Photoinduced skin reactions of cardiovascular drugs—a systematic review
Bibliographic record
Abstract
This systemic review aims to provide a practical overview of the prevalence, clinical manifestation, and management of adverse photoinduced skin reactions caused by frequently used cardiovascular drugs and to assess their potential relevance for skin cancer development. Data search included PubMed, Web of Science, and the Cochrane Library. A systematic review of peer-reviewed studies reporting the photosensitizing and/or skin cancer-inducing properties of common cardiovascular drugs was performed and a guide to clinical management of photoinduced skin eruptions by cardiovascular drugs was provided. Study quality was assessed for major methodological biases. A total of 58 studies were identified (i.e. 23 case reports, 14 observational studies, 10 review articles, 10 experimental studies, and 1 meta-analysis). Most commonly, drug-associated adverse photoinduced cutaneous reactions were caused by phototoxic and photoallergic mechanisms. There is evidence suggesting that amiodarone and dronedarone, thiazide diuretics, thiazide-like diuretics, angiotensin receptor blockers, dihydropyridine-type calcium channel blockers, and certain angiotensin-converting enzyme inhibitors and statins may cause photoinduced adverse cutaneous reactions. Other drugs such as anticoagulants, antiplatelets, aldosterone antagonists, and fibrates have not been linked with photosensitizing reactions or adverse cutaneous reactions. Some drugs, i.e. thiazides and thiazide-like diuretics, were associated with an increased risk of non-melanoma skin cancers (basal cell carcinoma and squamous cell carcinoma). Certain commonly used cardiovascular drugs have been associated with adverse photoinduced cutaneous reactions. If they occur, further diagnosis and treatment might be needed, depending on the severity and progress. Whether photosensitizing drugs increase the risk of skin cancer remains elusive and further randomized controlled trials are required.
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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 | 0.013 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.030 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".