Background Very little has been reported about health care workers' (HCWs) adherence to the Centers for Disease Control and Prevention (CDC) guidelines of doffing personal protective equipment (PPE) amid the COVID-19 pandemic. Real-time remote audio-visual doffing surveillance (RADS) system for assisting doffing might reduce the risk of self-contamination. We used this system to determine the incidence of the breach in biosafety during doffing of PPE among HCWs involved in the care of Covid-19 patients. Methods A total of 100 HCWs were enrolled in this observational study who performed duties in the COVID intensive care unit (ICU) of our tertiary care centre. With a real-time RADS system, trained observers from remote locations assisted HCWs during doffing of PPE and noted breach at any step using the CDC doffing checklist. The breach was considered major if committed during removal of gloves/gown/N-95 or if ≥3 errors occurred in any other steps. Results Overall, 40% of the HCWs committed a breach during doffing at least one step. The majority of the errors were observed during hand hygiene (34%), followed by glove removal (12%) and N-95 removal (8%). Nineteen percent of HCWs committed the major breach, out of which 37.5% were done by house-keeping sanitation staff (p = 0.008 and RR 2.85; 95% CI of 1.313-6.19), followed by technicians (22.5%), nursing staff (16.7%) and resident doctors (6.5%). Conclusions Performing doffing using a real-time RADS system is associated with a relatively low incidence of a breach in biosafety compared with earlier studies using an onsite standard observer. Overall adherence of HCWs to the CDC guidelines of doffing PPE was satisfactory. This study highlights the importance of the RADS system during doffing of PPE in a health care setting amid the COVID-19 pandemic.
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http://dx.doi.org/10.7759/cureus.18071 | DOI Listing |
Eur Radiol
January 2025
Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands.
Objectives: The use of deep learning models for quantitative measurements on coronary computed tomography angiography (CCTA) may reduce inter-reader variability and increase efficiency in clinical reporting. This study aimed to investigate the diagnostic performance of a recently updated deep learning model (CorEx-2.0) for quantifying coronary stenosis, compared separately with two expert CCTA readers as references.
View Article and Find Full Text PDFRadiol Imaging Cancer
January 2025
Department of Radiology, University Medical Center Groningen, Groningen, the Netherlands.
Purpose To validate a deep learning (DL) model for predicting the risk of prostate cancer (PCa) progression based on MRI and clinical parameters and compare it with established models. Materials and Methods This retrospective study included 1607 MRI scans of 1143 male patients (median age, 64 years; IQR, 59-68 years) undergoing MRI for suspicion of clinically significant PCa (csPCa) (International Society of Urological Pathology grade > 1) between January 2012 and May 2022 who were negative for csPCa at baseline MRI. A DL model was developed using baseline MRI and clinical parameters (age, prostate-specific antigen [PSA] level, PSA density, and prostate volume) to predict the time to PCa progression (defined as csPCa diagnosis at follow-up).
View Article and Find Full Text PDFJ Ultrasound Med
January 2025
Department of Ultrasonic Medicine, Fetal Medical Centre, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Introduction: Acoustic shadowing is an important benign ultrasound (US) feature for adnexal masses (AMs). To validate the diagnostic performance and interobserver agreement of the 2019 version and 2022 version of Ovarian-Adnexal Reporting and Data System Ultrasound (O-RADS US) and ascertain whether adding acoustic shadowing to O-RADS US v2019 as a benign ultrasound feature can enhance its diagnostic efficacy among junior radiologist.
Methods: This retrospective study included consecutive women with suspected adnexal masses who underwent ultrasound examinations between September 2022 and January 2024.
Radiographics
February 2025
From the Washington University School of Medicine, Mallinckrodt Institute of Radiology, 510 S Kingshighway Blvd, St. Louis, MO 63110.
Annual review of false-negative (FN) mammograms is a mandatory and critical component of the Mammography Quality Standards Act (MQSA) annual mammography audit. FN review can help hone reading skills and improve the ability to detect cancers at mammography. Subtle architectural distortion, asymmetries (seen only on one view), small lesions, lesions with probably benign appearance (circumscribed regular borders), isolated microcalcifications, and skin thickening are the most common mammographic findings when the malignancy is visible at retrospective review of FN mammograms.
View Article and Find Full Text PDFAbdom Radiol (NY)
January 2025
First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Purpose: HER2 expression is crucial for the application of HER2-targeted antibody-drug conjugates. This study aims to construct a predictive model by integrating multiparametric magnetic resonance imaging (mpMRI) based multimodal radiomics and the Vesical Imaging-Reporting and Data System (VI-RADS) score for noninvasive identification of HER2 status in bladder urothelial carcinoma (BUC).
Methods: A total of 197 patients were retrospectively enrolled and randomly divided into a training cohort (n = 145) and a testing cohort (n = 52).
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