Evidence map›Paper›PMID 41430751›Full record

Observational studyJournal of Korean medical science2025

Analysis of Treatment Pattern of Antiplatelet in First-Ever Ischemic Stroke Without Previous Antiplatelet Use: A Real-World Distributed Network Analysis of 11 Observational Korean Databases Using a Common Data Model.

Soo-Hyun Park, Kyung Joo Lee, Jinseob Kim, Seung In Seo, Dong Yun Lee, Rae Woong Park, Sang Youl Rhee, Jae Myung Cha, Hyeon-Jong Yang, Jae-Won Jang and 9 more

Abstract readObservational Study
In one paragraph

Observational study in Journal of Korean medical science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

19 authors.

Soo-Hyun ParkDepartment of Neurology, Soonchunhyang University Seoul Hospital, Seoul, Korea.ORCID https://orcid.org/0000-0003-1626-3940
Kyung Joo LeeDepartment of Medical Informatics & Statics, Kangdong Sacred Heart Hospital, Seoul, Korea.ORCID https://orcid.org/0000-0001-8881-0558
Jinseob KimDepartment of Epidemiology, School of Public Health, Seoul National University, Seoul, Korea.ORCID https://orcid.org/0009-0008-6931-5023
Seung In SeoDepartment of Internal Medicine, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0003-4417-0135
Dong Yun LeeDepartment of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea.ORCID https://orcid.org/0000-0003-4613-6838
Rae Woong ParkDepartment of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea.ORCID https://orcid.org/0000-0003-4989-3287
Sang Youl RheeDepartment of Digital Health and Department of Endocrinology and Metabolism, Kyung Hee University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0003-0119-5818
Jae Myung ChaDepartment of Internal Medicine, Kyung Hee University Hospital at Gangdong, Kyung Hee University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0001-9403-230X
Hyeon-Jong YangDepartment of Pediatrics, Soonchunhyang University Seoul Hospital, Soonchunhyang University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-7287-4300
Jae-Won JangDepartment of Neurology, Kangwon National University School of Medicine, Chuncheon, Korea.ORCID https://orcid.org/0000-0003-3540-530X
Seunguk JungDepartment of Neurology, Gyeongsang National University College of Medicine, Jinju, Korea.ORCID https://orcid.org/0000-0003-2331-024X
Jeeun LeeDepartment of Neurology, Myongji Hospital, Hanyang University College of Medicine, Goyang, Korea.ORCID https://orcid.org/0000-0001-6470-788X
Minwoo LeeDepartment of Neurology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, Korea.ORCID https://orcid.org/0000-0001-8474-5744
Sang-Hwa LeeDepartment of Neurology, Chuncheon Sacred Heart Hospital, Hallym University College of Medicine, Chuncheon, Korea.ORCID https://orcid.org/0000-0002-0609-1551
Chulho KimDepartment of Neurology, Chuncheon Sacred Heart Hospital, Hallym University College of Medicine, Chuncheon, Korea.ORCID https://orcid.org/0000-0001-8762-8340
Jong Seok BaeDepartment of Neurology, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-4313-1786
Yeo Jin KimDepartment of Neurology, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-6564-3774
Ju-Hun LeeDepartment of Neurology, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0001-6831-7248
Yerim KimDepartment of Neurology, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Korea. brainyrk@hallym.ac.kr.ORCID https://orcid.org/0000-0002-7108-6302

Funding

National Research Foundation of Korea NRF-2022R1F1A1074643Soonchunhyang University
6 · The paper itself

Abstract

backgroundAntiplatelet agents are widely prescribed to prevent cardiovascular events, with cardiovascular disease being the leading global cause of death and the second most common in Korea. As the demand for antiplatelets increases, understanding real-world prescribing patterns is essential.

methodsThis study analyzed antiplatelet prescription trends for patients with first-ever ischemic stroke (IS) using 11 Korean observational databases transformed to a Common Data Model, spanning 1995-2023. Prescription shifts were assessed in relation to the 2013 CHANCE trial.

resultsThe analysis included 162,361 patients with first-ever IS who had no prior antiplatelet therapy. Aspirin was the most commonly prescribed initial medication (39.4%), followed by aspirin-clopidogrel combination (28.2%), clopidogrel alone (13.7%), and cilostazol (5.0%). Initial medication were typically maintained: however, some patients initially on aspirin or clopidogrel switched to dual antiplatelet therapy (DAPT; aspirin and clopidogrel), while those on initial DAPT primarily transitioned to clopidogrel, then to aspirin. Following the CHANCE trial, a marked shift in prescription patterns was observed. Before CHANCE, aspirin was predominant (45.7%), followed by aspirin-clopidogrel (19.2%), and clopidogrel (15.5%). Post-CHANCE, aspirin-clopidogrel became the leading therapy (40.6%), with aspirin (30.3%) and clopidogrel (11.3%) monotherapy.

conclusionWhile aspirin remains the mainstay for secondary prevention of IS, the CHANCE trial significantly influenced increased use of DAPT. As evidence continues to grow for P2Y12 inhibitors in the IS context, analyzing antiplatelet prescription patterns is vital for evaluating the implementation of guidelines in clinical practice.

Indexed as

Ischemic StrokePlatelet Aggregation InhibitorsPractice Patterns, Physicians'AgedAspirinCilostazolClopidogrelDatabases, FactualDrug Therapy, CombinationFemaleHumansMaleMiddle AgedRepublic of KoreaAspirinCilostazolClopidogrelPlatelet Aggregation InhibitorsAspirinCerebral InfarctionClopidogrelIschemic StrokeStandard of CareStroke

Identifiers

PMID41430751
PMCPMC12722781

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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.