Citations

Introduction: Endovascular thrombectomy (EVT) is an effective treatment for basilar artery occlusion (BAO) stroke in select patients. While there is a growing body of literature suggesting that advanced imaging modalities such as computed tomography perfusion (CTP) and magnetic resonance (MR) may not be necessary for selecting anterior circulation large vessel occlusion stroke patients for EVT, whether advanced imaging may be superior to conventional imaging (non-contrast CT and CT angiography) in identifying good treatment candidates among BAO patients is less clear. Patients and methods: This was a multicenter retrospective cohort study of BAO EVT patients treated from 2013 to 2022 in the Stroke Thrombectomy and Aneurysm Registry. Patients selected for EVT by advanced imaging (CTP or MR) were matched with those selected by conventional imaging using propensity score matching (PSM) accounting for possible confounders. Primary outcome was functional independence at 90 days. Other outcomes include bedridden state or death at 90-days and symptomatic intracranial hemorrhage (sICH). Results: 268 patients were included. 150 patients were selected for BAO EVT by conventional imaging, 86 by CTP, and 32 by MR. Patients selected by advanced imaging were significantly older than those selected by conventional imaging (median age 71 vs 64 years, p = 0.001); patient characteristics were otherwise similar between cohorts. After PSM, 90-day outcomes were similar between the two cohorts ( p = 0.56), with similar rates of functional independence (39.4% vs 35.1%, p = 0.65), bedridden state or death (40.4% vs 44.7%, p = 0.66), and sICH (3.3% vs 5.7%, p = 0.49) for conventional and advanced imaging groups, respectively. Results were similar across treatment time windows (all p > 0.05). Conclusions: Selecting patients for basilar EVT using conventional versus advanced imaging did not result in different clinical outcomes, regardless of treatment time windows. Conventional imaging appears sufficient as a first-line tool for selecting basilar EVT patients in routine clinical practice.

ImportanceIndia’s goal of measles elimination remains unmet, as evidenced by significant recent outbreaks.ObjectiveTo identify seroprevalence rates among vaccinated children and to examine demographic factors that influence antibody responses.Design, Setting, and ParticipantsThis cross-sectional study included a highly vaccinated cohort of Indian children from the states of Kerala and Tamil Nadu between 2018 and 2023. Eligible children had received at least 2 doses of measles-containing vaccines; their mothers were recruited from various community settings, including local nursery and secondary schools, residential associations, and hospitals.ExposureMeasles-specific antibodies were quantified in serum samples.Main Outcomes and MeasuresMeasles-specific immunoglobulin G (IgG) and neutralizing antibodies were quantified in both children and mothers. Measles-specific IgM was also measured in children.ResultsThe total cohort comprised 684 children (median age, 9 years [range, 4-18 years]; 348 male [50.1%]) and 544 mothers. All children received at least 2 doses of measles-containing vaccines; 435 children (63.6%) received a third dose, and 7 (1.0%) received a fourth dose. Among the children, 621 (90.8%) had positive measles-specific IgG, and 623 (91.5%) had protective neutralizing antibodies titers, with a strong correlation between measles-specific IgG and neutralizing antibodies (r = 0.73; P < .001). Female children exhibited significantly higher titers of both measles-specific IgG and neutralizing antibodies compared with male children. While IgG and neutralizing antibody titers remained stable over time and were not associated with the number of vaccine doses in children, neutralizing antibody titers increased with age in mothers, likely due to repeated viral exposure. Notably, in 20 families with at least 2 children, differential measles-specific IgM profiles were observed between siblings despite high IgG and neutralizing antibody titers, suggesting ongoing breakthrough infections.Conclusions and RelevanceIn this cross-sectional study, substantial measles immunity gaps were found despite high vaccine coverage with evidence of breakthrough infections, posing significant challenges to India’s measles elimination efforts. These results underscore the urgent need to strengthen India’s immunization program and investigate the mechanisms driving suboptimal responses to measles vaccination; without addressing these immune response deficiencies, achieving measles elimination through increased vaccine coverage alone may remain unattainable in India.

Introduction: Pregnancy can be a complex and risk filled event for women with inflammatory bowel disease (IBD). High-quality studies in this population are lacking, with limited data on medications approved to treat IBD during pregnancy. For patients, limited knowledge surrounding pregnancy impacts pregnancy rates, medication adherence, and outcomes. Limited provider knowledge leads to highly varied practices in care affected by local dogma, available resources, individual interpretation of the literature, and fear of harming the fetus. The variations in guidelines by different societies and countries reflect this and lead to confusion for physicians and patients alike. The Global Consensus Consortium is a group of 39 IBD and content experts and 7 patient advocates from 6 continents who convened to review and assess current data and come to an agreement on best practices based on these data. Methods: The GRADE process was used when sufficient published data were available and the RAND process in those instances where expert opinion was needed to guide consistent practice. Recommendations were informed by the guiding principle that maternal health best supports infant health. Results: The topics were divided into 10 categories with 34 GRADE recommendations and 35 Consensus statements. Discussion: Overall, the goal of the group was to provide data-driven and practical guidance to improve the care of women with IBD around the globe based on the best available research.

Rubella is typically a mild viral illness, but it can lead to severe complications when contracted during pregnancy, such as pregnancy loss or developmental defects in the fetus (congenital rubella syndrome). Therefore, it is crucial to develop and maintain protective immunity in women of childbearing age. In this study, we assessed the transcriptional factors associated with rubella-specific immune outcomes (IgG binding antibody and avidity, neutralizing antibody, and memory B cell ELISpot response) following a third MMR vaccine dose in women of reproductive age to identify key factors/signatures impacting the immune response. We identified baseline (Day 0) and differentially expressed (Day 28–Day 0) genes associated with several RV-specific immune outcomes, including the transferrin receptor 2 (TFR2), which is an important factor regulating iron homeostasis and macrophage functional activity, and a close functional homolog of TFR1, the cellular receptor of the New World hemorrhagic fever arenaviruses. We also identified enriched KEGG pathways, “cell adhesion molecules”, “antigen processing and presentation”, “natural killer cell-mediated cytotoxicity”, and “immune network for IgA production”, relevant to immune response priming and immune activation to be associated with RV-specific immune outcomes. This study provides novel insights into potential biomarkers of rubella-specific immunity in women of childbearing age.

Abstract Objective: Electronic Health Record (EHR) data are critical for advancing translational research and AI technologies. The ENACT network offers access to structured EHR data across 57 CTSA hubs. However, substantial information is contained in clinical narratives, requiring natural language processing (NLP) for research. The ENACT NLP Working Group was formed to make NLP-derived clinical information accessible and queryable across the network. Methods: We established the ENACT NLP Working Group with 13 sites selected based on criteria including clinical notes access, IT infrastructure, NLP expertise, and institutional support. We divided sites into five focus groups targeting clinical tasks within disease contexts. Each focus group consisted of two development sites and two validation sites. We extended the ENACT ontology to standardize NLP-derived data and conducted multisite evaluations using the Open Health Natural Language Processing (OHNLP) Toolkit. Results: The working group achieved 100% site retention and deployed NLP infrastructure across all sites. We developed and validated NLP algorithms for rare disease phenotyping, social determinants of health, opioid use disorder, sleep phenotyping, and delirium phenotyping. Performance varied across sites (F1 scores 0.53–0.96), highlighting data heterogeneity impacts. We extended the ENACT common data model and ontology to incorporate NLP-derived data while maintaining Shared Health Research Informatics NEtwork (SHRINE) compatibility. Conclusion: This demonstrates feasibility of deploying NLP infrastructure across large, federated networks. The focus group approach proved more practical than general-purpose approaches. Key lessons include the challenge of data heterogeneity and importance of collaborative governance. This work also provides a foundation that other networks can build on to implement NLP capabilities for translational research.

Importance Obesity is associated with a higher risk of recurrence, mortality, comorbidities, treatment-related adverse effects, and poor quality of life in patients with breast cancer. Scalable interventions are needed to promote weight loss in this population. Objective To evaluate the impact of a remotely delivered weight loss intervention (WLI) on weight change at 1 year in patients with breast cancer and obesity and to explore factors associated with weight change. Design, Setting, and Participants The Breast Cancer Weight Loss trial is a phase 3, randomized clinical trial evaluating the impact of a telephone-based WLI on invasive disease–free survival and other outcomes in women with obesity and early breast cancer at 637 sites across the US and Canada. Participants were enrolled to the study between August 2016 and February 2021. Participants included women with stage II to III, ERBB2 -negative breast cancer and a body mass index (BMI) of 27 or higher. Interventions Participants were randomized to a 2-year, telephone-based WLI plus health education or health education alone control group. Main Outcome and Measures The primary end point for this prespecified secondary analysis was weight change at 1 year. Weight was measured at baseline and 1 year, and changes in weight were compared between groups. Weight change was evaluated with a linear mixed-effects model including treatment group, weight over time, a time-by-group interaction, menopausal status, race and ethnicity, and hormone receptor status. Results A total of 3180 women with breast cancer and BMI of 27 and higher were included in the study; 1591 were randomized to the WLI and 1589 to the control group. At baseline, the mean (SD) age of participants was 53.4 (10.6), and the mean (SD) BMI was 34.4 (5.6). The racial and ethnic breakdown included 406 (12.8%) Black, 231 (7.3%) Hispanic or Latino, 2906 (91.4%) non-Hispanic, and 2555 (80.3%) White participants. WLI participants lost a mean of 4.3 kg (95% CI 3.9-4.6 kg), or 4.7% (95% CI, 4.3%-5.0%) of baseline body weight at 1 year vs control participants, who gained 0.9 kg (95% CI, 0.5-1.3 kg), or 1.0% (95% CI 0.1%-1.4%) of baseline body weight ( P < .001). Participants randomized to WLI experienced significant weight loss (vs control group participants) across demographic and tumor factors. WLI effect differed significantly by menopausal status, with postmenopausal participants having greater weight loss than premenopausal participants, and by race and ethnicity, with Black and Hispanic participants having less weight loss compared to other races and ethnicities. Conclusions and Relevance In this secondary analysis of a randomized clinical trial, a telephone-based WLI induced significant weight loss in patients with breast cancer with overweight and obesity across demographic and treatment factors. Further follow-up of the Breast Cancer Weight Loss trial will evaluate whether the WLI improves disease outcomes. Trial Registration ClinicalTrials.gov Identifier: NCT02750826

Abstract Background The isocitrate dehydrogenase (IDH) mutation status is a key molecular marker in diagnosing and treating brain tumors. Currently, it is determined via invasive tissue biopsy. Recent advances in deep learning (DL) have offered promising non-invasive alternatives for determining IDH status. However, their clinical translation is hindered by a significant gap between DL predictions and their clinical applicability. The limited transparency of many DL-networks and inadequate evaluation metrics hinders trust and adoption, as clinicians require clear and validated insights for determining IDH status. These challenges highlight the need for robust validation and measures of predictive reliability to make DL-predictions clinically actionable. Methods We developed a unique approach for non-invasive prediction of IDH status using MRI. We combine a voxel-wise-segmentation network(MC-net) with Bayesian logistic regression (BLR) to provide an IDH status and estimate confidence scores. We utilized a comprehensive dataset of 2,481 glioma cases from eight institutions. Results Our framework(MC-net + BLR) demonstrated robust performance achieving 96.4% and 95.1% classification accuracies on diverse databases, with an AUC of 0.98. The BLR was implemented exclusively on held-out test data, ensuring that the derived confidence scores are independent of the training or validation phases. The derived confidence scores showed a low Brier score of 0.0125, highlighting its superior calibration and uncertainty quantification. Conclusion The developed framework provides an IDH status and a confidence score, offering clinicians an additional layer of assurance in prediction reliability. It bridges the gap between high-performing DL models and their clinical applicability by addressing the challenges in prediction reliability. Our framework is a significant advancement in non-invasive determination of IDH-status and confidence-informed therapeutic decision-making in neuro-oncology.

Abstract Background Acamprosate is an FDA-approved medication for the treatment of alcohol use disorder (AUD), however, only about 50% of patients will respond to acamprosate. Previously, we conducted an acamprosate trial (n=442), which is one of the largest acamprosate clinical studies ever conducted and currently the only study with multi-omics data. To date, no biological measures are utilized to predict response to acamprosate treatment. Aims & Objectives We set out to apply our established pharmaco-omics informed genomics strategy to identify potential biomarkers associated with acamprosate treatment response. Method Our open-label acamprosate clinical trial recruited 442 patients with AUD, all of whom were treated with acamprosate for three months. The primary outcomes were 1) relapse to alcohol use and 2) relapse to heavy drinking. Alcohol consumption was measured using the self-reported timeline follow back method. Plasma protein levels were measured using Olink proximity extension immunoassays. Results Our established “Pharmaco-Omics-informed genome-wide association study (GWAS)” research strategy identified 12 proteins, including interleukin-17 receptor B (IL17RB), that were associated with acamprosate treatment response. A GWAS for IL17RB concentrations identified several genome-wide significant signals. Specifically, the top hit single nucleotide polymorphism (SNP) rs6801605 with a minor allele frequency of 38% in the European American population mapped 4 kilobase (Kb) upstream of IL17RB, and intron 1 of the choline dehydrogenase (CHDH) gene on chromosome 3 (p: 4.8E-20). The variant genotype (AA) for the SNP rs6801605 was associated with lower IL17RB protein expression. In addition, we identified a series of genetic variants in IL17RB that were associated with acamprosate treatment outcomes. Furthermore, the variant genotypes for all of those IL17RB SNPs were protective against alcohol relapse. Finally, we demonstrated that the basal level of mRNA expression of IL17RB was inversely correlated with those of nuclear factor-κB (NF-κB) subunits, and a significantly higher expression of NF-κB subunits was observed in AUD patients who relapsed to alcohol use. Discussion & Conclusions This study illustrates that IL17RB genetic variants might contribute to acamprosate treatment outcomes. This series of studies represents an important step toward generating functional hypotheses that could be tested to gain insight into mechanisms underlying variation in acamprosate treatment response phenotypes.

Abstract Changes in the clinical symptoms of acute graft-versus-host disease (GVHD) are currently used to assess treatment responses. The Mount Sinai Acute GVHD International Consortium (MAGIC) consortium has recently revealed that the integration of serum biomarkers with clinical symptoms at the onset of treatment in a MAGIC composite score (MCS) more accurately predicts treatment response and 6-month nonrelapse mortality (NRM) than clinical symptoms alone. In this study, we evaluated whether the integration of serum biomarkers and clinical symptoms on day 28 (D28) would also better predict NRM than clinical response only (CRO). We analyzed data from 1135 patients receiving systemic treatment for acute GVHD and created a fourth MCS category for patients with complete resolution of symptoms and low-risk clinical biomarkers on D28. Using a classification and regression tree model with 6-month NRM as the end point, we identified status of MCS 0 or MCS 1 at D28 as responses, which we termed the MAGIC composite response (MCR). In the validation cohort (n = 309), MCR more accurately predicted 6-month NRM than CRO (area under the curve: 0.77 vs 0.69; P = .014) and demonstrated higher negative and positive predictive values. MCR correctly reclassified both clinical nonresponders and responders: 28 of 213 clinical responders (13%) became nonresponders with fivefold higher NRM (34.3% vs 6.8%, P < .001) and a larger group (29/96, 30%) of clinical nonresponders became responders with sixfold lower NRM (7.6% vs 50.7%, P < .001). These findings support the use of MCR as a superior surrogate end point for long-term GVHD control and survival in future clinical trials.