Volume Matters: Improved Outcomes for Patients Presenting to High-Volume Emergency Departments with Atrial Flutter and Fibrillation
Bibliographic record
Abstract
OBJECTIVES: Clinical familiarity plays a role in health outcomes; the relationship between emergency department (ED) volume and outcomes for atrial fibrillation and flutter (AFF) are not clear. We compared ED presentation outcomes for AFF between high (HV) and low volume (LV) EDs in Alberta, Canada. METHODS: 45,372 AFF presentations for patients aged ≥ 35 years from all 104 EDs in Alberta during 1999 to 2011 using administrative health databases formed a retrospective cohort. EDs were grouped by annual AFF volume: 11 high (>100 presentations) or 93 low (≤100 presentations). Outcomes included hospital admission rate, return to ED for AFF within 30 and 90 days, and death within 30 and 90 days. Analyses included statistical tests and mixed effects modeling. RESULTS: Mean age at ED presentation was 69.8 years (52% male). HV ED presentations were associated with lower admissions (adjusted odds ratio [aOR] = 0.68, 95% confidence interval [CI] 0.64, 0.72; p-value [p]<0.001), ED returns at 90 (aOR = 0.81, 95% CI 0.73, 0.90; p<0.001) days, and a higher likelihood of specialist visits at 30 (aOR = 1.81, 95% CI 1.68, 1.94; p<0.001) and 90 (aOR = 1.82, 95% CI 1.76, 2.03; p<0.001) days. For admitted patients, there were fewer returns to HV EDs at 30 (aOR = 0.37, 95% CI 0.15, 0.87; p = 0.02) and 90 (aOR = 0.48, 95% CI 0.26, 0.89; p = 0.02) days after hospital discharge. There was no difference in death between the two groups. CONCLUSIONS: AFF patients presenting to HV EDs experienced fewer admissions and AFF ED revisit and higher specialist referrals compared to LV EDs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".