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A Clinical Application of Artificial Intelligence ECG Technology to Patients with Embolic Stroke of Undetermined Source

Research for Clinical application of Artificial Intelligence-enhanced Electrocardiogram Algorithm for Patients with Embolic Stroke of Undetermined Source; (a single center retrospective study)

Status
Unknown
Phases
Unknown
Study type
Observational
Source
CRIS
Registry ID
KCT0009318
Enrollment
200
Registered
2024-04-08
Start date
Unknown
Completion date
Unknown
Last updated
2026-01-27

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

Conditions

None listed

Interventions

None listed

Sponsors

Inha University Hospital
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: Embolic Stroke of University of Inha Hospital from 2016 to 2023 with unknown cause Among patients over 19 years of age diagnosed with Source; ESUS), those with an ECG record at hospitalization and follow-up after 6 months

Exclusion criteria

Exclusion criteria: The above study is a data collection study using an electrocardiogram, and there are no exclusion criteria other than patients who are unsuitable as subjects by the researcher's judgment.

Design outcomes

Primary

MeasureTime frame
ILR-detected siginal AF in patients with cerebral infarction of unknown cause—

Secondary

MeasureTime frame
Stroke after ILR in patients with cerebral infarction of unknown cause—

Countries

Korea, Republic of

Contacts

Public Contacthyerim park

Inha University Hospital

rimvely1126@naver.com+82-32-890-2555

Outcome results

None listed

Source: CRIS (via WHO ICTRP) · Data processed: Feb 4, 2026