Safety and feasibility of a real-time electronic heart team decision-making approach in patients with complex coronary artery disease: a protocol for a randomised controlled trial (EHEART trial)
Bibliographic record
Abstract
INTRODUCTION: The implementation of a heart team still faces many challenges which may be facilitated with advanced communication technology. There is a knowledge gap to support the use of an electronic real-time heart team decision-making approach based on communication technology in the real clinical practice and evaluate its safety and feasibility in patients with complex coronary artery disease (CAD). METHODS AND ANALYSIS: The EHEART (Electronic HEArt team with Real-Time decision-making) trial is a prospective, multicentre, two-arm, randomised controlled trial that will randomise 490 patients with complex CAD to either an electronic real-time heart team group or conventional heart team group. For patients allocated to the real-time electronic group, heart team meetings will be initiated during the coronary angiography and guided by a supporting system based on communication technology to help with information synchronisation, real-time communication between specialists, meeting process recording and assistance and joint decision-making with patients' families. The primary and safety endpoint is a composite of all-cause death, myocardial infarction, stroke, revascularisation or re-angina hospital admission at 1 year. The primary secondary outcome is the time interval from the coronary angiography to the final treatment, which is the major indicator of feasibility. We will also compare the practical feasibility from the specialist's and patient's perspectives (for example, specialist's workload and patient's decision results) between the two groups. ETHICS AND DISSEMINATION: The study was approved by the Institutional Review Board (IRB) of Fuwai Hospital (no. 2022-1749). Informed consent will be obtained from all participants. The results of this trial will be disseminated through manuscript publication and national/international conferences, and reported in the trial registry entry. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov Registry (NCT05514210).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.038 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.036 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".