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

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.

NCT Number	NCT07449429
Lead Sponsor	China National Center for Cardiovascular Diseases
Conditions	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)
Enrollment	10 participants
Start Date	2026-02-28
Primary Completion	2026-03-08 (estimated)
Study Completion	2026-03-08 (estimated)
Updated on ClinicalTrials.gov	2026-03-04