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Although pelvic landmarks have traditionally been used to estimate the femoral head center (FC), their reliability may be limited in patients with developmental dysplasia of the hip (DDH). In contrast, femoral-based reference methods have been insufficiently investigated. This study aimed to evaluate the feasibility and clinical utility of estimating the FC location in DDH using a three-dimensional model derived from trochanteric landmarks. We retrospectively analyzed 128 femurs from 84 female patients with DDH (mean age, 36.9 years) who underwent curved periacetabular osteotomy (CPO) from April 1, 2010, to September 30, 2020, and had no symptoms involving the spine or knee. The FC was estimated using multiple regression models based on the three-dimensional coordinates (x, y, and z) of the greater and lesser trochanter tips. Differences between the estimated and actual FC positions were assessed along all three axes. Correlation coefficients between the estimated and actual FC ranged from 0.725 to 0.875 across the three directions. The mean absolute error was 2-3 mm, with greater errors observed in the anteroposterior direction than in the craniocaudal direction. An estimation error within 3 mm may be considered relatively small in the context of clinically acceptable ranges reported in previous studies for restoring femoral offset and leg length during total hip arthroplasty (THA), supporting the practical applicability of this method in preoperative planning. The accuracy of the present approach was comparable to that reported in healthy populations and exceeded that of previous pelvic landmark-based regression techniques. This trochanter-based three-dimensional method enables clinically acceptable estimation of the FC in patients with DDH and may serve as a useful adjunct for planning of the femoral component when the native FC is difficult to identify.

Accurate kidney ultrasound segmentation is fundamental for clinical measurement and computer-aided diagnosis. However, domain shifts across devices and centers-manifested as differences in grayscale intensity, contrast, and speckle texture statistics-can substantially degrade model generalization, while acquiring new pixel-level annotations is costly. To address this, we propose a statistical spectral-similarity-guided ultrasound-to-ultrasound translation method to improve kidney segmentation performance without target-domain annotations. Motivated by frequency-domain analysis of renal ultrasound data, we observe that mid-to-low frequency components, which encode global organ structure, exhibit high consistency across domains, whereas mid-to-high frequency components, dominated by device-dependent speckle and texture statistics, vary substantially. Based on dataset-level frequency statistics, our method automatically identifies spectrally similar frequency bands shared by the source and target domains and derives structural guidance from them. This guidance is injected as a soft condition throughout a diffusion-based image generation process, enabling translation to target-device appearance while preserving anatomical structure. The translated images, paired with source-domain labels, are then used to train a segmentation network without requiring any target-domain annotations. Experiments on two public renal ultrasound datasets (OKUS and UNK) and an in-house multi-center dataset demonstrate superior structural preservation in image translation and consistently improved downstream segmentation performance, with particularly large reductions in boundary error. In the challenging OKUS to UNK adaptation scenario, our method boosts the mean Dice score by up to 20.52% (from 56.05% to 76.57%) and drastically reduces the 95% Hausdorff Distance (HD95) boundary error by 71.96 mm compared to the direct transfer baseline. Furthermore, consistent performance gains are achieved across the in-house multi-center dataset. These results indicate that the proposed spectral-similarity-based guidance effectively handles ultrasound domain shifts, substantially improving robustness and generalization for kidney segmentation under zero-shot and cross-center settings.

Regional diversity may influence the composition of human milk fat globule membrane (HMFGM) protein composition and protein glycosylation. Here, we first systematically evaluated the efficiency and stability of six methods for the extraction of HMFGM proteins from breast milk. The optimal method (methanol-chloroform precipitation of MFGM proteins, followed by solubilization in 0.4% SDS lysis buffer) was further applied to the proteome and N-glycoproteome analysis of 49 breast milk samples from five regions across China. Proteomic analysis revealed the geographically divergent expression of BST2, COCH, FUCA1 and FGFBP1 in MFGM. The parallel N-glycoproteomic profiling identified 4914 site-specific N-glycans mapping to 689 glycoproteins, 699 glycosylation sites, and 420 glycan structures. This multiomics study reveals region-specific variations in the molecular composition of HMFGM proteins and their N-glycoprotein derivatives, elucidating the structural and functional dynamics of the human HMFGM in representative regions of China.

Formal theories translate verbal theories into a mathematical representation, such as a coupled differential equation or other dynamical systems, intending to strengthen the deductive power of (clinical) theories and to formulate testable and novel hypotheses. Work in clinical formal theories mainly relies on simulations, which is an intuitive method for evaluating overall model performance, but may fall short of establishing a precise link between the mathematical properties of the model and the dynamic properties of its outcome. Moreover, when the model's outcome contradicts clinical observations, it is unclear where the discrepancy lies and how to improve the model. In this article, we introduce formal mathematical techniques for graphical model analysis, including phase plane analysis, which allows identifying a system's stable and unstable equilibria, and bifurcation analysis, a framework to delineate parameter regimes corresponding to qualitatively different dynamical outcomes for a model. Using two formal dynamic models in psychology (one for panic disorder and one for suicidal ideation), we illustrate those methods through an easy-to-use R package, deBif, with a graphical user interface. These examples demonstrate the importance of using graphical tools to investigate the hypothesized mechanisms of psychological systems.

The International Prognostic Index (IPI) and IPI related prognostic indexes are widely used for risk-stratification in lymphoma. However, identifying poor prognostic group patients remains a significant objective. This study aimed to develop a predictive prognostic model for DLBCL treated with R-CHOP immunochemotherapy. A cohort comprising 167 individuals newly diagnosed with DLBCL between January 2016 and June 2021 at Jiangsu cancer hospital, Nanjing Medical University were enrolled for investigation. Univariate and multivariate Cox analysis were used for variable selection. The Akaike information criterion (AIC) guided the selection of factors for constructing the nomograms, along with a novel prognostic index for assessing both progression-free survival (PFS) and overall survival (OS). Internal validation was performed with the bootstrap method(B = 1000). Age, Lactate dehydrogenase (LDH), stage, extra-nodal sites and absolute CD4 + T cell counts (ACD4C) were associated with both PFS and OS. These discerned prognostic factors were subsequently employed in constructing nomograms for PFS and OS, respectively. The C-indexes of Internal validation performed with the Bootstrap method were 0.76 (PFS: 95%CI 0.67-0.80),0.81(OS:95%CI 0.72-0.85), respectively. The calibration plots, alongside internal bootstrap resampling, demonstrated commendable consistency between predictions and observations. For enhanced clinical applicability, we devised a novel immune prognostic index, categorizing DLBCL patients into four distinct risk groups: low, low-intermediate, high-intermediate, and high risk, corresponding to 0, 1-2, 3, 4-5 risk factors respectively. Kaplan-Meier analysis underscored the superior discriminatory capacity of the immune index in assessing the prognosis across various risk groups. The proposed immune index is a useful tool to predict the prognosis of DLBCL patients treated with R-CHOP immunochemotherapy in this study.

Intracavitary drug instillation is a crucial therapeutic strategy for treating bladder cancer. However, current methods are limited in efficacy due to insufficient tumour targeting and drug penetration across tissue barriers in pathophysiological conditions. Here we devise biohybrid magnetic algae microrobots with hierarchical nanoporous structure and develop an 'algebot'-mediated, non-contact convective transport strategy to synergistically integrate targeted carrier transport, selective drug release and ultrafast tissue penetration. Our approach leverages machine-intelligent image feedback for autonomous navigation, magnetite-endowed multimodal control for reconfigurable swarming and flow-tuned convective diffusion for on-demand therapeutic delivery. We exemplify this approach with doxorubicin-loaded magnetic Coscinodiscus granii evaluated in a murine model of bladder tumour, demonstrating an over tenfold increase in drug permeation and substantially reduced tumour burden to less than 3% compared with conventional intravesical instillation in a preclinical trial of 1-week therapy without inducing systemic toxicity. Our drug delivery system offers a non-invasive solution to overcome complex biological barriers, advancing the efficacy and safety of intracavitary chemotherapy.

Liver retraction is critical for safe and efficient robotic liver transection. Conventional methods often require additional instruments, tacking sutures or continuous bedside assistance. This "How I Do It" article presents our double rubber band technique, which enables stable, hands-free retraction during robotic liver transection. We provide a video demonstration of our standard retraction technique for hemihepatectomy and describe adaptations for complex resections.

This study describes the development and feasibility testing of a digital health guide (DHG) to streamline genetic education, reduce barriers, and promote informed genetic testing (GT) decisions among cancer survivors. This study reports on the DHG's development, usability testing, acceptability, feasibility, and preliminary efficacy in improving genetic counseling (GC) and GT access for cancer survivors. Guided by the Ottawa Decision Support Framework, the DHG prototype was developed following community engagement with cancer patients and at-risk relatives from diverse sociodemographically backgrounds. It was refined through user (content-focused) and usability (functionality-focused) testing. Pilot trial participants provided data through semi-structured interviews and usability assessments. Qualitative data were analyzed using the Framework Method. The preliminary impact of the DHG on GC and GT uptake, and informed decision-making, was assessed in a feasibility and accessibility trial. The Chatbot Usability Questionnaire score for the DHG was 70.3 (IQR = 12.5), indicating good acceptability. The DHG also facilitated GT uptake (73.3%) compared to enhanced usual care (EUC; 7.7%). Pretest GC was requested by 1 of 13 patients in the EUC arm, while no request (0 of 15 patients) was made in the DHG arm. Users' feedback led to clearer language, improved navigation, and stronger messaging regarding data security. DHG participants had lower decisional conflict (33.37 ± 21.09) and decision regret (17.5 ± 16.50) than those in the EUC arm (53.25 ± 22.66 and 37.08 ± 17.38, respectively). The digital intervention is feasible, acceptable, and a promising strategy for expanding GT access and promoting informed decision-making. Further testing in a definitive randomized controlled trial is warranted. Clinical trial registration. This study was preregistered at the NIH clinical trial registry ( https://clinicaltrials.gov/study/NCT06184867 ).

The popularity of domestic cats (Felis catus) as companion animals is undisputed. However, the human-feline proximity poses potential health risks due to zoonotic disease transmission as well as physical injuries from bites and scratches. It is alarming to note that epidemiological data supports the prevalence and colonisation of Staphylococcus spp., including methicillin resistant Staphylococcus aureus (MRSA) in the oral cavity of cats. Considering the problem of antibiotic resistance globally, this review collates recent findings on the role of cats as reservoirs of antibiotic resistant pathogenic Staphylococcus spp. and examines the clinical implications of staphylococcal infections in cats. It provides an in-depth study into the link between pathogenesis and antibiotic resistance. In the context of "one health" the pathogenesis mechanisms enabling persistence and virulence such as colonisation, invasion, toxin and enzyme production, and immune evasion are also discussed. A mechanistic overview of promotion of antibiotic resistance in bacteria is provided, focusing on genetic adaptations such as target modification, efflux pumps, and gene acquisition. Patterns of antimicrobial resistance (AMR) among cat-derived isolates are critically assessed, outlining emerging trends and their implications for therapeutic strategies. Zoonotic concerns, vis-a-vis the impact of resistant Staphylococcus spp. on human health are addressed. The threats posed by rising antibiotic resistance, such as compromised treatment outcomes and the heightened risk of transmission across species are reviewed and strategies for mitigation, including preventive methods, ongoing surveillance, and the adoption of alternative non-antibiotic measures such as probiotics, bacteriophage therapy, and antimicrobial peptides, are suggested herein.

The spread of generative artificial intelligence and large language model technologies, such as ChatGPT, has sparked interest in their applicability and potential role in reproductive health counseling. This qualitative study explored the perspectives of professional counselors providing pregnancy termination counseling in Germany on the integration of ChatGPT into their work. Between November 2024 and January 2025, 20 semi-structured interviews were conducted with counselors working at state-accredited counseling centers, using a case vignette design to explore the potentials, challenges, meanings, needs for support, and requirements involved in case evaluation while sparring with ChatGPT-4o Mini.Thematic analysis revealed four main themes. Participants expressed persistent skepticism, curiosity, and encouraging first experiences regarding the reliability, contextual appropriateness, ethical alignment, and legal accuracy of ChatGPT-generated content. Counselors emphasized that interpersonal relatedness is a crucial marker of quality and meaning of counseling, encompassing empathy, subjective competence, and situational sensitivity. Reflections on professional roles revealed that ChatGPT was perceived as a primarily supportive tool for non-relational tasks. ChatGPT's potential was described as significantly constrained by specific needs, fantasized relief, and working conditions marked by structural limitations and individual barriers to digital innovation, such as the centers' equipment, digital readiness, and privacy policies.We discuss the findings in relation to AI and technology acceptance models and the theory of professional practice, contributing to a refinement of the concept of conceptualized skepticism toward a more nuanced understanding that may be specific to counseling contexts. The findings underscore positions that argue counseling encompasses more than its methods, relying on in-betweens and subjectivities.

Introduction: A vast body of cognitive research in psychosis has focused on auditory hallucinations, though more recent studies are turning towards other sensory modalities. This study aimed to compare the cognitive profile of persons experiencing uni- or multisensory versus multimodal hallucinations. Methods: Participants with primary diagnosis of a psychotic disorder were subdivided into those experiencing uni- or multisensory (UMS; n = 31) versus multimodal (MM; n = 28) hallucinations relative to non-clinical controls (NC; n = 32). Cognitive assessment comprised the MATRICS Consensus Cognitive Battery, supplemented by a Colour Word Interference Test. Analyses of variance (ANOVAs) and correlation analyses were performed. Results: The UMS and MM groups performed significantly worse than the NC group on some cognitive domains (i.e. speed of processing, attention/vigilance, working memory, verbal learning), but not others (i.e. reasoning and problem-solving, social cognition). For visual learning, the MM group performed significantly worse than the NC group only, whereas for inhibition, the UMS group performed significantly worse than the NC group only. Conclusion: A novel cognitive profile associated with multimodal hallucinations was documented. Dissociation between performance of the two clinical groups on visual learning and inhibition suggests these cognitive domains may be of relevance to hallucinations, pending further investigations.

Superior orbital sulcus hollowness is a common aesthetic concern that may result from structural changes, trauma, or excessive fat removal during upper blepharoplasty, and it can be further exacerbated by age-related orbital remodeling. Traditional corrective approaches such as fat redistribution and autologous fat grafting carry limitations, including graft atrophy and the risk of embolic complications. This study evaluated the safety and outcomes of superior orbital sulcus correction using a medial-pedicled preseptal orbicularis oculi muscle flap. This retrospective study analyzed 481 patients who underwent upper blepharoplasty between January 2017 and June 2024, of whom 45 received additional correction of superior orbital sulcus hollowness with a medial-pedicled preseptal orbicularis oculi muscle flap. Exclusion criteria included male sex, previous upper eyelid surgery, levator dehiscence, less than six months of follow-up, and refusal to complete the FACE-Q Adverse Effects questionnaire. The mean follow-up duration was 8 months, and the mean patient age was 51.4 years. Postoperative complications and patient-reported outcomes were evaluated and compared with those of patients undergoing conventional upper blepharoplasty. Early postoperative complications, including transient lagophthalmos and edema, were self-limiting. In the conventional blepharoplasty group, 16 patients developed medial canthal scarring, with four requiring revision. In the flap group, transient supraorbital hypoesthesia occurred in 71% of patients and resolved within a few months, and no cases of flap necrosis were observed. Statistical analysis using the Mann-Whitney U test demonstrated no significant difference in FACE-Q scores between the two groups (U = 8828.0, p = 0.251). The medial-pedicled preseptal orbicularis oculi muscle flap appears to be a safe, reproducible, and anatomically sound technique for selected patients with superior orbital sulcus hollowness. Although the relatively uniform flap volume may not fully correct the deformity in all cases and patient numbers were limited, this method provides a promising alternative to fat grafting without adding long-term complications, with the potential to enhance aesthetic outcomes and patient satisfaction. Level of Evidence IV This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Fungal infections, especially in people with weakened immune systems, are a significant global health burden. Accurate identification of fungal morphology from microscopic images is a critical step in guiding timely antifungal treatment decisions. However, manual morphological assessment remains highly dependent on expert mycologists and is prone to inter-observer variability. In this study, we propose a hybrid deep learning framework that integrates the ConvNeXtV2-Base architecture with a Multi-Head Attention-based Multiple Instance Learning module for automated classification of microscopic fungal morphology images. The framework was evaluated on the open-access DeFungi dataset, consisting of 3696 microscopic images representing five clinically meaningful fungal morphology classes. In comparative experiments, classical vision transformer (ViT) models achieved 91.20% accuracy, while MIL-enhanced ViT models reached 93.99%. The proposed ConvNeXtV2-Base + MIL hybrid method outperformed all evaluated architectures, achieving 98.90% classification accuracy. These results establish a new benchmark for automated fungal morphology classification and highlight the potential of AI-assisted decision-support tools to aid expert mycologists in morphology-based assessment workflows.

PIWI-interacting RNAs (piRNAs) are an important class of non-coding RNA molecules in epigenetic regulation. It plays a crucial role in maintaining genomic stability and inhibiting transposable elements, and have been proven to participate in various diseases by regulating gene expression and influencing signaling pathways. Traditional biological experimental methods have limitations such as low throughput, long cycles, and high costs, making them difficult to meet the requirements of large-scale systematic screening. In this study, we develop a predictive framework named PiDA-DVLSA. We integrate autoencoder, dual graph transformer, and multi-head self-attention mechanisms, and construct an end-to-end multimodal deep learning system. We use autoencoder to perform nonlinear dimensionality reduction and denoising on piRNA sequence features and disease phenotype semantic features, and extract potential representations with strong discriminative ability. Then, we use graph transformers to model the high-order topological relationships between nodes in isomorphic similar graphs, and input heterogeneous graph transformers to learn complex cross-entity interaction patterns in heterogeneous networks. Finally, we achieve adaptive fusion of multi-source information through multi-head self-attention mechanisms. PiDA-DVLSA performs excellently on the benchmark dataset, with AUC and AUPR reach 0.9437 and 0.9195, respectively, significantly outperform eight mainstream algorithms. In independent case validations for breast cancer, clioblastoma, and Alzheimer disease, our model successfully predicts multiple biologically significant potential associations, further confirming its practicality and effectiveness in real scientific research scenarios and providing a solid computational basis for future precision diagnostic and therapeutic applications. PiDA-DVLSA is freely available at https://github.com/zhaoqi106/PiDA-DVLSA .

Accurate MRI-based quantification of abdominal adipose tissue is critical for metabolic risk assessment but is limited by labor-intensive manual segmentation and the extensive labeled-data dependency of deep learning models. We introduce Dynamic Fuzzy-Gaussian Modeling (DynFGM), a fully automated, unsupervised framework for adipose tissue segmentation designed to operate without requiring training data, expert annotations, or anatomical priors. DynFGM was developed and validated on 776 abdominal MRI scans, using a benchmark cohort (n = 20) with expert ground truth segmentations and a large validation cohort (n = 756). The pipeline dynamically adapts its complexity for each MRI slice by using image intensity kurtosis to select the optimal number of tissue clusters. A fuzzy C-means (FCM) algorithm then initializes a Gaussian mixture model (GMM) for segmentation, providing a mathematically interpretable alternative to black-box neural networks. Finally, a radial distance transform with an adaptive cutoff differentiates subcutaneous (SAT) from visceral adipose tissue (VAT). Performance was evaluated against the ground truth using dice similarity coefficient (DSC) and intraclass correlation coefficient (ICC). DynFGM achieved strong spatial agreement with expert annotations (mean DSC: 0.94) and high volumetric reliability (ICC: 0.82-0.97), comparable to reported inter-expert variability. The framework reduced mean absolute volumetric error by 92.6% compared to standard FCM (482.2 cm3 vs. 6547.5 cm3). On the large validation cohort (n = 756), the method demonstrated operational stability, producing physiologically plausible adipose distributions with a low technical failure rate (3.0%). Furthermore, the computational throughput averaged 13.6 s per participant on standard CPU (Intel® Core™ i9, 3.0 GHz) hardware. DynFGM provides an interpretable and data-efficient approach for abdominal adipose tissue phenotyping, offering an alternative to supervised deep learning in settings where labeled data are limited or unavailable. By bridging the gap between manual segmentation and labeled-data-dependent AI, this unsupervised framework offers a scalable tool for population-level research and may serve as an automated labeling tool to facilitate future model development.

We sought to evaluate oxidative changes in premature infants receiving 100% oxygen compared with 30% during deferred cord clamping (DCC). Premature infants born at 220/7 to 286/7 weeks received DCC in conjunction with either 30% (LO Group) or 100% (HI Group) oxygen. Blood was extracted from a preserved umbilical segment and a postnatal sample was collected from umbilical vascular lines within two hours of birth. Reduced-to-oxidized glutathione (GSH/GSSG) ratios were analyzed using liquid chromatography coupled to tandem mass spectrometry. Sixty-eight infants had data available for analysis. The median (IQR) gestational age of infants was 264/7 (246/7, 282/7) weeks in both groups. Among infants receiving 100% versus 30% oxygen, median (IQR) GSH/GSSG ratio were not statistically different in arterial cord blood [7.5 (0.6, 290) vs 37 (1.1, 265), p = 0.52] or venous cord blood [8.4 (2,50) vs 76 (5, 210), p = 0.12] or postnatal samples [14 (2, 290) vs 8 (2, 280), p = 0.98)]. Briefly providing 30% vs. 100% oxygen for 90 seconds during DCC showed no significant difference in GSH/GSSG ratios, but redox effects remain unclear given variability, sample size and limited power. Further studies are needed to ascertain potential oxidative damage during neonatal resuscitation and deferred cord clamping. THIS TRIAL IS REGISTERED ON CLINICALTRIALS. NCT04413097 IMPACT: The effect of oxygen administration during deferred cord clamping on redox status is unclear due to large variability in GSH and GSSG values and small sample size. These data provide some insights about umbilical arterial and venous oxygen levels and the effect of placenta on GSH/GSSG in preterm infants. Further basic and clinical studies are needed to better ascertain the potential for oxidative damage during neonatal resuscitation and deferred cord clamping.

Accurate acetabular cup placement is essential in total hip arthroplasty (THA). We hypothesized that the newly introduced Computed Tomography (CT)-based portable navigation system would demonstrate accuracy comparable to that of the imageless portable navigation system. The aim of this study was to compare cup placement accuracy between the CT-based and imageless portable navigation systems of the same platform in THA performed in the lateral decubitus position. This retrospective cross-sectional study included 36 patients who underwent primary THA via a direct lateral approach in the lateral decubitus position. In all cases, both imageless and CT-based portable navigation systems were used concurrently. Postoperative cup alignment was evaluated using three-dimensional CT (3D-CT). The primary outcome was the absolute error in cup inclination and anteversion, defined as the difference between intraoperative navigation values and postoperative 3D-CT measurements in the functional. Secondary outcomes included outlier rates and registration success rates. No statistically significant differences were observed between the imageless and CT-based portable navigation systems in the mean absolute error for inclination (2.2 ± 1.8° vs. 2.3 ± 1.8°, p = 0.93) or anteversion (2.3 ± 2.3° vs. 2.6 ± 2.5°, p = 0.41). There were no significant differences in outlier proportions. The registration success rate was 92% (36/39) due to three technical failures. In this preliminary study, the CT-based portable navigation system demonstrated cup placement accuracy comparable to that of the imageless portable navigation system. Although the CT-based system may provide additional spatial information intraoperatively, its impact on clinical outcomes remains unclear and requires further longitudinal investigation.

Deep Brain Stimulation (DBS) is an established treatment for advanced Parkinson's disease (PD), yet registry-based data from developing countries remain limited. This study reports the establishment and feasibility of the Iranian Deep Brain Stimulation Registry for Parkinson's Disease (IDBSR-PD). We conducted a single-center feasibility study at the Research Center for Neuromodulation and Pain, including all PD patients undergoing DBS implantation since 2014. Primary feasibility outcomes included patient enrollment coverage, follow-up adherence, data completeness, multidisciplinary implementation, and the sustainability of technical infrastructure. Secondary outcomes included descriptive patient characteristics. Only descriptive statistics were performed; no hypothesis testing or longitudinal outcome analyses were conducted. A total of 208 patients were enrolled (65.4% male; mean age 58.4 ± 10.2 years). Enrollment increased progressively over time, peaking in 2024 (n = 41). Patients were referred from multiple provinces across Iran. Data validation mechanisms and regular surveillance ensured acceptable data completeness. The IDBSR-PD demonstrates the feasibility and sustainability of a web-based DBS registry in a developing country. These findings confirm the viability of structured data collection and provide a foundation for future multicenter and longitudinal outcome research.

Endothelial activation and stress index (EASIX) is a biomarker of endothelial dysfunction and has been validated previously as a prognostic score for mortality in various diseases, including oncologic diseases, sepsis, and cardiac disease. Since endothelial dysfunction is an established mediator of adverse outcomes in acute ischemic stroke, this study investigates the prognostic value of EASIX for risk of mortality in these patients. We analyzed data from the Heidelberg (n&#x2009;=&#x2009;4,188) and Vienna (n&#x2009;=&#x2009;2,273) prospective acute ischemic stroke registries. EASIX was calculated as creatinine [mg/dL]&#x2009;&#xd7;&#x2009;LDH [U/L] / platelet count [109/L]. An EASIX cut-off was established using maximal Youden index. Validation was performed using Brier score and C-statistics. Higher EASIX was associated with higher risk of mortality in the training cohort in a multivariable Cox regression (HR of all-cause mortality per log2 increase: 1.20 (95% CI 1.12-1.28), p&#x2009;<&#x2009;0.001). An optimal EASIX cut-off value of 1.211 was identified in the derivation cohort. In the independent validation cohort, this cut-off was associated with risk of 3-month mortality in a multivariable binary logistic regression model (OR 1.86 (1.28-2.70), p&#x2009;<&#x2009;0.01). Brier score and C-statistics validated the superior predictive performance of EASIX in the multivariable model. EASIX predicts mortality in acute ischemic stroke patients and retained prognostic validity across two heterogeneous European cohorts. Incorporation of EASIX improved risk stratification beyond established clinical scores. EASIX may serve as a useful tool for risk stratification and outcome prediction in acute ischemic stroke patients.