Implantable Loop Recorder Allows an Etiologic Diagnosis in One-Third of Patients
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Bibliographic record
Abstract
BACKGROUND: The implantable loop recorder (ILR) is a useful tool for diagnosing paroxysmal conditions potentially related to arrhythmias. Most investigations have focused on selected clinical studies or high-volume centers. The aim of this study was to evaluate the indications and outcomes of the ILR in real clinical practice. METHODS AND RESULTS: This was a prospective, multicenter registry of patients undergoing ILR implantation for clinical indications (April 2006-December 2008). Clinical characteristics (symptoms, arrhythmias, treatments) were recorded in a database. Follow-up data at 1 year or after the occurrence of the first episode were also recorded. Total enrollment: 743 patients (male, 413, 55.6%; 64.9 ± 16 years); 228 (30.7%) had structural heart disease (SHD), and 183 (24.6%), bundle branch block (BBB). Recurrent syncope (76.4%) was the most common indication for implantation. Complete follow-up was obtained for 680 patients (91.5%). Three hundred and twenty-five patients (48%) presented 414 events, with a final diagnosis in 230 patients (70.8% of patients with events; 33.1% of patients with follow-up). Syncope secondary to bradyarrhythmia was the most frequent diagnosis. Similar rates of final diagnoses were noted in subgroups of SHD, BBB and normal heart. Regarding the cause of implantation, higher event rates were registered among patients with recurrent syncope. CONCLUSIONS: One-third of patients obtained a final diagnosis with the ILR, independent of the baseline characteristics. Only the cause of implantation provided different rates of final diagnosis.
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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 | 0.000 |
| 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 it