A Privacy-Preserving OCR-LLM System for Coronary Syndrome Subtyping From Admission HPI: Multicenter Validation in China and the US

Starting soon

Conditions studied: Coronary Artery Disease (CAD) (E.G., Angina, Myocardial Infarction, and Atherosclerotic Heart Disease (ASHD)), Acute Coronary Syndromes, ST-segment Elevation Myocardial Infarction (STEMI), Non-ST-Segment Elevation Myocardial Infarction (NSTEMI)

In brief

This study develops and validates a privacy-preserving OCR-LLM pipeline that converts admission history of present illness (HPI) records into structured coronary syndrome subtypes (STEMI, NSTEMI, unstable angina, and chronic coronary syndrome). The system first extracts text from de-identified HPI images using locally deployed OCR, then applies large language models with a fixed diagnostic prompt to generate subtype classification and evidence. Performance is evaluated in an internal validation cohort and multiple external datasets covering heterogeneous EHR templates, emergency department cases, and an English dataset from MIMIC-IV. A clinician usability study assesses changes in diagnostic accuracy and time with and without tool assistance.

Key facts

Study ID

NCT07449429

Run by

China National Center for Cardiovascular Diseases

People needed

10

Starts

2026-02-28

Expected to finish

2026-03-08

Last updated by the study team

2026-03-04

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

Full record on ClinicalTrials.gov

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