Sephton B M, Bakhshayesh P, Edwards T C, Ali A, Kumar Singh V, Nathwani D
Department of Orthopaedics, Imperial College Healthcare NHS Trust, Charing Cross Hospital, London, W6 8RF, UK.
J Clin Orthop Trauma. 2020 Mar;11(Suppl 2):S239-S245. doi: 10.1016/j.jcot.2019.09.009. Epub 2019 Sep 11.
To identify factors that independently predict extended length of stay after unicompartmental knee arthroplasty (UKA) surgery (defined as length of stay longer than 3 days), and to identify factors predicting early post-operative complications.
A retrospective analysis of all patients undergoing UKA from January 2016-January 2019 at our institution was performed. Clinical notes were reviewed to determine the following information: Patient age (years), gender, American Society of Anesthesiologists (ASA) grade, weight (kg), height (meters), body mass index (BMI), co-morbidities, indication for surgery, surgeon, surgical volume, surgical technique (navigated or patient-specific instrumentation), implant manufacturer, estimated blood loss (ml), application of tourniquet during the surgery, application of drain, hospital length of stay (days) and surgical complications.
Multivariate regression analysis showed that ASA 3-4 vs. ASA 1-2 [OR 4.4 (CI; 1.8-10.8, p = 0.001)] and a history of cardiovascular disease [OR 2.8 (CI; 1.4-5.5), p = 0.004)] were significant independent predictors of prolonged length of stay. Hosmer-Lemeshow goodness of fit of the model showed a p-value of 0.214. Nagelkerke R-Square was 0.2. For complications, multivariate regression analysis showed that ASA 3-4 vs. ASA 1-2 [OR 5.8 (CI; 1.7-20.7)] and high BMI (BMI >30) [OR 4.3 (CI; 1.1-17.1)] were significant independent predictors of complications. Hosmer-Lemeshow goodness of fit was 0.89 and Nagelkerke R-Square was 0.2. Patients treated with robotics (Navio) techniques had shorter length of stay median 51 h (IQR; 29-96) when compared to other techniques 72 h (IQR; 52-96), p = 0.008.
Based on the results of our study, high ASA grade (≥3) appears to be the most important factor excluding eligibility for fast-track UKA. Any number of co-morbidities may increase ASA, but in and of themselves, apart from a history of cardiovascular disease, they should not be seen as contraindications. Appropriate patient selection, technical tools and details during the surgery could facilitate fast track surgery.
确定单髁膝关节置换术（UKA）后独立预测延长住院时间（定义为住院时间超过3天）的因素，并确定预测术后早期并发症的因素。
对2016年1月至2019年1月在本机构接受UKA手术的所有患者进行回顾性分析。查阅临床记录以确定以下信息：患者年龄（岁）、性别、美国麻醉医师协会（ASA）分级、体重（kg）、身高（米）、体重指数（BMI）、合并症、手术指征、外科医生、手术量、手术技术（导航或定制器械）、植入物制造商、估计失血量（ml）、手术中止血带的应用、引流管的应用、住院时间（天）和手术并发症。
多因素回归分析显示，ASA 3 - 4级与ASA 1 - 2级相比[比值比（OR）4.4（可信区间CI；1.8 - 10.8，p = 0.001）]以及有心血管疾病史[OR 2.8（CI；1.4 - 5.5），p = 0.004]是住院时间延长的显著独立预测因素。模型的Hosmer - Lemeshow拟合优度显示p值为0.214。Nagelkerke决定系数R²为0.2。对于并发症，多因素回归分析显示，ASA 3 - 4级与ASA 1 - 2级相比[OR 5.8（CI；1.7 - 20.7）]以及高BMI（BMI > 30）[OR 4.3（CI；1.1 - 17.1）]是并发症的显著独立预测因素。Hosmer - Lemeshow拟合优度为0.89，Nagelkerke决定系数R²为0.2。与其他技术（72小时，四分位间距IQR；52 - 96）相比，采用机器人技术（Navio）治疗的患者住院时间更短，中位数为51小时（IQR；29 - 96），p = 0.008。
根据我们的研究结果，高ASA分级（≥3）似乎是排除快速通道UKA资格的最重要因素。任何数量的合并症都可能增加ASA分级，但就其本身而言，除了心血管疾病史外，不应将其视为禁忌证。适当的患者选择、技术工具和手术中的细节可以促进快速通道手术。
