Emergency Department Volume and Outcomes for Patients After Chest Pain Assessment
Bibliographic record
Abstract
BACKGROUND: Chest pain is one of the most common reasons for emergency department (ED) visits in developed countries. Whether higher volume EDs have better outcomes, specifically for patients with chest pain, is unknown and pertinent. METHODS AND RESULTS: We conducted a study using population-based data on 498 291 patients ≥40 years old, presenting to ED in Ontario, Canada from 2008 to 2014, with chest pain and were discharged after assessment. We evaluated processes of care after discharge from ED. The primary outcome was a composite of all-cause death or hospitalization for acute coronary syndrome. Hierarchical logistic regression models adjusting for potential confounding variables were used to evaluate the association of annual ED chest pain volume and outcome. We also determined if there was a volume threshold above which an increased ED volume was not associated with a lower adverse outcome. The mean age of our patients was 59 years, 46.7% were men, and 20% had diabetes mellitus. Patients discharged from higher volume EDs had higher rates of cardiologist consultations, cardiac medication use, and cardiac testing within 30 days of ED assessment. Higher ED volume was associated with significantly lower adjusted odds ratio for mortality or acute coronary syndrome (odds ratio, 0.87; 95% CI, 0.82-0.92 per each unit increase in the log of volume) at 30 days and at 1 year (odds ratio, 0.92; 95% CI, 0.88-0.92). Once the annual ED chest pain volume reached 1400 cases (95% CI, 910-1900), an increase of annual chest pain volume of 100 was associated with relative decrease in the odds of the composite outcome at 30 days of <1%. CONCLUSIONS: Evaluations of chest pain in EDs with higher chest pain volume had lower rates of death or hospitalizations for acute coronary syndrome. There was a volume threshold above which an increase in volume was no longer associated with reduced outcomes.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".