Development of a Novel Risk-Prediction Tool for Emergency Department Patients with Symptoms of Coronary Artery Disease: A Research Study Protocol
Bibliographic record
Abstract
Patients with chest pain and symptoms of acute coronary syndromes account for > 600,000 emergency department (ED) visits annually in Canada. Of these patients, 85% do not have acute coronary syndromes, and most are discharged from the ED after a thorough evaluation. However, a large proportion of these patients are referred for outpatient cardiac testing after ED discharge, even though their short-term risk of major adverse cardiac events (MACE), including death, new myocardial infarction, and need for revascularization, is very small. These referrals contribute to substantial low-value healthcare utilization, and limit access for those patients who are more likely to benefit from objective testing.Existing risk-prediction tools-developed prior to the advent of new high-sensitivity cardiac troponin assays-were derived in nonrepresentative populations, and when applied to ED patients with low cardiac troponin concentrations, systematically overestimate the short-term risk of MACE.This multicentre prospective cohort study will enroll ED patients with chest pain to derive and validate a novel risk prediction tool that distinguishes patients at low risk of MACE who do not require further cardiac testing from those who may benefit from additional cardiac testing. We will enroll 6500 patients in 13 Canadian EDs and prospectively follow them to ascertain a primary outcome of MACE within 30 days after their index ED encounter. The risk-prediction tool developed in this project will guide the safe, efficient, and appropriate referral of ED patients with chest pain. Clinical Trial Registration: NCT06743672.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".