Journal of the American Heart Association最新文献

Background: A recent randomized prospective controlled trial demonstrated that atorvastatin for up to 2 years was safe but did not significantly alter rebleeding in cerebral cavernous malformations. However, any consequences of discontinuing atorvastatin remain unknown. We hypothesized that symptomatic hemorrhage (SH) recurs more frequently in cerebral cavernous malformations after discontinuation of atorvastatin than placebo.

Methods: We conducted a 12-month posttreatment follow-up of patients enrolled in the Atorvastatin Therapy in Cavernous Angiomas with Symptomatic Hemorrhage Exploratory Proof of Concept (AT CASH EPOC) trial (41 randomized to atorvastatin, 39 to placebo) to identify potential recurrent SH after trial drug discontinuation. Every SH was adjudicated by review of imaging and corresponding symptoms. Patients were excluded from follow-up for <90% compliance with study drug, for its discontinuation <3 months after trial enrollment, for statin reinitiation <3 months after discontinuation, or for lack of follow-up. Cases were censored during follow-up upon cerebral cavernous malformation resection/radiation or later statin reinitiation.

Results: Follow-up included 33 patients who had been randomized to placebo and 32 who had taken atorvastatin. Four SH events occurred at 3, 49, 84, and 225 days after atorvastatin discontinuation, and 1 SH at 395 days after discontinuing placebo. There was significantly lower symptomatic hemorrhage-free survival in the atorvastatin-discontinuation group (log-rank χ²=4.136, P=0.042). The hazard ratio was 0.162 (95% CI, 0.027-0.977) for placebo versus atorvastatin discontinuation.

Conclusions: Discontinuation of atorvastatin was associated with a higher risk of recurrent SH compared with placebo discontinuation. Additional studies are warranted to confirm this hypothesis-generating observation, examine potential mechanisms, and how best to mitigate this risk.

Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02603328.

Background: Transcatheter edge-to-edge mitral valve repair is a key therapeutic option for patients with severe symptomatic mitral regurgitation at high surgical risk. This prospective study aimed to develop a novel end-to-end deep learning model for preoperative artificial intelligence assessment in transcatheter edge-to-edge mitral valve repair (TEERAI-pre) candidates using multiview, multimodal echocardiography.

Methods: TEERAI-pre, a video vision transformer-based classification model, predicts morphological suitability for transcatheter edge-to-edge mitral valve repair from multiview, multimodal echocardiography. A transformer-based feature-level fusion module was designed in TEERAI-pre to integrate multiview, multimodal features for final prediction. An internal data set of 633 patients (7997 transthoracic echocardiographic videos; 766 pulsed-wave Doppler images) was split for 5-fold cross-validation. An external data set of 150 patients (1735 transthoracic echocardiographic videos; 169 pulsed-wave Doppler images) across 2 hospitals evaluated generalizability. Reference standards were provided by 2 experienced valvular cardiologists per international guidelines.

Results: On the internal data set, TEERAI-pre achieved 75.0% accuracy (95% CI, 71.7%-78.4%) for classifying red (unsuitable), yellow (challenging), and green (ideal) zones, with 77.1% precision, 75.5% recall, and 76.2% F1 score. External validation yielded 73.3% accuracy, 74.0% precision, and 74.0% recall. Multiview multimodal integration improved performance. Binary classification (red versus green) showed TEERAI-pre matched senior experts and outperformed intermediate/junior echocardiologists. Feature-level fusion outperformed output-level fusion and single-view model. Backbone selection and calibration analysis confirmed robust performance.

Conclusions: TEERAI-pre demonstrates strong performance in transcatheter edge-to-edge mitral valve repair preoperative assessment using transthoracic echocardiographic videos and images, supporting more accurate patient selection and enhancing clinical workflow efficiency.

Registration: URL: clinicaltrials.gov; Unique Identifier: NCT05508438.

Background: The synergistic effects of multiple environmental factors on stroke remain unknown. The aim of this study was to explore the relationship between multiple living environment factors and stroke in middle-aged and older Chinese adults.

Methods: This study used data of the CHARLS (China Health and Retirement Longitudinal Study). Living environmental factors included ambient fine particulate matter, indoor fuel use, tap water use, room temperature, and residence type. Stroke was ascertained by self-reported physician-diagnosed stroke. Cox proportional hazard regression models were applied to explore the association between living environmental risk factors and stroke events in a cohort analysis. Multiple sensitivity analyses were used to test the robustness of the present finding.

Results: A total of 6483 participants from CHARLS (mean age: 58.17 years; female: 54.17%) were included in the 7-year follow-up. Individuals in the middle-risk (adjusted hazard ratio [HR], 0.73 [95% CI, 0.58-0.90]) and low-risk groups (adjusted HR, 0.56 [95% CI, 0.39-0.80]) demonstrated a 27% and 44% reduction in stroke risk, respectively, compared with the high-risk reference group, when evaluating the synergistic effects of residential environmental exposures. In the fully adjusted continuous model, each 1-unit increment in living environmental quality scores was associated with a 15% lower risk of stroke incidence (adjusted HR, 0.85 [95% CI, 0.78-0.91]). The results of the sensitivity analysis confirmed that our findings are robust.

Conclusions: Living environmental quality is significantly associated with stroke. Poor living quality may increase the risk of stroke. Future studies should focus more on the synergistic effects of exposure to living environmental factors.

Background: Atrial fibrillation (AF) is common in hypertrophic cardiomyopathy (HCM) and increases stroke risk, primarily due to thromboembolism from the left atrial appendage (LAA). Oral anticoagulation (OAC) is recommended, but data on LAA thrombus (LAAT) in HCM and AF are limited. The current study aimed to assess LAAT prevalence in patients with HCM and AF.

Methods: We retrospectively analyzed 170 patients with HCM and AF (mean age, 67.7±12.4 years; 57.1% men) who underwent at least one transesophageal echocardiogram (TEE) during a median follow-up of 41.5 months (interquartile range, 15-77 months).

Results: At the time of TEE, 147 (86.5%) patients were undergoing OAC, with 52 (30.6%) taking vitamin K antagonists and 95 (55.9%) taking non-vitamin K antagonist oral anticoagulants. LAAT was found in 36 patients (21.2%), with prevalence rates of 23.1% (n=12) in vitamin K antagonist users, 16.8% (n=16) in non-vitamin K antagonist oral anticoagulant users, and 34.8% (n=8) in those without OAC. Non-vitamin K antagonist oral anticoagulant use was associated with a significant LAAT risk reduction compared with no OAC (odds ratio, 0.20 [95% CI, 0.05-0.73]; P=0.02). Decreased LAA flow velocity (P<0.001) was independently linked to LAAT.

Conclusions: LAAT is common in patients with HCM and AF, even among those receiving OAC. Reduced LAA flow velocity may increase thrombus risk. TEE should be considered before rhythm-control strategies, even in patients with HCM receiving anticoagulation, to minimize thromboembolic complications.

Background: Transcatheter aortic valve replacement using self-expandable valves requires permanent pacemaker implantation (PPI) more often compared with balloon-expandable systems. The Navitor prosthesis is a novel, tubular-shaped self-expandable valve with increasing use.

Methods: Thirty-day PPI rates were compared between 148 patients treated with the Navitor system and 165 patients treated with the Evolut system. Patients with preexisting PPI, high-risk ECG (right bundle-branch block), and Navitor 35-mm/Evolut 34-mm prostheses were excluded. Multivariable logistic regression was used to adjust for baseline differences.

Results: Patients treated with Navitor were older (83.0 [IQR, 78-86] versus 81.0 [IQR, 76-84] years; P < 0.01) and had higher Society of Thoracic Surgeons mortality risk (5.6% [IQR, 3.0%-9.9%] versus 4.3% [IQR, 2.5%-7.0%]; P = 0.04). Overall, PPI occurred more frequently with Navitor (17.6%) than with Evolut (6.7%; P < 0.01), and this difference persisted after adjustment (adjusted odds ratio, 3.07 [95% CI, 1.10-8.40]; P = 0.03; adjusted probability, 17.7% [95% CI, 15.1%-20.2%] versus 6.7% [95% CI, 5.5%-7.9%]). In patients with small annuli (<430 mm²), unadjusted PPI rate (9.1% versus 6.4%; P = 0.55) and adjusted probabilities were similar (7.8% [95% CI, 5.0%-10.6%] versus 6.4% [95% CI, 4.8%-8.0%]; interaction P = 0.03). Within the Navitor cohort, PPI was more frequent with 27/29 mm than with 23/25 mm prostheses (22.3% versus 6.7%; P=0.02). Implantation depth was greater in Navitor patients requiring PPI (5.3±1.8 versus 4.3±2.2 mm; P=0.04) and lower PPI rates (2.9% versus 30.8%; P<0.01) were observed with high target implantation depth.

Conclusions: Depending on prosthesis size, transcatheter aortic valve replacement with the Navitor system may have PPI rates comparable to other self-expandable valves. High implantation of the Navitor may be attempted to reduce PPI rates.

Background: Individuals with an evening chronotype often experience circadian misalignment, which may disrupt health behaviors and cardiometabolic functions.

Methods: We conducted a prospective study in 322 777 UK Biobank participants aged 39 to 74 years free of known cardiovascular disease (CVD). Chronotype was self-reported using a single representative question. The Life's Essential 8 (LE8) score was calculated from 8 CVD risk factors and ranged from 0 to 100 with higher scores indicating better cardiovascular health. Incident CVD was defined as first myocardial infarction or stroke. Cox proportional hazards models estimated the association between chronotype and CVD risk, adjusted for sociodemographics, shift work, and family history of CVD. We evaluated the role of LE8 in the chronotype-CVD association by decomposing the total effect into natural direct effect (independent of LE8) and natural indirect effect (mediated by LE8).

Results: Participants with a "definite evening" chronotype were associated with 79% higher prevalence of an overall poor LE8 score (<50 points) compared with "intermediate" type (95% CI, 1.72-1.85). Over a median 13.8 years of follow-up, there were 17 584 incident CVD events (11 091 myocardial infarction; 7214 stroke). The hazard ratio (HR) for total CVD was 1.03 (95% CI, 0.998-1.07) for the "definite morning" and 1.16 (95% CI, 1.10-1.22) for "definite evening" compared with "intermediate" chronotype (P-trend: 0.10). LE8 explained 75% of the association between evening chronotype and CVD (natural indirect effect comparing "definite evening" with "intermediate": HR, 1.11 [95% CI, 1.09-1.13]).

Conclusions: Our findings suggest that individuals with an evening chronotype may particularly benefit from interventions targeting CVD risk factors.

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; Δχ²=57; P<0.001). Among 1259 patients with indeterminate echocardiographic grading, AI-enabled electrocardiography added prognostic value (ΔHarrell concordance statistic, 0.02; Δχ²=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: The risk of ischemic stroke is highest during the first year following a new diagnosis of cancer, but no tools exist to identify patients at highest risk.

Methods: Using linked clinical and administrative databases, we conducted a population-based retrospective cohort study of adults in Ontario, Canada, with newly diagnosed cancer from 2010 to 2021. Patients were randomly selected for prediction model derivation (60%) or validation (40%). The final model predicting ischemic stroke within 1 year following cancer diagnosis was derived using multivariable Fine-Gray regression with candidate predictors selected via backward elimination. Subdistribution-adjusted hazard ratios and 95% CIs were calculated, where all-cause mortality was treated as a competing event. Performance of the prediction model was assessed in the validation cohort based on the C statistic and calibration plots for discrimination and calibration, respectively.

Results: There were 698 566 eligible patients, with 418 911 in the derivation cohort and 279 576 in the validation cohort. The overall rate of stroke per 1000 person-years was 6.7 (95% CI, 6.4-6.9). The final model included 22 predictors, including age, sex, demographic factors, cancer characteristics, and treatment characteristics. Discrimination was good, with a C statistic of 0.73. The model was well calibrated, with points following the desired 45-degree line.

Conclusions: We derived and validated the PRIME (Predicting Risk of Ischemic Stroke in Malignancy Estimation) tool with good discrimination for ischemic stroke in patients with a new cancer diagnosis. The model was built into an online calculator (https://study.ohri.ca/PRIME/) and has the potential to stratify patients with cancer based on their risk of stroke within a year following their diagnosis.

Background: Inflammasome hyperactivation drives neuroinflammation following cerebral ischemia, yet pharmacological strategies inducing their selective clearance remain largely unexplored. Selective autophagy holds particular promise as a therapeutic strategy by eliminating detrimental substrates while avoiding the side effects of excessive autophagy. However, few compounds are currently available to achieve this selective regulation.

Methods: Transient middle cerebral artery occlusion was used to screen the active compounds from Fritillaria, combined with TTC staining and neurological scores. Postischemic apoptosis, inflammation, and autophagy were evaluated via immunofluorescence and immunoblotting. RNA sequencing of the ischemic penumbra revealed transcriptomic changes. Cell-specific effects were confirmed using cell coculture and glial-deficient transgenic mice. Compound-inflammasome interactions were studied by biolayer interferometry and molecular dynamics.

Results: Peiminine demonstrates robust neuroprotection after cerebral ischemia. RNA sequencing and immunoblotting analyses revealed that peiminine markedly suppresses postischemic inflammation. Correspondingly, peiminine exerts its neuroprotective effect primarily through actions on microglia but not astrocytes, indicated by neuron-glia cocultures and transgenic mice models with targeted cell-type depletion. Biolayer interferometry and molecular dynamics simulations indicated that peiminine selectively binds to AIM2, showing no interaction with NLRP1 (NLR family pyrin domain containing 1) and approximately 100-fold higher affinity compared with NLRP3. Notably, peiminine specifically activates the selective autophagic clearance of AIM2 inflammasomes within microglia without increasing overall autophagic flux or affecting other inflammasomes. Selective blockage of autophagy in microglia abolished the neuroprotective effect of peiminine.

Conclusions: Peiminine exhibited robust neuroprotection against cerebral ischemia by selectively promoting the autophagic clearance of AIM2 inflammasomes to mitigate neuroinflammation.

Background: Limited data are available comparing clinical outcomes between patients with small and large annuli following transcatheter aortic valve replacement using balloon-expandable valves. This study sought to investigate 5-year clinical outcomes in patients with severe aortic stenosis with a small annulus compared with those with a large annulus following transcatheter aortic valve replacement with newer-generation balloon-expandable valves.

Methods: A total of 3182 patients with aortic stenosis treated with balloon-expandable valves were divided into small-annulus (≤430 mm²) and large-annulus (>430 mm²) groups. A 1:1 propensity-matched analysis was performed to adjust baseline differences. The primary end point was all-cause death at 5-year follow-up. Secondary end points included heart failure hospitalization, bioprosthetic valve failure, and aortic valve reintervention.

Results: Among 533 matched pairs, compared with the large-annulus group, the small-annulus group had higher rates of aortic valve mean gradients ≥20 mm Hg (14.1% versus 2.9%; P<0.001) and severe prosthesis-patient mismatch (9.8% versus 5.2%; P=0.019). At 5 years, there were no significant differences in all-cause death (hazard ratio, 0.75 [95% CI, 0.52-1.09]; P=0.13). The incidence of heart failure rehospitalization, bioprosthetic valve failure, and aortic valve reintervention were similar between groups. Both groups achieved similar sustained improvements in New York Heart Association functional class and Kansas City Cardiomyopathy Questionnaire-Overall Summary scores.

Conclusions: Despite higher transvalvular gradients and a greater rate of severe prosthesis-patient mismatch, 5-year clinical outcomes in patients with a small annulus were comparable to those with a large annulus following transcatheter aortic valve replacement using newer-generation balloon-expandable valves.