Ambulance use, distance and outcomes in patients with suspected cardiovascular disease: a registry-based geographic information system study
Bibliographic record
Abstract
BACKGROUND: Despite guideline recommendations, the majority of patients with symptoms suggestive of acute coronary syndrome do not use emergency medical services to reach the emergency department (ED). The aim of this study was to investigate the factors associated with EMS utilisation and subsequent patient outcomes. METHODS: Using administrative data, all patients who presented to an ED in the metropolitan areas of Edmonton and Calgary in the years of 2007-2013 with main ED diagnosis of acute coronary syndrome, stable angina or chest pain were included. The travel distance was estimated using the geographic information system method to approximate the distance between the ED and patient home. The clinical endpoints were the 7-day and 30-day all-cause events (death, re-hospitalisation and repeat ED visit). RESULTS: Of 50,881 patients, 30.5% presented by emergency medical services. Patients with older age, female sex, ED diagnosis of acute coronary syndrome, more comorbidities and lower household income were more likely to use emergency medical services to reach the hospital. Longer travel distance was associated with higher emergency medical services use (odds ratio 1.09, 95% confidence interval 1.09-1.10), but it was not a predictor of clinical events. After adjustment for covariates and inverse propensity score weighting, emergency medical services use was associated with a higher risk of 7-day and 30-day clinical events. CONCLUSION: Several demographic and clinical features were associated with higher emergency medical services use including geographical variation. Although longer travel distance was shown to be linked to higher emergency medical services use, it was not an independent predictor of patient outcome. This has implications for the design of emergency medical services systems, triage and early diagnosis and treatment options.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".