Background and Aims Despite surgical and chemotherapeutic advances, the 5‐year survival rate for stage IV hepatoblastoma (HB), the predominant pediatric liver tumor, remains at 27%. Yes‐associated protein 1 (YAP1) and β‐catenin co‐activation occurs in 80% of children’s HB; however, a lack of conditional genetic models precludes tumor maintenance exploration. Thus, the need for a targeted therapy remains unmet. Given the predominance of YAP1 and β‐catenin activation in HB, we sought to evaluate YAP1 as a therapeutic target in HB. Approach and Results We engineered the conditional HB murine model using hydrodynamic injection to deliver transposon plasmids encoding inducible YAP1S127A, constitutive β‐cateninDelN90, and a luciferase reporter to murine liver. Tumor regression was evaluated using bioluminescent imaging, tumor landscape characterized using RNA and ATAC sequencing, and DNA footprinting. Here we show that YAP1S127A withdrawal mediates more than 90% tumor regression with survival for 230+ days in mice. YAP1S127A withdrawal promotes apoptosis in a subset of tumor cells, and in remaining cells induces a cell fate switch that drives therapeutic differentiation of HB tumors into Ki‐67‐negative hepatocyte‐like HB cells (“HbHeps”) with hepatocyte‐like morphology and mature hepatocyte gene expression. YAP1S127A withdrawal drives the formation of hbHeps by modulating liver differentiation transcription factor occupancy. Indeed, tumor‐derived hbHeps, consistent with their reprogrammed transcriptional landscape, regain partial hepatocyte function and rescue liver damage in mice. Conclusions YAP1S127A withdrawal, without silencing oncogenic β‐catenin, significantly regresses hepatoblastoma, providing in vivo data to support YAP1 as a therapeutic target for HB. YAP1S127A withdrawal alone sufficiently drives long‐term regression in HB, as it promotes cell death in a subset of tumor cells and modulates transcription factor occupancy to reverse the fate of residual tumor cells to mimic functional hepatocytes.

BACKGROUND:Venous thromboembolism (VTE) in injured children is rare, but its consequences are significant. Several risk stratification algorithms for VTE in pediatric trauma exist with little consensus, and all are hindered in development by relying on registry data with known inaccuracies. We performed a multicenter review to evaluate trauma registry fidelity and confirm the effectiveness of one established algorithm across diverse centers. METHODS:Local trauma registries at 10 institutions were queried for all patients younger than 18 years admitted between 2009 and 2018. Additional chart review was performed on all "VTE" cases and random non-VTE controls to assess registry errors. Corrected data were then applied to our prediction algorithm using 10 real-time variables (Glasgow Coma Scale, age, sex, intensive care unit admission, transfusion, central line placement, lower extremity/pelvic fracture, major surgery) to calculate VTE risk scores. Contingency table classifiers and the area under a receiver operator characteristic curve were calculated. RESULTS:Registries identified 52,524 pediatric trauma patients with 99 episodes of VTE; however, chart review found that 13 cases were misclassified for a corrected total of 86 cases (0.16%). After correction, the algorithm still displayed strong performance in discriminating VTE-fated encounters (sensitivity, 69%; area under the receiver operating characteristic curve, 0.96). Furthermore, despite wide institutional variability in VTE rates (0.04-1.7%), the algorithm maintained a specificity of >91% and a negative predictive value of >99.7% across centers. Chart review also revealed that 54% (n = 45) of VTEs were directly associated with a central line, usually femoral (n = 34, p < 0.001 compared with upper extremity), and that prophylaxis rates were underreported in the registries by about 50%; still, only 19% of the VTE cases had been on prophylaxis before diagnosis. CONCLUSION:The VTE prediction algorithm performed well when applied retrospectively across 10 diverse pediatric centers using corrected registry data. These findings can advance initiatives for VTE screening/prophylaxis guidance following pediatric trauma and warrant prospective study.

BACKGROUND To describe the demographic characteristics and burden of pediatric suicides by firearm in the United States using a large all-payer pediatric inpatient care database. METHODS Children and young adults (<21 years old) were identified with an International Classification of Diseases, Ninth Revision diagnosis of suicide and self-inflicted injury with a firearm (SIF) in the Kids' Inpatient Database for the study years of 2006, 2009, and 2012. National estimates were obtained using case weighting. Multivariable logistic regression was performed to examine the association between SIF and risk factors while adjusting for various sociodemographic characteristics using separate models incorporating mental health diagnoses. RESULTS There were a total of 613 hospitalizations for SIF during the years under study. Almost four hospitalizations per week occurred, and in-hospital mortality was 39.1%. The mean age of the study population was 17.3 years, and this population was predominantly male (87.5%), white (62.4%), resided in an urban area (43.8%), lived in the south (51.3%), and within the lowest income quartile (33.8%). Mental health (38.3%) and mood disorders (28.3%) were common. Males had a markedly increased likelihood of hospitalization for SIF (adjusted odds ratio [aOR], 7.56; 95% confidence interval [CI], 5.54–10.30). Children and adolescents from rural environments and those in the south were more likely to have a hospitalization for SIF than respective comparison groups. Using separate regression models, a diagnosis of any mental health disorder increased the likelihood of hospitalization for a SIF (aOR, 11.9: 95% CI, 9.51–14.9), mood disorders (aOR, 17.2; 95% CI, 13.3–22.3), and depression (aOR, 21.3; 95% CI, 16.1–28.3). CONCLUSION Pediatric hospitalizations for SIF are a common occurrence with high associated mortality. The prevalence of mental health disorders and their impact on this population highlight the need for early identification and intervention for individuals at risk. LEVEL OF EVIDENCE Epidemiological, level III.

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