College of Nursing, East Carolina University, Greenville, NC 27858, USA.
Cardiovascular Sciences, East Carolina Heart Institute at Vidant Medical Center Greenville, Greenville, NC 27858, USA.
Int J Environ Res Public Health. 2018 Dec 28;16(1):73. doi: 10.3390/ijerph16010073.
An assumption regarding transcatheter aortic valve replacement (TAVR), a minimally invasive procedure for treating aortic stenosis, is that patients remain at, or near baseline and soon return to their presurgical home to resume activities of daily living. However, this does not consistently occur. The purpose of this study was to identify preoperative factors that optimally predict discharge to a skilled nursing facility (SNF) after TAVR. Delineation of these conditions is an important step in developing a risk stratification model to assist in making informed decisions. Data was extracted from the American College of Cardiology (ACC) transcatheter valve therapy (TVT) registry and the Society of Thoracic Surgeons (STS) database on 285 patients discharged from 2012⁻2017 at a tertiary referral heart institute located in the southeastern region of the United States. An analysis of assessment, clinical and demographic variables was used to estimate relative risk (RR) of discharge to a SNF. The majority of participants were female (55%) and white (84%), with a median age of 82 years (interquartile range = 9). Approximately 27% ( = 77) were discharged to a SNF. Age > 75 years (RR = 2.3, 0.0026), female (RR = 1.6, = 0.019), 5-meter walk test (5MWT) >7 s (RR = 2.0, = 0.0002) and not using home oxygen (RR = 2.9, = 0.0084) were identified as independent predictive factors for discharge to a SNF. We report a parsimonious risk-stratification model that estimates the probability of being discharged to a SNF following TAVR. Our findings will facilitate making informed treatment decisions regarding this older patient population.
经导管主动脉瓣置换术(TAVR)是一种治疗主动脉瓣狭窄的微创方法,人们假设患者保持在基线或接近基线水平,并很快返回术前住所,恢复日常生活活动。然而,情况并非总是如此。本研究的目的是确定 TAVR 后患者出院至熟练护理机构(SNF)的最佳预测术前因素。明确这些条件是制定风险分层模型以协助做出明智决策的重要步骤。数据从美国东南部一家三级转诊心脏研究所 2012-2017 年期间出院的 285 名患者的美国心脏病学会(ACC)经导管瓣膜治疗(TVT)登记处和胸外科医师学会(STS)数据库中提取。对评估、临床和人口统计学变量进行分析,以估计出院至 SNF 的相对风险(RR)。大多数参与者为女性(55%)和白人(84%),中位年龄为 82 岁(四分位距=9)。约 27%(=77)出院至 SNF。年龄>75 岁(RR=2.3,P=0.0026)、女性(RR=1.6,P=0.019)、5 米步行测试(5MWT)>7 s(RR=2.0,P=0.0002)和不使用家庭氧气(RR=2.9,P=0.0084)是出院至 SNF 的独立预测因素。我们报告了一个简洁的风险分层模型,可估计 TAVR 后患者出院至 SNF 的概率。我们的发现将有助于针对这一老年患者群体做出明智的治疗决策。