时红, 于海涛, 靳泽岳. 心脏瓣膜置换术后急性肾损伤的列线图预测模型研究[J]. 临床肾脏病杂志, 2024, 24(3): 177-184. DOI: 10.3969/j.issn.1671-2390.2024.03.001
    引用本文: 时红, 于海涛, 靳泽岳. 心脏瓣膜置换术后急性肾损伤的列线图预测模型研究[J]. 临床肾脏病杂志, 2024, 24(3): 177-184. DOI: 10.3969/j.issn.1671-2390.2024.03.001
    Shi Hong, Yu Hai-tao, Jin Ze-yue. Homogram prediction modeling of acute kidney injury after heart valve replacement[J]. Journal of Clinical Nephrology, 2024, 24(3): 177-184. DOI: 10.3969/j.issn.1671-2390.2024.03.001
    Citation: Shi Hong, Yu Hai-tao, Jin Ze-yue. Homogram prediction modeling of acute kidney injury after heart valve replacement[J]. Journal of Clinical Nephrology, 2024, 24(3): 177-184. DOI: 10.3969/j.issn.1671-2390.2024.03.001

    心脏瓣膜置换术后急性肾损伤的列线图预测模型研究

    Homogram prediction modeling of acute kidney injury after heart valve replacement

    • 摘要:
      目的  构建并验证心脏瓣膜置换术后急性肾损伤(acute kidney injury,AKI)的列线图(Nomogram)预测模型。
      方法  选择2020年1月1日至2022年3月31日河北医科大学第三医院150例心脏瓣膜置换术后心脏瓣膜病患者作为训练人群,开展前瞻性队列研究。统计术后7 d内AKI发生情况,根据是否发生AKI分为AKI组(发生AKI)和非AKI组(未发生AKI)。比较两组患者临床资料,通过Logistic多因素回归模型分析心脏瓣膜置换术后发生AKI的影响因素,根据影响因素构建Nomogram预测模型。另根据1∶1配对原则选取同期150例心脏瓣膜置换术后心脏瓣膜病患者作为验证人群,通过受试者工作特征(receiver operating characteristic,ROC)曲线、决策曲线(decision curve analysis,DCA)评价该模型预测心脏瓣膜置换术后发生AKI的价值及临床效用进行外部验证。
      结果  150例心脏瓣膜病患者在心脏瓣膜置换术后7 d内AKI发生率为34.67%(52/150);AKI组男性占比、年龄、合并糖尿病占比、合并高血压占比、肾功能异常占比、有心脏手术史占比、红细胞体积分布宽度(red blood cell distribution width,RDW)、血清同型半胱氨酸(homocysteine,Hcy)、胱抑素C(cystatin C,Cys C)水平分别为67.31%、(61.23 ± 6.35)岁、26.92%、48.08%、34.62%、38.46%、(0.71 ± 0.22)%、(16.10 ± 4.28)μmol/L、(2.03 ± 0.57)mg/L,高于非AKI组的41.84%、(54.26 ± 5.19)岁、10.20%、24.49%、9.18%、13.27%、(0.39 ± 0.12)%、(13.65 ± 3.71)μmol/L、(1.02 ± 0.45)mg/L;术前营养风险指数(nutritional risk index,NRI)为(82.34 ± 9.20),低于非AKI组的(113.57 ± 10.58);体外循环时间、主动脉阻断时间分别为(98.12 ± 18.69)min、(84.27 ± 16.73)min,长于非AKI组的(84.19 ± 15.37)min、(73.58 ± 15.11)min,差异有统计学意义(P<0.05);性别(OR = 5.810)、年龄(OR = 5.380)、糖尿病(OR = 5.113)、高血压(OR = 5.625)、肾功能异常(OR = 7.825)、有心脏手术史(OR = 6.935)、术前NRI(OR = 7.630)、RDW(OR = 6.495)、血清Hcy(OR = 3.244)、Cys C(OR = 6.819)、体外循环时间(OR = 3.604)、主动脉阻断时间(OR = 3.374)均为心脏瓣膜置换术后发生AKI的影响因素(P<0.05);基于影响因素构建预测心脏瓣膜置换术后发生AKI的Nomogram预测模型,通过外部验证显示其预测曲线下面积为0.864(95%CI: 0.815~0.901),预测敏感度、特异度分别为86.01%、85.36%,DCA显示该模型在预测心脏瓣膜置换术后发生AKI方面具备良好临床效用。
      结论  心脏瓣膜置换术后发生AKI的影响因素包括性别、年龄、糖尿病、高血压、肾功能异常、有心脏手术史、术前NRI、RDW、血清Hcy、Cys C水平、体外循环时间、主动脉阻断时间,基于上述影响因素构建的Nomogram预测模型可辅助临床筛选高危AKI患者。

       

      Abstract:
      Objective  To construct and validate a nomogram prediction model for acute kidney injury (AKI) after heart valve replacement (HVR).
      Methods  A prospective cohort study was conducted by selecting 150 patients with heart valve disease after HVR at Third Hospital of Hebei Medical University from January 1, 2020 to March 31, 2022 as a training population. The postoperative incidence of AKI within 7 days was statistically analyzed. According to the occurrence of AKI, they were assigned into two groups of AKI and non-AKI. The relevant clinical data of two groups were compared and the influencing factors of AKI after HVR examined by Logistic regression. And a Nomogram prediction model was constructed on the basis of various influencing factors. Another 150 patients with cardiac valve disease after HVR were selected as a validation population during the same period according to the 1∶1 matching principle. The value and clinical utility of this model in predicting AKI after HVR were evaluated through receiver operating characteristic (ROC) curve and decision curve analysis (DCA) for external validation.
      Results  The postoperative incidence of AKI within 7 days post-HVR was 34.67%(52/150). In AKI group, proportion of male, age, proportion of diabetes mellitus (DM), hypertension, renal dysfunction, history of cardiac surgery, red blood cell distribution width (RDW), serum homocysteine (Hcy) and serum cystatin C (Cys C) were 67.31%, (61.23 ± 6.35) year, 26.92%, 48.08%, 34.62%, 38.46%, (0.71 ± 0.22)%, (16.10 ± 4.28) μmol/L and (2.03 ± 0.57) mg/L. They were higher than (41.84%), (54.26 ± 5.19) year, 10.20%, 24.49%, 9.18%, 13.27%, (0.39 ± 0.12)%, (13.65 ± 3.71) μmol/L and (1.02 ± 0.45) mg/L in non-AKI group. Preoperative nutritional risk index (NRI) was lower than non-AKI group (82.34 ± 9.20) vs (113.57 ± 10.58). Extracorporeal circulation time and aortic occlusion time were (98.12 ± 18.69) vs (84.19 ± 15.37) min and (84.27 ± 16.73) vs (73.58 ± 15.11) min. The differences were statistically significant (P<0.05). Gender (OR = 5.810), age (OR = 5.380), DM (OR = 5.113), hypertension (OR = 5.625), renal dysfunction (OR = 7.825), history of cardiac surgery (OR = 6.935), preoperative NRI (OR = 7.630), RDW (OR = 6.495), serum Hcy (OR = 3.244), Cys C (OR = 6.819), cardiopulmonary bypass time (OR = 3.604) and aortic occlusion time (OR = 3.374) were all influencing factors for AKI post-HVR (P<0.05). A nomogram prediction model was employed for predicting the post-HVR occurrence of AKI. External validation indicated that its area under the curve (AUC) was 0.864(95%CI: 0.815-0.901) with a predictive sensitivity and specificity of 86.01% and 85.36% respectively. And DCA showed that the model demonstrated an excellent clinical efficacy in predicting the post-HVR occurrence of AKI.
      Conclusion  The influencing factors for AKI post-HVR include gender, age, DM, hypertension, renal dysfunction, history of cardiac surgery, preoperative NRI, RDW, serum levels of Hcy and Cys C, extracorporeal circulation time and aortic occlusion time. A nomogram prediction model based upon the above factors may assist in clinical screening of high-risk AKI patients.

       

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