Citations

Importance Novel blood culture diagnostics provide rapid antimicrobial susceptibility testing (AST) results for bacteria causing bloodstream infections (BSIs) but have unclear clinical impact. Objective To evaluate clinical outcomes of blood culture testing using a rapid AST method compared with standard AST in patients with BSIs caused by gram-negative bacilli in regions with high prevalence of antimicrobial resistance. Design, Setting, and Participants Open-label randomized clinical trial that enrolled participants from December 2023 to May 2025 (final follow-up, June 18, 2025) at 7 medical centers in Greece (n = 2), India (n = 1), Israel (n = 3), and Spain (n = 1). Hospitalized patients (adults and children) with BSIs caused by gram-negative bacilli were eligible. Statistical analysis was conducted from August 2025 to January 2026. Intervention Patients were randomized to undergo blood culture evaluation using rapid, phenotypic AST directly from positive blood cultures plus standard susceptibility testing (n = 413) vs standard susceptibility testing alone (n = 437). Local antimicrobial stewardship teams reviewed all patients and provided treatment recommendations. Main Outcomes and Measures The primary outcome was a desirability of outcome ranking (DOOR) at day 30, with 3 categories (alive without deleterious events, alive with deleterious events, and death). The difference between rapid and standard testing was summarized as the probability that the DOOR outcomes were more desirable in the rapid testing group. Superiority was concluded if the lower limit of the 95% CI exceeded 50%. Secondary outcomes included 30-day mortality, length of hospitalization, intensive care unit admission, acquisition of hospital-acquired infections, time to effective antibiotic therapy within 3 days, and time to antibiotic escalation or deescalation within 3 days. Results Of the 899 patients randomized, 850 were included in the primary outcome analysis (median [IQR] age, 72 [21] years; 43% female). The probability that DOOR outcomes were more favorable in the rapid testing group was 48.8% (95% CI, 45.3%-52.4%). Median time to effective antibiotic therapy was not different between the groups in the as-randomized population. Median time to antibiotic escalation or deescalation was faster in the rapid testing group by 14 hours (95% CI, 6-22) in the as-randomized population. There were no differences between the groups in other secondary outcomes. In the prespecified subgroup with carbapenem-resistant infections, median time to effective therapy was 9.5 hours in the rapid testing group vs 28 hours in the standard testing group (difference, −18 hours [95% CI, −42 to 6]). Conclusions and Relevance Among patients with gram-negative bacilli BSIs, rapid blood culture AST was not superior to standard testing by DOOR. When considered with other efficacy and safety outcomes, these findings may help inform the use of rapid susceptibility testing in clinical practice. Trial Registration ClinicalTrials.gov Identifier: NCT06174649

The 2025 Voice AI Symposium represented a transition from conceptual research to clinical implementation in vocal biomarker science. Hosted by the NIH-funded Bridge2AI-Voice consortium, the meeting convened global experts to address the methodological, ethical, and translational challenges of integrating voice-based artificial intelligence (AI) into healthcare. This mini-review synthesizes symposium insights across six domains: multimodal integration, FAIR (Findable, Accessible, Interoperable, Reusable) and CARE (Collective Benefit, Authority to Control, Responsibility, Ethics) data governance, clinical translation, interdisciplinary training, and cross-sector innovation. Research presented demonstrated voice as a latent, multimodal biomarker reflecting neurological, cardiopulmonary, and psychological states, while discussions emphasized ethical data practices and human-centered design. The implementation-focused panels underscored the importance of workflow alignment and usability for adoption in real-world care. Collectively, the symposium reflects a field advancing toward translational readiness and ethical accountability, positioning voice AI as a scalable, inclusive tool for next-generation healthcare.

Abstract Background Coagulation markers are used to guide clinical anticoagulation decisions. We aimed to identify circulating metabolites that are associated with coagulation markers in children with congenital heart disease (CHD). Methods Plasma samples were separated from whole blood under consistent conditions. Untargeted metabolomic data were measured in plasma from up to 203 young patients (age range: 0 days-24 years) with CHD before cardiac surgery. Coagulation markers included activated partial thromboplastin time (aPTT), prothrombin time (PT), and activated clotting time (ACT). Weighted Gene Co-expression Network Analysis (WGCNA) was performed to explore metabolite modules (clusters). Associations of metabolites with the coagulation markers were assessed cross-sectionally with regression models, with false discovery rate (FDR) correction for multiple comparison. Associations between coagulation markers and ‘eigenmetabolites’ from WGCNA modules were assessed by correlation analysis. Results A total of 776 metabolites were included in the final analysis. Among these, 20 metabolites were associated with PT and one (valine) with ACT (FDR q value < 0.05). Among the metabolites associated with PT, the top three were retinol, 1-palmitoyl-GPI (16:0), and X-25371 (identity unknown). One module from WGCNA with metabolites from the lipid super pathway was correlated with PT (P = 0.004). Conclusion In this first attempt to identify novel metabolites for coagulation markers, we report 21 metabolites associated with PT or ACT in children with CHD. Future studies are needed to replicate these findings in independent cohorts and to elucidate the biological mechanisms linking these metabolites to hemostatic regulation.

Abstract Importance Voice-based health technologies are growing rapidly, but they lack standardized terminology, which hinders interdisciplinary collaboration, research quality, and clinical translation. Objective The objective of this work is to develop universally accepted definitions in the rapidly evolving field of vocal biomarkers, as part of the VOCAL ( V ocal Biomarker Guidelines for O ntology, C lassification, A pplication, and L ogistics) initiative, a structured, international consensus-based framework that aims to provide standards, and guidelines. Design VOCAL is a rigorous, international, multi-stage consensus-building study conducted in 2024-2025. Setting Multi-institutional collaboration between representatives from the Bridge2AI-Voice Consortium (North America) and the eVoiceNet Network (European Union), culminating in an in-person workshop at the 2025 Bridge2AI Voice Symposium. Participants A group of 24 international experts in medicine, clinical research, speech and language, audio signal processing, statistics, methodology, regulation, ethics. Methods VOCAL’s iterative process involved five rounds of review, feedback, and an in-person workshop at the international 2025 Bridge2AI Voice Symposium, ensuring the incorporation of diverse perspectives and achieving a robust agreement on the proposed definitions. Main outcomes and measures Consensus-based definitions for vocal biomarkers, spanning from broad concepts (biomarker, digital biomarker, vocal biomarker) to domain-specific measures (cardio-respiratory acoustic, voice, speech/articulatory, cognitive/language). Results A hierarchical continuum model of vocal biomarkers was established. We first distinguished between the concepts of vocal measures and vocal biomarkers. We then defined terms from broad, overarching concepts (Level 0: Biomarker, Digital Biomarker, Vocal Biomarker) to more specific physiological and cognitive domains (Level 1: Cardio-Respiratory Acoustic; Level 2: Voice; Level 3: Speech/Articulatory; Level 4: Cognitive/Language, including linguistic and paralinguistic subtypes). Conclusions and Relevance This work provides a shared vocabulary that is essential for fostering communication through interdisciplinary collaboration, improving the quality and efficiency of research and development, and ensuring the ethical, reliable, and scalable deployment of future voice-based health technologies. It lays foundational groundwork for upcoming guidelines and standards, which are crucial for advancing the field of vocal biomarkers into widespread clinical utility. Key points Question Can we establish an international consensus on the definitions related to vocal biomarkers? Findings Through a multi-stage international consensus process involving expert representatives from the Bridge2AI-Voice Consortium and eVoiceNet Network, a hierarchical model of vocal biomarkers was developed, defining terms from broad concepts (biomarker, digital biomarker, vocal biomarker) to specific physiological and cognitive domains (cardio-respiratory acoustic, voice, speech/articulatory, cognitive/language). Meaning Standardized definitions for vocal biomarkers provide an essential shared vocabulary for interdisciplinary collaboration and lay the foundational groundwork for future guidelines needed to advance the implementation of voice-based health technologies into clinical practice and clinical research.

Pulmonary Langerhans cell histiocytosis (PLCH) is a rare diffuse parenchymal lung disease representing 3% of all interstitial lung diseases. PLCH occurs either as part of multi-system Langerhans cell histiocytosis (LCH) or an isolated disease of the lung. Isolated involvement of lungs is observed in approximately 50–70% of LCH cases and the age of onset peaks between 20 and 40 years without gender difference. Cigarette smoking is the only identified environmental risk factor. PLCH is characterized by Langerhans cell infiltrates that in general are in a bronchiolocentric distribution. Pulmonary lesions can occur after chronic systemic disease or are an initial sign of disease. The aims of this study are to (1) report five rare cases of PLCH in adults; (2) discuss the relationship of PLCH with interstitial lung fibrosis; (3) provide a concise review of PLCH epidemiology, pathophysiology, diagnosis, treatment, and prognosis to improve the knowledge of PLCH by pneumologists and internal medicine physicians.

Introduction: Cardiorenal fibrotic remodeling (CFR), often in the setting of heart failure (HF) and kidney disease (CKD), is a major cause for increased risk in mortality, for which there are no effective drugs. C-type natriuretic peptide (CNP) is a 22 amino acid (AA) ligand for the particulate guanylyl cyclase receptor-B (GC-B) and exerts anti-fibrotic actions, with little effect on blood pressure (BP) or renal function, via its second messenger cGMP. To overcome CNP’s limited efficacy with its short half-life, we designed 2 novel CNP-based peptides (C53 and CU32). C53 consists of CNP plus a 31 AA N-terminus extension, while CU32 is the CNP ring fused with the N- and C-termini of urodilatin (GC-A agonist). Here we investigated the cGMP generating actions of C53 and CU32, with the goal of advancing novel GC-B/cGMP therapeutics for CFR. Hypotheses: We hypothesized that C53 and CU32 would have cGMP activating actions in vivo, however only C53 would generate cGMP production selectively via GC-B in vitro. We also hypothesize that the addition of the C-termini to CU32 would form a non-selective GC-B/cGMP agonist with renal and BP lowering actions. Methods: HEK293 cells expressing human GC-B or -A and human fibroblasts (hFs), where GC-B is abundant, were stimulated with C53 or CU32 (10-8M) for 10 min. Two groups of normal rats (n=8) received a 75 min equimolar IV infusion of C53 or CU32. Change in mean arterial pressure (ΔMAP), sodium (Na) excretion and plasma and urinary cGMP were assessed. *p<0.05. Results: C53 and CU32 activated cGMP in GC-B cells (C53: 75±9, CU32: 24±2 pmol/well*), while only CU32 activated cGMP in GC-A cells (C53: 0±0, CU32: 50±3 pmol/well*). In hFs, both C53 and CU32 generated cGMP. In vivo, plasma cGMP (C53: 91±4, CU32: 94±6 pmol/ml) and urinary cGMP excretion (C53: 177±28, CU32: 227±28 pmol/min) were similar with both peptides. Yet, CU32 induced a greater reduction in ΔMAP (C53: -7±1, CU32: -16±3 mmHg*) and increased Na excretion (C53: 1.4±0.2, CU32: 2.4±0.2 uEq/m*) compared to C53. Conclusions: We report the engineering of a selective (C53) and non-selective (CU32) GC-B agonist that has favorable cGMP generating action in hFs and in vivo. Thus, C53 and CU32 may represent novel GC-B therapeutics that could be tailored to specific phases of HF or CKD to prevent CFR.

Introduction: As importantly underscored by the SPRINT Trial, innovative blood pressure (BP) lowering and multiorgan protective drugs are needed for treating hypertension (HTN). We engineered a Mayo Clinic designer atrial natriuretic peptide (ANP)-based drug, ZD100, which possesses a unique 12 amino acid (AA) carboxy-terminus (CT) extension while maintaining the N-terminus (NT) of ANP. ZD100 is more potent than ANP in reducing BP, inducing natriuresis and inhibiting aldosterone via pGC-A and its second messenger cGMP. To date, the in vivo actions of ZD100 in a model of essential HTN are undefined. Further, in attempt to enhance and/or minimize pGC-A activation, the importance of specific AAs in the CT and NT of ZD100 is unknown and is critical to define. Hypothesis: We hypothesize that ZD100 is a potent anti-HTN drug activating pGC-A/cGMP system and that specific AA variations in the CT and/or NT of ZD100 will modify the ability of activating pGC-A. Methods: Spontaneously hypertensive rats (SHRs) received intravenous (IV) ZD100 or vehicle and BP, plasma and urinary cGMP and the natriuretic effects were determined. We then engineered 15 strategic ZD100 variants (Vs) consisting of mutated peptides in the CT or NT or both. We stimulated HEK293 cells overexpressing pGC-A with ZD100 and the 15 Vs (10-8 M) and measured intracellular cGMP generation. Results: In SHRs, acute IV ZD100 reduced BP, increased plasma and urinary cGMP generation and induced natriuresis demonstrating efficacy in HTN. In vitro, we found two more potent pGC-A activators (+100% cGMP activation) only among the CT-only mutated ZD100 Vs. Importantly, key mutations of either the CT or NT resulted in 6 loss-of-function Vs identifying importance of peptide-receptor dependency. Conclusions: We demonstrate for the first time in a genetic model of HTN that ZD100 reduces BP, activates systemic and renal pGC-A/cGMP and induces natriuresis. Enhanced or reduced pGC-A activation with targeted AA mutations in the CT and NT of ZD100 provides key structure function insights into ZD100 which may lead to next generation ZD100 therapeutic peptides. These findings support ZD100 as a novel peptide therapeutic strategy for HTN and will help guide the selection of best-in-class ZD100 analogues.

Background: Diagnosis of heart failure with preserved ejection fraction (HFpEF) is challenging due to non-diagnostic imaging outputs and discordant clinical features. Using only a single videoclip from a standard transthoracic echocardiogram (TTE), we developed an artificial intelligence (AI) model to differentiate patients with HFpEF from those without HFpEF. In a separate test population, we assessed the model’s ability to predict cardiac mortality. Methods: A 3-dimensional convolutional neural network was developed and trained on apical 4-chamber videoclips to classify patients with HFpEF (cases) versus without HFpEF (controls). Overall and cardiac mortality were obtained from the National Death Index. Results: The model was independently tested in 646 cases and 638 controls from 8 centers in 4 states. Sensitivity (87.8%; 84.5-90.9%) and specificity (81.9%; 78.2-85.6%) were high and sustained in various subgroups, including increased left atrial volume index, average E/e’ ≥15, and pulmonary artery systolic pressure >35 mm Hg. During follow-up (median [IQR] 3.4 [1.7-6.5] years), 540 patients died. There were 135 cardiac deaths attributable to heart failure (47%), coronary artery disease (41%), valve disease (4%), arrhythmia (4%), and others (5%). Compared to a negative output, all-cause mortality was higher in patients with a positive (HR 2.9 [2.4-3.5]) or uncertain output (HR 1.8 [1.2-2.5]), and cardiac mortality (Figure) was also higher in patients with a positive (HR 7.7 [4.5-13.3]) or uncertain output (HR 3.4 [1.4-8.1]). Cardiac mortality differences according to AI model prediction remained after age adjustment (positive: HR 5.9 [3.3-10.4], p<0.001; uncertain: HR 2.8 [1.2-6.8], p=0.02). Conclusion: A novel AI model to detect HFpEF based on a single routinely acquired TTE videoclip also identifies those at increased risk of cardiac mortality.

BACKGROUND: Thrombosis is a major complication after cardiac surgery in children with congenital heart disease. The mechanisms underlying thrombosis development remain poorly understood. We aimed to identify novel circulating metabolites before cardiac surgery that are associated with thrombosis after surgery in children with congenital heart disease. METHODS: In this prospective cohort study, all blood samples were drawn right before surgical incision and after the induction of anesthesia, and plasma was separated immediately under 4 °C. Untargeted metabolomic data were measured by Metabolon in plasma from children (age range, 0 days–18 years) with congenital heart disease undergoing cardiac surgery. The primary outcome was thrombosis within 30 days of surgery or before discharge. Associations of individual metabolites with thrombosis were assessed with logistic regression with false discovery rate correction for multiple comparison and adjustment for clinical characteristics; elastic net regression was used to select a prediction model. RESULTS: Out of 1115 metabolites measured in samples from 203 children, 776 met the quality control criteria. In total, 25 children (12.3%) developed thrombosis. Among the 776 metabolites, 175 were significantly associated with thrombosis (false discovery rate Q <0.05). The top 3 metabolites showing the strongest associations with thrombosis were eicosapentaenoate, stearidonate, and andro steroid monosulfate C 19 H 28 O 6 S (false discovery rate, 0.01 for all). Pathway analysis showed that the pathways of nicotinate and nicotinamide metabolism and glycerophospholipid metabolism were enriched (false discovery rate, 0.003 for both) and had significant impact on the development of thrombosis. In elastic net regression analysis, the area under the receiver operating-characteristic curve of a prediction model for thrombosis was 0.969 in the training sample (70% of the total sample) and 0.833 in the testing sample (the remaining 30%). CONCLUSIONS: We have identified promising novel metabolites and metabolic pathways associated with thrombosis. Future studies are warranted to confirm these findings and examine the mechanistic pathways to thrombosis.

Background: The bicuspid aortic valve (BAV) exhibits abnormal geometry and transvalvular flow and is susceptible to calcification with subsequent cardioembolic stroke from calcific embolic material. However, the description of embolic ischemic strokes in patients with BAV is limited to case reports. Methods: Consecutive patients from 1975-2015 with BAV (n=5401) at our institution were retrospectively identified. Patients with ischemic stroke before aortic valve replacement (AVR) were analyzed, and the stroke was characterized. Patients were grouped according to stroke etiology: calcific embolism from a BAV (BAV stroke); large artery atherosclerotic or lacunar stroke (LA stroke); and non-BAV, non-large artery embolic stroke (nLA stroke). Results: There were 83/5401 (1.5%) patients with ischemic stroke. Mean age was 54 ± 12 years and 28% were female. Stroke etiology was BAV stroke in 26/83 (31%), LA stroke in 23/83 (28%), nLA stroke in 30/83 (36%), and other in 4/83 (5%). Stroke was embolic in 72/83 (87%), as shown in Figure 1. CHA 2 DS 2 -VASc score was not different in patients with BAV stroke (1.4 ± 1.2) versus nLA stroke (1.8 ± 1.2, p=0.188) but was higher in LA stroke (2.3 ± 1.2, p=0.005 vs. BAV stroke). Recurrent stroke occurred in 41% overall (50% BAV stroke vs. 30% LA stroke vs. 47% nLA stroke, both p=NS vs. BAV stroke). BAV stroke was more commonly located in the retinal circulation (39% BAV stroke vs. 13% LA stroke [p=0.044] vs. 0% nLA stroke [p=0.002]). Patients with BAV and LA stroke were more likely to have moderate-to-severe aortic stenosis and undergo AVR sooner after stroke compared to patients with nLA stroke. Conclusions: Stroke is an important complication in patients with BAV. The most common type of stroke in BAV is embolic. Greater than one-third of embolic stroke resulted from embolism from a calcific aortic valve. Patients with BAV stroke commonly have a history of recurrent cerebral ischemic events, severe valvular disease, and proceed to AVR soon after stroke.