Genomic Medicine Guidance: A Point-of-Care App for Heritable Thoracic Aortic Diseases
Patil, R.; Ashraf, F.; Dayeh, S. A.; Prakash, S.
Show abstract
Genetic testing can determine familial and personal risks for heritable thoracic aortic aneurysms and dissections (TAD). The 2022 ACC/AHA guidelines for TAD recommend management decisions based on the specific gene mutation. However, many clinicians lack sufficient comfort or insight to integrate genetic information into clinical practice. We therefore developed the Genomic Medicine Guidance (GMG) app, an interactive point-of care tool to inform clinicians and patients about TAD diagnosis, treatment, and surveillance. GMG is a REDCap-based app that combines publicly available genetic data and clinical recommendations based on the TAD guidelines into one translational education tool. TAD genetic information in GMG was sourced from the Montalcino Aortic Consortium, a worldwide collaboration of TAD centers of excellence, and the NIH genetic repositories ClinVar and ClinGen. The app streamlines data on the 13 most frequently mutated TAD genes with 2,286 unique pathogenic mutations that cause TAD so that users receive comprehensive recommendations for diagnostic testing, imaging, surveillance, medical therapy, preventative surgical repair, as well as guidance for exercise safety and management during pregnancy. The app output can be displayed in a clinician view or exported as an informative pamphlet in a patient-friendly format. The overall goal of the GMG app is to make genomic medicine more accessible to clinicians and patients, while serving as a unifying platform for research. We anticipate that these features will be catalysts for collaborative projects that aim to understand the spectrum of genetic variants that contribute to TAD.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- HeartBioPortal2.0: new developments and updates for genetic ancestry and cardiometabolic quantitative traits in diverse human populations 94%
- Color Data v2: a user-friendly, open-access database with hereditary cancer and hereditary cardiovascular conditions datasets 94%
- Integrated ACMG approved genes and ICD codes for the translational research and precision medicine 92%
Similar papers in this journal
Similar papers in this journal
- Rationale and design of the Learning Implementation of Guideline-based decision support system for Hypertension Treatment (LIGHT) Trial and LIGHT-ACD Trial 90%
- Moderate-Intensity Exercise Versus High-Intensity Interval Training to Recover Walking Post-Stroke: Protocol for a Randomized Controlled Trial 89%
- Decision support system to evaluate VENTilation in the Acute Respiratory Distress Syndrome (DeVENT study) – Trial Protocol 89%
Similar papers in this journal
- Development and Validation of Phenotype Classifiers across Multiple Sites in the Observational Health Sciences and Informatics (OHDSI) Network 92%
- A Comparative Analysis of Privacy-Preserving Large Language Models For Automated Echocardiography Report Analysis 92%
- Observer: Creation of a Novel Multimodal Dataset for Outpatient Care Research 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.