Citations

Abstract Background and Aims Stroke and systemic embolism are recognized but poorly characterized complications of atrial fibrillation (AF) and left atrial flutter (AFL) catheter ablation. Their incidence, outcomes, and procedural associations remain insufficiently defined. Methods Retrospective global registry was initiated by the European Heart Rhythm Association Scientific Committee. A secure database captured data from ablation centres worldwide on general AF and left AFL ablation activity, as well as detailed information on patients with symptomatic embolic events between 2017 and 2024. Results Overall, 204 centres reported 335 743 ablation procedures and 550 embolic events (incidence 0.16%). Centre-level rate ranged from 0% to 3.1%. Most events were cerebral (94%), followed by peripheral (5%), and combined (1%). Coronary air embolism accounted for 62% of all peripheral events. Intraprocedural events occurred in 93 patients (17%), within 72 h in 357 (78%) and beyond 72 h in 100 (22%); 128 cases (23%) were diagnosed after hospital discharge. Nonparoxysmal AF (0.23% vs 0.15%; P < .001), centre experience, and ablation energy source (radiofrequency, 0.16%; cryoballoon, 0.16%; pulsed field ablation, 0.25%; laserballoon, 0.88%; P < .001) were associated with embolic risk. Median NIHSS score after stroke was 4 (interquartile range, 2–9). Three-month follow-up was available for 518 patients with embolism (95%): 181 (35%) had sequelae and 16 (3%) died. Conclusions Symptomatic embolic events are infrequent but associated with significant morbidity and mortality. Most events occur early, though a substantial proportion arise later. Higher event rates were observed with laser and possibly with pulsed field ablation. A greater centre experience was associated with a lower embolism incidence.

ABSTRACT Background This exploratory analysis of the NEURO‐TTRansform Phase 3 trial evaluated the efficacy of eplontersen in patients with hereditary transthyretin (ATTRv) amyloidosis with polyneuropathy by genetic variant. Methods Changes from baseline in NEURO‐TTRansform primary endpoints serum transthyretin (TTR) at Week 65, modified Neuropathy Impairment Score+7 (mNIS+7) composite score, and Norfolk Quality of Life‐Diabetic Neuropathy (Norfolk QoL‐DN) total score at Week 66 were evaluated in patients with early‐onset (aged < 50 years) and late‐onset (aged ≥ 50 years) Val30Met (p.Val50Met) or non‐Val30Met ATTRv amyloidosis with polyneuropathy. Secondary endpoints from NEURO‐TTRansform were also evaluated by genetic variant. Results In total, 144 patients with early‐onset ( n = 54) or late‐onset ( n = 31) Val30Met or non‐Val30Met ( n = 59), ATTRv amyloidosis with polyneuropathy were randomized to eplontersen. A further 60 patients from NEURO‐TTR with early‐onset ( n = 16) or late‐onset ( n = 17) Val30Met or non‐Val30Met ( n = 27), served as a historical placebo group. The mean percentage difference (95% confidence interval) in serum TTR was −79.9 (−87.8, −72.0), −85.0 (−93.3, −76.6), and −70.6 (−77.7, −63.5) with eplontersen versus placebo in the early‐ and late‐onset Val30Met, and non‐Val30Met groups, respectively. Across subgroups, the change from baseline to Week 66 in mNIS+7 composite score was generally well maintained, and the Norfolk QoL‐DN total score improved with eplontersen versus worsening with placebo. The Polyneuropathy Disability score was maintained in most patients. From baseline to Week 65, the modified body mass index was maintained with eplontersen compared to a marked reduction (worsening) for placebo. Conclusions Findings were suggestive of consistent benefits in reducing neuropathy impairment and improving QoL with eplontersen versus historical placebo, across TTR variants. Trial Registration ClinicalTrials.gov: NCT04136184, NCT01737398

Importance Alzheimer disease (AD) biomarker and genetic testing results are increasingly disclosed to cognitively unimpaired adults in research and could in the future inform clinical treatment decisions in this population. Objectives To assess psychological outcomes after returning 3 categories of amyloid biomarker results as well as apolipoprotein E ( APOE ) genotypes. Design, Setting, and Participants This cohort study was a secondary analysis of data collected as part of screening for the multisite AHEAD preclinical AD trial. Participants were individuals aged 55 to 80 years undergoing screening from July 14, 2020, to October 15, 2024. Exposure Participants were informed whether they had not-detected, intermediate, or elevated amyloid positron emission tomography levels, as well as their APOE genotype, which were categorized as noncarrier, ε4 heterozygote, or ε4 homozygote. Main outcomes and measures Impact of Events Scale (IES; 15 items to assess intrusive thoughts and avoidance; each item is scored as not at all [0], rarely [1], sometimes [3], or often [5]; total range, 0-75), collected 24 to 72 hours after disclosure, and change in a scale measuring concerns about AD dementia (adapted scale using 6 items in which participants indicated their level of agreement with statements related to their perceived probability of developing AD dementia; items scored as strongly disagree [1] through strongly agree [5]; total range, 6-30), calculated by subtracting the score collected before biomarker testing from 1 collected after biomarker and genetic test results disclosure. Results Among 3414 included individuals, the mean (SD) age was 68.8 (6.0) years and 2116 (62%) were female. Group mean IES scores were below clinically significant thresholds. Nevertheless, across genetic groups, learning an elevated amyloid result (1184 participants) was associated with higher IES (mean [SD], 10.5 [10.9]) than intermediate amyloid (482 participants; mean [SD] IES, 8.8 [9.8]), and intermediate amyloid was associated with higher scores than not-detected amyloid (1748 participants; mean [SD] IES, 6.5 [8.4]). Across amyloid groups, learning APOE ε4 homozygosity (337 participants) was associated with higher mean (SD) IES (12.7 [11.6]) than heterozygosity (1609 participants; 9.1 [10.2]), and heterozygosity was associated with higher IES than noncarrier status (1468 participants; mean [SD] IES, 6.2 [8.1]). Both types of information were significant in an analysis of covariance model; no interaction effect was observed. In contrast, only biomarker disclosure was associated with differential change in concerns about AD dementia. Those with elevated amyloid showed a mean (SD) increase in concern (0.8 [3.5]), those with intermediate amyloid showed a smaller increase (0.4 [3.7]), and those with not-detected amyloid showed decreased concerns (−1.1 [4.2]). Conclusions and Relevance In this cohort study of cognitively unimpaired adults, associations with intrusive thoughts were observed to differ among genetic and biomarker subgroups; such associations were limited to biomarker subgroups for measures of perceived dementia risk.

ABSTRACT The increasing prevalence of carbapenem-resistant Klebsiella pneumoniae represents a serious global health challenge. Rapid and accurate detection methods are essential to inform early and correct use of antimicrobial therapy to idealize patient outcomes and limit the spread of resistant isolates. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been evaluated for resistance detection, but its clinical application remains limited. In this study, MALDI-TOF MS was integrated with machine learning (ML) to improve detection of Klebsiella pneumoniae carbapenemase (KPC) among K. pneumoniae isolates harboring KPC carbapenemase. Ensemble learning strategies were applied to 435 clinical isolates from different geographic locations (Spain, United States, South America, and Asia), with validation performed using external data sets. By constructing two peak matrices and applying four ML algorithms, as well as combinations of two and three in ensemble models, 92 different classifiers were tested. Ensemble combinations increased the specificity of classifiers to over 95%, while sensitivity reached 72%, being significantly higher than that of the MALDI Biotyper KPC module. Low sensitivity may be affected by technical variability during spectral acquisition. The first annotated MALDI-TOF MS spectrum for K. pneumoniae by in silico prediction of protein masses was developed to enable peak identification, including peaks potentially related to antimicrobial resistance. Overall, the results of this study show that combining MALDI-TOF MS with ensemble learning can enhance KPC detection performance. IMPORTANCE Rapid and accurate detection of Klebsiella pneumoniae carbapenemase (KPC)-producing Klebsiella pneumoniae informs early and correct use of antimicrobial therapy to idealize patient outcomes and limit the spread of antimicrobial resistance. In this study, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and ensemble machine learning were employed to detect KPC-producing isolates, using diverse isolate collections, obtaining excellent specificity. An annotated K. pneumoniae MALDI-TOF MS profile is provided with peak annotation, providing a resource for peak analysis.

Abstract INTRODUCTION Visual perceptual difficulties occur in dementia with Lewy bodies (DLB). Normative data and cut scores for DLB and mild cognitive impairment with Lewy bodies (MCI‐LB) are needed for the 20‐item Noise Pareidolia Task. METHODS Participants included 344 cognitively unimpaired (CU), 112 DLB, and 105 MCI‐LB. Cumulative percentile ranking was used for normative classification. Receiver operating characteristic analyses, convergent validity, and associations with visual hallucinations (VH) were assessed. RESULTS In CU participants, a perfect score was average, one error was low average, and two or more errors fell below average. A cut score of one or more errors optimally distinguished CU participants from DLB (Total score area under the curve [AUC]: 0.82, Noise score AUC: 0.77) and MCI‐LB (Total score AUC: 0.75, Noise score AUC: 0.74). A cut score of two or more errors lowered sensitivity but increased specificity to 94%. Performance was associated with VH in DLB, but not MCI‐LB. DISCUSSION Results establish normative data for the 20‐item Noise Pareidolia Task and support its use in DLB and MCI‐LB.

Variants in TMEM106B and GRN , which encode lysosomal proteins, interact through unknown mechanisms to increase the risk of age-related cognitive decline and neurodegeneration. Here, we show that these variants converge on a single molecular intermediate: the cleaved intra-lysosomal fibril core of TMEM106B, a precursor to amyloid fibrils that accumulate in the aging brain. A protein-coding TMEM106B risk variant (p.T185) drives fibril core accumulation by impairing its degradation and GRN risk variants amplify this effect. Mice over-expressing the fibril core develop hallmarks of neurodegeneration, and cryo-electron tomography reveals intra-lysosomal fibrils in cultured neurons, mice, and diseased human brain. In GRN -mutation carriers, in whom fibril burden is greatest, fibrils extrude through ruptured lysosomal membranes. These findings identify intra-lysosomal TMEM106B fibrillization as a convergent neurodegeneration mechanism and potential therapeutic target.

ABSTRACT Electrocardiography (ECG) is a critical diagnostic tool for identifying cardiac conditions. While standard lead positions are widely used to ensure diagnostic accuracy, alternative lead placements have been developed to address specific clinical scenarios. These alternative configurations can overcome physical or technical challenges, enhance rhythm assessment, improve signal quality, and provide greater specificity for certain conditions, ultimately enabling more personalized diagnostic strategies. This paper examines the clinical significance of alternative ECG lead positions, highlighting their advantages, limitations, and potential applications in various clinical settings.

PURPOSE Chronic myelomonocytic leukemia (CMML) is a rare myeloid neoplasm characterized by clinical heterogeneity and is associated with poor outcomes. To date, limited molecular information has been incorporated into disease classification and risk stratification. We aimed to integrate genomic features into the clinical decision-making process for CMML. PATIENTS AND METHODS We analyzed a retrospective cohort of 3013 patients with CMML (training set) and a prospective population of 516 patients (validation set). Using an innovative framework for multimodal data analysis, we developed molecular-based disease taxonomy and prognostication. RESULTS Unsupervised clustering identified nine entities with distinct genomic features and outcomes ( P < .001), including splicing machinery, transcription factors, signal transduction and tyrosine kinase pathways aberrations, and high-risk molecular signatures. Notably, 15% of patients showed molecular/clinical overlap with other myeloid neoplasms. We integrated molecular and clinical information to build the international CMML Prognostic Scoring System (iCPSS), incorporating mutations in nine genes together with hematologic parameters and cytogenetic abnormalities. The iCPSS identified five groups with distinct probability of overall and leukemia-free survival in both training and validation cohorts ( P < .001), outperforming existing prognostic models. Importantly, 55% of patients were reassigned to higher or lower risk groups by the iCPSS. Decision analysis demonstrated that iCPSS could refine the optimal timing of allogeneic transplantation at the individual level; compared with conventional prognostic tools, iCPSS-based decision modeling changed transplantation strategy in 31% of cases, resulting in a significant gain-in-life expectancy for eligible patient population ( P < .001). A federated learning platform was implemented to enable continuous, privacy-preserving model update across multiple centers. CONCLUSION Molecular information improves CMML classification and prognostication, supports more effective clinical decision making, and potentially refines the design of clinical trials.