In malnourished geriatric patients, deficient intake of energy and protein impairs tissue metabolism and microcirculation, significantly contributing to the development of skin failure. This study aims to develop and validate a prediction model for protein-energy malnutrition-associated skin failure among hospitalized elderly patients, facilitating early identification and targeted clinical interventions. This prospective, single-center study involves 391 hospitalized patients aged ≥ 65 years. The research is conducted in two stages: identifying independent risk factors and developing a risk prediction model. Bedside ultrasound (US) is utilized as a core assessment tool to quantify nutritional and tissue integrity markers. Specifically, the model incorporates: (a) dermal blood perfusion via power Doppler to evaluate microcirculatory status; (b) subcutaneous tissue thickness to assess structural depletion; and (c) tissue elastography to measure changes in skin stiffness and biomechanical properties. These sonographic data are integrated with clinical and biochemical variables to derive a risk score. Model performance is evaluated using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. By quantifying early subclinical changes in tissue perfusion and elasticity, the model is intended to identify high-risk patients before overt skin breakdown occurs, providing a critical window for preventive nutritional and nursing care. This prospective study establishes a novel, nutrition-based prediction model for skin failure in geriatric patients. By integrating multi-parametric ultrasound indicators, the model enables a shift from reactive to proactive care. Early identification of high-risk individuals facilitates targeted interventions, ultimately reducing skin-related complications and optimizing the quality of care for the hospitalized elderly population. Chinese Clinical Trial Registry, ChiCTR2500111057, registered October 24, 2025.
Shen et al. (Tue,) studied this question.