The Intersection Between Malaria Treatment and Chemoprophylaxis and Their Potential Adverse Dermatologic Manifestations: A Narrative Review
Bibliographic record
Abstract
mosquito. The parasitic infection is endemic in 90 countries, with approximately 500 million cases reported annually and an estimated annual mortality of 1.5-2.7 million individuals. Historically, the use of antimalarial drugs has been promising for the chemoprophylaxis and treatment of malaria, mitigating the annual mortality rate. Notably, these antimalarial drugs have been associated with various adverse effects, including gastrointestinal upset and headaches. However, the adverse cutaneous manifestations these antimalarial drugs may lead to are poorly documented and understood. We aim to describe the lesser-studied adverse cutaneous pathologies of malaria treatment to better educate physicians on the proper treatment of their patients. Our narrative review describes the skin manifestations associated with specific antimalarial treatments and their associated prognoses and treatments. The cutaneous pathologies discussed include aquagenic pruritus (AP), palmoplantar exfoliation, Steven-Johnson syndrome, toxic epidermal necrolysis, cutaneous vasculitis, psoriasis, ecchymosis, and tropical lichenoid dermatitis. Further studies and vigilant documentation of the cutaneous adverse events of antimalarial drugs need to be performed and emphasized to prevent potential life-threatening adverse outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".