Providing Rapid Out of Hospital Acute Cardiovascular Treatment 4 (PROACT‐4)
Bibliographic record
Abstract
BACKGROUND: Whether prehospital point-of-care (POC) troponin further accelerates the time to diagnosis in patients with chest pain (CP) is unknown. We conducted a randomized trial of POC-Troponin testing in the ambulance. METHODS AND RESULTS: Patients with chest pain presenting by ambulance were randomized to usual care (UC) or POC-Troponin; ST-elevation myocardial infarction patients or those with noncardiovascular symptoms were excluded. Pre-hospital high-sensitivity troponin was analyzed on a POC device and available to the paramedic and emergency department (ED) staff. The final diagnosis was centrally adjudicated. The primary endpoint was time from first medical contact to discharge from ED or admission to hospital. We randomized 601 patients in 19 months; 296 to UC and 305 to POC-Troponin. After ambulance arrival, the first troponin was available in 38 minutes in POC-Troponin and 139 minutes in UC. In POC-Troponin, the troponin was >0.01 ng/mL in 17.4% and >0.03 ng/mL in 9.8%. Patients spent a median of 9.0 hours from first medical contact to final disposition, and 165 (27.4%) were admitted to the hospital. The primary endpoint was shorter in patients randomized to POC-Troponin (median 8.8 hours [6.2-10.8] compared to UC (median 9.1 hours [6.7-11.2]; P=0.05). There was no difference in the secondary endpoint of repeat ED visits, hospitalizations, or death in the next 30 days. CONCLUSIONS: In this broad population of patients with CP, ambulance POC-Troponin accelerated the time to final disposition. Enhanced and more cost-effective early ED discharge of the majority of patients with CP calling 911 is an unrealized opportunity. CLINICAL TRIAL REGISTRATION: URL: https://www.ClinicalTrials.gov/. Unique identifier: NCT01634425.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".