Evidence map›Paper›PMID 31584125›Full record

ReviewCurrent treatment options in cardiovascular medicine2019

Coronary Computed Tomography Angiography: Enhancing Risk Stratification and Diagnosis of Cardiovascular Disease in Women.

Sara Karnib, Kavitha M Chinnaiyan

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current treatment options in cardiovascular medicine, 2019. 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
0.3field-weighted citation impact, top 36% 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, 5 citations in OpenAlex.

  1. Review
  2. 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

2 authors at 1 institution in 1 country.

Sara KarnibDepartment of Cardiovascular Medicine, Beaumont Health-Royal Oak, 3601 West 13 Mile Road, Royal Oak, MI, 48073, USA.
Kavitha M ChinnaiyanDepartment of Cardiovascular Medicine, Beaumont Health-Royal Oak, 3601 West 13 Mile Road, Royal Oak, MI, 48073, USA. kavitha.chinnaiyan@beaumont.org.
Beaumont Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewThere are numerous gender- and sex-based differences that contribute to the increased morbidity and mortality related to atherosclerotic cardiovascular disease (ASCVD) in women. Early detection of risk and targeted management of atherosclerotic disease is fundamental to reduce ASCVD risk and improve outcomes in women. In this review, we examine the utility of cardiac computed tomography (CT) and coronary CT angiography (CTA) in three ASCVD scenarios including coronary artery calcium scoring for risk stratification in asymptomatic women, and coronary CTA for diagnosis and prognosis of stable ischemic heart disease and acute chest pain. The risks of radiation exposure and the potential applications of novel technologies in women are explored. RECENT

findingsCTA provides the capabilities of early recognition and management of nonobstructive coronary artery disease (CAD). Recent advancements in plaque composition and morphology further enhance the prognostic yield from coronary CTA. Innovations in stress perfusion and computational fluid dynamics allow for evaluation of physiological measures of ischemia. In addition, developments in artificial intelligence (AI) may also help unlock a deeper understanding of atherosclerosis and risk in women. Coronary CTA is an accurate and useful modality for early detection and management of ASCVD in women. Novel technologies hold great promise for furthering our understanding of sex-specific pathophysiology and potential improvement in clinical management and outcomes.

Indexed as

Coronary Calcium ScoreCoronary CT angiographyMortalitySex-specific

Identifiers

PMID31584125
OpenAlexW2978763897

What OpenQuestion holds

Textmetadata
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.