Emergence of African species of dermatophytes in tinea capitis: A 17‐year experience in a Montreal pediatric hospital
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: An increase in dermatophyte infections caused by African species is reported in countries receiving African immigrants. Our goal was to determine the epidemiologic and clinical characteristics of tinea capitis in children infected with African species of dermatophytes in Montreal, Canada. METHODS: Demographic and clinical data from medical records of children infected with African species of dermatophytes were retrieved retrospectively (2000-2016) at Sainte-Justine University Hospital Center. RESULTS: In Montreal, the number of tinea capitis cases caused by African species of dermatophytes increased sixfold over 17 years. African immigrant children (84%), men and boys (61%), and preschoolers (2-5 years old) (51%) were the most frequently affected in our 315 cases. Family contamination was frequent (45%). Referring physicians prescribed systemic antifungal treatment in 39% of cases and pediatric dermatologist consultants in 90%. Treatment failure to oral terbinafine occurred in 39% of Microsporum audouinii infections. CONCLUSION: In Montreal, there was a significant increase in tinea capitis caused by African species of dermatophytes. Microsporum audouinii is highly transmissible and often resistant to oral terbinafine. Recognizing tinea capitis trends in a given environment will improve patient care.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".