肝移植术后早期并发症风险预测模型的建立与评价
DOI: 10.3969/j.issn.1001-5256.2022.02.027
Establishment and validation of a risk prediction model for early-stage complications after liver transplantation
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摘要:
目的 探讨影响肝移植受者术后早期并发症发生的危险因素,建立并验证肝移植术后早期并发症风险预测模型。 方法 回顾性收集2016年1月—2018年12月于天津市第一中心医院肝移植科接受原位肝移植234例患者的临床资料。根据肝移植术后是否发生Clavien-Dindo 3级以上并发症,将所有患者分为并发症组(n=97)和无并发症组(n=137),比较2组年龄、性别、BMI、血型、腰大肌厚度/身高值(PMTH)、控制营养状态(CONUT)评分、MELD评分、血清总胆红素、血肌酐、凝血酶原时间国际标准化比值(PT-INR)、血尿素氮、血红蛋白、白细胞计数、血小板计数、术中输注红细胞量、输注冰冻血浆量、失血量、无肝期、手术时间以及供体年龄、BMI、供肝冷缺血时间和供肝热缺血时间等指标。符合正态分布的计量资料2组间比较采用独立样本t检验,非正态分布的计量资料2组间比较采用Mann-Whitney U检验,计数资料2组间比较采用χ2检验。采用单因素分析和二元logistic回归分析法分析肝移植术后早期并发症发生的危险因素,根据Framingham研究中心提供的logistic模型建立积分系统的方法建立肝移植术后并发症风险预测模型。采用一致性指数、受试者工作特征(ROC)曲线、模型校准曲线、Hosmer-Lemeshow检验对模型进行内部验证;采用决策曲线评价模型临床实用性。采用Kaplan-Meier法比较不同风险评分组患者肝移植术后早期并发症发生率。 结果 并发症组患者MELD评分、低PMTH比例、血清总胆红素、血肌酐、血尿素氮、CONUT评分、术中输注红细胞量、术中输注冰冻血浆量均明显高于无并发症组,血红蛋白水平明显低于无并发症组(P值均<0.1)。二元logistc多因素分析结果显示,MELD评分、PMTH、CONUT评分是肝移植术后早期3级以上并发症发生的独立危险因素(OR分别为1.104、2.858、1.481,95%CI分别为1.057~1.154、1.451~5.626、1.287~1.703,P值均<0.05)。将MELD评分、PMTH、CONUT评分纳入预测模型,该预测模型最高分为24分,一致性指数为0.828,ROC曲线下面积为0.812,P<0.001,敏感度为0.792,特异度为0.751,表明该预测模型具有良好的区分度;该预测模型校正曲线接近参考曲线,Hosmer-Lemeshow检验表明该预测模型具有良好的拟合度(χ2=8.525,P=0.382);决策曲线显示大部分患者均能从预测模型中获益,且净获益率较高,表明该预测模型具有良好的临床实用性。根据最佳约登指数0.507,选择11分为截点值,将所有患者分为低风险组(<8分,n=55)、中风险组(8~10分,n=63)、高风险组(11~14分,n=67)、极高风险组(≥15分,n=49),4组术后90 d累积并发症发生率分别为3.6%、28.6%、59.7%、75.5%,并发症发生率随着风险评分的上升而递增(P<0.001)。 结论 MELD评分、PMTH、CONUT评分是肝移植术后早期3级以上并发症发生的独立危险因素,以此建立的风险预测模型对高风险患者具有较高的预测价值。 Abstract:Objective To investigate the risk factors for early-stage complications among liver transplant recipients, and to establish and validate a risk prediction model for early-stage complications after transplantation. Methods A retrospective analysis was performed for the clinical data of 234 patients who underwent orthotopic liver transplantation in Department of Liver Transplantation, Tianjin First Central Hospital, from January 2016 to December 2018. According to the presence or absence of Clavien-Dindo grade ≥Ⅲ complications after liver transplantation, the patients were divided into complication group with 97 patients and non-complication group with 137 patients. The two groups were compared in terms of the indices including age, sex, body mass index (BMI), blood type, psoas muscle thickness/height (PMTH), Controlling Nutritional Status (CONUT) score, Model for End-Stage Liver Disease (MELD) score, total serum bilirubin, serum creatinine, international normalized ratio of prothrombin time, blood urea nitrogen, hemoglobin, white blood cell count, platelet count, amount of intraoperative red blood cell transfusion, amount of frozen plasma transfusion, blood loss, anhepatic phase, time of operation, donor age, donor BMI, cold ischemia time of donor liver, and warm ischemia time of donor liver. The independent samples t-test was used for comparison of normally distributed continuous data between two groups, and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups; the chi-square test was used for comparison of categorical data between two groups. Univariate analysis and the binary logistic regression analysis were used to investigate the risk factors for early-stage complications after liver transplantation, and a risk prediction model for complications after liver transplantation was established based on the method for establishing a scoring system using the logistic model provided by Framingham Research Center. Internal validation of the model was performed by C-index, receiver operating characteristic (ROC) curve, calibration curve, and the Hosmer-Lemeshow test, and the decision curve was used to evaluate the clinical applicability of the model. The Kaplan-Meier method was used to compare the incidence rate of early-stage complications after liver transplantation between the patients with different risk scores. Results Compared with the non-complication group, the complication group had significantly higher MELD score, proportion of patients with low PMTH, total serum bilirubin, serum creatinine, blood urea nitrogen, CONUT score, amount of intraoperative red blood cell transfusion, and amount of frozen plasma transfusion, as well as a significantly lower level of hemoglobin (all P < 0.1). The multivariate binary logistic regression analysis showed that MELD score (odds ratio [OR]=1.104, 95% confidence interval [CI]: 1.057-1.154, P < 0.05), PMTH (OR=2.858, 95%CI: 1.451-5.626, P < 0.05), and CONUT score (OR=1.481, 95%CI: 1.287-1.703, P < 0.05) were independent risk factors for grade ≥Ⅲ complications in the early stage after liver transplantation. MELD score, PMTH, and CONUT score were included in a predictive model, and this model had the highest score of 24 points, a C-index of 0.828, an area under the ROC curve of 0.812(P < 0.001), a sensitivity of 0.792, and a specificity of 0.751, suggesting that this predictive model had good discriminatory ability. The calibration curve of this model was close to the reference curve, and the Hosmer-Lemeshow test obtained a chi-square value of 8.528(P=0.382), suggesting that this predictive model had a high degree of fitting. The decision curve showed that most patients were able to benefit from the predictive model and achieved a high net benefit rate, suggesting that this predictive model had good clinical applicability. The score of 11 was selected as the cut-off value according to the optimal Youden index of 0.507, and the patients were divided into low-risk (< 8 points) group with 55 patients, moderate-risk (8-10 points) group with 63 patients, high-risk (11-14 points) group with 67 patients, and extremely high-risk (≥15 points) group with 49 patients. These four groups had a 90-day cumulative incidence rate of early-stage postoperative complications of 3.6%, 28.6%, 59.7%, and 75.5%, respectively, and the incidence rate of complications increased with the increase in risk score (P < 0.001). Conclusion MELD score, PMTH, and CONUT score are independent risk factors for early-stage complications among liver transplant recipients, and the risk prediction model established based on these factors has a high predictive value in high-risk patients. -
Key words:
- Liver Transplantation /
- Spostoperative Complications /
- Risk Factors /
- Forecasting /
- Models, Statistical
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表 1 肝移植术后早期并发症危险因素单因素分析
指标 并发症组(n=97) 无并发症组(n=137) 统计值 P值 受者信息 年龄(岁) 50±9 49±10 t=0.780 0.354 性别[例(%)] χ2=0.070 0.791 男 73(75) 101(74) 女 24(25) 36(26) BMI (kg/m2) 24.0(21.7~27.0) 23.5(21.2~26.0) Z=-0.944 0.345 血型不相容[例(%)] 5(5.2) 8(5.8) χ2=0.051 1.000 MELD评分 20(16~24) 13(10~20) Z=5.499 <0.001 PMTH[例(%)] χ2=14.381 <0.001 低 44(45) 30(22) 高 53(55) 107(78) 血清总胆红素(μmol/L) 123.0(72.1~379.2) 29.9(18.0~115.6) Z=6.792 <0.001 血肌酐(μmol/L) 68.0(51.0~118.5) 61.0(50.0~69.5) Z=2.371 0.018 PT-INR 1.50(1.18~2.03) 1.45(1.19~1.97) Z=0.228 0.820 血尿素氮(mmol/L) 5.3(3.7~11.8) 4.7(3.5~5.8) Z=2.560 0.010 血红蛋白(g/L) 100±25 107±29 t=-2.097 0.044 白细胞计数(×109/L) 4.9(3.4~6.8) 4.6(3.1~6.8) Z=0.985 0.324 血小板计数(×109/L) 93(47~152) 117(54~170) Z=-1.441 0.150 ConUT评分(分) 7(6~8) 5(3~7) Z=6.308 0.004 手术情况 术中输注红细胞量(U) 10(8~12) 8(6~10) Z=2.456 0.014 术中输注冰冻血浆量(mL) 2000(1600~2350) 2000(1400~2000) Z=2.171 0.030 术中失血量(mL) 2000(1500~2450) 1800(1500~2400) Z=1.365 0.172 无肝期(min) 45(35~50) 45(40~50) Z=-0.051 0.959 手术时间(h) 8.0±1.6 7.8±1.5 t=1.144 0.200 供者信息 年龄(岁) 41±9 42±10 t=-0.904 0.939 BMI(kg/m2) 24.1(21.4~27.4) 23.8(22.1~26.4) Z=-0.255 0.799 CIT(h) 7.3(6.4~7.9) 6.8(6.2~7.8) Z=1.138 0.255 WIT(min) 5.8±1.7 5.7±1.5 t=0.237 0.182 表 2 肝移植术后早期并发症危险因素多因素分析
危险因素 β值 P值 OR 95%CI MELD评分 0.099 0.002 1.104 1.057~1.154 PMTH 1.050 <0.001 2.858 1.451~5.626 ConUT评分 0.393 <0.001 1.481 1.287~1.703 表 3 肝移植术后早期并发症风险预测模型
危险因素 得分 MELD评分 <10分 0 10~19分 3 20~29分 6 ≥30分 9 PMTH 高 0 低 3 血清白蛋白 ≥35.0 g/L 0 30.0~34.9 g/L 2 25.0~29.9 g/L 4 <25.0 g/L 6 血清总胆固醇 ≥180 g/L 0 140~179 g/L 1 100~139 g/L 2 <100 g/L 3 总淋巴细胞计数 ≥1.60×109/L 0 1.20×109/L~1.59 ×109/L 1 0.80×109/L~1.19×109/L 2 <0.8×109/L 3 -
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