Quality of Life in the Antiarrhythmics Versus Implantable Defibrillators Trial
Bibliographic record
Abstract
BACKGROUND: Implantable cardioverter defibrillator (ICD) use reduces mortality in patients with serious ventricular arrhythmias compared with antiarrhythmic drug (AAD) use. However, the relative impact of these therapies on self-perceived quality of life (QoL) is unknown. METHODS AND RESULTS: Three self-administered instruments were used to measure generic and disease-specific QoL in Antiarrhythmics Versus Implantable Defibrillators trial participants. Generalized linear models were used to assess the relationships between self-perceived QoL and treatment (AAD versus ICD) and adverse symptoms and ICD shocks. To minimize the impact of missing data, only patients surviving 1 year were included in the primary analyses. Baseline characteristics among QoL participants (n=905) and nonparticipants (n=111) were similar, but participants who survived 1 year (n=800) were healthier at baseline than nonsurvivors (n=105). Of the 800 patients in the primary analysis, characteristics of those randomized to AAD (n=384) versus ICD (n=416) were similar. Overall, ICD and AAD use were associated with similar alterations in QoL. The development of sporadic shocks and adverse symptoms were each associated with reduced physical functioning and mental well-being and increased concerns among ICD recipients, whereas development of adverse symptoms was associated with reduced physical functioning and increased concerns among AAD recipients. CONCLUSIONS: ICD and AAD therapy are associated with similar alterations in self-perceived QoL over 1-year follow-up. Adverse symptoms were associated with reduced self-perceived QoL in both groups, and sporadic shocks were associated with reduced QoL in ICD recipients.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".