Citations

Background. Metabolic dysfunction–associated steatotic liver disease (MASLD) is increasingly recognized as a significant indication for liver transplantation (LT) in North America. Yet data on its impact in other countries, such as Spain, remain limited. This study aimed to evaluate the prevalence and trajectory of MASLD-related LT in Spain and compare these findings with broader national data and international data sets. Methods. Multicenter retrospective cohort study including adults (18 y and older) undergoing LT for MASLD between 2010 and 2023 in 5 large Spanish centers. Additional data were obtained from the Spanish Transplant Registry (Organización Nacional de Trasplantes) and high-prevalence LT centers in the United States (n = 7) and Canada (n = 1). Results. Among 3448 LTs performed in the 5 Spanish centers, 3.4% (n = 117) were MASLD-related. An increasing trajectory of MASLD-related LT was observed, with predictions suggesting a rise to 5.4%–10.8% of LTs for MASLD by 2028. These trends were consistent with Organización Nacional de Trasplantes data. Compared with North American data, the growth trajectory in Spain showed a less steep increase. Hepatocellular carcinoma rates were higher in the Spanish MASLD-LT recipients, yet metabolic comorbidities were frequent in all populations. Conclusions. The burden of MASLD-related LT in Spain is growing, yet at a less pronounced rate than in the United States/Canada. Whether this slower increase will persist or decline in the future as newer antiobesity and MASLD-related drugs are increasingly used is still unknown. In the meantime, our results highlight the need for tailored approaches to management and prevention in the Spanish population and underscore the importance of continued monitoring and research into the evolving impact of MASLD on LT in Spain and beyond.

Abstract Purpose: Mouse models demonstrate a role for RANK and its ligand, RANKL, in osteosarcoma. The primary objective of this single-arm, open-label phase 2 trial was to determine whether denosumab, a RANKL mAb, improved disease control in recurrent osteosarcoma relative to benchmarks derived from historic Children’s Oncology Group clinical trial data. Patients and Methods: Skeletally mature patients ages 11 to 49 years old with measurable disease were eligible for cohort 1, and those with complete surgical resection of all sites of disease were eligible for cohort 2. Patients received denosumab 120 mg subcutaneously every 4 weeks with calcium and vitamin D supplementation. The primary endpoints were RECIST response and remaining event-free for 4 months for cohort 1 and remaining event-free for 12 months for cohort 2. Toxicity, pharmacokinetics, and pharmacodynamic effects were additional endpoints. Results: Fifteen patients in cohort 1 and 38 in cohort 2 were eligible and evaluable for the primary endpoint. One of 15 cohort 1 patients remained event-free at 4 months. There were no objective responses. Ten of 38 cohort 2 patients were event-free at 12 months. The predefined efficacy criteria were not met in either cohort. The most common ≥ grade 3 adverse events were hypocalcemia and hypophosphatemia (8% and 11%, respectively). At steady state, mean serum denosumab trough concentrations were 23.7 to 31 μg/mL in cycles 2 to 7. Serum c-telopeptide and urine n-telopeptide decreased on treatment. Conclusions: Denosumab was well-tolerated with anticipated side effects and pharmacokinetic and pharmacodynamic parameters but had insufficient activity for further development in osteosarcoma.

Background To evaluate the short-term clinical performance of Symvess (acellular tissue engineered vessel-tyod), formerly known as human acellular vessel, or HAV, compared with autologous vein for the treatment of extremity arterial injury. Methods Subjects treated with acellular tissue engineered vessel (ATEV) from two clinical trials were propensity score-matched on a 1:2 basis to PROspective Observational Vascular Injury Trial (PROOVIT) registry subjects with the same injured artery and treated with autologous vein. Matching characteristics included age, sex, trauma type (penetrating vs blunt), injury severity score, mangled extremity severity score, concomitant fracture, shunt use, and ischemia duration>6 hours. Incidence of outcomes (primary/secondary patency, amputation, conduit infection, reintervention for thrombosis/stenosis, pseudoaneurysm, and death) was assessed by a generalized linear model. Outcomes were assessed at Day 30 (ATEV group) or during initial hospitalization (autologous group). Results ATEV subjects lacking suitable autologous vein (n=67) and PROOVIT subjects treated with autologous vein (n=134) suffered injuries to axillary, brachial, femoral, popliteal, and posterior tibial arteries. Subgroups were clinically similar; Injury Severity Score, Mangled Extremity Severity Score, and duration of follow-up (16 vs 30 days) were higher for the ATEV subgroup. Primary patency for the ATEV versus autologous group was 86.6% versus 91.8%, secondary patency: 91.0% versus 97.7%; amputation: 7.5% versus 8.2%; conduit infection: 1.5% versus 0%; reintervention for thrombosis or stenosis: 6.0% versus 8.2%; and death 4.5% versus 4.5%, respectively. No cases of pseudoaneurysm, true aneurysm, or significant differences between the ATEV and autologous groups for any outcome were observed. Conclusions Short-term outcomes were similar between ATEV subjects without feasible autologous vein, and propensity score-matched autologous vein recipients from the PROOVIT registry. The ATEV may provide effective and safe revascularization in subjects with extremity arterial injury without feasible autologous vein. Level of evidence Level 3, Therapeutic/Care Management

ABSTRACT The American Society for Apheresis (ASFA) Attending Physician Subcommittee of the Physicians' Committee performed an annual review of articles published in 2024 related to apheresis medicine. The 10 seminal apheresis articles selected by the subcommittee members are summarized in this review. PubMed was used to identify manuscripts published in 2024 in four areas of interest: donor apheresis, therapeutic apheresis, apheresis education, and apheresis for cellular therapy. Only full length, peer‐reviewed manuscripts in English with data from human subjects were included. Case reports, review articles, and meta‐analyses were excluded. Articles were considered seminal if they met at least one of the following previously established criteria: novel finding(s), practice‐altering outcomes, international in scope, randomized‐controlled trial, relevant to current clinical practice, and/or provide evidence for category III or IV indications based on the ASFA 9th special issue of the Guidelines on the Use of Therapeutic Apheresis in Clinical Practice‐Evidence‐Based Approach.

Abstract INTRODUCTION The Genetic Frontotemporal Initiative (GENFI) and Advancing Research and Treatment in Frontotemporal Lobar Degeneration (ARTFL)‐Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS) Longitudinal Frontotemporal Lobar Degeneration Study (ALLFTD) consortia developed Clinical Dementia Rating (CDR)‐derived scales with a motor domain to overcome systematic underestimation of disease severity by the CDR. We calculated disease severity scores using these scales in a mixed neurodegenerative cohort and correlated them with objective motor measures. METHODS The CDR plus National Alzheimer's Coordinating Center (NACC) Frontotemporal Lobar Degeneration (FTLD), CDR + NACC FTLD‐M (Motor), and Multidomain Impairment Rating (MIR) scores and motor measures were determined and correlated in 242 participants. RESULTS Both CDR + NACC FTLD‐M and MIR showed increased disease severity scores and correlated with motor measures. These findings were held in 81 amyotrophic lateral sclerosis (ALS) participants and correlated with the Revised Amyotrophic Lateral Sclerosis Functional Rating Scale. Including a motor domain required fewer study participants in a simulated clinical trial sample size calculation. DISCUSSION With a motor domain, CDR + NACC FTLD‐M and MIR improve disease severity classification and correlate with quantitative motor assessments. This addition more fully captures the extent of symptoms across the FTD‐ALS spectrum and improves clinical trial efficiency. Highlights CDR + NACC FTLD‐M and MIR strongly correlate with objective motor measures. The enhanced scales improve disease severity classification in FTD and ALS. Greater clinical trial efficiency is achieved using these enhanced scales.

Treatment-induced ovarian function loss is a significant concern for many young patients with breast cancer. Accurately predicting this risk is crucial for counselling young patients and informing their fertility-related decision-making. However, current risk prediction models for treatment-related ovarian function loss have limitations. To provide a broader representation of patient cohorts and improve feature selection, we combined retrospective data from six datasets within the FoRECAsT (Infertility after Cancer Predictor) databank, including 2679 pre-menopausal women diagnosed with breast cancer. This combined dataset presented notable missingness, prompting us to employ cross imputation using the k-nearest neighbours (KNN) machine learning (ML) algorithm. Employing Lasso regression, we developed an ML model to forecast the risk of treatment-related amenorrhea as a surrogate marker of ovarian function loss at 12 months after starting chemotherapy. Our model identified 20 variables significantly associated with risk of developing amenorrhea. Internal validation resulted in an area under the receiver operating characteristic curve (AUC) of 0.820 (95% CI: 0.817–0.823), while external validation with another dataset demonstrated an AUC of 0.743 (95% CI: 0.666–0.818). A cutoff of 0.20 was chosen to achieve higher sensitivity in validation, as false negatives—patients incorrectly classified as likely to regain menses—could miss timely opportunities for fertility preservation if desired. At this threshold, internal validation yielded sensitivity and precision rates of 91.3% and 61.7%, respectively, while external validation showed 92.9% and 60.0%. Leveraging ML methodologies, we not only devised a model for personalised risk prediction of amenorrhea, demonstrating substantial enhancements over existing models but also showcased a robust framework for maximally harnessing available data sources.

Objective: The specialty of critical care in the United States currently lacks a single, broad, unified database. We conducted a scoping review of existing established national ICU databases, describing national and international patterns of critical care delivery. Data Sources: A systematic literature search was undertaken using MEDLINE, Embase, and Web of Science search engines. Study Selection: Projects describing national critical care delivery (including any subspecialty) published in any language were included. Titles, abstracts, and full-text manuscripts were reviewed in duplicate for inclusion. Data Extraction: National database characteristics were collected, including the number and subspecialty of ICUs, the inaugural year, data entry methodology, the number of episodes of care included, and captured clinical data elements. Data Synthesis: Of 24,003 abstracts screened, 185 manuscripts were eligible for inclusion. Thirty countries were identified as having established national ICU registries: Argentina, Australia/New Zealand, Austria, Belgium, Brazil, Canada, Denmark, Ecuador, Finland, Germany, Iceland, India, Ireland, Italy, Japan, Kenya, Malaysia, Mexico, Nepal, Netherlands, Norway, Pakistan, Paraguay, Spain, Sri Lanka, Sweden, Switzerland, United Kingdom, United States and Uruguay. Data entry commonly incorporates a combination of automated data abstraction from electronic healthcare systems and manual data entry, followed by independent validation. Frequently recorded variables include patient demographics; admission vital signs and laboratory data; comorbidities; admission source and diagnoses; ICU diagnoses, treatments, and complications; illness severity scores; and clinically relevant outcomes including discharge disposition, functional status, lengths of stay, and mortality. Conclusions: Insights and experience gained from the study of mature national ICU registries may be used to guide an equivalent U.S. multidisciplinary program aimed at benchmarking, needs assessment, quality improvement, and research facilitation

Abstract INTRODUCTION Preclinical Alzheimer's disease (AD) can be described relative to biomarker positivity onset time. METHODS We estimated time from amyloid positivity (A+) using sampled iterative local approximation (SILA) in a longitudinal autosomal dominant AD (ADAD) sample ( N = 379) with amyloid positron emission tomography. We compared (1) predicted age at A+ to imputed age, (2) estimated age at A+ to estimated age at symptom onset, and (3) variance in cognitive performance explained. RESULTS Mean error between imputed and SILA‐estimated age at A+ ( N = 26) was 1.15 years. Age at A+ explained 39% of estimated years to symptom onset (EYO) variance. Time from A+ explained 19% of cognitive composite variance and 14% of Clinical Dementia Rating Sum of Boxes CDR‐SB variance; EYO explained 43% and 57%, respectively. DISCUSSION SILA estimates A+ age in ADAD with reasonably good accuracy. SILA‐estimated time from A+ describes the start of pathology, but the time from A+ onset to symptoms is variable in ADAD and better described by EYO. Highlights Amyloid chronicity predicts a 14‐year preclinical AD phase in ADAD. SILA accurately estimates age at A+ (MAE < 2 years). EYO outperforms chronicity in predicting symptom onset. APP mutation carriers show atypical amyloid accumulation. Chronicity models help reveal AD heterogeneity in preclinical stages.

ABSTRACT Suicidality contributes substantially to global morbidity and mortality, yet despite its heritability, its biological etiology remains largely elusive. We conducted multi-ancestry genome-wide association study meta-analyses of suicidal ideation (259,747 cases), suicide attempt (64,993 cases), suicide death (9,197 cases), and suicidal behavior (suicide attempt/ death, 75,300 cases), across 54 cohorts (e.g., the Psychiatric Genomics Consortium, Million Veteran Program, UK Biobank). We identified 77 significant loci across meta-analyses, including 59 previously unreported for suicidality. SNP-based heritability ranged from 2.0-6.7% and there were strong, yet incomplete, genetic correlations between suicidality phenotypes (0.70-0.88). Fine-mapping prioritized putative causal SNPs and 20 credible genes. Enrichment analyses implicated synaptic pathways and neuronal populations predominantly in subcortical brain regions (e.g., amygdala excitatory, medium spiny, hippocampal CA1-3). Together, these findings establish suicidality as a polygenic set of traits with both shared and distinct genetic influences, providing a foundation for future studies of suicide biology and etiology.