The Cost of Atrial Fibrillation: A Systematic Review
Bibliographic record
Abstract
OBJECTIVES: Atrial fibrillation (AF) is the most common cardiac arrhythmia, with an increasing incidence and prevalence because of progressively aging populations. Costs related to AF are both direct and indirect. This systematic review aims to identify the main cost drivers of the illness, assess the potential economic impact resulting from changes in care strategies, and propose interventions where they are most needed. METHODS: A systematic literature search of the PubMed and Scopus databases was performed to identify analytical observational studies defining the cost of illness in cases of AF. The search strategy was based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 recommendations. RESULTS: Of the 944 articles retrieved, 24 met the inclusion criteria. These studies were conducted in several countries. All studies calculated the direct medical costs, whereas 8 of 24 studies assessed indirect costs. The median annual direct medical cost per patient, considering all studies, was €9409 (13 333 US dollars in purchasing power parities), with a very large variability due to the heterogeneity of different analyses. Hospitalization costs are generally the main cost drivers. Comorbidities and complications, such as stroke, considerably increase the average annual direct medical cost of AF. CONCLUSIONS: In most of the analyzed studies, inpatient care cost represents the main component of the mean direct medical cost per patient. Stroke and heart failure are responsible for a large share of the total costs; therefore, implementing guidelines to manage comorbidities in AF is a necessary step to improve health and mitigate healthcare costs.
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 | 0.006 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".