MSN, RN, Intensive Care Specialist Nurse, Department of Critical Care Medicine, Zhejiang Hospital, Hangzhou, Zhejiang Province, People's Republic of China.
PhD, MD, Professor, Department of Critical Care Medicine, Zhejiang Hospital, Hangzhou, Zhejiang Province, People's Republic of China.
J Nurs Res. 2024 Aug 1;32(4):e338. doi: 10.1097/jnr.0000000000000627.
The risk factors for acute skin failure (ASF), a serious complication of the skin, are not fully understood.
This study was designed to explore the risk factors for ASF in critically ill patients and construct a clinical prediction model.
Intensive care unit patients were prospectively observed and assigned into two groups: with and without ASF. A logistic regression model was constructed, and its predictive power and clinical utility were evaluated.
Of the 204 eligible patients enrolled as participants, 58 (28.43%) developed ASF. Sepsis, vasoactive drugs, and age were shown to be risk factors for ASF, whereas peripheral perfusion index ratio and albumin level were shown to be protective factors. The area under the receiver operating characteristic curve was 0.83. The maximum Youden index of the model was 0.39 (specificity: 0.87, sensitivity: 0.77). The Hosmer-Lemeshow test (p = .20) and calibration curve showed good fitness and predictive utility with respect to the model.
The developed model effectively predicts ASF risk, allowing for the early identification of high-risk patients. Identifying risk factors such as sepsis, vasoactive drugs, and age and considering protective factors such as peripheral perfusion index and albumin levels may help optimize care plans. Clinical staff should pay special attention to these factors and their impact on skin health in critically ill patients.
急性皮肤衰竭（ASF）是一种严重的皮肤并发症，其风险因素尚未完全了解。
本研究旨在探讨重症患者 ASF 的风险因素，并构建临床预测模型。
前瞻性观察重症监护病房患者，并将其分为有 ASF 组和无 ASF 组。构建逻辑回归模型，并评估其预测能力和临床实用性。
在纳入的 204 名符合条件的患者中，有 58 名（28.43%）发生了 ASF。脓毒症、血管活性药物和年龄是 ASF 的危险因素，而外周灌注指数比和白蛋白水平是保护因素。受试者工作特征曲线下面积为 0.83。模型的最大约登指数为 0.39（特异性：0.87，敏感性：0.77）。Hosmer-Lemeshow 检验（p=0.20）和校准曲线表明该模型具有良好的拟合度和预测实用性。
该模型可有效预测 ASF 风险，有助于早期识别高危患者。识别脓毒症、血管活性药物和年龄等风险因素，并考虑外周灌注指数和白蛋白水平等保护因素，可能有助于优化护理计划。临床医护人员应特别关注这些因素及其对重症患者皮肤健康的影响。
