Evidence map›Paper›PMID 36964821›Full record

ReviewCurrent atherosclerosis reports2023

Brief Review: Racial and Ethnic Disparities in Cardiovascular Care with a Focus on Congenital Heart Disease and Precision Medicine.

Joseph Bayne, Jonah Garry, Michelle A Albert

Open access · hybridFull text readReview
In one paragraph

Review in Current atherosclerosis reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 2 pooled it
8.6field-weighted citation impact, top 3% of its field
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

6 citing papers in PubMed, 2 syntheses or guidelines pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Review
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Joseph BayneDivision of Cardiology, Department of Medicine, University of California San Francisco, 505 Parnassus Ave, San Francisco, CA, 94143-0474, USA. Joseph.bayne@ucsf.edu.ORCID 0000-0002-0690-8402
Jonah GarryDepartment of Medicine, University of California San Francisco, San Francisco, CA, USA.
Michelle A AlbertCeNter for the StUdy of AdveRsiTy and CardiovascUlaR DiseasE (NURTURE Center), Division of Cardiology, Department of Medicine, University of California at San Francisco School of Medicine, San Francisco, CA, USA.
University of California, San Francisco · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewThis is a brief review about racial and ethnic disparities in healthcare with focused attention to less frequently covered areas in the literature such as adult congenital heart disease, artificial intelligence, and precision medicine. Although diverse racial and ethnic populations such as Black and Hispanic groups are at an increased risk for CHD and have worse related outcomes, they are woefully underrepresented in large clinical trials. Additionally, although artificial intelligence and its application to precision medicine are touted as a means to individualize cardiovascular treatment and eliminate racial and ethnic bias, serious concerns exist about insufficient and inadequate available information from diverse racial and ethnic groups to facilitate accurate care. This review discusses relevant data to the aforementioned topics and the associated nuances. RECENT

findingsRecent studies have shown that racial and ethnic minorities have increased morbidity and mortality related to congenital heart disease. Artificial intelligence, one of the chief methods used in precision medicine, can exacerbate racial and ethnic bias especially if inappropriate algorithms are utilized from populations that lack racial and ethnic diversity. Dedicated resources are needed to engage diverse populations to facilitate participation in clinical and population-based studies to eliminate racial and ethnic healthcare disparities in adult congenital disease and the utilization of artificial intelligence to improve health outcomes in all populations.

Indexed as

Heart Defects, CongenitalPrecision MedicineAdultArtificial IntelligenceEthnicityHealthcare DisparitiesHumansUnited StatesAdult congenital heart diseaseCardiovascular diseasePrecision medicineRacial and ethnic disparitiesSocial determinants of health

Identifiers

PMID36964821
PMCPMC10039345
OpenAlexW4360942093

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read13
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.