Atrial High Rate Episodes Detected by Pacemaker Diagnostics Predict Death and Stroke
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Bibliographic record
Abstract
BACKGROUND: Some current pacing systems can automatically detect and record atrial tachyarrhythmias that may be asymptomatic. We prospectively studied a 312-patient (pt) subgroup of MOST (MOde Selection Trial), a 2010-patient, 6-year randomized trial of DDDR versus VVIR pacing in sinus node dysfunction (SND). The purpose of the study was to correlate atrial high rate events (AHREs) detected by pacemaker diagnostics with clinical outcomes. METHODS AND RESULTS: Pacemakers were programmed to log an AHRE when the atrial rate was >220 bpm for 10 consecutive beats. Analysis was confined to patients with at least 1 AHRE duration exceeding 5 minutes. The 312 patients were median age 74 years, 55% female, and 60% had a history of SVT. 160 of 312 (51.3%) patients enrolled had at least 1 AHRE >5 minutes duration over median follow-up of 27 months. Cox proportional hazards analysis assessed the relationship of AHREs with clinical events, adjusting for prognostic variables and baseline covariates. The presence of any AHRE was an independent predictor of the following: total mortality (hazard ratio AHRE versus no AHRE and 95% confidence intervals=2.48 [1.25, 4.91], P=0.0092); death or nonfatal stroke (2.79 [1.51, 5.15], P=0.0011); and atrial fibrillation (5.93 [2.88, 12.2], P=0.0001). There was no significant effect of pacing mode on the presence or absence of AHREs. CONCLUSIONS: AHRE detected by pacemakers in patients with SND identify patients that are more than twice as likely to die or have a stroke, and 6 times as likely to develop atrial fibrillation as similar patients without AHRE.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 it