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中华关节外科杂志(电子版)

中华关节外科杂志(电子版) ›› 2022, Vol. 16 ›› Issue (01) : 1 -7. doi: 10.3877/cma.j.issn.1674-134X.2022.01.001

临床论著

老年股骨颈骨折半髋关节置换术后输血预测模型的建立
贾大洲1, 孙钰1, 何世平1, 张亚鑫1, 戴纪杭1, 林群1, 李小磊1, 王强1,†()   
  1. 1. 225001　扬州大学临床医学院（江苏省苏北人民医院）
  • 收稿日期:2021-04-29 出版日期:2022-02-01
  • 通信作者: 王强
  • 基金资助:
    江苏省医学创新团队课题(CXTDB2017004)

Establishment of nomogram for predicting blood transfusion following hemiarthroplasty of femoral neck fractures in elderly patients

Dazhou Jia1, Yu Sun1, Shiping He1, Yaxin Zhang1, Jihang Dai1, Qun Lin1, Xiaolei Li1, Qiang Wang1,†()   

  1. 1. Department of Bone and Joint, Clinical Medical College of Yangzhou University, Northern Jiangsu People’s Hospital, Yangzhou 225001, China
  • Received:2021-04-29 Published:2022-02-01
  • Corresponding author: Qiang Wang
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引用本文：

贾大洲, 孙钰, 何世平, 张亚鑫, 戴纪杭, 林群, 李小磊, 王强. 老年股骨颈骨折半髋关节置换术后输血预测模型的建立[J/OL]. 中华关节外科杂志(电子版), 2022, 16(01): 1-7.

Dazhou Jia, Yu Sun, Shiping He, Yaxin Zhang, Jihang Dai, Qun Lin, Xiaolei Li, Qiang Wang. Establishment of nomogram for predicting blood transfusion following hemiarthroplasty of femoral neck fractures in elderly patients[J/OL]. Chinese Journal of Joint Surgery(Electronic Edition), 2022, 16(01): 1-7.

目的

分析老年股骨颈骨折患者半髋关节置换术后输血的危险因素，建立老年股骨颈骨折患者半髋关节置换术后输血的列线图预测模型。

方法

回顾性分析2016年1月至2020年6月江苏省苏北人民医院股骨颈骨折行半髋关节置换术的235例患者。纳入标准：年龄≥60岁，新发、单侧股骨颈骨折；手术方式为半髋关节置换术。排除标准：合并全身其他骨折；术前输血；合并凝血功能障碍或者其他血液系统疾病；身体状况较差无法耐受手术者；病历资料不完整者。根据术后是否输血，分为输血组和未输血组。收集其临床资料，包括性别、年龄、身体质量指数(BMI)、高血压、糖尿病、冠心病、脑卒中、吸烟、饮酒、术前血红蛋白(Hb)、术前血小板(PLT)、术前白蛋白、术前凝血功能、术前抗凝药使用、骨折Garden分型、受伤至手术时间、假体类型、术后是否引流、术后血钙浓度、美国麻醉师协会(ASA)分级、麻醉方式、手术时间、术中出血量等。应用单因素和多因素logistic回归模型筛选术后输血的独立危险因素；通过R软件构建列线图预测模型，并绘制出受试者工作特征(ROC)曲线及校准曲线来评价模型的区分度和准确度。

结果

本研究共纳入235例研究对象，输血组60例，输血率为25.5%。两组患者在术前Hb(χ2＝62.831)、麻醉方式(χ2＝6.539)、手术时间(χ2＝79.392)、术中出血量(χ2＝74.515)、假体类型(χ2＝5.631)方面的组间差异有统计学意义(均为P<0.05)。多因素logistic回归模型分析显示：术前Hb水平(Hb<100 g/L)、手术时间延长(时间≥60 min)、术中出血量增多(出血量≥200 ml)是老年股骨颈骨折患者半髋关节置换术后输血的独立危险因素(均为P<0.05)。列线图预测模型曲线下面积AUC为0.95，校准曲线的斜率接近1，提示该预测模型具有良好的区分度和准确度。

结论

基于术前血红蛋白、手术时间、术中出血量这3项独立危险因素构建的老年股骨颈骨折患者半髋关节置换术后输血预测的列线图模型具有良好的区分度和准确度，望为临床上早期甄别术后高风险输血患者提供指导意义。

关键词: 股骨颈骨折, 关节成形术，置换，髋, 输血, 危险因素, 列线图
Objective

To analyze the risk factors of blood transfusion after hemiarthroplasty in elderly patients with femoral neck fracture, and to establish a nomogram prediction model of blood transfusion after hemiarthroplasty in elderly patients with femoral neck fracture.

Methods

A total of 235 patients who underwent hemiarthroplasty for femoral neck fractures in the Northern Jiangsu People’s Hospital from January 2016 to June 2020 were analyzed retrospectively.Inclusion criteria: age ≥60 years, new onset, unilateral femoral neck fracture; surgical method is hemiarthroplasty. Exclusion criteria: other fractures; preoperative blood transfusion; coagulation disorders or other hematological diseases; poor physical condition; incomplete medical records. According to whether blood transfusion was performed or not, the patients were divided into transfusion group and non-transfusion group. The clinical data were collected, including sex, age, body mass index (BMI), hypertension, diabetes, coronary heart disease, stroke, smoking, drinking, preoperative hemoglobin (Hb), preoperative platelet (PLT), preoperative albumin, preoperative use of anti-coagulants, Garden classification of femoral neck fracture, time of injury to operation, the type of prosthesis, postoperative drainage, postoperative serum calcium concentration, American Association of anesthesiologists (ASA) grade, mode of anesthesia, operation time, intraoperative blood loss and so on. Single-factor and multi-factor logistic regression models were used to screen the independent risk factors of postoperative blood transfusion, and the nomogram prediction model was constructed by R software, and the receiver operating characteristic (ROC) curve and calibration curve were drawn to evaluate the differentiation and accuracy degree of the model.

Results

A total of 235 subjects were included in this study, including 60 cases in the blood transfusion group, with a blood transfusion rate of 25.5%. There were significant differences between the two groups in preoperative Hb(χ2=62.831), mode of anesthesia(χ2=6.539), operation time(χ2=79.392), intraoperative blood loss(χ2=74.515) and the type of prosthesis(χ2=5.631)(all P<0.05). Multivariate logistic regression model analysis showed that lower preoperative Hb(Hb<100 g/L), prolonged operation time (time ≥60 min) and increased intraoperative blood loss (blood loss≥200 ml) were independent risk factors for blood transfusion after hemiarthroplasty in elderly patients with femoral neck fracture(all P<0.05). The area under the curve (AUC) of the nomogram prediction model was 0.95, and the slope of the calibration curve was close to one, indicating that the prediction model had good degree of differentiation and sccuracy.

Conclusions

The nomogram model for predicting blood transfusion after hemiarthroplasty in elderly patients with femoral neck fracture based on three independent risk factors(preoperative hemoglobin, operation time and intraoperative blood loss) has good differentiation and accuracy degree. It is expected to provide guidance for early screening of patients with high-risk blood transfusion after operation.

Key words: Femoral neck fracture, Arthroplasty, replacement, hip, Blood transfusion, Risk factors, Nomogram
表1 两组患者基线资料及单因素分析结果
变量   未输血组 输血组 统计值 P值
例数   175 60    
性别(例) 男 46 19 χ2＝0.647 >0.05
  女 129 41    
年龄[岁，M(P25，P75)]   83.0 (80.0，87.0) 84.5 (80.8，88.0) Z＝1.441 >0.05
BMI (例) <25 kg/m2 154 54    
  ≥25 kg/m2 21 6 χ2＝0.176 >0.05
高血压(例) 无 89 31    
  有 86 29 χ2＝0.012 >0.05
糖尿病(例) 无 141 50    
  有 34 10 χ2＝0.224 >0.05
冠心病(例) 无 152 52    
  有 23 8 χ2＝0.001 >0.05
脑卒中(例) 无 145 49    
  有 30 11 χ2＝0.044 >0.05
吸烟史(例) 无 164 58    
  有 11 2 χ2＝0.287 >0.05
饮酒史(例) 无 172 58    
  有 3 2 χ2＝0.054 >0.05
受伤至手术时间(例) <7 d 103 29    
  ≥7 d 72 31 χ2＝2.010 >0.05
术前抗凝药使用(例) 无 152 51    
  有 23 9 χ2＝0.131 >0.05
  Ⅱ 17 4    
Garden分型(例) Ⅲ 62 25 χ2＝1.018 >0.05
  Ⅳ 96 31    
  <100 g/L 2 19    
术前Hb(例) 100~120 g/L 63 28    
  120~140 g/L 90 12 χ2＝62.831 <0.01
  ≥140 g/L 20 1    
术前PLT [109个/L，M(P25，P75)]   176.0(132.5，212.5) 164.0(121.2，212.8) Z＝0.616 >0.05
术前凝血功能          
D-二聚体[mg/L，M(P25，P75)]   3.3(2.0，9.1) 3.3(1.8，7.2) Z＝0.149 >0.05
凝血酶原时间[s，M(P25，P75)]   13.7(13.3，14.2) 13.7(13.1，14.4) Z＝0.050 >0.05
PT国际标准化比值M(P25，P75)   1.1(1.0，1.1) 1.1(1.0，1.1) Z＝0.246 >0.05
活化部分凝血酶时间[s，M(P25，P75)]   38.9(35.9，42.1 ) 40.1(36.2，41.9) Z＝0.823 >0.05
凝血酶时间[s，M(P25，P75)]   17.0(16.1，17.8 ) 17.0(16.2，17.8) Z＝0.326 >0.05
纤维蛋白原浓度[g/L，M(P25，P75)]   4.0(3.3，4.8 ) 3.9(3.3，4.5) Z＝0.851 >0.05
白蛋白[g/L，M(P25，P75)]   39.5(37.4, 42.4 ) 38.9(35.9，41.0) Z＝1.568 >0.05
  Ⅱ 22 6    
ASA分级(例) Ⅲ 150 52 χ2＝0.762 >0.05
  Ⅳ 3 2    
麻醉方式(例) 局麻 161 48    
  全麻 14 12 χ2＝6.539 <0.05
手术时间(例) <60 min 161 22    
  ≥60 min 14 38 χ2＝79.392 <0.01
假体类型(例) 生物型 74 36    
  骨水泥型 101 24 χ2＝5.631 <0.05
  <100 ml 54 4    
术中出血量(例) 100~200 ml 112 24 χ2＝74.515 <0.01
  ≥200 ml 9 32    
术后血钙[mmol/L，M(P25，P75)]   2.2 ( 2.2，2.3 ) 2.2 ( 2.1，2.3 ) Z＝0.761 >0.05
术后引流(例) 无 156 55    
  有 19 5 χ2＝0.310 >0.05
表2 输血组与非输血组患者多因素logistic回归分析结果
变量   回归系数 标准误 Wald值 OR值(95%CI) P值
术前Hb(g/L) <100 参考 - - - -
  100~120 -4.877 1.119 -4.360 0.008(0.001，0.053) <0.001
  120~140 -6.990 1.336 -5.230 0.001(0，0.009) <0.001
  ≥140 -5.618 1.545 -3.640 0.004(0，0.05) <0.001
  ≥200 参考 - - - -
术中出血量(ml) 100~200 -2.634 0.671 -3.930 0.072(0.018，0.253) <0.001
  <100 -4.799 1.112 -4.320 0.008(0.001，0.059) <0.001
手术时间(min) ≥60 参考 - - - -
  <60 -3.675 0.668 -5.500 0.025(0.006，0.085) <0.001
假体类型 生物型 参考 - - - -
  骨水泥型 -0.661 0.574 -1.150 0.516(0.161，1.584) 0.250
麻醉方式 局麻 参考 - - - -
  全麻 0.993 0.853 1.160 2.699(0.49，14.179) 0.244
图1 预测老年股骨颈骨折患者半髋关节置换术后输血的列线图模型注：HB-血红蛋白
图2 列线图预测老年股骨颈骨折患者半髋关节置换术后输血的受试者ROC(工作特征)曲线
图3 列线图预测老年股骨颈骨折患者半髋关节置换术后输血的校准曲线
[1]
He M, Han W, Zhao CP, et al. Evaluation of a bi-planar robot navigation system for insertion of cannulated screws in femoral neck fractures[J]. Orthop Surg, 2019, 11(3): 373-379.
[2]
Pauyo T, Drager J, Albers A, et al. Management of femoral neck fractures in the young patient: a critical analysis review[J]. World J Orthop, 2014, 5(3): 204-217.
[3]
Bhandari M, Devereaux PJ, Tornetta P, et al. Operative management of displaced femoral neck fractures in elderly patients. An international survey[J]. J Bone Joint Surg Am, 2005, 87(9): 2122-2130.
[4]
Liodakis E, Antoniou J, Zukor DJ, et al. Major complications and transfusion rates after hemiarthroplasty and total hip arthroplasty for femoral neck fractures[J]. J Arthroplasty, 2016, 31(9): 2008-2012.
[5]
Morris R, Rethnam U, Russ B, et al. Assessing the impact of fracture pattern on transfusion requirements in hip fractures[J]. Eur J Trauma Emerg Surg, 2017, 43(3): 337-342.
[6]
Woon CYL, Moretti VM, Schwartz BE, et al. Total hip arthroplasty and hemiarthroplasty: US national trends in the treatment of femoral neck fractures[J]. Am J Orthop(Belle Mead NJ), 2017, 46(6): E474-E478.
[7]
Kadar A, Chechik O, Steinberg E, et al. Predicting the need for blood transfusion in patients with hip fractures[J]. Int Orthop, 2013, 37(4): 693-700.
[8]
Nichols C, Vose JG, Nunley RM. Clinical outcomes and 90-day costs following hemiarthroplasty or total hip arthroplasty for hip fracture[J]. J Arthroplasty, 2017, 32(9S): S128-S134.
[9]
Kim Y, Spolverato G, Lucas DJ, et al. Red cell transfusion triggers and postoperative outcomes after major surgery[J]. J Gastrointest Surg, 2015, 19(11): 2062-2073.
[10]
Bagante F, Spolverato G, Ruzzenente A, et al. Validation of a nomogram to predict the risk of perioperative blood transfusion for liver resection[J]. World J Surg, 2016, 40(10): 2481-2489.
[11]
Hu C, Wang YH, Shen R, et al. Development and validation of a nomogram to predict perioperative blood transfusion in patients undergoing total knee arthroplasty[J]. BMC Musculoskelet Disord, 2020, 21(1): 315-324.
[12]
Wang H, Wang K, Lv B, et al. Establishment and assessment of a nomogram for predicting blood transfusion risk in posterior lumbar spinal fusion[J]. J Orthop Surg Res, 2021, 16(1): 39-50.
[13]
To J, Sinha R, Kim SW, et al. Predicting perioperative transfusion in elective hip and knee arthroplasty: a validated predictive model[J]. Anesthesiology, 2017, 127(2): 317-325.
[14]
Wang JQ, Chen LY, Jiang BJ, et al. Development of a nomogram for predicting blood transfusion risk after hemiarthroplasty for femoral neck fractures in elderly patients[J/OL]. Med Sci Monit, 2020, 26(1): e920255. DOI: 10.12659/MSM.920255.
[15]
沈瑞，孟祥英，于腾波，等．股骨颈骨折全髋关节置换围手术期输血预测的列线图模型[J]．中国骨与关节损伤杂志，2020，35(10): 1016-1019.
[16]
赵世新，王丹，王朕，等．全髋关节置换术后异体输血的相关因素分析[J]．中国矫形外科杂志，2020，28(10): 865-869.
[17]
Adunsky A, Lichtenstein A, Mizrahi E, et al. Blood transfusion requirements in elderly hip fracture patients[J]. Arch Gerontol Geriatr, 2003, 36(1): 75-81.
[18]
Guarino S, Di Matteo FM, Sorrenti S, et al. Bloodless surgery in geriatric surgery[J]. Int J Surg, 2014, 12(2): S82-S85.
[19]
Hou G, Zhou F, Tian Y, et al. Predicting the need for blood transfusions in elderly patients with pertrochanteric femoral fractures[J]. Injury, 2014, 45(12): 1932-1937.
[20]
Huang Z, Huang C, Xie J, et al. Analysis of a large data set to identify predictors of blood transfusion in primary total hip and knee arthroplasty[J]. Transfusion, 2018, 58(8): 1855-1862.
[21]
Morritt DG, Morritt A, Kelley SP, et al. Blood ordering protocol based on proposed surgical implant in fractured neck of femur patients[J]. Ann R Coll Surg Engl, 2005, 87(6): 445-448.
[22]
Ross D, Erkocak O, Rasouli MR, et al. Operative time directly correlates with blood loss and need for blood transfusion in total joint arthroplasty[J]. Arch Bone Jt Surg, 2019, 7(3): 229-234.
[23]
Sehat KR, Evans RL, Newman JH. Hidden blood loss following hip and knee arthroplasty. Correct management of blood loss should take hidden loss into account[J]. J Bone Joint Surg Br, 2004, 86(4): 561-565.
[24]
蔡立泉，胡舒，代曹阳，等．髋膝关节置换围手术期血液管理的研究进展[J/CD]．中华关节外科杂志(电子版)，2019，13(2): 220-224.
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