Evidence map›Paper›PMID 39949422›Full record

ArticleEuropean heart journal open2025

Health improvements by understanding residual risk in coronary artery disease and new targets for prevention/treatment: rationale and research protocol of the HURRICANE project.

Chiara Caselli, Mariaelena Occhipinti, Katia Pane, Carmelo De Gori, Silvia Rocchiccioli, Nicoletta Botto, Concetta Prontera, Carlo Cavaliere, Rosetta Ragusa, Cecilia Vecoli and 11 more

Abstract read
In one paragraph

Article in European heart journal open, 2025. 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
–field-weighted citation impact
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.

  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

21 authors.

Chiara CaselliInstitute of Clinical Physiology, Department of Biomedical Sciences, Consiglio Nazionale delle Ricerche (CNR), Via G. Moruzzi 1, 56124 Pisa, Italy.ORCID https://orcid.org/0000-0001-6705-2460
Mariaelena OcchipintiDivision of Radiology, Fondazione Toscana Gabriele Monasterio, Via G. Moruzzi 1, 56124 Pisa, Italy.ORCID https://orcid.org/0000-0003-3324-4063
Katia PaneIRCCS SYNLAB SDN, Via Emanuele Gianturco 113, 80143 Napoli, Italy.ORCID https://orcid.org/0000-0002-7594-7931
Carmelo De GoriDivision of Radiology, Fondazione Toscana Gabriele Monasterio, Via G. Moruzzi 1, 56124 Pisa, Italy.ORCID https://orcid.org/0000-0002-6051-3698
Silvia RocchiccioliInstitute of Clinical Physiology, Department of Biomedical Sciences, Consiglio Nazionale delle Ricerche (CNR), Via G. Moruzzi 1, 56124 Pisa, Italy.ORCID https://orcid.org/0000-0003-3831-4200
Nicoletta BottoDivision of Cardiology, Fondazione Toscana Gabriele Monasterio, Via G. Moruzzi 1, 56124 Pisa, Italy.ORCID https://orcid.org/0000-0002-8336-3610
Concetta PronteraDivision of Cardiology, Fondazione Toscana Gabriele Monasterio, Via G. Moruzzi 1, 56124 Pisa, Italy.ORCID https://orcid.org/0000-0001-8328-523X
Carlo CavaliereIRCCS SYNLAB SDN, Via Emanuele Gianturco 113, 80143 Napoli, Italy.
Rosetta RagusaInstitute of Clinical Physiology, Department of Biomedical Sciences, Consiglio Nazionale delle Ricerche (CNR), Via G. Moruzzi 1, 56124 Pisa, Italy.ORCID https://orcid.org/0000-0002-6914-6089
Cecilia VecoliInstitute of Clinical Physiology, Department of Biomedical Sciences, Consiglio Nazionale delle Ricerche (CNR), Via G. Moruzzi 1, 56124 Pisa, Italy.ORCID https://orcid.org/0000-0002-5921-3604
Francesco SansoneInstitute of Clinical Physiology, Department of Biomedical Sciences, Consiglio Nazionale delle Ricerche (CNR), Via G. Moruzzi 1, 56124 Pisa, Italy.
Emanuela PassaroIRCCS SYNLAB SDN, Via Emanuele Gianturco 113, 80143 Napoli, Italy.ORCID https://orcid.org/0009-0009-4575-2007
Elisa CeccheriniInstitute of Clinical Physiology, Department of Biomedical Sciences, Consiglio Nazionale delle Ricerche (CNR), Via G. Moruzzi 1, 56124 Pisa, Italy.ORCID https://orcid.org/0000-0003-3912-2753
Antonio MorlandoInstitute of Clinical Physiology, Department of Biomedical Sciences, Consiglio Nazionale delle Ricerche (CNR), Via G. Moruzzi 1, 56124 Pisa, Italy.ORCID https://orcid.org/0009-0009-7803-6963
Alberto ClementeDivision of Radiology, Fondazione Toscana Gabriele Monasterio, Via G. Moruzzi 1, 56124 Pisa, Italy.ORCID https://orcid.org/0000-0002-4285-9468
Monica FranzeseIRCCS SYNLAB SDN, Via Emanuele Gianturco 113, 80143 Napoli, Italy.ORCID https://orcid.org/0000-0002-6490-7694
Erica MaffeiIRCCS SYNLAB SDN, Via Emanuele Gianturco 113, 80143 Napoli, Italy.ORCID https://orcid.org/0000-0002-0388-4433
Bruna PunzoIRCCS SYNLAB SDN, Via Emanuele Gianturco 113, 80143 Napoli, Italy.ORCID https://orcid.org/0000-0003-0915-4682
Alessia GimelliDivision of Radiology, Fondazione Toscana Gabriele Monasterio, Via G. Moruzzi 1, 56124 Pisa, Italy.ORCID https://orcid.org/0000-0003-3378-1723
Filippo CademartiriIRCCS SYNLAB SDN, Via Emanuele Gianturco 113, 80143 Napoli, Italy.ORCID https://orcid.org/0000-0002-0579-3279
Danilo NegliaInstitute of Clinical Physiology, Department of Biomedical Sciences, Consiglio Nazionale delle Ricerche (CNR), Via G. Moruzzi 1, 56124 Pisa, Italy.ORCID https://orcid.org/0000-0003-0016-9538

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Optimal medical treatment in patients with stable coronary artery disease (CAD) reduced morbidity and mortality but left a substantial residual risk (RR) of disease progression and events. According to recent evidence, insulin resistance or pre-diabetes together with elevated levels of triglycerides, low levels, and functionality of HDL-cholesterol, often associated with a chronic inflammatory state, are deemed to be relevant components of cardiometabolic and vascular RR. In the present project, we aim at discovering specific individual genetic/molecular profiles subtending emerging cardiometabolic and vascular risk patterns and associated with more severe stable CAD phenotypes. To this end, we will analyse clinical data, blood samples, and imaging data already gathered in a retrospective population of 561 patients with suspected stable coronary disease and will develop integrated predictive models of severity and extent of disease defined by qualitative and quantitative analysis of coronary plaques by cardiac computed tomography. The new predictive models, which will incorporate relevant clinical and genetic/molecular variables associated with more severe coronary atherosclerosis, will be validated in a similar prospective population of patients and extended to the prediction of progression (at 1 year follow-up) of coronary disease phenotypes, occurring despite optimal medical treatment.

Indexed as

Cardiac CT (CCT)Cardiovascular risk factorsCoronary artery disease (CAD)GeneticsInsulin resistance (IR)Molecular medicine

Identifiers

PMID39949422
PMCPMC11823827

What Socratic holds

Textmetadata
LicenceCC BY-NC
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.