Turcotte Justin J, Menon Nandakumar, Kelly McKayla E, Grover Jennifer J, King Paul J, MacDonald James H
Department of Orthopedics, Anne Arundel Medical Center, Annapolis, MD, USA.
Arthroplast Today. 2021 Feb 1;7:182-187. doi: 10.1016/j.artd.2020.12.006. eCollection 2021 Feb.
In January 2020, The Centers for Medicare and Medicaid Services approved total knee arthroplasty (TKA) to be performed in ambulatory surgery centers (ASCs). This study aims to develop a predictive model for targeting appropriate patients for ASC-based TKA.
A retrospective review of 2266 patients (205 same-day discharge [SDD; 9.0%] and 2061 one-day length of stay [91.0%]) undergoing TKA at a regional medical center between July 2016 and September 2020 was conducted. Multiple logistic regression was used to evaluate predictors of SDD, as these patients represent those most likely to safely undergo TKA in an ASC.
Controlling for other demographics and comorbidities, patients with the following characteristics were at reduced odds of SDD: increased age (odds ratio [OR] = 0.935, < .001), body mass index ≥35 (OR = 0.491, = .002), female (OR = 0.535, < .001), nonwhite race (OR = 0.456, = .003), primary hypertension (OR = 0.710, = .032), ≥3 comorbidities (OR = 0.507, = .002), American Society of Anesthesiologists score ≥3 (OR = 0.378, < .001). The model was deemed to be of adequate fit using the Hosmer and Lemeshow test (χ = 12.437, = .112), and the area under the curve was found to be 0.773 indicating acceptable discrimination.
For patients undergoing primary TKA, increased age, body mass index ≥35, female gender, nonwhite race, primary hypertension, ≥3 comorbidities, and American Society of Anesthesiologists score ≥3 decrease the likelihood of SDD. A predictive model based on readily available patient presentation and comorbidity characteristics may aid surgeons in identifying patients that are candidates for SDD or ASC-based TKA.
2020年1月,美国医疗保险和医疗补助服务中心批准在门诊手术中心(ASC)进行全膝关节置换术(TKA)。本研究旨在建立一个预测模型,以确定适合在ASC进行TKA的患者。
对2016年7月至2020年9月期间在某地区医疗中心接受TKA的2266例患者(205例当日出院[SDD;9.0%]和2061例住院1天[91.0%])进行回顾性分析。采用多因素logistic回归评估SDD的预测因素,因为这些患者代表了最有可能在ASC安全接受TKA的人群。
在控制其他人口统计学和合并症因素后,具有以下特征的患者SDD几率降低:年龄增加(比值比[OR]=0.935,P<0.001)、体重指数≥35(OR=0.491,P=0.002)、女性(OR=0.535,P<0.001)、非白人种族(OR=0.456,P=0.003)、原发性高血压(OR=0.710,P=0.032)、≥3种合并症(OR=0.507,P=0.002)、美国麻醉医师协会评分≥3(OR=0.378,P<0.001)。使用Hosmer和Lemeshow检验(χ²=12.437,P=0.112)评估,该模型拟合度良好,曲线下面积为0.773,表明具有可接受的区分度。
对于接受初次TKA的患者,年龄增加、体重指数≥35、女性、非白人种族、原发性高血压、≥3种合并症以及美国麻醉医师协会评分≥3会降低当日出院的可能性。基于易于获取的患者表现和合并症特征的预测模型可能有助于外科医生识别适合当日出院或在ASC进行TKA的患者。