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Record W4391378621 · doi:10.58722/nure.v21i128.2458

Efectividad del cianocrilato en la reparación de heridas en cuero cabelludo, región ciliar y zona mentoniana en pediatría

2024· article· es· W4391378621 on OpenAlexaboutno aff
Miguel Ángel Consuegra Pérez, J. Ferrer, Virginia Martin Prieto, A. Espeso, Jorge González, Adrián Maldonado García

Bibliographic record

VenueNURE Investigación · 2024
Typearticle
Languagees
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyMedicine

Abstract

fetched live from OpenAlex

Resumen: Introducción. El uso en pediatría de adhesivos tisulares como el cianocrilato para el cierre de heridas ofrece ventajas significativas. Es un procedimiento sencillo rápido e indoloro, conformándose como una alternativa en la población pediátrica debido a las características específicas de estos pacientes. Objetivo. Evaluar la efectividad del adhesivo tisular con cianocrilato en el cierre de heridas en zonas pilosas y mentón. Metodología. Se diseñó un estudio observacional prospectivo conformado por pacientes pediátricos que acudieron a urgencias con heridas que requerían sutura en zona mentoniana, ceja y cuero cabelludo. Se valoraron variables demográficas y clínicas, así como la colaboración del menor y grado de satisfacción de padres y profesionales tras la aplicación de cianocrilato. A los 3 meses se valoró la cicatrización. Los datos se analizaron mediante el programa estadístico SSPS. Resultados. Las heridas en zonas pilosas presentaron una correcta epitelización con un índice ≤ 2 según escala de Vancouver. Se establecieron diferencias estadísticamente significativas entre la localización de la herida y su cicatrización (p<0.05). Se objetivó un grado de concordancia moderado entre la satisfacción de los padres y los profesionales con un p-valor < 0.001. Discusión. Los adhesivos tisulares con base de cianocrilato parecen una alternativa válida y segura para la reparación de heridas en zonas con folículo piloso. Cuenta con la aprobación de pacientes, familiares y profesionales que realizaron el procedimiento. Los resultados respecto a la cicatrización evaluados a los 3 meses son más satisfactorios en áreas pilosas. ABSTRACT Introduction. The use of tissue adhesives like cyanoacrylate for wound closure in pediatrics offers significant advantages. It is a simple, fast, and painless procedure, making it an alternative in the pediatric population due to the specific characteristics of these patients. Objective. To evaluate the effectiveness of tissue adhesive with cyanoacrylate in closing wounds on the scalp or hairy areas and the chin region. Methodology. A prospective observational study was designed, consisting of pediatric patients who presented to the emergency department with wounds requiring sutures in the chin, eyebrow, and scalp areas. Demographic and clinical variables were assessed, as well as the cooperation of the child and the satisfaction level of parents and healthcare professionals after the application of cyanoacrylate. Scar healing was assessed at 3 months. Data were analyzed using the statistical software SPSS. Results. Wounds in hairy areas showed proper epithelialization with an index ≤2 according to the Vancouver scale. Statistically significant differences were found in the relationship between wound location and its healing (p<0.05). Additionally, a moderate level of agreement was observed between parent and professional satisfaction, with a p-value <0.001. Discusión. Cyanoacrylate-based tissue adhesives appear to be a valid and safe alternative for wound repair in areas with hair follicles. They are well-received by patients, their families, and the professionals who performed the procedure. The results regarding scar healing evaluated at 3 months are more satisfactory on the scalp and eyebrow compared to the chin region.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.314
Teacher spread0.303 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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