Publications by authors named "T Westover"
Article Synopsis
- Tandem duplications (TDs) in the UBTF gene are a recently identified genetic alteration linked to pediatric and adult acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS), establishing UBTF-TD as a distinct subtype of AML.
- A study of 27 pediatric patients revealed that UBTF-TD is commonly associated with symptoms like cytopenia and characteristic changes in bone marrow, such as erythroid hyperplasia and trilineage dysplasia.
- The findings suggest that patients with MDS and AML exhibiting UBTF-TD have similar prognoses, indicating that both conditions may represent different manifestations of the same underlying disease.
Purpose: Advances in fetal fraction amplification in prenatal cell-free DNA screening now allow for high-resolution detection of copy-number variants (CNVs). However, approaches to interpreting CNVs as part of a primary screen are still evolving and require consensus. Here, we present a conservative, patient-centered framework for reporting fetal CNVs.
View Article and Find Full Text PDFPurpose: Clinically significant copy-number variants (CNVs) occur in 1% to 2% of pregnancies and are difficult to detect via prenatal cell-free DNA (cfDNA) screening because of the low fraction of fetal-derived cfDNA in maternal plasma. Here, we use fetal fraction amplification (FFA) and improved computational algorithms to enhance the resolution and sensitivity of CNV detection.
Methods: We implemented and characterized the performance of a hidden Markov model that identifies fetal CNVs.
Article Synopsis
- Unstructured and structured data in electronic health records (EHR) can provide valuable insights for research, but extracting this information can be challenging; researchers introduced an automated model to identify patients with Alzheimer's Disease, related dementias (ADRD), and mild cognitive impairment (MCI).
- The study involved a sample of 3,626 outpatient adults, using medical notes and diagnoses from chart reviews to develop a logistic regression model that predicts MCI/ADRD diagnoses with high performance metrics.
- The model demonstrated impressive accuracy (99.88%) and other metrics (like AUROC of 0.98), showing that automated EHR phenotyping could effectively facilitate large-scale research on MCI/ADRD.
Objective: 22q11.2 deletion syndrome (DS) is a serious condition with a range of features. The small microdeletion causing 22q11.
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