Citations

Abstract Aims Cardiac amyloidosis (CA) is common in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). Cardiac amyloidosis has poor outcomes, and its assessment in all TAVR patients is costly and challenging. Electrocardiogram (ECG) artificial intelligence (AI) algorithms that screen for CA may be useful to identify at-risk patients. Methods and results In this retrospective analysis of our institutional National Cardiovascular Disease Registry (NCDR)-TAVR database, patients undergoing TAVR between January 2012 and December 2018 were included. Pre-TAVR CA probability was analysed by an ECG AI predictive model, with >50% risk defined as high probability for CA. Univariable and propensity score covariate adjustment analyses using Cox regression were performed to compare clinical outcomes between patients with high CA probability vs. those with low probability at 1-year follow-up after TAVR. Of 1426 patients who underwent TAVR (mean age 81.0 ± 8.5 years, 57.6% male), 349 (24.4%) had high CA probability on pre-procedure ECG. Only 17 (1.2%) had a clinical diagnosis of CA. After multivariable adjustment, high probability of CA by ECG AI algorithm was significantly associated with increased all-cause mortality [hazard ratio (HR) 1.40, 95% confidence interval (CI) 1.01–1.96, P = 0.046] and higher rates of major adverse cardiovascular events (transient ischaemic attack (TIA)/stroke, myocardial infarction, and heart failure hospitalizations] (HR 1.36, 95% CI 1.01–1.82, P = 0.041), driven primarily by heart failure hospitalizations (HR 1.58, 95% CI 1.13–2.20, P = 0.008) at 1-year follow-up. There were no significant differences in TIA/stroke or myocardial infarction. Conclusion Artificial intelligence applied to pre-TAVR ECGs identifies a subgroup at higher risk of clinical events. These targeted patients may benefit from further diagnostic evaluation for CA.

Objective The aims of this study were to assess whether a relationship between anti–SSA-52 and interstitial lung disease (ILD) can be further defined, and to enhance screening, detection, and potentially guide treatment. Methods A historical cohort study of 201 patients was conducted at a single tertiary care center between January 1, 2016 and December 31, 2020. All included patients were anti–SSA-52 antibody positive. Chart review was performed for laboratory values, symptoms, pulmonary function tests, treatment, and imaging. Chest computed tomographies were reviewed by chest radiologists. Results Among anti–SSA-52 antibody–positive patients, ILD was found in 125 (62.2%) compared with 76 (37.8%) with no ILD (p = 0.001). For those with ILD, 78 (62.4%) were diagnosed with connective tissue disease (CTD)–associated ILD, 28 (22.4%) were diagnosed ILD only, and 19 (15.2%) met the criteria for interstitial pneumonia with autoimmune features. In patients with CTD-ILD, 18 (23.0%) had their ILD diagnosis made over 6 months before a CTD diagnosis, and an additional 43 (55.1%) had their ILD and CTD diagnosed within 6 months of each other (p < 0.001). Common computed tomography patterns were nonspecific interstitial pneumonia/organizing pneumonia overlap in 44 (35.2%), 25 (20.0%) nonspecific interstitial pneumonia, and 15 (12%) usual interstitial pneumonia. Twenty-eight (35.9%) had antisynthetase syndrome, followed by 16 (20.5%) with dermatomyositis, 10 (12.8%) with CTD overlap, and 6 (7.7%) with systemic scleroderma. Conclusions There was a significant association between anti–SSA-52 antibodies and ILD across a wide spectrum of rheumatological diagnoses. A significant portion of patients were diagnosed with ILD either at the same time or before their CTD diagnosis. Further study will be needed to assess effective treatment and response.

Abstract Aims HELIOS-A was a Phase 3, open-label study of vutrisiran, an RNA interference therapeutic, in patients with hereditary transthyretin (ATTRv) amyloidosis with polyneuropathy. This analysis evaluated vutrisiran's impact on exploratory cardiac endpoints in HELIOS-A patients. Methods and results Patients were randomized 3:1 to subcutaneous vutrisiran 25 mg every 3 months or intravenous patisiran 0.3 mg/kg every 3 weeks (reference group) for 18 months. Exploratory cardiac endpoints included change from baseline in N-terminal prohormone of brain-type natriuretic peptide (NT-proBNP) and echocardiographic parameters versus external placebo (APOLLO study). The modified intent-to-treat (mITT) population comprised randomized patients receiving any study drug (n = 122). A cardiac subpopulation with evidence of cardiac amyloid involvement (n = 40) was prespecified. 99mTc scintigraphy exploratory assessments in a planned vutrisiran-treated cohort at select sites were compared with baseline. At Month 18, vutrisiran demonstrated beneficial effects on NT-proBNP versus external placebo in the mITT and cardiac subpopulations (adjusted geometric mean fold change ratio [95% confidence interval] 0.480 [0.383–0.600], p = 9.606 × 10−10 and 0.491 [0.337–0.716], p = 0.0004, respectively). Benefits or trends towards benefit in echocardiographic parameters versus external placebo were observed for both populations. In 99mTc scintigraphy assessments, 32/47 (68.1%) and 31/48 (64.6%) patients exhibited reduced normalized left ventricular total uptake and heart-to-contralateral lung ratio, respectively. Perugini grade was reduced or unchanged versus baseline in 55/57 (96.5%) evaluable patients. No increase in cardiac adverse events was observed with vutrisiran versus external placebo. Conclusions Vutrisiran demonstrated evidence of potential benefit on cardiac manifestations in patients with ATTRv amyloidosis with polyneuropathy, with an acceptable safety profile.

Abstract Patient‐reported quality‐of‐life (QoL) and carer impacts are not reported after leucine‐rich glioma‐inactivated 1‐antibody encephalitis (LGI1‐Ab‐E). From 60 patients, 85% (51 out of 60) showed one abnormal score across QoL assessments and 11 multimodal validated questionnaires. Compared to the premorbid state, QoL significantly deteriorated ( p < 0.001) and, at a median of 41 months, fatigue was its most important predictor ( p = 0.025). In total, 51% (26 out of 51) of carers reported significant burden. An abbreviated five‐item battery explained most variance in QoL. Wide‐ranging impacts post‐LGI1‐Ab‐E include decreased QoL and high caregiver strain. We identify a rapid method to capture QoL in routine clinic or clinical trial settings.

Introduction: Acute ischemic stroke (AIS) patients often require multiple passes during mechanical thrombectomy (MT) to open the vessel. Yet, at times, even numerous passes are unsuccessful. This study aims to investigate the impact of the number of passes on the outcomes of patients who underwent failed MT. Methods: We used Data from the Stroke Thrombectomy and Aneurysm Registry (STAR) from 2013 to August 2023. Patients who underwent MT for ICA, M1, or M2 with unsuccessful recanalization (modified Thrombolysis in Cerebral Infarction ≤ 2a) were included. Primary outcome was 90- day modified Rankin Scale (mRS) 0-2. Secondary outcomes included any intracranial hemorrhage (ICH) and symptomatic ICH (sICH). Outcomes were compared among patients who received ≤ 2, 3, 4, and ≥ 5 MT passes. Results: 736 patients met inclusion criteria. 90-day mRS 0-2 was found to decrease with number of passes (Figure 1). Multivariate logistic regression analysis revealed that 3 passes (OR: 0.48, 95% CI: 0.23 -0.96, P-value: 0.04), 4 passes (OR: 0.46, 95% CI: 0.19 -1.03, P-value: 0.07), and ≥ 5 passes (OR: 0.22, 95% CI: 0.08 -0.50, P-value: <0.001) were associated with lower odds of mRS 0-2 compared to ≤ 2 passes. However, there were no significant differences between groups in ICH, sICH, or 90-day mortality. Conclusion: The number of passes affects functional outcomes among stroke patients who underwent failed MT.

Introduction: Recent randomized control trials suggested that mechanical thrombectomy (MT) was associated with good functional outcomes after acute ischemic stroke (AIS) due to large vessel occlusion (LVO) in patients presenting with low Alberta Stroke Program Early CT Score (ASPECTS) (defined as ASPECTS 2-5). The aim of this study is to develop and validate a stroke prediction tool for outcome in MT for AIS patients with low ASPECTS using data from an ongoing international multicenter registry, the Stroke Thrombectomy and Aneurysm Registry (STAR). Methods: 236 AIS patients with low ASPECTS caused by LVO who undertook MT between January 2010 and December 2022 were retrospectively investigated. Univariate and multivariate logistic regression results were used to screen model predictors and construct nomograms of 90-day modified Rankin Scale scores (mRS) 0-3. The performance of the model was detected by using receiver operating characteristic analysis. The bootstrap resampling method was considered internal validation of the model. Results: Age (< 70 years), premorbid status (mRS 0), National Institutes of Health Stroke Scale (NIHSS) (< 20), and recanalization status after the MT (modified Thrombolysis in Cerebral Ischemia [mTICU] ≥2b) were related to 90-day mRS 0-3. Predictive score was calculated by adding 1 point for age (< 70 years), premorbid status (mRS 0), and NIHSS < 20 and 3 points for a mTICI ≥2b (ranging 0-6). 90-day mRS 0-3 was observed in 0% of patients with a score of 0 or 1, 6.3% with a score of 2, 17.7% with a score of 3, 22.2% with a score of 4, 45.7% with a score of 5, and 73.7% with a score of 6. The score showed relatively high performance in predicting 90-day mRS0-3 (area under the curve: 0.79 [95% CI 0.73-0.79] and 0.78 [95% CI 0.78-0.78] for derivation and validation cohorts, respectively). Conclusions: This study indicates the STAR score can be calculated with baseline and periprocedural characteristics to predict the 90-day outcome after MT in AIS patients with low ASPECTS.

Introduction: Despite comparable outcomes for different frontline techniques in mechanical thrombectomy (MT) for acute ischemic stroke (AIS), there are sparse data regarding if and when to switch techniques if the first pass is unsuccessful. We aimed to investigate the impact of converting from one MT technique to another on the second MT attempt for AIS among patients with large vessel occlusion (LVO). Methods: This was a retrospective observational study using data from the large multicenter international Stroke Thrombectomy and Aneurysm Registry (STAR). Data from 29 stroke centers for 10,229 AIS patients treated with MT for LVO between January 2010 and December 2022 was investigated. The primary outcome measure was successful recanalization defined as modified Thrombolysis in Cerebral Ischemia (mTICI) score of 2b or higher. 90-day modified Rankin score (mRS) 0-2, mortality and symptomatic hemorrhage were used as secondary outcomes. Clinical and technical outcomes after the second MT attempt were compared between those with or without technique conversion. Results: Among 10,229 AIS patients, 1,797 AIS patients with LVO failed first pass recanalization and were included in this retrospective analysis. 927 patients were female (52%) and median (interquartile range) age was 72 (61-81) years. Converting to alternative techniques following a first failed attempt was more likely to be associated with successful recanalization at the second attempt (adjusted odds ratio 2.30, 95% CI: 1.37-3.86, P = 0.002) and 90-day good clinical outcome (adjusted odds ratio 2.10, 95% CI: 1.15-3.85, P = 0.02) after multivariate adjustment. Conclusions: This study demonstrates better clinical and technical outcomes with conversion of MT technique for the second attempt in AIS patients with LVO who failed first pass recanalization.

Introduction: The benefits of intravenous thrombolysis (IVT) in acute ischemic stroke (AIS) patients with unsuccessful mechanical thrombectomy (MT) are not well established. Methods: This study included patients from the Stroke Thrombectomy and Aneurysm Registry (STAR) who underwent MT for ICA, M1, or M2 occlusions with unsuccessful MT (mTICI score ≤ 2a). Patients who received IVT prior to MT were compared to those who received MT alone. Propensity score (PS) matching was performed using age, sex, premorbid modified Rankin Scale (mRS), admission National Institute of Health Stroke Scale (NIHSS), occluded vessel, ASPECTS score, mTICI score, and symptom onset to groin puncture time. The primary outcome was favorable 90-day outcomes (mRS 0-2). Results: Of 610 patients with unsuccessful MT, 219 were matched in each group. Median ages were 70 [IQR: 61 - 80] and 73 [IQR: 62 - 81] in the IVT + MT and MT alone groups, respectively. In the IVT + MT group. Final TICI scores of 0, 1, and 2a were achieved in 92 (42.0%), 33 (15.1%), and 94 (42.9%) patients, respectively, compared to 76 (34.7%), 29 (13.2%), and 114 (52.1%) in the MT alone group. The IVT + MT group showed a significantly. higher 90-day mRS of 0-2 (aOR: 2.54, 95% CI: 1.53-4.32) and mRS of 0-3 (aOR: 2.05, 95% CI: 1.36-3.12). There were no significant differences between the groups in intracranial hemorrhage (ICH), symptomatic ICH, or 90-day mortality rates. Conclusions: IVT is associated with improved functional outcomes in patients with unsuccessful MT. Ensuring that IVT is provided to all eligible stroke patients should remain a priority.

Introduction: Up to 50% of acute ischemic stroke (AIS) patients who undergo successful mechanical thrombectomy (MT) fail to achieve favorable outcomes (futile recanalization). In this study we aim to develop a machine learning (ML) model to predict futile recanalization (FR) in AIS patients who undergo MT. Methods: We used data from an ongoing large, multicenter database from 2013 to 2023. We included AIS patients treated with MT for ICA, M1, or M2 occlusion with successful recanalization (modified Thrombolysis in Cerebral Infarction [mTICI] score ≥ 2C) and procedure durations under 60 minutes. FR was defined as successful recanalization with 90-day modified Rankin Scale (mRS) 3-6. The dataset was divided into 75% for training and 25% for external validation. Using the Caret Package in R, multiple models were tested, and their performances were evaluated by the area under the curve (AUC) of receiver operating. Both baseline and pre-interventional characteristics were incorporated into the model. The selected model was then externally validated on a 25% validation dataset. Results: Among 2,546 qualified patients, FR occurred in 1,342 (52.7%). In univariate analysis, baseline characteristics were significantly different between FR and non-FR groups. The M5P model demonstrated the highest performance (AUC: 0.833; 95% CI: 0.7989-0.852; PPV: 0.8101) in comparison to other tested models such as logistic regression (AUC: 0.74), RF (AUC: 0.78), J48 (AUC: 0.78), SVM (AUC: 0.79), and GB (AUC: 0.79). The external validation of the model showed satisfactory results (AUC: 75.25; 95% CI: 70-80; PPV: 76.87). Conclusion: Utilizing clinical, pre-procedural, and imaging parameters, the M5P model can efficiently predict F) in AIS patients before attempting MT. This tool can assist neurointerventionalists in adequately choosing their MT candidates.