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Updated: Jan 28, 2026

A Mouse Model of Mechanotransduction-driven, Human-like Hypertrophic Scarring
Published on: November 29, 2024
Predictive Factors for Facial Hypertrophic Scar Risk: A Retrospective Study Based on Injury Type and Inflammatory
1Department of Plastic Surgery, The First Affiliated Hospital of Anhui Medical University, Anhui Public Health Clinical Center, Yaohai, Hefei, Anhui, People's Republic of China.
Background:
Facial hypertrophic scar is a common clinical problem after trauma and surgery. Different injury types and healing processes may affect its risk, but a systematic analysis of relevant predictive factors is lacking.
Objective:
To analyze the relationship between different types of facial injuries and inflammation-healing-related factors and the occurrence of hypertrophic scar, and to construct a predictive model.
Methods:
Sixty patients who developed facial scars between June 2020 and June 2025 were retrospectively included. The primary outcome was the occurrence of hypertrophic scar. Firth-corrected univariate and multivariate logistic regression analyses were used to screen predictive factors, and the model performance was evaluated using ROC curves and bootstrap internal validation.
Results:
Hypertrophic scar occurred in 29 of the 60 patients, with an incidence rate of 48.3%. The highest incidence of hypertrophic scar was observed in burn patients (87.5%). Univariate analysis showed that burns, infection, and prolonged epithelialization time were significantly associated with hypertrophic scarring. In multivariate analysis, delayed epithelialization, infection, and burns remained independent risk factors. The apparent AUC of the predictive model was 0.815, and the bootstrap-corrected AUC was 0.792, indicating good calibration performance.
Conclusion:
Burn injury type, infection, and delayed epithelialization are important predictors of hypertrophic scarring in the head and face. The model constructed based on clinical indicators has good predictive ability and can provide a reference for early risk assessment.
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