Evidence map›Paper›PMID 38234729›Full record

ArticlemedRxiv : the preprint server for health sciences2023

Genomic Medicine Guidance: A Point-of-Care App for Heritable Thoracic Aortic Diseases.

Rohan Patil, Fatima Ashraf, Samer Abu Dayeh, Siddharth K Prakash

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Rohan PatilDepartment of Internal Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, Texas, USA.
Fatima AshrafMcWilliams School of Bioinformatics, University of Texas Health Science Center at Houston, Houston, Texas, USA.
Samer Abu DayehDepartment of Internal Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, Texas, USA.
Siddharth K PrakashDepartment of Internal Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, Texas, USA.
The University of Texas Health Science Center at Houston · US

Funding

Convalescent Plasma to Limit Coronavirus Associated ComplicationsUL1TR003167 · NCATS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI KARP, DANIEL D, MCPHERSON, DAVID D · 2019 to 2023
$45.3M
NCATS NIH HHS UL1 TR003167
6 · The paper itself

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.

Indexed as

aortic dissectiondecision supportgenomic medicinepoint-of-carethoracic aortic aneurysm

Identifiers

PMID38234729
PMCPMC10793513
OpenAlexW4390236805

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.