Development of a Clinical Care Pathway for Patients with Suspected Acute Coronary Syndromes in the Emergency Department
Bibliographic record
Abstract
Chest pain is a predominant reason for emergency department (ED) visits and hospitalizations in Canada. ED physicians use diagnostic tools (e.g., biomarkers) to identify patients with myocardial infarction (MI) requiring intervention, and prognostic tools (e.g., risk scores) to determine which patients without MI are eligible for discharge. While clinical guidelines recommend that these two portions of the assessment occur sequentially, the evidence for each has emerged in isolation. There is also a paucity of evidence on risk score use in the era of high-sensitivity cardiac troponin (hs-cTn) assays, adverse event risk factors for patients without MI, and appropriate timelines for follow-up. This project had three complimentary objectives: (1) Synthesize available evidence on prognostic prediction score performance when hs-cTn assays are incorporated; (2) Quantify the time course of major adverse cardiac events (MACE) in patients without index MI and identify characteristics with potential predictive value for MACE, and; (3) Develop a sequential clinical pathway for the assessment of chest pain in the ED and measure the impacts on diagnostic and prognostic accuracy as well as ED patient flow. A systematic review was conducted to synthesize evidence on the chest pain risk scores to be prioritized for integration into the clinical pathway. A time-to-event analysis was then conducted to measure timing of MACE in patients without index MI, as well as a stratified analysis to identify characteristics with predictive value for 30-day MACE to be used in the pathway for clinical stratification. Trial clinical pathways were developed and quantitatively compared. Pathways combined a validated 2-hour hs-cTn diagnostic algorithm with variable clinical pre-stratification, risk score types, and low-risk cut-offs. A sequential clinical pathway using a validated hs-cTn algorithm and the HEART score can identify nearly 40% of ED chest pain patients as eligible for discharge without the need for further testing with no missed MI or 30-day MACE. This thesis project contributed evidence necessary for the updating and advancing of the ED chest pain assessment and presents an evidence-based sequential clinical pathway that maximizes the efficiency of the ED chest pain assessment.
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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 | 0.019 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".