Phillip Kim is a postdoctoral fellow, Department of Surgery, University of California, San Francisco.
Vamsi K. Aribindi is a postdoctoral fellow, Department of Surgery, University of California, San Francisco.
Am J Crit Care. 2022 Jan 1;31(1):42-50. doi: 10.4037/ajcc2022657.
Accurately measuring the risk of pressure injury remains the most important step for effective prevention and intervention. Relative contributions of risk factors for the incidence of pressure injury in adult critical care patients are not well understood.
To develop and validate a model to identify risk factors associated with hospital-acquired pressure injuries among adult critical care patients.
This retrospective cohort study included 23 806 adult patients (28 480 encounters) with an intensive care unit stay at an academic quaternary care center. Patient encounters were randomly split (7:3) into training and validation sets. The training set was used to develop a multivariable logistic regression model using the least absolute shrinkage and selection operator method. The model's performance was evaluated with the validation set.
Independent risk factors identified by logistic regression were length of hospital stay, preexisting diabetes, preexisting renal failure, maximum arterial carbon dioxide pressure, minimum arterial oxygen pressure, hypotension, gastrointestinal bleeding, cellulitis, and minimum Braden Scale score of 14 or less. On validation, the model differentiated between patients with and without pressure injury, with area under the receiver operating characteristic curve of 0.85, and performed better than a model with Braden Scale score alone (P < .001).
A model that identified risk factors for hospital-acquired pressure injury among adult critical care patients was developed and validated using a large data set of clinical variables. This model may aid in selecting high-risk patients for focused interventions to prevent formation of hospital-acquired pressure injuries.
准确测量压疮风险仍然是有效预防和干预的最重要步骤。成人重症监护患者压疮发生率相关风险因素的相对贡献尚不清楚。
开发和验证一种模型，以确定与成人重症监护患者医院获得性压疮相关的风险因素。
这项回顾性队列研究纳入了在学术四级护理中心接受重症监护的 23806 名成年患者（28480 例次）。患者例次随机（7:3）分为训练集和验证集。使用最小绝对收缩和选择算子方法，利用训练集开发多变量逻辑回归模型。使用验证集评估模型的性能。
逻辑回归确定的独立风险因素包括住院时间、既往糖尿病、既往肾衰竭、最大动脉二氧化碳分压、最低动脉氧分压、低血压、胃肠道出血、蜂窝织炎和Braden 量表评分低至 14 分。在验证中，该模型可区分有和无压疮的患者，受试者工作特征曲线下面积为 0.85，且优于仅使用Braden 量表评分的模型（P <.001）。
使用临床变量的大型数据集开发和验证了一种识别成人重症监护患者医院获得性压疮风险因素的模型。该模型可以帮助选择高危患者，以便进行有针对性的干预，预防医院获得性压疮的形成。
