To Josephine, Sinha Romi, Kim Susan W, Robinson Kathryn, Kearney Brendon, Howie Donald, To Luen Bik
From the Division of Aged Care, Rehabilitation and Palliative Care, Modbury Hospital, Modbury, South Australia, Australia (J.T.); School of Pharmacy and Medical Sciences, University of South Australia, Adelaide, South Australia, Australia (J.T.); Blood, Organ and Tissue Programs, Public Health and Clinical Systems, Department of Health, Adelaide, South Australia, Australia (R.S.); Faculty of Health Sciences (R.S.) and Flinders Centre for Epidemiology and Biostatistics, School of Medicine (S.W.K.), Flinders University, Bedford Park, South Australia, Australia; South Australia Bloodsafe Program, Adelaide, Australia (K.R.); Queen Elizabeth Hospital, Woodville, South Australia, Australia (K.R.); Departments of Haematology (B.K.) and Orthopaedics and Trauma (D.H.), Clinical Haematology Service (L.B.T.), and Clinical Section (L.B.T.), Royal Adelaide Hospital, Adelaide, South Australia, Australia; and Discipline of Orthopaedics and Trauma (D.H.) and Clinical Pathology (L.B.T.), University of Adelaide, Adelaide, South Australia, Australia.
Anesthesiology. 2017 Aug;127(2):317-325. doi: 10.1097/ALN.0000000000001709.
Preoperative anemia is a significant predictor of perioperative erythrocyte transfusion in elective arthroplasty patients. However, interactions with other patient and procedure characteristics predicting transfusion requirements have not been well studied.
Patients undergoing elective primary total hip arthroplasty or total knee arthroplasty at a tertiary hospital in Adelaide, South Australia, Australia, from January 2010 to June 2014 were used to identify preoperative predictors of perioperative transfusion. A logistic regression model was developed and externally validated with an independent data set from three other hospitals in Adelaide.
Altogether, 737 adult patients in the derivation group and 653 patients in the validation group were included. Binary logistic regression modeling identified preoperative hemoglobin (odds ratio, 0.51; 95% CI, 0.43 to 0.59; P < 0.001 for each 1 g/dl increase), total hip arthroplasty (odds ratio, 3.56; 95% CI, 2.39 to 5.30; P < 0.001), and females 65 yr of age and older (odds ratio, 3.37; 95% CI, 1.88 to 6.04; P = 0.01) as predictors of transfusion in the derivation cohort.
Using a combination of patient-specific preoperative variables, this validated model can predict transfusion in patients undergoing elective hip and knee arthroplasty. The model may also help to identify patients whose need for transfusion may be decreased through preoperative hemoglobin optimization.
术前贫血是择期关节置换术患者围手术期红细胞输血的重要预测指标。然而,其与其他预测输血需求的患者及手术特征之间的相互作用尚未得到充分研究。
选取2010年1月至2014年6月在澳大利亚南澳大利亚州阿德莱德一家三级医院接受择期初次全髋关节置换术或全膝关节置换术的患者,以确定围手术期输血的术前预测指标。建立了一个逻辑回归模型,并用来自阿德莱德其他三家医院的独立数据集进行了外部验证。
推导组共纳入737例成年患者,验证组纳入653例患者。二元逻辑回归模型确定,术前血红蛋白(比值比,0.51;95%可信区间,0.43至0.59;每增加1 g/dl,P < 0.001)、全髋关节置换术(比值比,3.56;95%可信区间,2.39至5.30;P < 0.001)以及65岁及以上女性(比值比,3.37;95%可信区间,1.88至6.04;P = 0.01)为推导队列中输血的预测指标。
使用特定患者的术前变量组合,这个经过验证的模型可以预测择期髋关节和膝关节置换术患者的输血情况。该模型还可能有助于识别那些通过术前优化血红蛋白水平可能减少输血需求的患者。