Disproportionality Analysis of Hypotension-Related Adverse Drug Reactions Associated With Type 1a Selective Alpha-Blockers in VigiBase
Bibliographic record
Abstract
INTRODUCTION: Some evidence suggests no association between type 1a (T1a) selective alpha-blockers and hypotension-related adverse drug reactions (HR-ADRs), although safety concerns still exist. We sought to investigate the association of HR-ADRs with selective T1a blockers and identify at-risk groups. METHODS: We used disproportionality analysis to detect signals of HR-ADRs (dizziness, fainting, falls, and fractures) reported with selective T1a blocker use (tamsulosin and silodosin) in VigiBase, a global database of individual case safety reports. Excluding duplicates, all reports were included (1967-2022). Significance was determined using lower bound 95% empiric Bayes estimator > 1; only then were reporting odds ratios (RORs) and 95% CIs reported. Subgroup analyses were stratified by sex, age (<65 and ≥65 years), and indication for men only (urinary stone disease [USD] and benign prostatic hyperplasia [BPH]). RESULTS: We identified 5963 reports of HR-ADRs with selective T1a blockers. Selective T1a blockers were significantly associated with HR-ADRs (ROR 1.46; 95% CI 1.42-1.49). In men, selective T1a blockers for USD were associated with increased risk of HR-ADRs (ROR 1.60; 95% CI 1.56-1.65), which only remained significant in the older subgroup (ROR 6.70; 95% CI 3.20-14.01). No association was found for BPH. In women, selective T1a blockers were associated with an increased risk of HR-ADRs (ROR 1.09; 95% CI 0.99-1.09). This was only significant in the younger subgroup (ROR 1.17; 95% CI 1.03-1.32). CONCLUSIONS: In older men with USD and younger women, selective T1a blockers were associated with higher risk of HR-ADRs, suggesting the need for continued monitoring in these populations. No signal was observed for men with BPH.
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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 | 0.018 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.011 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".