Delmore Barbara, Lebovits Sarah, Suggs Barbara, Rolnitzky Linda, Ayello Elizabeth A
Barbara Delmore, PhD, RN, CWCN, DAPWCA, IIWCC-NYU, Wound & Ostomy Nursing Service, NYU Langone Medical Center, New York. Sarah Lebovits, MSN, RN, ANP-BC, CWOCN, DAPWCA, IIWCC-NYU, Wound & Ostomy Nursing Service, NYU Langone Medical Center, New York. Barbara Suggs, BSN, RN, Department of Nursing, Critical Care, NYU Langone Medical Center, New York. Linda Rolnitzky, MS, Department of Population Health and Environmental Medicine, Division of Biostatistics, NYU Langone Medical Center, New York. Elizabeth A. Ayello, PhD, RN, ACNS-BC, CWON, MAPWCA, FAAN, Excelsior College School of Nursing, Clinical Editor Advances in Skin and Wound Care, Ayello, Harris and Associates, Inc, IIWCC-NYU Course Coordinator, New York.
J Wound Ostomy Continence Nurs. 2015 May-Jun;42(3):242-8; quiz E1-2. doi: 10.1097/WON.0000000000000134.
To develop and validate a method of predicting whether patients will develop a heel pressure ulcer during their hospital stay.
This retrospective case-control study used 2 separate data sets, one for an initial analysis followed by a second data set for validation analysis.
From 2009 to 2011, medical records of discharged patients with a DRG code for heel pressure ulcers in our urban, tertiary medical center were retrospectively reviewed. Using age as the matching criterion, we then reviewed cases of patients without heel pressure ulcers. The initial analysis comprised 37 patients with hospital-acquired heel pressure ulcers and 300 without. The validation analysis included 12 patients with heel pressure ulcers and 68 without.
In order to develop this method of identifying patients with heel pressure ulcers, logistic regression modeling was used to select a set of patient characteristics and hospital conditions that, independently and in combination, predicted heel pressure ulcers. Logistic modeling produced adjusted and unadjusted odds ratios for each of the significant predictor variables. The validation analysis was employed to test the predictive accuracy of the final model.
Initial analysis revealed 4 significant and independent predictors for heel pressure ulcer formation during hospitalization: diabetes mellitus, vascular disease, immobility, and an admission Braden Scale score of 18 or less. These findings were also supported in the validation analysis.
Beyond a risk assessment scale, staff should consider other factors that can predispose a patient to heel pressure ulcer development during their hospital stay, such as comorbid conditions (diabetes mellitus and vascular disease) and immobility.
开发并验证一种预测患者在住院期间是否会发生足跟压疮的方法。
这项回顾性病例对照研究使用了2个独立的数据集，一个用于初始分析，另一个用于验证分析。
回顾性分析了2009年至2011年期间在我们城市的三级医疗中心出院的、诊断相关分组（DRG）代码为足跟压疮的患者的病历。以年龄作为匹配标准，我们随后回顾了无足跟压疮患者的病例。初始分析包括37例医院获得性足跟压疮患者和300例无足跟压疮患者。验证分析包括12例足跟压疮患者和68例无足跟压疮患者。
为了开发这种识别足跟压疮患者的方法，采用逻辑回归模型来选择一组独立或综合预测足跟压疮的患者特征和医院状况。逻辑模型为每个显著预测变量生成了调整和未调整的比值比。采用验证分析来检验最终模型的预测准确性。
初始分析揭示了住院期间足跟压疮形成的4个显著且独立的预测因素：糖尿病、血管疾病、活动受限以及入院时Braden量表评分≤18分。这些发现也在验证分析中得到了支持。
除了风险评估量表外，医护人员还应考虑其他可能使患者在住院期间易发生足跟压疮的因素，如合并症（糖尿病和血管疾病）及活动受限。
