Heart Failure Events After Long-term Continuous Screening for Atrial Fibrillation: Results From the Randomized LOOP Study
Bibliographic record
Abstract
BACKGROUND: Mounting evidence indicates that even device-detected subclinical atrial fibrillation is associated with a higher risk of heart failure (HF). However, the potential impact of atrial fibrillation screening on HF remains unknown. METHODS: The LOOP Study (Atrial Fibrillation detected by Continuous ECG Monitoring using Implantable Loop Recorder to prevent Stroke in High-risk Individuals) evaluated the effects of atrial fibrillation screening on stroke prevention using an implantable loop recorder (ILR) versus usual care in older individuals with additional stroke risk factors. In this secondary analysis, we explored the following HF end points: (1) HF event or cardiovascular death; (2) HF event; (3) event with HF with reduced ejection fraction (HFrEF); and (4) HFrEF event or cardiovascular death. Outcomes were assessed in a Cox model both as time-to-first events and as total (first and recurrent) events analyzed using the Andersen-and-Gill method. RESULTS: Of 6004 participants (mean age 74.7 and 52.7% men), 1501 were randomized to ILR screening and 4503 to the control group. In total, 77 (5.1%) in the ILR group versus 295 (6.6%) in the control group experienced the primary outcome of an HF event or cardiovascular death. Compared with usual care, ILR screening was associated with a nonsignificant reduction in the primary outcome for the time-to-first event analysis (hazard ratio, 0.78 [95% CI, 0.61-1.01]) and the total event analysis (hazard ratio, 0.77 [95% CI, 0.59-1.01]). Similar results were obtained for the HF event. A significant risk reduction in total events was observed in the ILR group for the composite of HFrEF event or cardiovascular death and for HFrEF event (hazard ratio, 0.74 [95% CI, 0.56-0.98] and 0.65 [95% CI, 0.44-0.97], respectively). CONCLUSIONS: In an older population with additional stroke risk factors, ILR screening for atrial fibrillation tended to be associated with a lower rate of total HF events and cardiovascular death, particularly those related to HFrEF. These findings should be considered hypothesis-generating and warrant further investigation. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02036450.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".