Objectives: This study aimed to explore how medical students experience contacts with real patients and what they learn from them.
Methods: We carried out a post hoc, single-group study in one teaching sector of a 5-year, problem-based, horizontally integrated, outcome-based and community-oriented undergraduate programme, in which students lacked clinical exposure in the pre-clerkship phase. Subjects comprised five cohorts of students on their first clerkships. Data consisted of purposively selected, voluntary, self-report statements regarding real patient learning (RPL). Constant comparative analysis was performed by two independent researchers.
Results: Respondents valued patients as an instructional resource that made learning more real. They reported learning through visual pattern recognition as well as through dialogue and physical examination. They more often used social than professional language to describe RPL. They reported affective outcomes including enhanced confidence, motivation, satisfaction and a sense of professional identity. They also reported cognitive outcomes including perspective, context, a temporal dimension, and an appreciation of complexity. Real patient learning helped respondents link theory learned earlier with reality as represented by verbal, visual and auditory experiences. It made learning easier, more meaningful and more focused. It helped respondents acquire complex skills and knowledge. Above all, RPL helped learners to remember subject matter. Most negative responses concerned the difficulty of acquiring appropriate experience, but RPL made a minority of respondents feel uncomfortable and incompetent.
Conclusions: Real patient learning led to a rich variety of learning outcomes, of which at least some medical students showed high metacognitive awareness. Sensitivity from clinical mentors towards the positive and negative outcomes of RPL reported here could support reflective clinical learning.
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http://dx.doi.org/10.1111/j.1365-2923.2009.03508.x | DOI Listing |
Background: Our previous study identified that Sildenafil (a phosphodiesterase type 5 [PDE5] inhibitor) is a candidate repurposable drug for Alzheimer's Disease (AD) using in silico network medicine approach. However, the clinically meaningful size and mechanism-of-actions of sildenafil in potential prevention and treatment of AD remind unknown.
Method: We conducted new patient data analyses using both the MarketScan® Medicare with Supplemental database (n = 7.
Alzheimers Dement
December 2024
The University of Texas Health Science Center at Houston, Houston, TX, USA.
Background: Developing drugs for treating Alzheimer's disease (AD) has been extremely challenging and costly due to limited knowledge on underlying biological mechanisms and therapeutic targets. Repurposing drugs or their combination has shown potential in accelerating drug development due to the reduced drug toxicity while targeting multiple pathologies.
Method: To address the challenge in AD drug development, we developed a multi-task machine learning pipeline to integrate a comprehensive knowledge graph on biological/pharmacological interactions and multi-level evidence on drug efficacy, to identify repurposable drugs and their combination candidates RESULT: Using the drug embedding from the heterogeneous graph representation model, we ranked drug candidates based on evidence from post-treatment transcriptomic patterns, mechanistic efficacy in preclinical models, population-based treatment effect, and Phase 2/3 clinical trials.
Alzheimers Dement
December 2024
Case Western Reserve University, Cleveland, OH, USA.
Background: Traumatic Brain Injury (TBI) is one of the most common nonheritable causes of Alzheimer's disease (AD). However, there is lack of effective treatment for both AD and TBI. We posit that network-based integration of multi-omics and endophenotype disease module coupled with large real-world patient data analysis of electronic health records (EHR) can help identify repurposable drug candidates for the treatment of TBI and AD.
View Article and Find Full Text PDFBackground: Small, soluble oligomers, rather than mature fibrils, are the major neurotoxic agents in Alzheimer's disease (AD). In the last few years, Aprile and co-workers designed and purified a single-domain antibody (sdAb), called DesAb-O, with high specificity for Aβ oligomeric conformers. Recently, Cascella and co-workers showed that DesAb-O can selectively detect synthetic Aβ oligomers both in vitro and in cultured cells, neutralizing their associated neuronal dysfunction.
View Article and Find Full Text PDFIt is well recognised that Alzheimer's disease and related dementia disorders (ADRD) are associated with very high societal costs. The total global costs of dementia have been estimated to over 1.3 trillion US$ annually (Wimo, Seeher et al.
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