Epidemiology, clinical characteristics and potential mechanism of ibrutinib-induced ventricular arrhythmias
Bibliographic record
Abstract
The Bruton's Tyrosine Kinase Inhibitor, ibrutinib, has been widely employed due to its significant efficacy in B-cell lymphoma. However, the subsequent cardiac complications, notably atrial fibrillation (AF) and ventricular arrhythmias (VAs),associated with ibrutinib treatment have emerged as a major concern in cardio-oncology and hematology. Ibrutinib-induced AF has been well described, whereas mechanisms of ibrutinib-induced VAs are still under-investigation. The incidence of ibrutinib-induced VAs can vary vastly due to under-recognition and limitations of the retrospective studies. Recent investigations, including our previous work, have proposed several potential mechanisms contributing to this adverse event, necessitating further validation. The development of effective strategies for the prevention and treatment of ibrutinib-induced VAs still requires in-depth exploration. This review aims to establish a comprehensive framework encompassing the epidemiology, mechanistic insights, and clinical considerations related to ibrutinib-induced VAs. This article outlines potential strategies for the clinical management of patients undergoing ibrutinib therapy based on suggested mechanisms.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".