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Record W4412166481 · doi:10.1017/cjn.2025.10323

P.186 Trends in the management of scalp aplasia cutis congenita

2025· article· en· W4412166481 on OpenAlexvenueno aff
TM Bitonti, Anh-Hue Thi Tu

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSkin and Cellular Biology Research
Canadian institutionsnot available
Fundersnot available
KeywordsAplasia cutis congenitaScalpMedicineDermatology

Abstract

fetched live from OpenAlex

Background: Aplasia Cutis Congenita is a rare congenital abnormality characterized by varying absence of skin and mesodermal tissues. Management remains controversial, with significant inconsistency across specialties and over time. This review evaluates trends in management based on journal specialty and publication epoch. Methods: A review of pediatric scalp Aplasia Cutis Congenita management was conducted. Articles were categorized by journal type (neurosurgery, plastic surgery, dermatology, other medical, and other surgical) and management approach (surgical, conservative, or combined). Descriptive statistics were used to summarize trends in recommendations, and assess associations between journal type and treatment. Trends over time were analyzed based on publication year. Results: A total of 171 studies were included. Among surgical journals, 33.7% recommended surgical management, while medical journals favored conservative (14.1%) or combined approaches (84.5%) (p < 0.001). Recommendations for surgical management decreased from 80% in the 1970s to 30% in the 2020s. Notably, among 119 studies advocating for a combined approach, only 27 provided criteria for surgical indications, with lesion thresholds ranging from >1cm to >15 cm. Conclusions: This study highlights the lack of guidelines for ACC management and reveals specialty and time epoch of publication-dependent biases in treatment. These findings emphasize the need for multidisciplinary guidelines for consistent, patient-centered 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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.005
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.294
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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