Diagnostic Accuracy of GPT-4o and Claude for HEART Score Calculation in Chest Pain

Condition(s) studied

Investigational drug(s) / intervention(s)

GPT-4o HEART Score Calculator: OpenAI GPT-4o (model: gpt-4o-2024-11-20, temperature=0, max\_tokens=500, response\_format=JSON). Each patient's anonymized anamnesis text, ECG report text, troponin value, and age are submitted via a separate API call with no conversation history. Output: HEART score components (0-2 each), total score (0-10), risk group, and indeterminate status.

Claude HEART Score Calculator: Anthropic Claude (model: claude-sonnet-4-6, temperature=0, max\_tokens=500, response\_format=JSON). Identical system prompt and input format as GPT-4o. Processed independently with no cross-contamination between models. Output: same JSON schema as GPT-4o.

Three-Expert Consensus HEART Score: Three emergency medicine physicians (\>=3 years experience, HEART-score trained) independently score each anonymized record. Majority vote (2/3) determines component scores; a 4th adjudicator resolves ties. Experts are blinded to LLM scores, each other's scores, and MACE outcomes.

Study summary

This prospective observational diagnostic accuracy study evaluates whether large language models (LLMs) - GPT-4o (OpenAI, gpt-4o-2024-11-20) and Claude (Anthropic, claude-sonnet-4-6) - can accurately calculate HEART scores from unstructured Turkish clinical notes and predict 30-day major adverse cardiac events (MACE) in emergency department patients presenting with non-traumatic chest pain.

The study will enroll 600 consecutive adult patients. For each patient, the same anonymized data (free-text anamnesis, ECG report text, troponin value, and age) will be independently processed by both LLMs via separate API calls with deterministic settings (temperature=0, JSON format). A three-expert consensus HEART score - derived through blinded independent scoring by three emergency medicine physicians with majority-vote adjudication - serves as the reference standard for agreement analysis. Actual 30-day MACE (all-cause death, AMI Type 1/2/4b, unplanned revascularization) determined via national health database and telephone follow-up serves as the outcome for diagnostic accuracy analysis.

A secondary documentation-quality sub-study will quantify how spontaneously Turkish emergency anamnesis notes capture HEART score parameters.

Eligibility

Primary outcome measure(s)

• Area Under the ROC Curve (AUC) of GPT-4o and Claude HEART Score for 30-Day MACE Prediction — 30 days after index emergency department visit
  AUC calculated separately for GPT-4o and Claude using the Hanley-McNeil method. MACE is defined as a composite of all-cause death, acute myocardial infarction (Type 1/2/4b), and unplanned revascularization within 30 days. HEART score range is 0-10; a higher score indicates a higher risk of MACE. Analysis will be performed on complete cases only (0 indeterminate components).

Trial sites (1)

More Marmara University Pendik Training and Research Hospital trials in Turkey

Other trials for the same condition