Our protocols for disinfecting nonendocavity and endocavity probes are compliant with sonography guidelines and general disinfecting guidelines. Although limited by a small sample size, our study showed that our protocol for disinfecting endocavity probes seems adequate. With a 25.9% bacterial contamination rate for nonendocavity probes, the adequacy of our protocol for disinfecting nonendocavity probes is more debatable; however, this bacterial contamination rate is at the lower end of the values reported in the literature. With the use of an effective disinfectant, education of sonographers, and implemented changes, we hope to decrease bacterial contamination rates and thus decrease the potential for bacterial transmission.
BackgroundThe COVID-19 pandemic has necessitated efficient and accurate triaging of patients for more effective allocation of resources and treatment.ObjectivesThe objectives are to investigate parameters and risk stratification tools that can be applied to predict mortality within 90 days of hospital admission in patients with COVID-19.MethodsA literature search of original studies assessing systems and parameters predicting mortality of patients with COVID-19 was conducted using MEDLINE and EMBASE.Results589 titles were screened, and 76 studies were found investigating the prognostic ability of 16 existing scoring systems (area under the receiving operator curve (AUROC) range: 0.550–0.966), 38 newly developed COVID-19-specific prognostic systems (AUROC range: 0.6400–0.9940), 15 artificial intelligence (AI) models (AUROC range: 0.840–0.955) and 16 studies on novel blood parameters and imaging.DiscussionCurrent scoring systems generally underestimate mortality, with the highest AUROC values found for APACHE II and the lowest for SMART-COP. Systems featuring heavier weighting on respiratory parameters were more predictive than those assessing other systems. Cardiac biomarkers and CT chest scans were the most commonly studied novel parameters and were independently associated with mortality, suggesting potential for implementation into model development. All types of AI modelling systems showed high abilities to predict mortality, although none had notably higher AUROC values than COVID-19-specific prediction models. All models were found to have bias, including lack of prospective studies, small sample sizes, single-centre data collection and lack of external validation.ConclusionThe single parameters established within this review would be useful to look at in future prognostic models in terms of the predictive capacity their combined effect may harness.
This study examined whether category boundaries between Black and White faces relate to individual attitudes about race. Fifty-seven (20 Black, 37 White) participants completed measures of explicit racism, implicit racism, collective self-esteem (CSE), and racial centrality. Category boundaries between Black and White faces were measured in three separate conditions: following adaptation to (1) a neutral gray background, a sequence of (2) Black or (3) White faces. Two additional conditions measured category boundaries for facial distortion to investigate whether attitudes relate to mechanisms of racial identity alone, or to more global mechanisms of face perception. Using a two-alternative forced-choice staircase procedure, participants indicated whether a test image appeared to be Black or White (or contracted or expanded). Following neutral adaptation, participants with higher CSE showed category boundaries shifted toward faces with a higher percentage of Black features. In addition, the strength of short-term sensitivity shifts following adaptation to Black and White faces was related to explicit and implicit attitudes about race. Sensitivity shifts were weaker when participants scored higher on explicit racism, but were stronger when participants scored higher on implicit but lower on explicit racism. The results of this study indicate that attitudes about race account for some individual differences in natural category boundaries between races as well as the strength of identity aftereffects following face adaptation.
A 53-year-old female presented to the emergency room with a few-weeks' duration of pain and swelling of the lateral aspect of the right foot. She had no history of trauma or recent infections.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.