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Predictive Models for Medical Adhesive-Related Skin Injury: A Systematic Review and Meta-Analysis
Yujing Gu1, Zhouzhou Lu1, Yun Zhao1
1Department of Scientific Research, Affiliated Children's Hospital of Jiangnan University (Wuxi Children's Hospital), Wuxi, China.
Aims:
To systematically evaluate existing prediction models for medical adhesive-related skin injury and assess their potential contribution to nurse-led risk assessment and preventive care planning.
Methods:
A systematic review and meta-analysis was conducted. Seven databases were searched from inception to 25 October 2025. Studies developing prediction models for medical adhesive-related skin injury in adults were assessed using the Prediction Model Risk of Bias Assessment Tool. Random-effects meta-analyses were used to synthesize prevalence estimates, model discrimination and common predictors.
Results:
Twelve studies comprising 14 prediction models were included. Reported area under the curve or C-index values ranged from 0.789 to 0.960. In the nine studies included in the discrimination meta-analysis, the pooled area under the curve was 0.87 (95% confidence interval: 0.84-0.90). All studies had a high overall risk of bias, and none performed external validation. The pooled prevalence of medical adhesive-related skin injury was 22.0% (95% confidence interval: 18.5%-25.4%). Age over 60 years, a history of medical adhesive-related skin injury, allergy history, edema, study-defined hypoproteinemia, and moist skin were associated with higher odds, whereas higher Braden Scale scores were associated with lower odds.
Conclusions:
Existing models are not ready for stand-alone clinical use because of their high risk of bias and lack of external validation. Further well-designed studies are needed to develop and externally validate clinically useful prediction models for medical adhesive-related skin injury.
Implications For Nursing Practice:
The identified factors may help nurses prioritise closer skin assessment, surveillance, and individualised preventive care. They should be considered within a comprehensive nursing assessment rather than used as a validated risk score or intervention threshold.
No Patient Or Public Contribution:
None because this review used previously published evidence.
Registration:
PROSPERO registration number CRD420251179067.