β-blockers and risk of neuropsychiatric adverse events: An active-comparator restricted disproportionality on the FAERS
Bibliographic record
Abstract
BACKGROUND: β-blockers (β-adrenoceptor antagonists), commonly used for cardiovascular conditions, may be linked to neuropsychiatric adverse events (AEs). However, many prevalent ones, including delirium and hallucinations, remain insufficiently studied. AIMS: To compare the neuropsychiatric risks of β-blockers with other antihypertensive drugs using data from the FDA Adverse Event Reporting System (FAERS) and differences between lipophilic and hydrophilic β-blockers. METHOD: An active-comparator restricted disproportionality analysis was conducted using data from the FAERS (2004Q1-2023Q4). Neuropsychiatric AEs were analyzed using Preferred Terms and the System Organ Classes from the Medical Dictionary for Regulatory Activities for β-blockers compared to lisinopril and losartan. Adjusted Reporting Odds Ratios (aRORs) were calculated using logistic regression to account for potential confounders. RESULTS: β-blockers were linked to a significantly higher risk of nervous and psychiatric disorders, compared to lisinopril and losartan. Among the nine types of neuropsychiatric events studied, six-dizziness, nightmares, insomnia, hallucinations, somnolence, and disorientation-showed higher aRORs with β-blockers. Propranolol, a lipophilic β-blocker, exhibited the highest aRORs for psychiatric disorders and six types of neuropsychiatric events, including nightmares, delirium, hallucinations, disorientation, altered mental status, and somnolence, compared to lisinopril and losartan. Compared to atenolol, propranolol remained significantly associated with delirium, hallucinations, and disorientation. CONCLUSION: β-blockers, especially propranolol, may be associated with a higher risk of neuropsychiatric AEs compared to lisinopril and losartan. These findings highlight the importance of considering the specific β-blocker prescribed, particularly in patients at risk for central nervous system side effects. Further population-based studies are warranted to confirm these results.
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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 | 0.026 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.009 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".