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Antepartum multidisciplinary approach improves postpartum pain scores in patients with opioid use disorder.
J Perinat Med
January 2025
Department of Obstetrics, Gynecology, and Reproductive Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, New York, USA.
Objectives: Pregnancies affected by opioid use disorder (OUD) face difficulties with postpartum pain control. This study aims to determine if prenatal anesthesia consultation for patients on medication for opioid use disorder (MOUD) affects maternal postpartum pain control.
Methods: This is a retrospective cohort study of pregnant patients diagnosed on MOUD who received prenatal care and delivered at a single academic institution between January 2017 and July 2023.
Refining breast cancer genetic risk and biology through multi-ancestry fine-mapping analyses of 192 risk regions.
Nat Genet
January 2025
Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA.
Genome-wide association studies have identified approximately 200 genetic risk loci for breast cancer, but the causal variants and target genes are mostly unknown. We sought to fine-map all known breast cancer risk loci using genome-wide association study data from 172,737 female breast cancer cases and 242,009 controls of African, Asian and European ancestry. We identified 332 independent association signals for breast cancer risk, including 131 signals not reported previously, and for 50 of them, we narrowed the credible causal variants down to a single variant.
View Article and Find Full Text PDFPrioritizing cases from a multi-institutional cohort for a dataset of pathologist annotations.
J Pathol Inform
January 2025
U.S. Food and Drug Administration, Center for Devices and Radiological Health, Office of Science and Engineering Laboratories, Division of Imaging, Diagnostics, and Software Reliability, Silver Spring, MD, United States of America.
Objective: With the increasing energy surrounding the development of artificial intelligence and machine learning (AI/ML) models, the use of the same external validation dataset by various developers allows for a direct comparison of model performance. Through our High Throughput Truthing project, we are creating a validation dataset for AI/ML models trained in the assessment of stromal tumor-infiltrating lymphocytes (sTILs) in triple negative breast cancer (TNBC).
Materials And Methods: We obtained clinical metadata for hematoxylin and eosin-stained glass slides and corresponding scanned whole slide images (WSIs) of TNBC core biopsies from two US academic medical centers.
Background: Few treatments are available for individuals with marked treatment-resistant depression (TRD).
Objective: Evaluate the safety and effectiveness of FDA-approved adjunctive vagus nerve stimulation (VNS) in patients with marked TRD.
Methods: This 12-month, multicenter, double-blind, sham-controlled trial included 493 adults with marked treatment-resistant major depression who were randomized to active or no-stimulation sham VNS for 12 months.
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