Introduction: Localisation methods for surgical excision of impalpable breast lesions have advanced in recent years, with increasing utilization of new wire-free technologies. The Hologic LOCalizer™ radiofrequency identification (RFID) tag is one such device; however, as is the case when new technologies are first introduced, little is known about clinical experiences, potential complications, and learning used to overcome perioperative challenges when changing from guidewires to RFID tags. This study reports shared learning experiences of clinicians using the LOCalizer™ as part of the national iBRA-NET localisation study.
Methods: This mixed-methods study captured shared-learning themes relating to LOCalizer™ usage as part of a multicentre prospective registry study, which collected data on each LOCalizer™ placement. Prospective, anonymized clinical and demographic data were collected and managed using a Research Electronic Data Capture (REDCap) database. Shared learning was captured prospectively as part of the registry study between January 2021 and July 2022, combined with a virtual qualitative webinar-style focus group. Learning events were then coded, grouped by theme, and suggestions for practice were produced.
Results: Twenty-four UK breast units submitted data on 1188 patient records pertaining to RFID-guided localisation between January 2021 and July 2022, of which 59 (5.0%) included a shared-learning event. The virtual webinar was attended by 108 healthcare professionals, including oncoplastic breast surgeons and breast radiologists. Shared-learning themes were categorized into preoperative, intraoperative, and postoperative events.
Conclusions: By sharing learning outcomes associated with localisation techniques in this paper, the aim is to shorten the learning curve and potential for adverse events for users new to the LOCalizer™ technique.
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http://dx.doi.org/10.1016/j.crad.2024.06.014 | DOI Listing |
BMC Nurs
December 2024
Institute of Health and Allied Professions, Nottingham Trent University, Nottingham, UK.
Background: This study was undertaken to understand the role of the Health Care Assistants and how they negotiate roles and responsibilities with Registered Nurses in adult acute hospitals.
Methods: The qualitative approach of focused ethnography used non-participant observation and interviews with staff from four acute wards. Field notes and interview data, analysed using NVIVO10, moved data from description through explanation, interpretation and identification of themes.
Front Endocrinol (Lausanne)
December 2024
Department of Neurosurgery, Binhai Branch of Nation al Regional Medical Center, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, China.
Objective: Preoperative prediction of visual recovery after pituitary adenoma resection surgery remains challenging. This study aimed to investigate the value of clinical and radiological features in preoperatively predicting visual outcomes after surgery.
Methods: Patients undergoing endoscopic transsphenoidal surgery (ETS) for pituitary adenoma were included in this retrospective and prospective study.
Front Immunol
December 2024
Department of Dermatology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Introduction: Bullous pemphigoid (BP) and prurigo nodularis (PN) are chronic pruritic skin diseases that severely impact patients' quality of life. Despite the widespread attention these two diseases have garnered within the dermatological field, the specific pathogenesis, particularly the molecular mechanisms underlying the pruritus, remains largely unclear. Limited clinical sequencing studies focusing on BP and PN have hindered the identification of pathological mechanisms and the exploration of effective treatment strategies.
View Article and Find Full Text PDFRadiother Oncol
December 2024
Department of Digital Medicine, School of Biomedical Engineering and Medical Imaging, Army Medical University, Chongqing 400038, China. Electronic address:
Background And Purpose: Accurate segmentation of the clinical target volume (CTV) is essential to deliver an effective radiation dose to tumor tissues in cervical cancer radiotherapy. Also, although automated CTV segmentation can reduce oncologists' workload, challenges persist due to the microscopic spread of tumor cells undetectable in CT imaging, low-intensity contrast between organs, and inter-observer variability. This study aims to develop and validate a multi-task feature fusion network (MTF-Net) that uses distance-based information to enhance CTV segmentation accuracy.
View Article and Find Full Text PDFChemosphere
December 2024
Department of Civil and Environmental Engineering, Dongguk University-Seoul, Seoul 04620, South Korea. Electronic address:
Even at trace concentrations, micropollutants, including pesticides and pharmaceuticals, pose considerable ecological risks, and the increasing presence of synthetic chemical substances in aquatic systems has emerged as a growing concern. Moreover, limited machine-learning (ML) approaches exist for analyzing environmental data, and the increasing complexity of ML models has made it challenging to understand predictor-outcome relationships. In particular, understanding complex interactions among multiple variables remains challenging.
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