Citations

ABSTRACT Introduction Children with hepatoblastoma (HB) and other solid tumors frequently undergo intraoperative blood transfusion (IBT) with unknown impact on oncologic outcomes and scant data to guide transfusion in this population. This study tested the hypothesis that IBT is associated with poorer survival in children with HB. Methods A multicenter retrospective observational study of patients aged <18 years with HB who underwent primary tumor resection, including liver transplantation, from 2010 to 2019 was performed at 19 institutions. The association of IBT with risk of recurrence and death were determined using propensity score reweighted (PSR) Cox proportional hazards regression analyses. Results There were 338 patients identified who met inclusion criteria and had sufficient data for inclusion. Of those, 257 (76%) received IBT, including 253 (98%) who received packed red blood cells (pRBC), 84 (33%) who received plasma, and 28 (11%) who received platelets. IBT was associated with higher pretreatment extent of disease ( p < 0.001), presence of annotation factors (+VPEFR: 50%, n = 129 vs. 37%, n = 30, p = 0.035), and complex resections (extended, meso‐, or total hepatectomy: 54%, n = 139 vs. 27%, n = 22, p < 0.001); these differences were mitigated after applying propensity score weighting. Patients who received IBT had greater postoperative hemoglobin (g/dL) (median 10 (I8–11) vs. 9 (8–10), p = 0.013) and required more postoperative plasma and platelet transfusions ( p < 0.05). Median follow‐up was 4.4 (2.0–8.3) years. Compared with non‐IBT patients, those with IBT had higher incidence of death (PSR HR 2.35, 95% CI 1.10–5.02). Recurrence did not significantly differ across groups (PSR HR = 0.82, 95% CI 0.45–1.48). Conclusion IBT was associated with greater hazard of death. Postoperative hemoglobin levels suggested that unnecessary transfusions occurred and a pRBC‐focused approach to IBT led to coagulopathy. Development of optimal transfusion strategies for HB are needed to minimize unnecessary transfusions.

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.

Abstract Objectives Effective communication is crucial in healthcare, and for patients with a non-English language preference (NELP), professional interpreters are recognized as the gold standard in supporting bidirectional communication. However, interpreters are not always readily available, prompting the exploration of other options for translation and interpretation. The recent developments in artificial intelligence-based neural network translation tools, namely neural machine translation (NMT) may enable robust interpretation and translation. Materials and Methods We conducted a systematic review (SR) to evaluate the literature on NMT for this purpose. We did a comprehensive search of several databases with guidance from a professional librarian. The search was limited to the year 2000 onwards and English language. Title and abstract screening and full-text review were independently conducted by two reviewers with conflicts resolved by a third reviewer Results 2867 studies were identified with 10 studies included in the final analysis. Among these, six evaluated interpretation in real or simulated clinical settings and four examined translation of discharge materials. Google Translate and ChatGPT were assessed in several studies. Accuracy differed by language, with low-resource languages performing worse. Discussion NMT technologies in healthcare have several advantages including broad language accessibility and potential cost savings for institutions. Despite improved accuracy of these novel tools, due to possible critical errors NMT tools are not yet ready for widespread clinical use. Conclusion Future studies should focus on optimizing evaluation methods as well as how best to integrate these technologies into real-time clinical settings.

Hypertension is the single most important modifiable risk factor for preventable disability and death worldwide and disproportionately affects socially disadvantaged populations. We face a paradox—blood pressure control is low and recent trends suggest it is even declining, despite the availability of inexpensive and effective therapies. A variety of barriers on the system, patient, and healthcare provider side hinder effective drug-based risk factor management. Clinical inertia represents a major barrier on the clinician side, as well as workload and limited education. Common barriers on the patient side include limited English proficiency, low health literacy, and nonadherence with misaligned incentives, limited resources, lack of structured clinical pathways, and reimbursement issues. New innovations in the field of RNA-targeted therapies and device-based interventions could prevent and potentially even cure diseases previously designated as chronic health conditions, such as hypertension. Such novel therapies could potentially overcome several major barriers to effective treatment, including nonadherence. Drug development of novel, long-acting treatments requires consideration of specific clinical trial design aspects, including safety collection, benefit: risk assessment, the development and assessment of novel, qualitative surrogate end points, such as time-in-therapeutic range, the use of representative trial settings as well as the definition of standard of care in placebo-controlled trials, which should be of reasonably high-quality allowing for credible evaluation of effectiveness. Here, we provide an overview on barriers to effective treatment and a framework for trials assessing novel treatments for cardiovascular disease risk factors, including early and broad implementation programs.

Abstract Background Breast cancer genome-wide association studies (GWAS) have identified more than 200 susceptibility loci, but most studies are dominated by European and East Asian populations. Methods We analyzed breast cancer GWAS summary statistics from African (AFR), East Asian (EAS), European (EUR), and Hispanic/Latina (H/L) samples (159,297 cases and 212,102 controls). We estimated logit-scale SNP-based heritability, polygenicity, and cross-ancestry genetic correlation, partitioned heritability across functional annotations, and integrated GWAS results with the Tabula Sapiens single-cell atlas using scDRS+. Results The logit-scale heritability of breast cancer ranged from ℎ 2 =0.47 (SE = 0.07) in EAS to AFR ℎ 2 =0.61 (SE = 0.10), with no significant differences across ancestries (p=0.63). The estimated number of susceptibility markers in a sparse normal-mixture effects model also varied from 4,446 (SE = 3,100) in EAS to 8,308 (SE = 2,751) in AFR, but differences were not significant across ancestries (p=0.55). Cross-sample genetic correlations varied, with the strongest correlation between EUR and EAS (𝜌 = 0.79, SE = 0.08) and weakest between AFR and H/L (𝜌 = 0.26, SE = 0.24). Regulatory annotations were enriched for breast cancer heritability across samples. Integration with single-cell expression profiles implicated ancestry-shared associations with innate immune, secretory epithelial, and stromal cell types. Conclusion These results indicate substantial cross-ancestry sharing of breast cancer polygenic architecture, highlight a consistent contribution of regulatory variation, and identify convergent cellular contexts that motivate functional follow-up and inform expectations for the transferability and attainable performance of common-variant risk prediction across populations.

Increasing evidence strongly links neuroinflammation to Alzheimer’s disease (AD) pathogenesis. Peripheral monocytes are crucial components of the human immune system, but their contribution to AD pathogenesis is still largely understudied partially due to limited human models. Here, we introduce human cortical organoid microphysiological systems (hCO-MPSs) to study AD monocyte-mediated neuroinflammation. By culturing doughnut-shape organoids on 3D-printed devices within standard 96-well plates, we generate hCO-MPSs with reduced necrosis, minimized hypoxia, and improved viability. Using these models, we found that monocytes from AD patients exhibit increased infiltration ability, decreased amyloid-β clearance capacity, and stronger inflammatory response than monocytes from age-matched control donors. Moreover, we observed that AD monocytes induce pro-inflammatory effects such as elevated astrocyte activation and neuronal apoptosis. Furthermore, the marked increase in IL1B and CCL3 expression underscores their pivotal role in AD monocyte-mediated neuroinflammation. Our findings provide insight into understanding monocytes’ role in AD pathogenesis, and our lab-compatible MPS models may offer a promising way for studying various neuroinflammatory diseases.

Background and objectives Arteriovenous malformations (AVMs) with perinidal aneurysms and single draining vein are associated with an elevated risk of rupture and increased procedural complexity. The role of preoperative embolization in this high-risk anatomical subset remains unclear. This study aimed to evaluate the safety and efficacy of microsurgery with preoperative embolization, compared with microsurgery alone in patients with such AVMs. Methods We conducted a multicenter retrospective analysis of an AVM registry from the MISTA (Multicenter International Study for Treatment of Brain AVMs) consortium and included AVMs with perinidal aneurysms and a single draining vein. Baseline characteristics, angiographic outcomes, functional outcomes, and complication rates were compared. Propensity score weighting (PSW) using the covariate balancing method was applied to adjust for baseline differences. Results Out of a total of 1919 patients, 65 met the inclusion criteria; 45 patients underwent preoperative embolization followed by microsurgery, and 20 underwent microsurgery alone. After adjustment, complete obliteration rates were similar between groups (OR 0.87, 95% CI 0.04 to 16.33, P=0.92), as were rates of functional independence at discharge and follow-up. Overall complication, symptomatic complication, and mortality rates did not differ significantly between groups. However, permanent complications were significantly lower in patients with preoperative embolization (OR 0.06, 95% CI 0.004 to 0.84, P=0.03). Discussion In patients with AVMs featuring perinidal aneurysms and single draining vein, preoperative embolization followed by microsurgery was associated with fewer permanent complications and no increase in adverse outcomes compared with microsurgery alone. However, given the small number of events, this finding should be interpreted cautiously.

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.