ANMCO-SIMEU consensus document: appropriate management of atrial fibrillation in the emergency department
Bibliographic record
Abstract
Atrial fibrillation (AF) accounts for 2% of the total presentations to the emergency department (ED) and represents the most frequent arrhythmic cause for hospitalization. It steadily increases the risk of thromboembolic events and is often associated with several comorbidities that negatively affect patient's quality of life and prognosis. AF has a considerable impact on healthcare resources, making the promotion of an adequate and coordinated management of this arrhythmia necessary in order to avoid clinical complications and to implement the adoption of appropriate technological and pharmacological treatment options. AF management varies across regions and hospitals and there is also heterogeneity in the use of anticoagulation and electric cardioversion, with limited use of direct oral anticoagulants. The ED represents the first access point for early management of patients with AF. The appropriate management of this arrhythmia in the acute setting has a great impact on improving patient's quality of life and outcomes as well as on rationalization of the financial resources related to the clinical course of AF. Therefore, physicians should provide a well-structured clinical and diagnostic pathway for patients with AF who are admitted to the ED. This should be based on a tight and propositional collaboration among several specialists, i.e. the ED physician, cardiologist, internal medicine physician, anesthesiologist. The aim of this ANMCO-SIMEU consensus document is to provide shared recommendations for promoting an integrated, accurate, and up-to-date management of patients with AF admitted to the ED or Cardiology Department, in order to make it homogeneous across the national territory.
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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 | 0.031 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.017 | 0.010 |
| Insufficient payload (model declined to judge) | 0.012 | 0.012 |
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".