Machine Learning Quantification of Pulmonary Regurgitation Fraction from Echocardiography.

Assessment of pulmonary regurgitation (PR) guides treatment for patients with congenital heart disease. Quantitative assessment of PR fraction (PRF) by echocardiography is limited. Cardiac MRI (cMRI) is the reference-standard for PRF quantification. We created an algorithm to predict cMRI-quantified PRF from echocardiography using machine learning (ML). We retrospectively performed echocardiographic measurements paired to cMRI within 3 months in patients with ≥ mild PR from 2009 to 2022. Model inputs were vena contracta ratio, PR index, PR pressure half-time, main and branch pulmonary artery diastolic flow reversal (BPAFR), and transannular patch repair. A gradient boosted trees ML algorithm was trained using k-fold cross-validation to predict cMRI PRF by phase contrast imaging as a continuous number and at > mild (PRF ≥ 20%) and severe (PRF ≥ 40%) thresholds. Regression performance was evaluated with mean absolute error (MAE), and at clinical thresholds with area-under-the-receiver-operating-characteristic curve (AUROC). Prediction accuracy was compared to historical clinician accuracy. We externally validated prior reported studies for comparison. We included 243 subjects (median age 21 years, 58% repaired tetralogy of Fallot). The regression MAE = 7.0%. For prediction of > mild PR, AUROC = 0.96, but BPAFR alone outperformed the ML model (sensitivity 94%, specificity 97%). The ML model detection of severe PR had AUROC = 0.86, but in the subgroup with BPAFR, performance dropped (AUROC = 0.73). Accuracy between clinicians and the ML model was similar (70% vs. 69%). There was decrement in performance of prior reported algorithms on external validation in our dataset. A novel ML model for echocardiographic quantification of PRF outperforms prior studies and has comparable overall accuracy to clinicians. BPAFR is an excellent marker for > mild PRF, and has moderate capacity to detect severe PR, but more work is required to distinguish moderate from severe PR. Poor external validation of prior works highlights reproducibility challenges.

Documentation Status as a Contextual Determinant of HIV Risk Among Young Transgender Latinas.

PURPOSE: The purpose of this study was to explore the contextual factors that determine or mitigate vulnerability to HIV among Latina transgender women. Documentation status (legal authorization to live in the United States) has been cited by other studies as a barrier to recruitment or engagement in HIV-related care among immigrant Latinos, but not explored as a determinant of HIV risk for transgender immigrant Latinas. METHODS: We collaborated with a community-based organization to explore these contextual, including social and structural, factors. In-depth interviews in Spanish captured life histories of eight 18- to 29-year-old transgender Latinas, who collectively self-identify as chicas trans. Codes were assigned deductively from the interview guide, and emerging themes were identified throughout data collection. RESULTS: Most participants migrated to the United States from Central America after experiencing discrimination and violence in their countries of origin. Participants emphasized documentation status as a critical factor in three areas related to social and structural determinants of HIV risk: gender identity expression, access to services, and relationship power dynamics. Chicas trans who gained legal asylum reported greater control over sexual relationships, improved access to services, and less risky employment. CONCLUSIONS: Documentation status emerged as a key HIV risk factor for this population. For undocumented transgender Latinas, legal asylum appears to be a promising HIV-related protective factor. Further research could assess whether legal assistance combined with wraparound support services affects HIV prevention for this population.

Using aided AAC models, recasts, and contrastive targets to teach grammatical morphemes to children who use AAC.

PURPOSE: The purpose of the investigation was to evaluate the effects of using aided augmentative and alternative communication (AAC) modeling and recasting on the expression of grammatical morphemes with children who used AAC. METHOD: A single-subject, multiple-probe, across-targets design was used for the study. Three participants were each taught to use 3 grammatical structures. Intervention consisted of aided AAC models and recasts during storybook reading tasks. RESULTS: All three children readily began using the targeted grammatical morphemes. However, none of the participants maintained use of the first morpheme. Error analyses revealed that the children either omitted the targeted morpheme or replaced it with another morpheme. To address this issue, a second intervention phase was implemented for the targets that were not maintained. During this phase, various grammatical morphemes were contrasted with each other (e.g., past tense -ed vs. possessive 's). Following the second intervention phase, participants maintained all targets. CONCLUSIONS: Aided AAC models and recasts may be used as part of intervention packages designed to help children acquire production of grammatical morphemes; however, it is important to provide contrasts of grammatical forms to ensure acquisition. Theoretical and clinical implications are discussed.

Open-tubular capillary cell affinity chromatography: single and tandem blood cell separation.

In this paper, an open-tubular capillary cell affinity chromatography (OT-CAC) method to enrich and separate target cells is described. Open tubular capillaries coated with anti-CD4, anti-CD14, or anti-CD19 antibodies were used as affinity chromatography columns to separate target blood cells. Cells were eluted using either shear force or bubbles. Bubbles were used to elute the captured cells without diluting the captured cells appreciably, while maintaining viability (the viability of the recovered cells was 85.83 +/- 7.34%; the viability of the cells was 90.41 +/- 3.49% before separation). Several aspects of the OT-CAC method were studied, such as the affinity of one antibody between two different cell lines, the effect of shear force, and the recovery of captured cells. Single- and multicell type separations were demonstrated by isolating CD4+ cells with antiCD4 coated capillary and isolating CD4+ and CD19+ cells with two capillaries in tandem from blood samples. In the one cell type isolation test, an average of 87.7% of the recovered cells from antiCD4 capillary were lymphocytes and an average of 97.7% of those lymphocytes were CD4+ cells. In the original blood sample, only 14.2% of the leukocytes were CD4+ cells. Two capillary columns were also run in tandem, separating two blood cell types from a single sample with high purity. The use of different elution shear forces was demonstrated to selectively elute one cell type. This method is an inexpensive, rapid, and effective method to separate target cells from blood samples.