Abstract 057: Understanding of Treatment Strategies Among Patients Newly Diagnosed With Atrial Fibrillation: Findings From SATELITTE
Bibliographic record
Abstract
Introduction: Patient understanding of available therapies for atrial fibrillation (AF) is foundational to shared medical decision making and long term medication adherence. Yet, there is a paucity of data regarding the extent to which patients newly diagnosed with AF in routine community practice understand their options. Hypotheses: 1) Understanding of warfarin, novel oral anticoagulants (NOAC), rhythm control therapy, cardioversion and radio frequency ablation changes little from baseline to 6 months and 2) treatment rates at 6 months are associated with patient understanding of therapies at baseline. Methods: We analyzed survey data from SATELLITE, a substudy of new-onset AF patients enrolled at 56 US sites participating in the ORBIT-AF registry. Patients were surveyed at the baseline and 6 month follow up clinic visit using Likert scales. Agreement between time points was assessed with the McNemar test, and the relationship between understanding and treatment was assessed only for the subset not on treatment at baseline. Results: Of 1000 patients enrolled in SATELLITE, 506 had 6-month survey data (data collection is continuing). Among these, the median age was 69.0 years (IQR 63.0 - 76.0) and 93.7% (474 of 506) were white. There was evidence of improvement in the self-reported understanding of warfarin and NOACs from baseline to 6 months, but not for rhythm control, ablation or cardioversion. The proportion reporting high understanding improved significantly for warfarin (p<.0001) and NOACs (p<.0001) from 47% (223 of 474) and 51% (245 of 481) at baseline to 60% (284 of 474) and 69% (332 of 481) at 6 months respectively (Figure 1). Patients with high understanding of the benefits of ablation (p=0.0005) and options for ablation (p=0.0093) at baseline were more likely to have this therapy at the 6 month follow up (N=590), but improved understanding was not associated with increased use of warfarin/NOACs (N=83) or rhythm control (N=444). Conclusions: Patients with new-onset AF had improved self-reported understanding of some treatment options over the first 6-months from diagnosis; however, factors other than patient understanding may influence AF treatments received at 6 months. Patient understanding of AF treatments remains suboptimal at 6 months, and our results suggest a need for ongoing patient education.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.005 | 0.001 |
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".