Low‐Dose Oral Minoxidil and Associated Adverse Events: Analyses of the <scp>FDA</scp> Adverse Event Reporting System ( <scp>FAERS</scp> ) With a Focus on Pericardial Effusions
Bibliographic record
Abstract
BACKGROUND: Low-dose oral minoxidil (LDOM) is used to treat hair loss, but the literature on its safety profile is relatively sparse. AIMS: Using the FDA Adverse Event Reporting System (FAERS) database, we determined signals for adverse events (AEs) with LDOM use. METHODS: Four sets of case/noncase study disproportionality analyses were conducted to determine reporting odds ratio (ROR) for 10 AEs including pericardial effusion (PE). The oral minoxidil dose ranges were: (i) ≤1.25 mg (i.e., 0-1.25 mg), (ii) ≤2.5 mg (i.e., 0-2.5 mg), (iii) ≤5 mg (i.e., 0-5 mg), and (iv) ≤10 mg (i.e., 0-10 mg). RESULTS: For ≤1.25 mg, we detected a signal for PE (ROR = 16.41, 95% CI: 2.29, 117.37, p < 0.05). For ≤2.5 mg, the analyses detected a signal for PE (ROR = 13.30, 95% CI: 5.96, 29.68, p < 0.05); the ROR in the absence of cardiac impairment was 5.34 (95% CI: 1.33, 21.37, p < 0.05); in the presence of cardiac impairment, the ROR was 49.42 (95% CI: 18.27, 133.66, p < 0.05). A signal for PE was also detected at ≤5 and ≤10 mg. For PE, there was a significant (p < 0.05) association with a patient outcome of "life threatening" only at the ≤10 mg dose range. CONCLUSIONS: Our study, the first FAERS-based signal detection study for LDOM, found significant associations between LDOM use and several AEs. In the absence of causal evidence, these correlations warrant more attention regarding safe use of LDOM. Until more safety data are available, we recommend using LDOM at the lowest effective dose (≤5 mg/day).
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".