Horn Susan D, Barrett Ryan S, Fife Caroline E, Thomson Brett
Susan D. Horn, PhD • Adjunct Professor • Department of Population Health Sciences Health System Innovation and Research Program • University of Utah School of Medicine • Salt Lake City • Senior Scientist • Institute for Clinical Outcomes Research • Salt Lake City, Utah Ryan S. Barrett, MStat • Quantitative Modeling Analyst • Zions Bancorporation • Salt Lake City, Utah • Senior Analyst • Institute for Clinical Outcomes Research • Salt Lake City, Utah Caroline E. Fife, MD • Chief Medical Officer • Intellicure, Inc • The Woodlands, Texas • Director • US Wound Registry • The Woodlands, Texas Brett Thomson, BS • Chief Information Officer • Intellicure, Inc • The Woodlands, Texas • Senior Analyst • US Wound Registry • The Woodlands, Texas.
Adv Skin Wound Care. 2015 Dec;28(12):560-72; quiz 573-4. doi: 10.1097/01.ASW.0000473131.10948.e7.
The purpose of this learning activity is to provide information regarding the creation of a risk-stratification system to predict the likelihood of the healing of body and heel pressure ulcers (PrUs).
This continuing education activity is intended for physicians and nurses with an interest in skin and wound care.
After participating in this educational activity, the participant should be better able to:1. Explain the need for a PrU risk stratification tool.2. Describe the purpose and methodology of the study.3. Delineate the results of the study and development of the Wound Healing Index.
: To create a validated system to predict the healing likelihood of patients with body and heel pressure ulcers (PrUs), incorporating only patient- and wound-specific variables.
The US Wound Registry data were examined retrospectively and assigned a clear outcome (healed, amputated, and so on). Significant variables were identified with bivariate analyses. Multivariable logistic regression models were created based on significant factors (P < .05) and tested on a 10% randomly selected hold-out sample.
Fifty-six wound clinics in 24 states
: A total of 7973 body PrUs and 2350 heel PrUs were eligible for analysis.
Not applicable
: Healed PrU MAIN RESULTS:: Because of missing data elements, the logistic regression development model included 6640 body PrUs, of which 4300 healed (64.8%), and the 10% validation sample included 709 PrUs, of which 477 healed (67.3%). For heel PrUs, the logistic regression development model included 1909 heel PrUs, of which 1240 healed (65.0%), and the 10% validation sample included 203 PrUs, of which 133 healed (65.5%). Variables significantly predicting healing were PrU size, PrU age, number of concurrent wounds of any etiology, PrU Stage III or IV, evidence of bioburden/infection, patient age, being nonambulatory, having renal transplant, paralysis, malnutrition, and/or patient hospitalization for any reason.
Body and heel PrU Wound Healing Indices are comprehensive, user-friendly, and validated predictive models for likelihood of body and heel PrU healing. They can risk-stratify patients in clinical research trials, stratify patient data for quality reporting and benchmarking activities, and identify patients most likely to require advanced therapeutics to achieve healing.
本学习活动的目的是提供有关创建风险分层系统的信息,以预测身体和足跟压疮(PrU)愈合的可能性。
本继续教育活动面向对皮肤和伤口护理感兴趣的医生和护士。
参加本教育活动后,参与者应能更好地:1. 解释PrU风险分层工具的必要性。2. 描述该研究的目的和方法。3. 阐述该研究的结果以及伤口愈合指数的开发情况。
创建一个经过验证的系统,仅纳入患者和伤口特定变量,以预测身体和足跟压疮患者的愈合可能性。
对美国伤口登记处的数据进行回顾性检查,并指定明确的结果(愈合、截肢等)。通过双变量分析确定显著变量。基于显著因素(P <.05)创建多变量逻辑回归模型,并在随机选择的10%保留样本上进行测试。
24个州的56家伤口诊所
共有7973例身体PrU和2350例足跟PrU符合分析条件。
不适用
PrU愈合
由于数据元素缺失,逻辑回归开发模型纳入了6640例身体PrU,其中4300例愈合(64.8%),10%的验证样本纳入了709例PrU,其中477例愈合(67.3%)。对于足跟PrU,逻辑回归开发模型纳入了1909例足跟PrU,其中1240例愈合(65.0%),10%的验证样本纳入了203例PrU,其中133例愈合(65.5%)。显著预测愈合的变量包括PrU大小、PrU形成时间、任何病因的并发伤口数量、PrU III期或IV期、生物负荷/感染证据、患者年龄、非行走状态、肾移植、瘫痪、营养不良和/或因任何原因住院。
身体和足跟PrU伤口愈合指数是用于预测身体和足跟PrU愈合可能性的全面、用户友好且经过验证的预测模型。它们可在临床研究试验中对患者进行风险分层,为质量报告和基准活动对患者数据进行分层,并识别最有可能需要先进治疗以实现愈合的患者。