Characterizing Decision-Making Surrounding Exercise in ARVC: Analysis of Decisional Conflict, Decisional Regret, and Shared Decision-Making
Bibliographic record
Abstract
Background: Limiting high-intensity exercise is recommended for patients with arrhythmogenic right ventricular cardiomyopathy (ARVC) due to its association with penetrance, arrhythmias, and structural progression. Guidelines recommend shared decision-making (SDM) for exercise level, but there is little evidence regarding its impact. Therefore, we sought to evaluate the extent and implications of SDM for exercise, decisional conflict, and decisional regret in patients with ARVC and at-risk relatives. Methods: Adults diagnosed with ARVC or with positive genetic testing enrolled in the Johns Hopkins ARVC Registry were invited to complete a questionnaire that included exercise history and current exercise, SDM (SDM-Q-9), decisional conflict, and decisional regret. Results: The response rate was 64.8%. Two-thirds of participants (68.0%, n=121) reported clinically significant decisional conflict regarding exercise at diagnosis/genetic testing (DCS [decisional conflict scale]≥25), and half (55.1%, n=98) in the past year. Prevalence of decisional regret was also high with 55.3% (n=99) reporting moderate to severe decisional regret (DRS [decisional regret scale]≥25). The extent of SDM was highly variable ranging from no (0) to perfect (100) SDM (mean, 59.6±25.0). Those diagnosed in adolescence (≤age 21) reported significantly more SDM ( P =0.013). Importantly, SDM was associated with less decisional conflict (ß=−0.66, R 2 =0.567, P <0.01) and decisional regret (ß=−0.37, R 2 =0.180, P <0.001) and no difference in vigorous intensity aerobic exercise in the 6 months after diagnosis/genetic testing or the past year ( P =0.56; P =0.34, respectively). Conclusions: SDM is associated with lower decisional conflict and decisional regret; and no difference in postdiagnosis exercise. Our data thus support SDM as the preferred model for exercise discussions for ARVC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".