Common Dermatoses in Children Referred to a Specialized Pediatric Dermatology Service in Mexico: A Comparative Study between Two Decades
Bibliographic record
Abstract
Background. Skin diseases among pediatric patients differ from those in adults. Epidemiological studies are scarce, and those performed in Mexican population date back thirty years. It is likely that these diseases might have changed their frequency. Material and Methods. Retrospective study in first-time patients referred to a pediatric dermatology service between January 1994 and December 2003. Demographics and diagnosis were recorded and compared with the results of a previous study performed in the same institution. Results. We included 5250 patients (52.55% female, 47.47% male) with 6029 diagnoses. The most frequent dermatoses found were atopic dermatitis (14.59%), viral warts (6.62%), acne (5.53%), pityriasis alba (3.98%), melanocytic nevi (3.85%), xerosis (3.57%), keratosis pilaris (3.19%), seborrheic dermatitis (2.37%), hemangioma (2.26%), and papular urticaria (2.24%). Most dermatoses increased their frequency when compared to the previous study. Conclusion. The frequency of pediatric dermatoses in our institution has changed in the last two decades. Environmental and sociocultural factors and institutional policies might account for these results.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".