Time-to-first appropriate shock in patients implanted prophylactically with an implantable cardioverter-defibrillator: data from the Survey on Arrhythmic Events in BRUgada Syndrome (SABRUS)
Bibliographic record
Abstract
AIMS: Data on predictors of time-to-first appropriate implantable cardioverter-defibrillator (ICD) therapy in patients with Brugada Syndrome (BrS) and prophylactically implanted ICD's are scarce. METHODS AND RESULTS: SABRUS (Survey on Arrhythmic Events in BRUgada Syndrome) is an international survey on 678 BrS patients who experienced arrhythmic event (AE) including 252 patients in whom AE occurred after prophylactic ICD implantation. Analysis was performed on time-to-first appropriate ICD discharge regarding patients' characteristics. Multivariate logistic regression models were utilized to identify which parameters predicted time to arrhythmia ≤5 years. The median time-to-first appropriate ICD therapy was 24.8 ± 2.8 months. A shorter time was observed in patients from Asian ethnicity (P < 0.05), those with syncope (P = 0.001), and those with Class IIa indication for ICD (P = 0.001). A longer time was associated with a positive family history of sudden cardiac death (P < 0.05). Multivariate Cox regression revealed shorter time-to-ICD therapy in patients with syncope [odds ratio (OR) 1.65, P = 0.001]. In 193 patients (76.6%), therapy was delivered during the first 5 years. Factors associated with this time were syncope (OR 0.36, P = 0.001), spontaneous Type 1 Brugada electrocardiogram (ECG) (OR 0.5, P < 0.05), and Class IIa indication (OR 0.38, P < 0.01) as opposed to Class IIb (OR 2.41, P < 0.01). A near-significant trend for female gender was also noted (OR 0.13, P = 0.052). Two score models for prediction of <5 years to shock were built. CONCLUSION: First appropriate therapy in BrS patients with prophylactic ICD's occurred during the first 5 years in 76.6% of patients. Syncope and spontaneous Type 1 Brugada ECG correlated with a shorter time to ICD therapy.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".