Paediatrics: how to manage pediculosis capitis
Bibliographic record
Abstract
Background: Pediculosis capitis is a common human parasitic infestation in childhood. This article aims to provide a narrative updated review on the management of pediculosis capitis. Methods: A PubMed search was performed with Clinical Queries using the key terms "pediculosis capitis" OR "head lice" OR "head louse". The search strategy included clinical trials, meta-analyses, randomized controlled trials, observational studies and reviews published within the past 10 years. The search was restricted to articles published in English literature. The information retrieved from the search was used in the compilation of the present article. Results: Topical permethrin and pyrethrin formulated with piperonyl butoxide are the pediculicides of choice in areas where resistance to these products is low. When resistance to these products is suspected based on local levels of resistance or when treatment with these products fails despite their correct use, and reinfestation does not seem to be responsible, other topical treatment options include malathion, benzyl alcohol, dimethicone, spinosad and ivermectin. Wet combing should be considered for children younger than 2 years. Oral ivermectin and trimethoprim/sulfamethoxazole should be reserved for patients who do not respond to appropriate topical pediculicides. Conclusion: Many topical pediculicides are effective for the treatment of pediculosis capitis. The use of some of these pediculicides is limited for safety reasons, especially in children younger than 2 years. Resistance to pediculicides, especially those with a neurotoxic mode of action, is another concern which may limit the use of some of these pediculicides. New products should be evaluated for effectiveness and safety. Wet combing is time-consuming and should not be used as the sole intervention in the general population.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".