Deep Learning-Based Prediction of Cardiovascular Outcomes using Optical Coherence Tomography in Patients with Acute Coronary Syndrome

Deep Learning-Based Prediction of Cardiovascular Outcomes using Optical Coherence Tomography in Patients with Acute Coronary Syndrome - Deep Learning-Based Prediction of Cardiovascular Outcomes using Optical Coherence Tomography in Patients with Acute Coronary Syndrome

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000049237

Enrollment

360

Registered

2023-01-01

Start date

2023-01-01

Completion date

Unknown

Last updated

2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

acute coronary syndrome

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: (1) Patients enrolled in a previous study, "A retrospective multicenter registry of the morphological characteristics of responsible plaques in patients with acute coronary syndromes from the perspective of age and gender" (UMIN000038442). (ii) Patients who received OCT examination after PCI to ACS

Exclusion criteria

Exclusion criteria: (1) Patients who have asked not to participate in this study based on publicly available information. (2) Patients who had ACS due to in-stent restenosis or occlusion (3) Patients with graft vessels (4) Patients with lesions in the left main trunk or the ostium of the right coronary artery (5) Patients who did not undergo stenting at PCI (6) Patients with Thrombolysis in myocardial infarction trial (TIMI) flow grade 2 or less at the final coronary angiogram

Design outcomes

Primary

Measure	Time frame
Target vessel failure	—

Countries

Japan

Contacts

Public ContactTomoyo Hamana

Kobe University Hospital Division of Cardiovascular Medicine

tomohamachi@yahoo.co.jp0783825846

Outcome results