College of Medicine and Dentistry, James Cook University, 1 James Cook Drive, Townsville, QLD, 4811, Australia.
Orthopaedic Research Institute of Queensland, 7 Turner Street, Townsville, QLD, 4812, Australia.
J Orthop Surg Res. 2020 Nov 10;15(1):513. doi: 10.1186/s13018-020-02042-5.
No validated pre-operative cardiac risk stratification tool exists that is specific for total hip and total knee arthroplasty (THA and TKA, respectively). To reduce the risk of post-operative cardiac complication, surgeons need clear guidance on which patients are likely to benefit from pre-operative cardiac optimisation. This is particularly important for asymptomatic patients, where the need is harder to determine.
Primary THA and TKA performed between January 1, 2010, and December 31, 2017, were identified from a single orthopaedic practice. Over 25 risk factors were evaluated as predictors for patients requiring additional cardiac investigation beyond an ECG and echocardiogram, and for cardiac abnormality detected upon additional investigation. A multivariate logistic regression was conducted using significant predictor variables identified from inferential statistics. A series of predictive scores were constructed and weighted to identify the influence of each variable on the ability to predict the detection of cardiac abnormality pre-operatively.
Three hundred seventy-four patients were eligible for inclusion. Increasing age (p < 0.001), history of cerebrovascular accident (p = 0.018), family history of cardiovascular disease (FHx of CVD) (p < 0.001) and decreased ejection fraction (EF) (p < 0.001) were significant predictors of additional cardiac investigation being required. Increasing age (p = 0.003), male gender (p = 0.042), FHx of CVD (p = 0.001) and a reduced EF (p < 0.001) were significantly predictive for the detection of cardiac abnormality upon additional cardiac investigation.
Increasing age, male gender, FHx of CVD and decreased ejection fraction are important risk factors to consider for pre-operative cardiac optimisation in THA and TKA patients. These findings can be applied towards future predictive models, to determine which asymptomatic patients are likely to benefit from pre-operative cardiac referral.
目前尚无专门针对全髋关节置换术（THA）和全膝关节置换术（TKA）的术前心脏风险分层工具。为降低术后心脏并发症的风险，外科医生需要明确指导，了解哪些患者可能从术前心脏优化中获益。这对于无症状患者尤为重要，因为更难确定他们的需求。
从一家骨科诊所确定了 2010 年 1 月 1 日至 2017 年 12 月 31 日期间进行的初次 THA 和 TKA。评估了 25 多个危险因素，这些因素可预测除心电图和超声心动图以外，还需要进一步心脏检查的患者，以及在进一步检查中发现的心脏异常。使用推断统计学确定的显著预测变量进行多元逻辑回归。构建并加权一系列预测评分，以确定每个变量对术前预测心脏异常检测能力的影响。
共有 374 名患者符合纳入标准。年龄增加（p<0.001）、脑血管意外史（p=0.018）、心血管疾病家族史（FHx of CVD）（p<0.001）和射血分数降低（p<0.001）是需要进一步心脏检查的显著预测因素。年龄增加（p=0.003）、男性（p=0.042）、FHx of CVD（p=0.001）和射血分数降低（p<0.001）是进一步心脏检查时发现心脏异常的显著预测因素。
年龄增加、男性、FHx of CVD 和射血分数降低是 THA 和 TKA 患者术前心脏优化的重要危险因素。这些发现可应用于未来的预测模型，以确定哪些无症状患者可能从术前心脏转诊中获益。
