Impact of a patient decision aid on care among patients with nonvalvular atrial fibrillation: a cluster randomized trial
Bibliographic record
Abstract
BACKGROUND: Too few patients with nonvalvular atrial fibrillation (NVAF) receive appropriate antithrombotic therapy. We tested the short-term (primary outcome) and long-term (secondary outcome) effect of a patient decision aid on the appropriateness of antithrombotic therapy among patients with NVAF. METHODS: We conducted a cluster randomized trial with blinded outcome assessment involving 434 NVAF patients from 102 community-based primary care practices. Patients in the intervention group received a self-administered booklet and audiotape decision aid tailored to their personal stroke risk profile. Patients in the control group received usual care. The primary outcome measure was change in antithrombotic therapy at 3 months. Appropriateness of therapy was defined using the American College of Chest Physicians (ACCP) recommendations. RESULTS: The mean patient age was 72 years, and the median duration of NVAF was 5 years. In the control group, there was a 3% decrease over 3 months in the number of patients receiving therapy appropriate to their risk of stroke (40% [85/215] at baseline v. 37% [79/215] at 3 months). In the intervention group, the number of patients receiving therapy appropriate to their stroke risk increased by 9% (32% [69/219] at baseline v. 41% [89/219] at 3 months). Although the proportion of patients whose therapy met the ACCP treatment recommendations did not differ between study arms at baseline (p = 0.11) or 3 months (p = 0.44), there was a 12% absolute improvement in the number of patients receiving appropriate care in the intervention group compared with the control group at 3 months (p = 0.03). The beneficial effect of the decision aid did not persist (p = 0.44 for differences between study arms after 12 months). INTERPRETATION: There was short-term improvement in the appropriateness of antithrombotic care among patients with NVAF who were exposed to a decision aid, but the improvement did not persist.
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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".