Evidence map›Paper›PMID 35159985›Full record

ArticleJournal of clinical medicine2022

Usefulness of Cardiac Computed Tomography in Coronary Risk Prediction: A Five-Year Follow-Up of the SPICA Study (Secure Prevention with Imaging of the Coronary Arteries).

David Viladés-Medel, Irene R Dégano, Isaac Subirana, Martin Descalzo, Mireia Padilla, Xavier Mundet, Francesc Carreras Costa, Xavier Alomar Serrallach, Anna Camps, Roberto Elosua and 2 more

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Observational
  2. Article
  3. Article
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  5. 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

12 authors at 3 institutions in 1 country.

David Viladés-MedelCardiac Imaging Unit, Cardiology Department, Hospital de la Santa Creu i Sant Pau, Universitat Autónoma de Barcelona (UAB), 08193 Barcelona, Spain.ORCID 0000-0002-3638-9703
Irene R DéganoCIBER de Enfermedades Cardio-Vasculares (CIBERCV), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain.
Isaac SubiranaCIBER de Enfermedades Cardio-Vasculares (CIBERCV), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain.
Martin DescalzoCardiac Imaging Unit, Cardiology Department, Hospital de la Santa Creu i Sant Pau, Universitat Autónoma de Barcelona (UAB), 08193 Barcelona, Spain.ORCID 0000-0003-3736-7191
Mireia PadillaCardiac Imaging Unit, Cardiology Department, Hospital de la Santa Creu i Sant Pau, Universitat Autónoma de Barcelona (UAB), 08193 Barcelona, Spain.
Xavier MundetUniversity Public Health Center El Carmel, Department of Medicine, Universitat Autonoma de Barcelona (UAB), 08193 Barcelona, Spain.
Francesc Carreras CostaCardiac Imaging Unit, Cardiology Department, Hospital de la Santa Creu i Sant Pau, Universitat Autónoma de Barcelona (UAB), 08193 Barcelona, Spain.
Xavier Alomar SerrallachRadiology Department, Clínica Creu Blanca, 08034 Barcelona, Spain.
Anna CampsCIBER de Enfermedades Cardio-Vasculares (CIBERCV), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain.ORCID 0000-0001-9644-8421
Roberto ElosuaCIBER de Enfermedades Cardio-Vasculares (CIBERCV), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain.
Jaume MarrugatCIBER de Enfermedades Cardio-Vasculares (CIBERCV), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain.
Rubén Leta PetraccaCardiac Imaging Unit, Cardiology Department, Hospital de la Santa Creu i Sant Pau, Universitat Autónoma de Barcelona (UAB), 08193 Barcelona, Spain.
Universitat Autònoma de Barcelona · ESInstituto de Salud Carlos III · ESUniversitat de Vic - Universitat Central de Catalunya · ES

Funding

Spain's Ministry of Science and Innovation (Madrid, Spain), co-financed with European Union European Regional Development Funds [CIBERCV (CB16/11/00229, 00276)]the Health Departament of the Generalitat de Catalunya (Barcelona, Spain) through the Agència de Gestió d'Ajuts Universitaris de Recerca de Catalunya (AGAUR) [2017SGR222]
6 · The paper itself

Abstract

Accurate identification of individuals at high coronary risk would reduce acute coronary syndrome incidence and morbi-mortality. We analyzed the effect on coronary risk prediction of adding coronary artery calcification (CAC) and Segment Involvement Score (SIS) to cardiovascular risk factors. This was a prospective cohort study of asymptomatic patients recruited between 2013-2017. All participants underwent a coronary computed tomography angiography to determine CAC and SIS. The cohort was followed-up for a composite endpoint of myocardial infarction, coronary angiography and/or revascularization (median = five years). Discrimination and reclassification of the REGICOR function with CAC/SIS were examined with the Sommer's D index and with the Net reclassification index (NRI). Nine of the 251 individuals included had an event. Of the included participants, 94 had a CAC = 0 and 85 a SIS = 0, none of them had an event. The addition of SIS or of SIS and CAC to the REGICOR risk function significantly increased the discrimination capacity from 0.74 to 0.89. Reclassification improved significantly when SIS or both scores were included. CAC and SIS were associated with five-year coronary event incidence, independently of cardiovascular risk factors. Discrimination and reclassification of the REGICOR risk function were significantly improved by both indexes, but SIS overrode the effect of CAC.

Indexed as

cardiac computed tomographycoronary artery calciumcoronary artery disease riskprimary prevention

Identifiers

PMID35159985
PMCPMC8836950
OpenAlexW4205637678

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.