Age of First Arrhythmic Event in Brugada Syndrome
Bibliographic record
Abstract
Background Data on the age at first arrhythmic event (AE) in Brugada syndrome are from limited patient cohorts. The aim of this study is 2-fold: (1) to define the age at first AE in a large cohort of patients with Brugada syndrome, and (2) to assess the influence of the mode of AE documentation, sex, and ethnicity on the age at first AE. Methods and Results A survey of 23 centers from 10 Western and 4 Asian countries gathered data from 678 patients with Brugada syndrome (91.3% men) with first AE documented at time of aborted cardiac arrest (group A, n=426) or after prophylactic implantable cardioverter–defibrillator implantation (group B, n=252). The vast majority (94.2%) of the patients were 16 to 70 years old at the time of AE, whereas pediatric (<16 years) and elderly patients (>70 years) comprised 4.3% and 1.5%, respectively. Peak AE rate occurred between 38 and 48 years (mean, 41.9±14.8; range, 0.27–84 years). Group A patients were younger than in Group B by a mean of 6.7 years (46.1±13.2 versus 39.4±15.0 years; P <0.001). In adult patients (≥16 years), women experienced AE 6.5 years later than men ( P =0.003). Whites and Asians exhibited their AE at the same median age (43 years). Conclusions SABRUS (Survey on Arrhythmic Events in Brugada Syndrome) presents the first analysis on the age distribution of AE in Brugada syndrome, suggesting 2 age cutoffs (16 and 70 years) that might be important for decision-making. It also allows gaining insights on the influence of mode of arrhythmia documentation, patient sex, and ethnic origin on the age at AE.
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 | 0.003 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".