Objective: The aim of this study was to explore what women are saying about noninvasive prenatal testing (NIPT) in online discussion forums.
Methods: Inductive thematic analysis of content from 13 open-access discussion forums written in English from 11 popular maternity websites from four different countries (the United Kingdom, United States, New Zealand, and Australia) between 2013 to 2017 (n = 127 women).
Results: The forums were a space where women were provided with emotional support and advice in making their decision about NIPT as screening option. Justifications were made for paying for NIPT with terminology echoing commercial advertising "price was high … well worth the peace of mind." Paying for NIPT was referred to as a shopping exercise to find the "best deal." Women in the United States often talked about having to choose between NIPT and a scan because their insurance "won't pay for both." Commercial influence on maternity care providers' preference for different brands of NIPT was evident: "my doctor only uses [brand]. He said it's the best one on the market."
Conclusion: Our findings highlight women's need for experiential information in prenatal screening counselling and how NIPT commercialization influences both routinized perspectives, and access, which may affect informed choice and best evidence screening practice.
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http://dx.doi.org/10.1002/pd.5500 | DOI Listing |
Purpose: This study investigates the capabilities of ultrasonography (US) in determing the stage of orbital inflammation in patients with granulomatosis with polyangiitis (GPA).
Material And Methods: The study included 24 patients (8 men and 16 women) with diffuse orbital tissue involvement in GPA. Group 1 (active stage) included nine patients, while group 2 (inactive stage) consisted of 18 patients.
ACS Appl Mater Interfaces
December 2024
Institute of Translational Medicine, Faculty of Health Sciences & Ministry of Education Frontiers Science Center for Precision Oncology, University of Macau, Taipa 999078, Macau, China.
Levels of tissue oxygenation and collagen regeneration are critical indicators in the early evaluation of wound healing. Traditionally, these factors have been assessed using separate instruments and different methodologies. Here, we adopt the spatially averaged phosphorescence lifetime approach using Re-diimine complexes (Re-probe) to enable simultaneous quantification of these two critical factors in healing wounds.
View Article and Find Full Text PDFTomography
December 2024
Department of Medical Imaging and Radiological Science, I-Shou University, Kaohsiung City 824005, Taiwan.
Breast cancer is a leading cause of mortality among women in Taiwan and globally. Non-invasive imaging methods, such as mammography and ultrasound, are critical for early detection, yet standalone modalities have limitations in regard to their diagnostic accuracy. This study aims to enhance breast cancer detection through a cross-modality fusion approach combining mammography and ultrasound imaging, using advanced convolutional neural network (CNN) architectures.
View Article and Find Full Text PDFNoncoding RNA
December 2024
Department of Genomic Medicine, D.O. Ott Research Institute for Obstetrics, Gynecology, and Reproduction, St. Petersburg 199034, Russia.
Pre-eclampsia (PE) is a serious condition affecting 2-8% of pregnancies worldwide, leading to high maternal and fetal morbidity and mortality. MicroRNAs (miRNAs), small non-coding RNA molecules, have emerged as potential biomarkers for various pregnancy-related pathologies, including PE. MiRNAs in plasma and serum have been extensively studied, but urinary miRNAs remain underexplored, especially during early pregnancy.
View Article and Find Full Text PDFJ Imaging
December 2024
Department of Computing, Electronics and Mechatronics, Universidad de las Américas Puebla, Sta. Catarina Martir, San Andrés Cholula 72810, Mexico.
Breast cancer is one of the leading causes of death for women worldwide, and early detection can help reduce the death rate. Infrared thermography has gained popularity as a non-invasive and rapid method for detecting this pathology and can be further enhanced by applying neural networks to extract spatial and even temporal data derived from breast thermographic images if they are acquired sequentially. In this study, we evaluated hybrid convolutional-recurrent neural network (CNN-RNN) models based on five state-of-the-art pre-trained CNN architectures coupled with three RNNs to discern tumor abnormalities in dynamic breast thermographic images.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!