Ability to remotely monitor atrial high-rate episodes using a single-chamber implantable cardioverter-defibrillator with a floating atrial sensing dipole
Bibliographic record
Abstract
AIMS: To allow timely initiation of anticoagulation therapy for the prevention of stroke, the European guidelines on atrial fibrillation (AF) recommend remote monitoring (RM) of device-detected atrial high-rate episodes (AHREs) and progression of arrhythmia duration along pre-specified strata (6 min…<1 h, 1 h…<24 h, ≥ 24 h). We used the MATRIX registry data to assess the capability of a single-lead implantable cardioverter-defibrillator (ICD) with atrial sensing dipole (DX ICD system) to follow this recommendation in patients with standard indication for single-chamber ICD. METHODS AND RESULTS: In 1841 DX ICD patients with daily automatic RM transmissions, electrograms of first device-detected AHREs per patient in each duration stratum were adjudicated, and the corresponding positive predictive values (PPVs) for the detections to be true atrial arrhythmia were calculated. Moreover, the incidence and progression of new-onset AF was assessed in 1451 patients with no AF history. A total of 610 AHREs ≥6 min were adjudicated. The PPV was 95.1% (271 of 285) for episodes 6min…<1 h, 99.6% (253/254) for episodes 1 h…<24 h, 100% (71/71) for episodes ≥24 h, or 97.5% for all episodes (595/610). The incidence of new-onset AF was 8.2% (119/1451), and in 31.1% of them (37/119), new-onset AF progressed to a higher duration stratum. Nearly 80% of new-onset AF patients had high CHA2DS2-VASc stroke risk, and 70% were not on anticoagulation therapy. Age was the only significant predictor of new-onset AF. CONCLUSION: A 99.7% detection accuracy for AHRE ≥1 h in patients with DX ICD systems in combination with daily RM allows a reliable guideline-recommended screening for subclinical AF and monitoring of AF-duration progression.
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 | 0.001 | 0.005 |
| 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) | 0.001 | 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 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".