Evidence map›Paper›PMID 41216259›Full record

ArticleCardiovascular diagnosis and therapy2025

Artificial intelligence for manuscript writing: policies and implementation in cardiovascular journals.

Todd A Laffaye, Brian H Carlson, William K Freeman, Chadi Ayoub

Abstract read
In one paragraph

Article in Cardiovascular diagnosis and therapy, 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

5 · Who and what money

Authors and funding

4 authors.

Todd A LaffayeMayo Clinic Alix School of Medicine, Mayo Clinic, Phoenix, AZ, USA.ORCID https://orcid.org/0009-0002-8036-8683
Brian H CarlsonMayo Clinic Alix School of Medicine, Mayo Clinic, Phoenix, AZ, USA.
William K FreemanDepartment of Cardiovascular Medicine, Mayo Clinic, Phoenix, AZ, USA.
Chadi AyoubDepartment of Cardiovascular Medicine, Mayo Clinic, Phoenix, AZ, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) has emerged as a widely used tool for writing, including in scientific research and publications. While its application to cardiovascular research is the focus of numerous studies, the policies related to its use for manuscript writing are rapidly evolving and not well understood. We sought to compare the policies of high-impact cardiovascular journals regarding AI for manuscript writing assistance and assess the prevalence of its use. Cardiovascular medicine journals with an SCImago Journal Rank (SJR) ≥3 and h-index ≥100 were screened for an AI policy. Journal policies were assessed for author disclosure requirements, standardization of disclosure section and language, and AI detection software used during the submission process. Each journal with an AI policy that required disclosure of its use was systematically searched to evaluate the prevalence of articles disclosing its use for writing assistance from January 2023 to August 2025. The number of publications with AI disclosure and publication characteristics was recorded. Seventeen journals met inclusion criteria and were screened for an AI policy, of which 14 journals (82%) contained such a policy. Among these, three journals (18%) had an AI policy that required disclosure, but that was not specific to AI use for manuscript writing. One journal (6%) did not require disclosure. The remaining three journals (18%) did not have any AI policy. None of the journals mandated a dedicated AI disclosure section or provided authors with standardized disclosure language. Fifteen journals (88%) used identifiable AI detection software, while only one posted this information publicly. Among the 14 journals with an AI disclosure policy, 11 AI-disclosing works were found. ChatGPT was the most common AI tool used (n=9, 82%). Journal policies regarding AI use for manuscript writing assistance vary widely, and therefore, there is a growing need for standardization. The prevalence of articles disclosing the use of AI was profoundly low across all journals evaluated, with significant variation in how AI use was disclosed. Having clear and consistent policies across journals and requiring authors to disclose their use of AI for manuscript writing is essential to uphold transparency and maintain medical research integrity.

Indexed as

Artificial intelligence (AI)cardiovascular journalsdisclosure policiesmanuscript writing

Identifiers

PMID41216259
PMCPMC12596447

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.