Standardized programming to reduce the burden of inappropriate therapies in implantable cardioverter defibrillators - Single centre follow up results
Bibliographic record
Abstract
BACKGROUND: Current algorithms and device morphology templates have been proposed in current Implantable Cardioverter-Defibrillators (ICDs) to minimize inappropriate therapies (ITS), but this has not been completely successful. AIM: Assess the impact of a deliberate strategy of using an atrial lead implant with standardized parameters; based on all current ICD discriminators and technologies, on the burden of ITS. METHOD: A retrospective single-centre analysis of 250 patients with either dual chamber (DR) ICDs or biventricular ICDs (CRTDs) over a (41.9 ± 27.3) month period was performed. The incidence of ITS on all ICD and CRTD patients was chronicled after the implementation of standardized programming. RESULTS: 39 events of anti-tachycardial pacing (ATP) and/or shocks were identified in 20 patients (8% incidence rate among patients). The total number of individual therapies was 120, of which 34% were inappropriate ATP, and 36% were inappropriate shocks. 11 patients of the 250 patients received ITS (4.4%). Of the 20 patients, four had ICDs for primary prevention and 16 for a secondary prevention. All the episodes in the primary indication group were inappropriate, while seven patients (43%) of the secondary indication group experienced inappropriate therapies. CONCLUSIONS: The burden of ITS in the population of patients receiving ICDs was 4.4% in the presence of atrial leads. The proposed rationalized programming criteria seems an effective strategy to minimize the burden of inappropriate therapies and will require further validation.
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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 | 0.001 | 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".