Identifying Low‐risk Patients for Early Discharge From Emergency Department Without Using Subjective Descriptions of Chest Pain: Insights From Providing Rapid Out of Hospital Acute Cardiovascular Treatment (<scp>PROACT</scp>) 3 and 4 Trials
Bibliographic record
Abstract
BACKGROUND: Several accelerated diagnostic protocols (ADPs) have been developed to allow emergency department (ED) physicians to identify appropriate patients for safe early discharge after presentation with symptom of chest pain. Most ADPs require chest pain to be described and modify the algorithm based on the subjective chest pain characteristics. We investigated the performance of three established major ADPs simplified by eliminating the need for chest pain as a descriptor. METHODS: We pooled patients from PROACT-3 and -4 trials, in which patients presenting to emergency medical services with chest pain or dyspnea were enrolled. The simplified Vancouver Chest Pain Rule (sVCPR), the simplified Emergency Department Assessment of Chest Pain Score (sEDACS) ADP and the Accelerated Diagnostic protocol to Assess Patients with chest pain using contemporary troponins as the only biomarker (ADAPT-ADP) were compared using the sensitivity, specificity, and positive and negative predictive values (NPV). The primary outcome of interest was 30-day major adverse cardiac events (MACE); the diagnosis of acute coronary syndrome (ACS) occurring within 30 days after ED presentation was also explored. RESULTS: A total of 1,081 patients were included (median age = 67 years, 53% male, median GRACE score = 113) of which 222 ACS diagnoses and 150 cardiac events occurred within 30 days after index ED presentation. The sVCPR, sEDACS ≥ 3, and ADAPT-ADP, respectively, identified 9.7, 13.3, and 4.1% of patients as low risk with a sensitivity and NPV of 100% for the primary outcome of 30-day MACE. The sEDACS-ADP identified 24.2% of patients as low risk with a cut-point score of 4 (sensitivity of 98.0% and NPV of 98.8%). The sVCPR, sEDACS ≥ 3, and ADAPT-ADP, respectively, had NPVs of 98.1, 95.8, and 93.3% in identifying patients at higher risk of ACS diagnosis within 30 days after index ED visit. CONCLUSION: The diagnostic protocols performed well without their chest pain characteristics component. Further studies are suggested to explore the performance of ADPs when these simplified ADPs are combined with high-sensitive troponin assays.
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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 | 0.016 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".