Evidence map›Paper›PMID 38548466›Full record

ReviewThe Medical clinics of North America2024

Racial and Ethnic Disparities in the Management of Chronic Coronary Disease.

Wilson Lay Tang, Fatima Rodriguez

Open access · greenAbstract readReview
In one paragraph

Review in The Medical clinics of North America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-weighted citation impact, top 22% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
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

2 authors at 2 institutions in 1 country.

Wilson Lay TangDepartment of Medicine, Stanford University, 300 Pasteur Drive, L154, Stanford, CA 94305-5133, USA.
Fatima RodriguezDivision of Cardiovascular Medicine and Cardiovascular Institute, Department of Medicine, Center for Academic Medicine, Stanford University School of Medicine, Stanford, CA, USA. Electronic address: frodrigu@stanford.edu.
Cardiovascular Institute of the South · USStanford University · US

Funding

Opportunistic Atherosclerotic Cardiovascular Disease Risk Estimation at Abdominal CTs with Robust and Unbiased Deep LearningR01HL167974 · NHLBI · STANFORD UNIVERSITY · PI Imon Banerjee, Akshay Chaudhari · 2023 to 2026
$2.4M
Adherence Determinants in the Health Electronic Record Evaluation of Statins (ADHERES)R01HL168188 · NHLBI · STANFORD UNIVERSITY · PI Fatima Rodriguez · 2024 to 2026
$2.1M
SURPASS: (Statin Use and Risk Prediction of Atherosclerotic Cardiovascular Disease in minority Subgroups)K01HL144607 · NHLBI · STANFORD UNIVERSITY · PI RODRIGUEZ, FATIMA · 2019 to 2023
$856k
NHLBI NIH HHS K01 HL144607NHLBI NIH HHS R01 HL167974NHLBI NIH HHS R01 HL168188
6 · The paper itself

Abstract

Chronic coronary disease (CCD) comprises a continuum of conditions that include obstructive and non-obstructive coronary artery disease with or without prior acute coronary syndrome. Racial and ethnic representation disparities are pervasive in CCD guideline-informing clinical trials and evidence-based management. These disparities manifest across the entire spectrum of CCD management, spanning from non-pharmacological lifestyle changes to guideline-directed medical therapy, and cardiac rehabilitation to invasive procedures. Recognizing and addressing the historical factors underlying these disparities is crucial for enhancing the quality and equity of CCD management within an increasingly diverse population.

Indexed as

Coronary DiseaseRacial GroupsChronic DiseaseHumansChronic coronary diseaseDisparitiesEthnicityManagementRace

Identifiers

PMID38548466
PMCPMC10979033
OpenAlexW4389943281

What OpenQuestion holds

Textmetadata
LicenceTDM
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.