Atrial arrhythmias following <scp>CAR‐chimeric</scp> antigen receptor T‐cell therapy: Incidence, risk factors and biomarker profile
Bibliographic record
Abstract
Recent reports have raised concerns about the association of chimeric antigen receptor T cell (CAR-T) with non-negligible cardiotoxicity, particularly atrial arrhythmias. First, we conducted a pharmacovigilance study to assess the reporting of atrial arrhythmias following CD19-directed CAR-T. Subsequently, to determine the incidence, risk factors and outcomes of atrial arrhythmias post-CAR-T, we compiled a retrospective single-centre cohort of non-Hodgkin lymphoma patients. Only commercial CAR-T products were considered. Atrial arrhythmias were nearly fourfold more likely to be reported after CAR-T therapy compared to all other cancer patients in the FAERS (adjusted ROR = 3.76 [95% CI 2.67-5.29]). Of the 236 patients in our institutional cohort, 23 (10%) developed atrial arrhythmias post-CAR-T, including 12 de novo arrhythmias, with most (83%) requiring medical intervention. Atrial arrhythmias frequently co-occurred with cytokine release syndrome and were associated with higher post-CAR-T infusion peak levels of IL-10, TNF-alpha and LDH, and lower trough levels of fibrinogen. In a multivariable analysis, risk factors for atrial arrhythmia were history of atrial arrhythmia (OR = 6.80 [2.39-19.6]) and using CAR-T product with a CD28-costimulatory domain (OR = 5.17 [1.72-18.6]). Atrial arrhythmias following CD19-CAR-T therapy are prevalent and associated with elevated inflammatory biomarkers, a history of atrial arrhythmia and the use of a CAR-T product with a CD28 costimulatory domain.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 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".