Differences in the yield of the implantable loop recorder between secondary and tertiary centers
Bibliographic record
Abstract
BACKGROUND: The implantable loop recorder (ILR) is a useful tool for diagnosis of syncope or palpitations. Its easy use and safety have extended its use to secondary hospitals (those without an Electrophysiology Lab). The aim of the study was to compare results between secondary and tertiary hospitals. METHODS: National prospective and multicenter registry of patients with an ILR inserted for clinical reasons. Data were collected in an online database. The follow-up ended when the first diagnostic clinical event occurred, or 1 year after implantation. Data were analyzed according to the center of reference; hospitals with Electrophysiology Lab were considered Tertiary Hospitals, while those hospitals without a lab were considered Secondary Hospitals. RESULTS: Seven hundred and forty-three patients (413 [55.6%] men; 65 ± 16 year-old): 655 (88.2%) from Tertiary Centers (TC) and 88 (11.8%) from Secondary Centers (SC). No differences in clinical characteristics between both groups were found. The electrophysiologic study and the tilt table test were conducted more frequently in Tertiary Centers. Follow-up was conducted for 680 (91.5%) patients: 91% in TC and 94% in SC. There was a higher rate of final diagnosis among SC patients (55.4% vs. 30.8%; p < 0.001). Tertiary Hospital patients showed a trend towards a higher rate of neurally mediated events (20% vs. 4%), while bradyarrhythmias were more frequent in SC (74% vs. 60%; p = 0.055). The rate of deaths and adverse events was similar in both populations. CONCLUSIONS: Patients with an ILR in SC and TC have differences in terms of the use of complementary tests, but not in clinical characteristics. There was a higher rate of diagnosis in Secondary Hospital patients.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".