Evidence map›Paper›PMID 37704309›Full record

ArticleJournal of the American College of Cardiology2023

Association of Coronary Artery Calcium Detected by Routine Ungated CT Imaging With Cardiovascular Outcomes.

Allison W Peng, Ramzi Dudum, Sneha S Jain, David J Maron, Bhavik N Patel, Nishith Khandwala, David Eng, Akshay S Chaudhari, Alexander T Sandhu, Fatima Rodriguez

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the American College of Cardiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 2 pooled it
11.7field-weighted citation impact, top 1% 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

37 citing papers in PubMed, 2 syntheses or guidelines pooled it, 51 citations in OpenAlex.

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  11. Opportunistic Screening on Chest CT, From theAJR. American journal of roentgenology · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 1 country.

Allison W PengDepartment of Medicine, Stanford University, Stanford, California, USA; Stanford Cardiovascular Institute, Stanford University, Stanford, California, USA. Electronic address: https://twitter.com/AllisonWPeng.
Ramzi DudumStanford Cardiovascular Institute, Stanford University, Stanford, California, USA; Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, California, USA.
Sneha S JainStanford Cardiovascular Institute, Stanford University, Stanford, California, USA; Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, California, USA.
David J MaronStanford Cardiovascular Institute, Stanford University, Stanford, California, USA; Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, California, USA; Stanford Prevention Research Center, Department of Medicine, Stanford University, Stanford, California, USA.
Bhavik N PatelDepartment of Radiology, Mayo Clinic, Phoenix, Arizona, USA.
Nishith KhandwalaBunkerhill Health, Palo Alto, California, USA.
David EngBunkerhill Health, Palo Alto, California, USA.
Akshay S ChaudhariStanford Cardiovascular Institute, Stanford University, Stanford, California, USA; Department of Radiology, Stanford University, Stanford, California, USA; Department of Biomedical Data Science, Stanford University, Stanford, California, USA.
Alexander T SandhuStanford Cardiovascular Institute, Stanford University, Stanford, California, USA; Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, California, USA; Veteran's Affairs Palo Alto Healthcare System, Palo Alto, California, USA. Electronic address: https://twitter.com/ATSandhu.
Fatima RodriguezStanford Cardiovascular Institute, Stanford University, Stanford, California, USA; Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, California, USA. Electronic address: frodrigu@stanford.edu.
Cardiovascular Institute of the South · USMayo Clinic Hospital · USTwitter (United States) · USVA Palo Alto Health Care System · 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
Novel Incidental Calcium Evaluation (NICE)R01HL169345 · NHLBI · STANFORD UNIVERSITY · PI Imon Banerjee, Akshay Chaudhari · 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
The Effect of Value-based Payment on Heart Failure Quality of Care (Value-HF)K23HL151672 · NHLBI · STANFORD UNIVERSITY · PI SANDHU, ALEXANDER · 2020 to 2024
$854k
NHLBI NIH HHS K01 HL144607NHLBI NIH HHS K23 HL151672NHLBI NIH HHS R01 HL167974NHLBI NIH HHS R01 HL169345
6 · The paper itself

Abstract

backgroundCoronary artery calcium (CAC) is a strong predictor of cardiovascular events across all racial and ethnic groups. CAC can be quantified on nonelectrocardiography (ECG)-gated computed tomography (CT) performed for other reasons, allowing for opportunistic screening for subclinical atherosclerosis.

objectivesThe authors investigated whether incidental CAC quantified on routine non-ECG-gated CTs using a deep-learning (DL) algorithm provided cardiovascular risk stratification beyond traditional risk prediction methods.

methodsIncidental CAC was quantified using a DL algorithm (DL-CAC) on non-ECG-gated chest CTs performed for routine care in all settings at a large academic medical center from 2014 to 2019. We measured the association between DL-CAC (0, 1-99, or ≥100) with all-cause death (primary outcome), and the secondary composite outcomes of death/myocardial infarction (MI)/stroke and death/MI/stroke/revascularization using Cox regression. We adjusted for age, sex, race, ethnicity, comorbidities, systolic blood pressure, lipid levels, smoking status, and antihypertensive use. Ten-year atherosclerotic cardiovascular disease risk was calculated using the pooled cohort equations.

resultsOf 5,678 adults without ASCVD (51% women, 18% Asian, 13% Hispanic/Latinx), 52% had DL-CAC >0. Those with DL-CAC ≥100 had an average 10-year ASCVD risk of 24%; yet, only 26% were on statins. After adjustment, patients with DL-CAC ≥100 had increased risk of death (HR: 1.51; 95% CI: 1.28-1.79), death/MI/stroke (HR: 1.57; 95% CI: 1.33-1.84), and death/MI/stroke/revascularization (HR: 1.69; 95% CI: 1.45-1.98) compared with DL-CAC = 0.

conclusionsIncidental CAC ≥100 was associated with an increased risk of all-cause death and adverse cardiovascular outcomes, beyond traditional risk factors. DL-CAC from routine non-ECG-gated CTs identifies patients at increased cardiovascular risk and holds promise as a tool for opportunistic screening to facilitate earlier intervention.

Indexed as

AtherosclerosisMyocardial InfarctionStrokeAdultCalciumCoronary VesselsFemaleHumansMaleTomography, X-Ray ComputedCalciumcardiovascular outcomescoronary artery calciumnongated computed tomographyprimary preventionrisk predictionscreening

Identifiers

PMID37704309
PMCPMC11009374
OpenAlexW4386596786

What Socratic 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 Socratic graph.