Emergency department presentations for atrial fibrillation and flutter in Alberta: a large population-based study
Bibliographic record
Abstract
BACKGROUND: Atrial fibrillation or flutter (AFF) are not infrequent presenting problems in Emergency Departments (ED); however, little is known of the pattern of these presentations. This study provides a description of AFF presentations and outcomes after ED discharge in Alberta. METHODS: Provincial administrative databases were used to obtain all primary ED encounters for AFF during 1999 to 2011 for patients aged >35 years. Data extracted included demographics, ED visit timing, and subsequent visits to non-ED settings. Analysis included summaries and standardized rates. RESULTS: During the study period, there were 63,398 ED AFF visits from 32,104 distinct adults. Median ages for females and males were 75 and 67 years, respectively; more men (52%) and patients > 65 presented. Overall, the standardized rates remained similar (2.8 per 1,000 over the study period). Specific populations of human services recipients and First Nations had higher ED visit rates for AFF than other groups. Predictable daily, weekly, and monthly trends were observed. The ED visits were followed by numerous subsequent visits in non-ED settings; however, First Nations and women had lower rates of specialist follow-up. CONCLUSIONS: Annually, over 5,000 ED presentations of patients experiencing AFF occur in Alberta and admissions proportions are declining. While presentation rates across the province are stable, follow-up with physicians, consultation with cardiologists and health outcomes vary based on socio-economic, age, sex, and First Nations status. Further research is required to understand the causes and consequences of these inequalities and to standardize care.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".