Rural Patient Access to Primary Percutaneous Coronary Intervention Centers is Improved by a Novel Integrated Telemedicine Prehospital System
Bibliographic record
Abstract
BACKGROUND: As per American Heart Association/American College of Cardiology guidelines, the delay between first medical contact and balloon inflation should not exceed 90 min for primary percutaneous coronary intervention (PCI). In North America, few prehospital systems have been developed to grant rural populations timely access to PCI. OBJECTIVES: The objective of the present study was to evaluate the ability of an ST-segment elevation myocardial infarction (STEMI) system serving suburban and rural populations to achieve the recommended 90-min interval benchmark for PCI. METHODS: A prehospital telemedicine program was implemented in a rural and suburban region of the Quebec province. Three patient groups with STEMI were created according to trajectory: 1) patients already en route to a PCI center, 2) patients initially directed to the nearest hospital who were subsequently diverted to a PCI center during transport, and 3) patients directed to the nearest hospital without transfer for PCI. Time intervals were compared across groups. RESULTS: Of the 208 patients diagnosed with STEMI, 14.9% were already on their way to a hospital with PCI capabilities, 75.0% were rerouted to a PCI center, and 10.1% were directed to the nearest local hospital. All patients but one arrived at the PCI center within the 60-min prehospital care interval, considering an additional 30 min for balloon inflation at the PCI center. CONCLUSION: This study demonstrated that a regionalized prehospital system for STEMI patients could achieve the recommended 90-min interval benchmark for PCI, while giving timely access to PCI to rural populations that would not otherwise have access to this treatment.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".