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Background:Aortic valve replacement is the primary treatment for aortic valve disease and can be performed using either transcatheter (TAVR) or surgical (SAVR) approaches. The risk of aortic dissection (AD) with TAVR compared with SAVR remains unclear. We aimed to compare AD risk between TAVR and SAVR using a large, real-world cohort. Methods:We conducted a retrospective cohort analysis using the TriNetX research network. Patients with a diagnosis of aortic stenosis, aortic insufficiency, mixed aortic valve disease (AVD), or unspecified AVDwho underwent either TAVR or SAVR were included. A 1:1 propensity score-matching (PSM) based on baseline characteristics was performed to adjust for potential confounding. Logistic regression and Cox proportional hazards models were used to estimate odds ratios (ORs) and hazard ratios (HRs), with 95% confidence intervals (CIs).Results:Among 95,043 patients undergoing isolated aortic valve replacement, 20,237 matched pairs were analyzed after 1:1 PSM. Baseline characteristics were well balanced, with a mean age of 73.3 ± 9.3 years in the TAVR group and 73.2 ± 8.5 years in the SAVR group; 60.8% and 60.7% were male, respectively. TAVR was associated with significantly lower odds of composite AD than SAVR at all time points (1-year OR 0.60; 95% CI 0.44–0.82; 3-year OR 0.64; 95% CI 0.48–0.83; 5-year OR 0.66; 95% CI 0.51–0.85; p < 0.01 for all). Stratified analyses demonstrated lower odds of both Stanford type A and type B AD at all time points. Kaplan–Meier analysis demonstrated a separation in composite AD-free survival between the two groups (HR 0.66; 95% CI 0.51–0.86; p = 0.002).Conclusion:In this large, real-world cohort, despite a low event rate, TAVR was associated with a significantly lower likelihood of composite AD than SAVR.

Patients in the liso-cel plus ibrutinib cohort of the phase 1/2, open-label TRANSCEND CLL 004 study had relapsed/refractory chronic lymphocytic leukemia (CLL)/small lymphocytic lymphoma (SLL) and received liso-cel (50×106 [dose level (DL)1] or 100×106 [DL2] chimeric antigen receptor-positive T cells) with concurrent ibrutinib from enrollment through 90 days after liso-cel infusion or longer per investigator discretion. Primary end point was complete response/remission (CR)/CR with incomplete marrow recovery (CRi) by investigator assessment. Among 56 patients who received ibrutinib plus liso-cel (DL1, n=5; DL2, n=51), median (range) age was 64.5 years (44‒77), 98% had high-risk cytogenetics, 55% had progression on Bruton tyrosine kinase inhibitor and venetoclax failure, and median (range) number of prior therapies was 5 (1‒13). Median (range) follow-up was 24.8 months (3.1‒51.8). At DL2, CR/CRi rate was 45% (95% confidence interval [CI], 31‒60) and overall response rate was 86% (95% CI, 74‒94). Median (95% CI) duration of response was not reached (NR; 28.7‒NR) for patients with CR/CRi and 41.4 months (23.3‒NR) for all responders. Median (95% CI) progression-free survival was 31.4 months (20.1‒NR). In DL1+DL2, most common grade ≥3 treatment-emergent adverse events (TEAE) were neutropenia (52%) and anemia (41%). Cytokine release syndrome was reported in 80% of patients (grade 3, 4%; no grade 4/5), and neurological events in 41% (grade 3/4, 11%; no grade 5). Ibrutinib-related TEAEs were reported in 68% of patients (grade 3/4, 43%; no grade 5). Liso-cel plus ibrutinib demonstrated notable efficacy in patients with relapsed/refractory CLL/SLL with predictable and manageable safety. Clinicaltrials.gov: NCT03331198; NCT03435796.

Abstract Background There is limited data on immune checkpoint inhibitor (ICI) use in patients with non-small cell lung cancer (NSCLC) and known pericardial effusions. Methods This international multi-center observational retrospective study included patients with advanced NSCLC with or without pericardial effusions receiving ICIs. Immune-related adverse events (irAEs) were graded per CTCAE v5.0. Overall survival (OS) and progression-free survival (PFS) were estimated by the Kaplan-Meier method. Cox proportional hazards multivariable models assessed the association between survival outcomes and clinicopathologic variables, and an inverse probability of treatment weighting (IPTW) model compared outcomes between the two groups. Results A total of 1248 patients with advanced NSCLC treated with ICIs across 13 institutions were included. Of these, 85 patients (6.8%) had pre-existing pericardial effusions. Compared to controls, patients with pericardial effusions were younger (median age 63 vs 67 years, P = .007), diagnosed more frequently with PD-L1 positive tumors (96% vs 76%, P &lt; .001), and had a higher median number of baseline metastatic sites (3 vs 1, P &lt; .001). IrAEs were similar between both groups (42% vs 38%), and no cardiac irAEs occurred in patients with pericardial effusions. PFS (median 5.6 vs 4.6 months, P = .3) and OS (median 10.2 vs 14.7 months, P = .50) were not statistically different between patients with pericardial effusions and the controls, respectively. In both multivariable and IPTW models, pericardial effusions were not associated with PFS or OS. Conclusions Among patients with NSCLC and pre-existing pericardial effusions, ICIs demonstrate meaningful clinical benefit similar to those without effusions, with no new cardiac or severe toxicities.

Background Randomized trials have shown equivocal outcomes between a direct aspiration as first-pass technique (ADAPT) and stent retriever (SR) stroke thrombectomy, yet whether specific patient subgroups benefit differentially from one technique over the other remains unknown. Methods In this retrospective multicenter cohort study, patients with large vessel occlusion were included, and those who underwent ADAPT versus SR first-pass thrombectomy (either as standalone or combined with aspiration) were compared. The primary outcome was a composite of first-pass effect (FPE, modified Thrombolysis In Cerebral Infarction (mTICI) 2c or better with one attempt) with no symptomatic intracranial hemorrhage (sICH). A causal forest model was used to estimate the conditional average treatment effect (CATE) for each patient, with larger CATEs indicating that ADAPT is expected to be more advantageous. Patients were stratified by CATEs, and outcomes were compared between treatment groups. Results Among 6700 included patients, ADAPT (n=3695, 55%) was associated with a higher rate of FPE with no sICH (39.9% vs 26.9%; adjusted OR (aOR) 2.07, 95% CI 1.77 to 2.41, P<0.001). The causal forest identified significant treatment effect heterogeneity (interaction P<0.001), where ADAPT was more advantageous in more recent years and among patients with M1 occlusions presenting in earlier time windows. Low-CATE patients showed no statistically significant difference between techniques (aOR 0.91, 95% CI 0.57 to 1.45, P=0.70), while medium- and high-CATE patients demonstrated progressively larger ADAPT advantages (aOR 2.06, 95% CI 1.67 to 2.55, and aOR 2.99, 95% CI 2.24 to 3.98, respectively, both P<0.001). Conclusions ADAPT may be superior to SR for a majority of patients, particularly in recent years, and among patients with M1 occlusions presenting in earlier time windows.

Abstract Aims Randomized trials comparing percutaneous left atrial appendage occlusion (LAAO) with oral anticoagulation (OAC) for stroke prevention in patients with atrial fibrillation have yielded conflicting results across device generations and anticoagulant eras. This Bayesian meta-analysis of randomized trials aimed to compare LAAO vs. OAC for stroke or systemic embolism (SSE) and non-procedural clinically relevant bleeding (CRB). Methods and results We conducted a systematic search across five databases (PubMed, Embase, Scopus, Web of Science, and Cochrane CENTRAL) to identify randomized trials of LAAO vs. OAC. Primary outcomes of stroke or systemic embolism, non-procedural CRB and clinical benefit composite were estimated using a Bayesian hierarchical random effects model and findings confirmed across robust sensitivity and subgroup analyses. Posterior probabilities for superiority, non-inferiority and equivalence were estimated using clinically meaningful margins. Six randomized trials including 7004 participants in the intention-to-treat groups, were analysed. LAAO was not associated with lower SSE vs. OAC (pooled RR, 1.11; 95% CrI, 0.80–1.49), with a 74.6% posterior probability of favouring OAC. The posterior probability of crossing non-inferiority was P(HR &lt; 1.4) of 89%. In contrast, LAAO reduced non-procedural CRB (pooled RR, 0.59; 95% CrI, 0.45–0.78). The net clinical benefit composite, pooling contemporary trials, demonstrated a pooled RR of 0.90 (95% CrI 0.51–1.50), with P(RR &lt; 1) of 76%, with substantial heterogeneity for this outcome. Conclusion This Bayesian meta-analysis found no clear evidence supporting clinically meaningful non-inferiority of LAAO over OAC for stroke prevention. Despite reduced non-procedural bleeding, LAAO did not demonstrate a similar reduction in major bleeding.

The Pulmonary Embolism Reporting and Data System (PE-RADS) provides a standardized framework for reporting acute pulmonary embolism at CT and MR angiography to guide treatment considerations based on clot location and right heart imaging features.

Abstract Deep mutational scanning (DMS) has proven effective for mapping protein–protein interactions (PPIs), but it cannot provide complete coverage of the mutation landscape, particularly for multi‐mutant variants. To address this limitation, we trained machine‐learning (ML) models on previously generated DMS data for a stabilized amyloid precursor protein inhibitor (APPI) binding to either of two serine proteases, mesotrypsin and kallikrein‐6 (KLK6), which are implicated in various human disorders. We combined the models to accurately predict the binding selectivity of APPI variants, including double‐mutant variants, for the two serine proteases. We achieved a Pearson correlation of 0.937 between predicted log 2 selectivity enrichment ratios and DMS‐derived values. We further validated the predictions of our combined model by yeast‐surface‐display measurements and inhibition assays of purified APPI variants and revealed epistatic interactions that shape protease selectivity. Guided by binding selectivity predictions, we identified highly selective APPI variants, including the most selective mesotrypsin inhibitor reported to date. Together, these findings support the use of DMS and ML as a framework for predicting PPI selectivity and prioritizing selective therapeutic protein variants.

Abstract Seizure forecasting has progressed from theoretical aspiration to a rapidly advancing research domain, yet clinical translation remains limited. Over the past decades, advances in algorithm development, chronic electroencephalography (EEG), wearable sensors, and the characterization of seizure cycles have demonstrated that seizure risk is not random but fluctuates according to identifiable biological rhythms and patient‐specific patterns. Forecasting algorithms have shown promising performance across diverse retrospective datasets, including intracranial EEG, subscalp recordings, wearable physiological signals, and even self‐reported diaries. However, the clinical value of forecasting is contentious. Prospective real‐world validation and regulatory approval of patient‐facing forecasting systems remain rare. This review incorporates perspectives presented at the 5th International Congress on Mobile Health and Digital Technology in Epilepsy (2025). We examine barriers impeding clinical translation and current attempts to address them. Crucially, forecasting performance cannot be evaluated in isolation from intended use. Applications range from low‐risk uses, like scheduling diagnostic monitoring or visualization of historical trends, to higher risk interventions, including medication titration and adaptive neuromodulation. Each application entails distinct performance thresholds, ethical considerations, and regulatory requirements. Translational challenges include reliable seizure annotation, nonstationarity dynamics of biological cycles, and practical constraints for real‐time deployment. Ethical concerns center on miscalibrated reliance on low‐risk states, potential anxiety associated with high‐risk advisories, and the heterogeneity of patient preferences and risk tolerance. Regulatory pathways are likely to depend on clearly defined use cases and clinically meaningful endpoints, which may extend beyond seizure counts to include quality of life, anxiety, locus of control, and other patient‐reported outcomes. Ultimately, translation will require rigorous prospective evaluation against transparent benchmarks, sustainable scientific–commercial partnerships, and integration of probabilistic risk information into clinical workflows. With careful implementation, seizure forecasting may evolve from proof‐of‐concept research into a clinically meaningful component of epilepsy management, and we remain cautiously optimistic.