). The primary outcome was all-cause mortality. Survival analyses were performed using Kaplan-Meier and Cox regression models adjusted for clinical and imaging covariates. RESULTS: In total, 6277 patients were included (median age of 65 years, 56% male). Median follow-up time was 3.8 years. There were 1895 patients with MFR ≤2 and 4382 with MFR >2. Patients with MFR ≤2 had significantly higher mortality than those with MFR >2 (n=701 [37.0%] versus n=537 [12.3%], respectively; P <0.001). Annualized all-cause mortality rates by MFR and summed stress score ranged from 1.7 to 15.8. In multivariable analysis, MFR ≤2 was independently associated with increased all-cause mortality in the overall population (hazard ratio, 2.70 [95% CI, 2.41–3.03]; P <0.001), even among patients with no perfusion defects (hazard ratio, 2.36 [95% CI, 1.93–2.89]; P <0.001). Mortality risk decreased across increasing MFR deciles, ranging from hazard ratio, 2.73 (95% CI, 2.39–3.11) to hazard ratio, 0.35 (95% CI, 0.25–0.49). CONCLUSIONS: In this large multicenter cohort, MFR derived from 13 N-ammonia PET myocardial perfusion imaging is a strong, independent predictor of all-cause mortality, even in patients with normal perfusion. An MFR of ≤2 identifies elevated risk, while higher values are associated with improved survival. These findings support the routine integration of MFR to enhance risk stratification in patients with suspected or known coronary artery disease.