Patient Clusters and Cost Trajectories in Atrial Fibrillation: Evidence from the Swiss Atrial Fibrillation Cohort
Bibliographic record
Abstract
Abstract Aims Evidence on long-term costs of atrial fibrillation (AF) and associated factors is scarce. As part of the Swiss-AF prospective cohort study we aimed to characterise AF costs and their development over time, and to assess specific patient clusters and their cost trajectories. Methods Swiss-AF enrolled 2,415 patients with variable duration of AF between 2014 and 2017. Patient clusters were identified using hierarchical cluster analysis of baseline characteristics. Ongoing yearly follow-ups include health insurance clinical and claims data. An algorithm was developed to adjudicate costs to AF and related complications. Results Hierarchical analysis identified three patient clusters. “Cardiovascular-dominated” (CV-dominated) patients had the highest proportions of prior myocardial infarction and presence of diabetes. “Heart failure-dominated” (HF-dominated) patients had the highest occurrence of heart failure and permanent AF. “Isolated symptomatic” (IS) patients were younger and had the highest occurrence of paroxysmal AF. A subpopulation of 1,024 Swiss-AF patients with available claims data was followed up for a median [interquartile range] of 3.24 [1.09] years. Average yearly AF-adjudicated costs amounted to CHF 5,679, remaining stable across the observation period. CV-dominated (N = 253 with claims data) and HF-dominated patients (N = 185) depicted similarly high costs across all cost outcomes, the IS (N = 586) patients accrued the lowest costs. Conclusion Our results highlight three well-differentiated patient clusters with specific costs that could be used for stratification in both clinical and economic studies. Patient characteristics associated with adjudicated costs as well as cost trajectories may enable an early understanding of the magnitude of upcoming AF-related healthcare costs. What is already known on this topic Atrial fibrillation (AF) is a complex disease and constitutes a major economic and societal challenge due to its high prevalence worldwide. What this study adds This study, based on a large prospective cohort study, provides evidence on real-world AF costs and their development over time. Data-derived patient clusters are linked to costs and their respective cost trajectories are assessed. How this study might affect research, practice or policy The identified patient clusters and their characteristics may help clinicians and payers to gain an early insight and understanding of the magnitude of the expected AF-related healthcare costs.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".