Citations

Abstract Rationale Legionella species can cause severe community-acquired pneumonia requiring targeted antimicrobial therapy. The impact of time to effective Legionella-directed therapy on mortality is not well defined. Objectives To evaluate the association between time to effective Legionella-directed therapy and mortality in hospitalized patients with community-acquired Legionella pneumonia and to determine whether differences in treatment timing contribute to the excess mortality observed among immunocompromised patients. Methods A retrospective multicenter cohort study of adults hospitalized with laboratory-confirmed community-acquired Legionella pneumonia (2019–2025) was performed. Time from presentation to effective therapy (macrolide, fluoroquinolone, or doxycycline) was recorded. The primary outcome was 90-day mortality. Multivariable logistic regression analysis was performed, adjusting for age, SOFA-2 score (first 6 hours), and immunocompromised status. Secondary analyses included a 24-hour landmark Cox model for 90-day survival and multivariable logistic regression for 30-day mortality. Results Among 310 patients (median age 66.9 years, 44.8% immunocompromised), 90-day mortality was 17.4%. Every 6-hour delay in effective therapy was independently associated with increased 90-day mortality (adjusted OR per 6 hours: 1.11; 95% CI, 1.06–1.17; P < 0.001). Delays >24 hours were associated with worse 90-day survival (adjusted HR, 2.72; 95% CI, 1.65–4.77; P < 0.001). Time to effective therapy was also independently associated with increased odds of 30 day mortality (adjusted OR per 6 hours: 1.06; 95% CI: 1.01-1.11, p = 0.024). Immunocompromised patients experienced longer delays (median, 7.1 versus 3.3 hours; P < 0.001) and higher unadjusted 90-day mortality (22.3% versus 13.5%; P = 0.041), but immunocompromised status was not independently associated with mortality after adjusting for severity and treatment timing. Conclusion Longer time to effective Legionella-directed therapy was independently associated with increased mortality in a graded fashion. Delays were more common among immunocompromised patients, partially accounting for excess mortality in this group, suggesting that timely pathogen-directed therapy may represent a clinically important and potentially modifiable contributor to risk.

Abstract Prediction errors (PEs) drive perceptual learning by updating internal models of the sensory environment, yet it remains unclear how attention reshapes their representation across distributed thalamocortical circuits. Using intracranial stereoelectroencephalography (sEEG) from 17 patients performing a roving auditory oddball task under attended and unattended conditions, we quantified PE encoding using mutual information and co-information to capture redundant and synergistic PE representations. Attention modulated PE encoding in both the thalamus and the temporal cortex, but with distinct informational dynamics. Thalamic encoding showed a stable reduction of PE information during distraction, consistent with state-dependent thalamocortical gating. In contrast, the temporal cortex expressed two opposing learning trajectories during attended listening that converged once attention was diverted, revealing distinct cortical learning regimes rather than a uniform attentional effect. Attention further reorganized the informational content of cortical PE representations by altering the balance between redundant and synergistic information. A biologically constrained neural network showed that attention-dependent changes in inhibition and long-range connectivity reproduced these dynamics through Hebbian learning. Together, these findings suggest that attention regulates predictive learning not simply by changing the strength of PE responses, but by reshaping how distributed thalamocortical circuits represent and integrate sensory evidence over time.

ABSTRACT Objective To provide expert recommendations for the development of a specialty bipolar clinic that promotes best clinical practices for the delivery of safe and effective care. Methods Members of the National Network of Depression Centers (NNDC) Bipolar Clinics Work Group met in a series of 1‐h monthly video calls over 18 months to discuss all aspects of their respective institution's bipolar clinics, including services provided, administrative processes, staffing models, characteristics of patients treated, patient volumes, finances, and research. The group also invited psychiatrists from outside of the NNDC who ran large bipolar clinics to contribute their thoughts and experiences on the subject. In addition, the NNDC sent a 20‐question survey to all 27 sites asking clinic directors specific questions about their bipolar clinics, if applicable. Further meetings and discussions incorporating results from the survey took place to produce a comprehensive set of recommendations. Results Twenty‐one of 27 NNDC sites (81%) responded to the survey. Twelve of 21 (57%) sites had a specific bipolar clinic, and another 4 (19%) were looking to start one. Clinics were based in university settings. The meetings, clinic survey, and discussions resulted in 10 recommendations describing services and operations for bipolar specialty clinics. Conclusions Given the complexity of bipolar disorder, specialty clinics are important to enhance care. Clinics with a wide array of services that include consultation, medication management, bipolar‐specific psychotherapies, and patient/family psychoeducation provide the most comprehensive care. Challenges to these clinics include maintaining ongoing patient access as well as ensuring long‐term financial stability.

Abstract We describe a case of a child with macrolide-resistant Mycobacterium abscessus who initially had clinical improvement on a dual β-lactam regimen but continued to have positive cultures. Suitable phages active against the bacterial strain were identified, administered both systemically and directly to the ear, and were associated with microbiological remission.

ABSTRACT Ischemic events after contemporary percutaneous coronary intervention (PCI) are uncommon but carry high morbidity/mortality. Identifying patients at highest risk is critical to guide dual antiplatelet therapy (DAPT) intensity while minimizing bleeding. Current machine learning (ML) model‐developed risk scores do not incorporate pharmacogenetic data. To develop and externally validate ML models that integrate clinical, demographic, and CYP2C19 genetic information to predict 1‐year ischemic outcomes post‐PCI to refine clinical decision making. We analyzed 8317 patients from TAILOR‐PCI trial ( n = 4572) and the Precision PCI registry ( n = 3745). The outcome was a composite of cardiovascular death, myocardial infarction, stroke, and stent thrombosis at 1 year. Boruta feature selection identified 11 predictors. Multiple ML algorithms were trained in TAILOR‐PCI and validated in Precision PCI using cross‐validation and synthetic minority oversampling (SMOTE). Model performance was assessed by area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. The best external performance was achieved with a support vector machine (SVM, polynomial kernel) (AUC 0.667; sensitivity 0.871; specificity 0.282), while XGBoost provided a more balanced profile (AUC 0.619; sensitivity 0.442; specificity 0.688). Variable importance for the SVM polynomial model demonstrated that all 11 included Boruta feature selected predictors had relatively high importance (> 75). ML models trained on large clinical trial and real‐world registry datasets can help identify the small subset of patients at high ischemic risk after PCI. This distinction is of relevance because ischemic events are rare, and most patients may safely de‐escalate DAPT to reduce bleeding risk while maintaining ischemic protection through a multimodal approach to risk stratification. Trial Registration: TAILOR‐PCI URL: https://clinicaltrials.gov/ct2/show/NCT01742117

Abstract Since its introduction in 2002, left atrial appendage closure (LAAC) has rapidly expanded as an alternative to anticoagulation in patients with atrial fibrillation at high risk of stroke. Harmonized processes for data collection, analysis, and reporting in LAAC trials are essential to enhance research quality and improve clinical practice. The Left Atrial Appendage Academic Research Consortium (LAARC) initiative is an independent collaboration of academic research organizations, cardiology and neurology experts, clinical trialists, and regulatory authorities from the USA, Europe, and Asia. The consortium engaged clinical experts, regulators—including the US Food and Drug Administration (FDA), European Notified Bodies, and Japan’s Pharmaceuticals and Medical Devices Agency (PMDA)—and industry leaders to define standardized study elements and endpoints for LAAC trials. Key considerations included alignment with prior Academic Research Consortium initiatives, procedural and mechanistic insights, and clinical relevance. Consensus definitions were proposed for mortality, stroke, bleeding, and device performance, along with composite endpoints for safety and effectiveness. The proposed LAARC consensus definitions aim to standardize endpoint reporting, improve comparability across studies, and support regulatory and clinical trial applications for this evolving therapy through broad dissemination in the peer-reviewed literature.

Abstract Background Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome comprising multiple pathophysiological phenotypes. HFpEF trials have largely enrolled diverse populations and reported average treatment effects, consistently yielding neutral results that may obscure drug-specific benefits within distinct subgroups. To address this issue, we employ an interaction-based that incorporates treatment-by-variable interactions to uncover drug-specific responses. Methods We leveraged four HFpEF clinical trials (TOPCAT, RELAX, NEAT-HFpEF, INDIE-HFpEF) and developed a framework comprising two complementary approaches. The first employed a prognostic responder model to evaluate whether conventional responder definitions reflect treatment-specific benefit or instead capture favorable clinical trajectories common to both treatment and placebo groups. The second used an interaction-based individual treatment effect (ITE) modeling to identify baseline variables that modify therapy effect, distinguishing drug-specific response from prognostic phenotypes. Results Although the prognostic responder model demonstrated good discrimination, further analisys suggested it primarily captured a prognostic signal associated with favorable clinical trajectories common to both treatment and placebo arms. In contrast, the ITE model identified distinct, drug-specific effect modifiers across trials (cardiorenal-inflammatory for spironolactone (TOPCAT), NO-mediated anti-inflammatory for isosorbide mononitrate (NEAT-HFpEF), afterload-reducing for inorganic nitrite (INDIE-HFpEF), and anti–volume-overload for sildenafil (RELAX). Each ITE model demonstrated significance only within its own trial suggesting drug-specific signal. Conclusions The proposed method identifies mechanism-specific effect modifiers, and uncovers clinically meaningful heterogeneity in treatment response, which is not captured by conventional MCID-based approaches. Although exploratory, these findings support phenotype-guided therapy in HFpEF and argue for phenotype-informed trial design to enhance treatment-effect detection and therapy targeting. Graphical Abstract

ABSTRACT Purpose Standard spatial‐spectral excitation pulses apply a fly‐back gradient between sub‐pulses, limiting, for example, how thin the slices can be (> 4 mm). Without fly‐back gradients, slices can be as thin as 1.7 mm but require a phase calibration for the sub‐pulses with inverted gradients due to system imperfections. Here we propose and test a fast (< 1 s), localized pre‐scan enabling thin‐slice frequency‐selective excitation. Methods The calibration pre‐scan determines the correction phase between even and odd sub‐pulses by measuring the phase difference of two FIDs excited with either the last or second‐to‐last RF sub‐pulse of the spatial‐spectral pulse. Non‐localized and localized versions of the calibration pre‐scan are tested and validated for water‐only excitation in phantoms and the human heart. As an example, breath‐held coronary MR angiography is performed with a spiral multi‐slice sequence employing the proposed pulses with a slice thickness of 1.7 mm. Results The proposed calibration pre‐scan takes 11.1 ms per slice, whether it is localized or not. Localized calibration phases are validated with an image‐based calibration map. Slice profiles are visualized for pulses with different time‐bandwidth products. Fat is suppressed to below 20% and 25% of the surrounding water signal in both phantoms and the human heart, respectively. High‐quality coronary angiograms are demonstrated in all test subjects. Conclusion Spatial‐spectral pulses without fly‐back gradients can be calibrated quickly (up to 90 slices in 1 s), enabling thinner slices, higher excitation angles, or pulses with sharper slice profiles using waveforms with higher time‐bandwidth products.

Background Irritable bowel syndrome (IBS) is a complex disorder of gut-brain interaction, with heterogeneous symptoms, no available biomarkers and limited pathogenetic insight. Objective To identify genetic risk factors and actionable mechanisms for future clinical translation in IBS. Design We conducted a genome-wide association study (GWAS) meta-analysis of IBS in 2 775 539 individuals from 22 biobanks. IBS genetics was studied across multiple ancestries, different case definitions and symptom-related subtypes. Heritability and genetic correlations with other traits were estimated, and Mendelian randomisation was used to test causal relationships. GWAS data were functionally annotated and fine-mapped to prioritise tissues, cell types, pathways, candidate genes, specific mechanisms and druggable targets. Results Significant heritability was only detected in individuals of European ancestry, with near-identical genetic architecture across case definitions. Genetic correlations with GI, psychiatric and cardiometabolic traits were observed, including causal relationships with triglyceride (TG) levels. Functional annotation of IBS risk loci highlighted cell types and pathways relevant to brain, enteric neuro-glial and cardiometabolic domains, as well as actionable targets like GCKR, a regulator of TG metabolism. Druggability analyses converged on cardiometabolic mechanisms, including TG modulation. IBS polygenic risk scores were derived and showed a significant association with case status in an independent case-control dataset, supporting further evaluation in external population-based and clinically ascertained cohorts. Conclusions This study provides the most comprehensive assessment of IBS genetics to date, demonstrating reproducible polygenic inheritance. We link IBS risk to convergent neurogastrointestinal and novel cardiometabolic mechanisms, highlight specific biological pathways and actionable mechanisms and outline translational opportunities emerging from integrated computational analyses.