Evidence mapPaperPMID 41590246Full record

ReviewDiseases (Basel, Switzerland)2026

An Integrative Review of the Cardiovascular Disease Spectrum: Integrating Multi-Omics and Artificial Intelligence for Precision Cardiology.

Gabriela-Florentina Țapoș, Ioan-Alexandru Cîmpeanu, Iasmina-Alexandra Predescu, Sergio Liga, Andra Tiberia Păcurar, Daliborca Vlad, Casiana Boru, Silvia Luca, Simina Crișan, Cristina Văcărescu and 1 more

Abstract readReview
In one paragraph

Review in Diseases (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Observational
  2. Review
  3. Article
  4. Review
  5. Review
  6. 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

11 authors.

Gabriela-Florentina ȚapoșDoctoral School, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania.
Ioan-Alexandru CîmpeanuDoctoral School, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania.
Iasmina-Alexandra Predescu"Victor Babes" University of Medicine and Pharmacy, 2nd Eftimie Murgu Square, 300041 Timisoara, Romania.
Sergio Liga"Victor Babes" University of Medicine and Pharmacy, 2nd Eftimie Murgu Square, 300041 Timisoara, Romania.ORCID 0000-0002-4866-934X
Andra Tiberia Păcurar"Victor Babes" University of Medicine and Pharmacy, 2nd Eftimie Murgu Square, 300041 Timisoara, Romania.
Daliborca VladDepartment of Biochemistry and Pharmacology, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy, 2nd Eftimie Murgu Square, 300041 Timisoara, Romania.ORCID 0000-0002-9243-1865
Casiana BoruFaculty of Medicine, "Vasile Goldis" Western University of Arad, 86 Liviu Rebreanu Street, 310048 Arad, Romania.ORCID 0009-0004-1725-3749
Silvia LucaCardiology Department, "Victor Babes" University of Medicine and Pharmacy, 300041 Timisoara, Romania.ORCID 0009-0005-0859-2498
Simina CrișanCardiology Department, "Victor Babes" University of Medicine and Pharmacy, 300041 Timisoara, Romania.ORCID 0000-0002-8760-5605
Cristina VăcărescuCardiology Department, "Victor Babes" University of Medicine and Pharmacy, 300041 Timisoara, Romania.
Constantin Tudor LucaCardiology Department, "Victor Babes" University of Medicine and Pharmacy, 300041 Timisoara, Romania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesCardiovascular diseases (CVDs) remain the leading cause of morbidity and mortality worldwide and increasingly are recognized as a continuum of interconnected conditions rather than isolated entities.

methodsA structured narrative literature search was performed in PubMed, Scopus, and Google Scholar for publications from 2015 to 2025 using combinations of different keywords: "cardiovascular disease spectrum", "multi-omics", "precision cardiology", "machine learning", and "artificial intelligence in cardiology".

resultsEvidence was synthesized across seven major clusters of cardiovascular conditions, and across these domains, common biological pathways were mapped onto heterogeneous clinical phenotypes, and we summarize how multi-omics integration, AI-enabled imaging and digital tools contribute to improved risk prediction and more informed clinical decision-making within this spectrum.

conclusionsInterpreting cardiovascular conditions as components of a shared disease spectrum clarifies cross-disease interactions and supports a shift from organ- and syndrome-based classifications toward mechanism- and data-driven precision cardiology. The convergence of multi-omics, and AI offers substantial opportunities for earlier detection, individualized prevention, and tailored therapy, but requires careful attention to data quality, equity, interpretability, and practical implementation in routine care.

Indexed as

cardiovascular disease spectrumheartintegrative reviewprecision cardiology

Identifiers

PMID41590246
PMCPMC12840068

What Socratic 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 Socratic graph.