Citations

Living liver donation is a critical component for addressing organ shortage and improving outcomes for patients with end-stage liver disease. As the prevalence of living donor liver transplantation (LDLT) increases worldwide, understanding and optimizing long-term donor health is paramount. The 2025 International Liver Transplantation Society and International Living Donor Liver Transplantation Society (ILTS-iLDLT) Consensus Conference convened experts in the field of liver transplantation to establish evidence-based guidelines focused on the long-term medical, psychological, and social considerations following living liver donation. The aim of this working group was to integrate current evidence and expert consensus on donor follow-up protocols, risk assessment, and management strategies to promote long-term donor health, quality of life, and living liver donor programs globally to safeguard the welfare of this unique population.

ABSTRACT Real time, chronic electrochemical detection of neurotransmitters will provide a positive step in the treatment and understanding of neurological disease. However, current electrodes using carbon fibers (CF) fail to perform chronically. While diamond‐based coatings show promise in improving their longevity, achieving a uniform layer of such coatings on CFs is challenging, and the electrodes often lose sensitivity after coating. In this work, a complete and uniform boron‐doped nanocrystalline material grown in a diamond reactor (B‐NCD) was developed to coat CF microelectrodes for neurochemical sensing. The coating was characterized electrically, optically, mechanically, and chemically. The B‐NCD coated CF electrodes were able to detect phasic dopamine at a sensitivity comparable to the most widely used alternatives (uncoated and PEDOT:Nafion coated CFs). During biofouling testing, the B‐NCD coated CF electrodes demonstrated better stability than uncoated CFs and comparable performance to PEDOT:Nafion coated CFs. Moreover, B‐NCD exhibited no signs of degradation during consecutive FSCV applications, while uncoated and PEDOT:Nafion coated CF electrodes degraded significantly over time. Furthermore, the B‐NCD coating supported the survival and development of neurons and astrocytes in vitro, exhibited excellent adhesion and durability during mechanical bending testing, and enabled successful in vivo recording of phasic dopamine release in the rat brain. Overall, B‐NCD coated CFs present as an ideal candidate for chronic, flexible neural implantable electrodes for long‐term neurochemical monitoring.

PURPOSE To compare patient-reported and clinical outcomes between radical cystectomy (RC) and bladder-sparing therapy (BST) in patients with recurrent high-grade non–muscle-invasive bladder cancer (NMIBC). PATIENTS AND METHODS This pragmatic, prospective observational cohort study was designed with patients, who selected and prioritized outcomes. Eligible adults were candidates for both RC or BST, had previous induction Bacillus Calmette-Guérin (BCG), and received their last treatment within 12 months. The primary outcome was the EORTC-QLQ-C30 physical function scale at 12 months. Secondary outcomes included other EORTC-QLQ-C30 scales, depression, anxiety, bladder cancer–specific quality of life (QOL), financial burden, and cancer-specific outcomes. Targeted maximum likelihood estimation (TMLE) was used to calculate average treatment effect (ATE) estimates between arms. Inverse probability weighted risk ratios (wRR) were calculated using quasi-Poisson regression. RESULTS Of 570 participants (mean age 71.4 years; 21% female), 371 selected BST and 199 selected RC. Physical function was significantly worse in the RC arm at 3 months; by 9 months, there was no difference between arms, and at 12 months, physical function did not differ (ATE, 0.9; 95% CI, –0.6 to 2.4; P = .22). RC was associated with better emotional function, generic health-related QOL, and financial burden, and lower depression and anxiety, while BST was associated with better bowel and sexual health. Cancer-specific survival was 99% for BST versus 96% for RC (wRR, 0.99; 95% CI, 0.97 to 1.01). RC was associated with a higher risk of adverse events and serious adverse events, including a 90-day mortality rate of 2.5%. CONCLUSION Most patient-prioritized outcomes were similar or better among participants who chose RC compared with BST. These findings support the continued role of RC in managing recurrent high-grade NMIBC.

ABSTRACT A major challenge in hematopoietic progenitor cell apheresis is determining the whole blood (WB) volume to process to achieve a CD34+ cell collection goal. We developed a web‐based calculator app that uses the Collection Efficiency 2 (CE2) model to estimate personalized WB processing volumes needed to reach a prescribed CD34+ cell collection goal. Retrospective evaluation of the app using collection data from two academic medical centers showed that actual processed WB volumes were frequently higher than the app's recommendations. The frequency of potential under‐collection events is predicted to be low had the app‐calculated volumes been utilized. Our findings suggest that using the app's recommendations may lower total WB processing volumes, reducing over‐collection and time spent on the apheresis machine, while maintaining a low under‐collection risk profile.

Background Cardiovascular disease (CVD) is a leading cause of death in cancer survivors. Predicting CVD risk in this population remains challenging. Risk prediction models that use machine learning algorithms could provide an objective method for accurate risk prediction to facilitate the prevention and management of CVD in cancer survivors. We evaluated previously tested machine learning algorithms and logistic regression (regularized by machine learning methods), in addition to testing and validating newer, more complex machine learning algorithms, for CVD prediction in cancer survivors. Methods This multicenter study used a database of 3835 multiracial cancer survivors with 89 clinical, laboratory, and echocardiographic features over 20 years. Models were trained using repeated random and time‐split samples and tested on a separate cohort of 329 patients. Model performance was assessed using the area under the receiver operating characteristic curve. Results Regularized logistic regression achieved an area under the receiver operating characteristic curve of 0.845 (heart failure), 0.783 (atrial fibrillation), 0.792 (coronary artery disease), and 0.806 (composite CVD). These are comparable to 0.837 and 0.848 for heart failure, using Bayesian additive regression tree and random forest as more advanced machine learning models, respectively. De novo composite CVD (post‐cancer diagnosis) was also predicted with an area under the receiver operating characteristic curve of 0.826 using regularized logistic regression, compared with 0.735 and 0.802 using decision tree and random forest, respectively. Conclusions Regularized logistic regression and advanced machine learning models demonstrated similar predictive performance, with institutional transferability. These tools may support risk stratification and prevention strategies in cardio‐oncology using longitudinal data. Registration URL: https://www.clinicaltrials.gov ; Unique identifier: NCT05377320.

Advances in cancer therapies have transformed many malignancies into chronic or manageable conditions, but have been linked to adverse, including cardiovascular, events. Vascular toxicities associated with cancer treatment range from abnormal vasoreactivity to accelerated atherosclerosis, arterial thrombotic events, vasculitis, and arterial aneurysms or dissections. 5-fluorouracil and VEGF (vascular endothelial growth factor) inhibitors are the agents most commonly linked to abnormal vasoreactivity, whereas BCR-ABL (breakpoint cluster region–Abelson murine leukemia viral oncogene homolog) inhibitors and immune checkpoint inhibitors have been associated with accelerated atherosclerosis. Arterial thrombotic events are seen with VEGF and BCR-ABL inhibitors as well as platinum drugs. Vasculitis emerged with the use of immune checkpoint inhibitors, and arterial aneurysms and dissections with VEGF inhibitors. Radiation therapy can lead to several of the outlined vascular toxicities. This review comprehensively explores the mechanisms of vascular complications associated with chemotherapy, targeted therapies, immunotherapies, and radiation therapy. Key contributors include endothelial injury and dysfunction, oxidative stress, and inflammation. An understanding of the mechanisms of vascular toxicities may facilitate optimal treatment and preventive strategies in patients with cancer.

Background: Accurate characterization of tumor stiffness and adhesion is crucial when surgically resecting meningiomas. Currently, such determinations are difficult to ascertain through standard preoperative imaging diagnostics and clinical experience. Herein, we explored magnetic resonance elastography (MRE) as a means of assessing these parameters and thereby improving neurosurgical resections. Methods: This prospective study of 193 patients with meningiomas involved three distinct patient subsets (cohort 1, 88 [2017–2021]; cohort 2, 55 [2022–2023]; cohort 3, 50 [2023–2024]. We analyzed preoperatively obtained MRE data on meningioma stiffness (cohorts 1 and 2) and adhesion (cohort 2) for accuracy, while matching subjects with or without MRE studies (cohort 3, 1:1 ratio) to define the role of preoperative MRE in improving operative outcomes. Results: Areas under the curve (AUCs) for MRE in gauging meningioma stiffness and adhesion were 0.87 and 0.89, respectively. Both parameters significantly surpassed empiric predictions of stiffness and adhesion rendered by surgeons and radiologists, based on routine magnetic resonance imaging (MRI). MRE-determined stiffness measures independently correlated with prolonged resection duration, whereas MRE-assessed adhesion showed independent associations with increased blood loss, longer duration of tumor resection, and higher risk of pial injury. Ultimately, results based on cohort 3 demonstrated that MRE has great potential in this setting to improve neurosurgical procedures by significantly reducing intraoperative bleeding, resection duration, and risks of pial injury. Conclusion: MRE is a promising, noninvasive tool for accurately assessing meningioma stiffness and adhesion, standing to improve the precision and safety of needed surgical intervention.

Abstract This study delineates a novel multisystem caliber-persistent arteriopathy syndrome, fundamentally redefining the classical Dieulafoy's lesion from a localized gastrointestinal anomaly to a systemic congenital vasculopathy. Through integrated histopathological and genomic analysis of a forensic autopsy case, we identified pervasive arterial remodeling across seven organ systems— characterized by absent physiological tapering— indicating developmental angiogenic dysregulation. Whole-genome sequencing uncovered pathogenic variants in PDE8B , LRCH1 , and ADA genes, with functional enrichment analyses implicating dysregulated purine–cAMP signaling and cytoskeletal organization as core pathogenic mechanisms. These findings establish a genetic basis for the observed pan-vascular phenotype and highlight the necessity of systematic vascular screening in cases of unexplained multiorgan hemorrhage. This work provides a foundational framework for diagnosing and investigating congenital vascular malformations with hemorrhagic risk, urging a paradigm shift in clinical evaluation and etiological assessment.

BACKGROUND: Guidelines recommend 3-hour cardiac amyloid radionuclide imaging (CARI) for transthyretin amyloid cardiomyopathy. Citing rapid blood clearance of 99m Tc-hydroxymethylene-diphosphonate (HMDP) and efficient laboratory throughput, 1-hour imaging is increasingly practiced despite limited supporting evidence. We sought to compare diagnostic performance and interpreter experience of 1-hour versus 3-hour HMDP-CARI. METHODS: Consecutive patients with suspected transthyretin amyloid cardiomyopathy (n=114) underwent both 1-hour and 3-hour HMDP single photon emission computed tomography (CT)/CT. Two cardiologist-radiologist reader teams, blinded to imaging timepoint (1 versus 3 hours), assessed overall interpretation, single photon emission CT–based Perugini grade, interpretation difficulty, interpreter confidence, and need for CT-fused images for anatomic localization. Discordant, equivocal, and difficult cases were arbitrated by a third tie-breaking team. The myocardial-to-blood-pool radiotracer uptake ratio (3-dimensional Score) was measured as a surrogate of contrast resolution. RESULTS: Interinterpreter agreement was high at both time points (κ≥0.81), with more cases requiring arbitration at 3 hours versus 1 hour (22% versus 13%; P =0.049). Overall interpretation and Perugini grades were concordant between time points in 111/114 (97%) and 106/114 (93%) patients, respectively. Three patients (3%) were negative at 1 hour but equivocal at 3 hours, all of which were clinically ruled out for transthyretin amyloid cardiomyopathy. Interpreter confidence was comparable at both timepoints (97% versus 95%; P =0.317). Compared with 3-hour imaging, contrast resolution was inferior (lower 3-dimensional score, P <0.001) and CT fusion was more frequently needed (57% versus 31%, P <0.001) at 1-hour imaging. CONCLUSIONS: In a prospective, blinded comparison of 1-hour versus 3-hour HMDP-CARI, diagnostic performance and interpreter experience were similar, with readers requesting CT fusion more frequently at 1 hour to optimize myocardial-to-blood pool discrimination.

Abstract Background Despite advances in the diagnosis and treatment of immune thrombotic thrombocytopenic purpura (iTTP), recent mortality estimates remain around 5–10%. Predicting iTTP mortality risk has been of interest, as it may help individualize treatment or potentially guide the use of more intensive or novel therapies based on disease severity. However, prior attempts at mortality prediction have yielded inconsistent results, and no individual variable has demonstrated independent or reliable predictive ability. In a previous analysis utilizing the USTMA iTTP registry, which included 419 patients from 15 TTP referral centers, we reported that mortality due to immune TTP was unpredictable (Blood. 2021;138[Suppl 1]:1047). Neither the French Thrombotic Microangiopathy (TMA) Reference Score (previously validated in the French TMA Registry), nor a previous logistic regression model attempt (developed by USTMA investigators in 2021) demonstrated sufficient accuracy in predicting iTTP mortality in the USTMA dataset (AUC = 0.63 and 0.69, respectively). We subsequently utilized gradient boosted machine, a machine learning approach capable of handling multiple continuous variables and the complex interactions between them in large datasets, and developed a novel prediction tool: the USTMA Mortality Index (Res Pract Thromb Haemost. 2024; 8(3):102388). It demonstrated good performance in predicting iTTP mortality (AUC = 0.77) in repeated 10-fold cross-validation. However, it has not yet undergone external validation. Objectives To externally validate the USTMA Mortality Index to predict mortality due to acute iTTP in a multicenter cohort. Methods We performed an external validation using an independent cohort of iTTP patients from 5 institutions: University of Utah, Case Western Reserve University, Rochester Regional Health, University of Illinois, and Mayo Clinic. Patients in the validation cohort were not part of the development cohort (the USTMA registry). We included patients with confirmed iTTP and defined acute iTTP mortality as death within 30 days of admission. USTMA Mortality Index variables were collected at initial presentation, which included (in order of highest to lowest relative influence): lactate dehydrogenase, serum creatinine, age, hemoglobin, platelet count, presence of stupor/coma, fever. The model's prediction accuracy was assessed using area under the receiver operating characteristic curve (AUC). We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) based on the previously defined cut-offs of 4.27% and 9.08% mortality risk in the original model, which categorized patients into standard risk, high risk, and very high risk of predicted mortality. Results The external validation cohort included 103 patients with confirmed iTTP and 11 deaths (10.7% mortality rate). The USTMA Mortality Index demonstrated poor performance with AUC of 0.69 (95% CI, 0.55–0.83) in the validation cohort. The wide confidence interval reflects substantial uncertainty in model performance, ranging from poor to excellent, and is likely due to the small number of deaths. At a risk threshold ≥4.27%:Sensitivity = 64%Specificity = 70%PPV = 20%NPV = 94% At a risk threshold ≥9.08%:Sensitivity = 18%Specificity = 87%PPV = 14%NPV = 90% Conclusion The USTMA Mortality Index demonstrated poor performance in the external validation cohort (AUC = 0.69, 95% CI, 0.55–0.83), contrasting with its previously favorable performance in repeated 10-fold cross-validation. This discrepancy likely reflects model overfitting, a known challenge in AI-based clinical modeling. Our study is limited by the small number of deaths, resulting in a wide confidence interval ranging from poor to excellent performance. Given that neither the French TMA Reference Score, nor our group's prior logistic regression model (2021), nor the USTMA Mortality Index (2024) could reliably predict mortality upon external validation in our cohorts, these findings collectively suggest that mortality in acute iTTP remains difficult to predict at this time, regardless of statistical methodology or current machine learning capabilities. Clinical decision-making, including the use of therapies such as caplacizumab, should not be guided solely by mortality risk predictions. Instead, efforts to reduce mortality and improve outcomes should prioritize individualized clinical assessment over model-based stratification at this time.