Validation of Variables for Use in Pediatric Obesity Risk Score Development in Demographically and Racially Diverse United States Cohorts.

OBJECTIVE: To evaluate the performance of childhood obesity prediction models in four independent cohorts in the United States, using previously validated variables obtained easily from medical records as measured in different clinical settings. STUDY DESIGN: Data from four prospective cohorts, Latinx, Eating, and Diabetes; Stress in Pregnancy Study; Project Viva; and Center for the Health Assessment of Mothers and Children of Salinas were used to test childhood obesity risk models and predict childhood obesity by ages 4 through 6, using five clinical variables (maternal age, maternal prepregnancy body mass index, birth weight Z-score, weight-for-age Z-score change, and breastfeeding), derived from a previously validated risk model and as measured in each cohort's clinical setting. Multivariable logistic regression was performed within each cohort, and performance of each model was assessed based on discrimination and predictive accuracy. RESULTS: The risk models performed well across all four cohorts, achieving excellent discrimination. The area under the receiver operator curve was 0.79 for Center for the Health Assessment of Mothers and Children of Salinas and Project Viva, 0.83 for Stress in Pregnancy Study, and 0.86 for Latinx, Eating, and Diabetes. At a 50th percentile threshold, the sensitivity of the models ranged from 12% to 53%, and specificity was ≥ 90%. The negative predictive values were ≥ 80% for all cohorts, and the positive predictive values ranged from 62% to 86%. CONCLUSION: All four risk models performed well in each independent and demographically diverse cohort, demonstrating the utility of these five variables for identifying children at high risk for developing early childhood obesity in the United States.

Asylum seeker trauma in a student-run clinic: reducing barriers to forensic medical evaluations.

Introduction This research, through the analysis of the case-law of the Inter-American Court of Human Rights (IACtHR), seeks to shed light on the nexus between families of the missing' claims, their agency and State compliance with reparations. The IACtHR has a unique follow-up system in the area of reparations, where victims can directly address the judges during hearings. This paper suggests that victims' participation - before and after the judgment- pervades the legal rigidity of international jurisdictions and contributes to a better understanding of reparations. INTRODUCTION: The number of forcibly displaced immigrants seeking asylum in the United States continues to rapidly increase. Movement from Latin America to the United States was the third-largest migration worldwide in 2017 (Leyva-Flores et al., 2019). As migration patterns change, understanding the background and trauma profile of newly displaced populations is essential to meet their health needs and aid successful resettlement. University-affiliated student-run asylum clinics conduct a growing number of forensic medical evaluations of asylum seekers and provide a vital lens to study changes in this population's profile over time. METHODS: A retrospective review was conducted of the first 102 asylum seekers receiving forensic medical evaluations between 2019 and 2021 at a university-affiliated student- run clinic, reporting demographics; trauma, medical, and mental health histories; referral patterns; and legal outcomes. Bivariate statistics were used to investigate the relationship between past trauma and mental health outcomes. RESULTS: Clients reported an average of 4.4 different types of physical, psychological, and sexual ill-treatment per person. The current mental health burden was extensive with 86.9 percent of clients reporting symptoms of PTSD and/or depression. Clinician-student teams evaluated clients within a clinic structure deploying a continuous improvement model to reduce common barriers to forensic evaluations and promote longitudinal follow- up and referrals. DISCUSSION: This study demonstrates the complexity of trauma exposure reported by asylum seekers, contributes to the evidence on how trauma results in mental health outcomes, and describes trauma-centred clinic adaptations that reduce barriers to forensic evaluations known to improve the rates of legal protection.

Integrated stem cell signature and cytomolecular risk determination in pediatric acute myeloid leukemia.

Relapsed or refractory pediatric acute myeloid leukemia (AML) is associated with poor outcomes and relapse risk prediction approaches have not changed significantly in decades. To build a robust transcriptional risk prediction model for pediatric AML, we perform RNA-sequencing on 1503 primary diagnostic samples. While a 17 gene leukemia stem cell signature (LSC17) is predictive in our aggregated pediatric study population, LSC17 is no longer predictive within established cytogenetic and molecular (cytomolecular) risk groups. Therefore, we identify distinct LSC signatures on the basis of AML cytomolecular subtypes (LSC47) that were more predictive than LSC17. Based on these findings, we build a robust relapse prediction model within a training cohort and then validate it within independent cohorts. Here, we show that LSC47 increases the predictive power of conventional risk stratification and that applying biomarkers in a manner that is informed by cytomolecular profiling outperforms a uniform biomarker approach.