Background A socioculturally appropriate appreciation of dignity is pivotal to the effective provision of care for dying patients. Yet concepts of dignity remain poorly defined. To address this gap in understanding and enhance dignity conserving end-of-life care, a review of current concepts of dignity is proposed. Methods To address its primary research question “How do patients conceive the concept of dignity at the end of life?”, this review appraises regnant concepts and influences of dignity, and evaluates current dignity conserving practices. To enhance accountability, transparency and reproducibility, this review employs the Ring Theory of Personhood (RToP) as its theoretical lens to guide a Systematic Evidence Based Approach guided Systematic Scoping Review (SSR in SEBA) of patient perspectives of dignity. Three independent teams of reviewers independently analysed included articles from a structured search of PubMed, Embase, PsycINFO, Scopus, CINAHL and Cochrane Databases using thematic and content analyses. The themes and categories identified were compared and combined using the Funnelling Process to create domains that guide the discussion that follows. Results Seventy-eight thousand five hundred seventy-five abstracts were identified, 645 articles were reviewed, and 127 articles were included. The three domains identified were definitions of dignity, influences upon perceptions of dignity, and dignity conserving care. Conclusions This SSR in SEBA affirms the notion that dignity is intimately entwined with self-concepts of personhood and that effective dignity conserving measures at the end of life must be guided by the patient’s concept of dignity. This SSR in SEBA posits that such personalised culturally sensitive, and timely support of patients, their family and loved ones may be possible through the early and longitudinal application of a RToP based tool.
Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide. Although alpha fetoprotein (AFP) remains a commonly used serological marker of HCC, the sensitivity and specificity of AFP in detecting HCC is often limited. Exosomal RNA has emerged as a promising diagnostic tool for various cancers, but its use in HCC detection has yet to be fully explored. Here, we employed Machine Learning on 114,602 exosomal RNAs to identify a signature that can predict HCC. The exosomal expression data of 118 HCC patients and 112 healthy individuals were stratified split into Training, Validation and Unseen Test datasets. Feature selection was then performed on the initial training dataset using permutation importance, and the predictive performance of the selected features were tested on the validation dataset using Support Vector Machine (SVM) Classifier. A minimum of nine features were identified to be predictive of HCC and these nine features were then evaluated across six different models in an unseen test set. These features, mainly in the immune, platelet/neutrophil and cytoskeletal pathways, exhibited good predictive performance with ROC-AUC from 0.79–0.88 in the unseen test set. Hence, these nine exosomal RNAs have potential to be clinically useful minimally invasive biomarkers for HCC.
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.