Predictive value of cardiac magnetic resonance parametric nomogram models for adverse cardiovascular events in elderly patients with dilated cardiomyopathy
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摘要:
目的 探究心脏磁共振（CMR）参数列线图模型对扩张型心肌病（DCM）老年患者主要不良心血管事件（MACE）的预测价值。 方法 回顾性分析2017年7月~2020年7月在武汉科技大学附属孝感医院接受CMR检查的DCM老年患者173例，将患者按6:4的比例随机分为训练集（n=104）及测试集（n=69）。通过LASSO回归及多因素Cox回归筛选潜在预测因子，以此构建DCM患者MACE列线图预测模型。通过校准曲线、ROC曲线、决策曲线分析法、Kaplan-Meier生存分析对列线图模型进行评估及验证。 结果 中位随访时间为29.7（16.4，45.4）月。随访结束时，59例（34.1%）患者发生MACE。LASSO回归及交叉验证筛选出9个潜在预测因子。多因素Cox回归分析结果显示，纽约心功能分级Ⅲ~Ⅳ级、N末端-脑钠肽前体、β受体阻断药、CMR晚期钆增强、左心室整体纵向应变是DCM患者发生MACE风险因子，并以此构建列线图预测模型。在训练集和测试集中，校准图显示列线图预测1年、3年生存率与实际生存率一致性较好。训练集1年、3年生存预测ROC曲线下面积分别为0.850（95%CI：0.748~0.953）、0.853（95% CI：0.797~0.909），测试集1年、3年生存预测ROC曲线下面积分别为0.858（95% CI：0.758~0.959）、0.887（95% CI：0.816~0.958）。决策曲线分析结果显示列线图模型的临床净获益率较高。Kaplan-Meier生存分析结果示，预测模型高风险组患者较低风险组生存概率降低（P＜0.05）。 结论 本研究通过临床和CMR特征参数构建了DCM老年患者MACE发生列线图预测模型，该模型具有较好校准度、区分度及临床应用价值。 Abstract:Objective To investigate the predictive value of cardiac magnetic resonance (CMR) parametric nomogram modeling for major adverse cardiovascular events (MACE) in elderly patients with dilated cardiomyopathy (DCM). Methods A total of 173 elderly patients with DCM who underwent CMR at Xiaogan Hospital of Wuhan University of Science and Technology from July 2017 to July 2020 were retrospectively analyzed, and they were randomly divided into a training set (n=104) and a test set (n=69) in a ratio of 6:4. Potential predictors were screened by Lasso regression and multifactorial Cox regression, and the MACE nomogram prediction model for DCM patients was constructed with these factors. The nomogram model was evaluated and validated by calibration curve, ROC curve, decision curve analysis, and Kaplan-Meier survival analysis. Results The median follow-up was 29.7 (16.4, 45.4) months. At the end of follow-up, MACE occurred in 59 (34.1%) patients. A total of 9 potential predictors were screened by LASSO regression and cross-validation. The results of multifactorial Cox regression analysis showed that NYHA class Ⅲ-Ⅳ, N-terminal-brain natriuretic peptide precursor, beta-blocker, CMR late gadolinium enhancement, and overall longitudinal strain of the left ventricle were risk factors for the development of MACE in patients with DCM, and a nomogram prediction model was constructed with these indicators. In the training and test sets, the calibration plots showed that the nomogram predicted 1-year and 3-year survival in good agreement with the actual survival. The area under the ROC curve for 1-year and 3-year survival prediction in the training set was 0.850 (95% CI: 0.748-0.953) and 0.853 (95% CI: 0.797-0.909), respectively, and that for 1-year and 3-year survival prediction in the test set was 0.858 (95% CI: 0.758-0.959) and 0.887 (95% CI: 0.816-0.958), respectively. The results of the decision curve analysis showed that the nomogram model had a higher net clinical benefit rate. The results of Kaplan-Meier survival analysis showed that patients in the high-risk group of the predictive model had a reduced probability of survival compared with the low-risk group (P < 0.05). Conclusion In this study, we constructed a nomogram prediction model for the occurrence of MACE in elderly patients with DCM by clinical and CMR characteristic parameters, which has good calibration, differentiation and clinical application value. -
图 1 DCM患者CMR图像
Figure 1. CMR images of a patient with DCM. A-C: Long-axis (four-chambered heart, two-chambered heart) cine imaging of the heart showing left ventricular myocardial contours; D-F: LGE images of the left ventricular shortaxis basal, intermediate, and apical layers showing linear mid-wall enhancement (red arrows).
图 2 LASSO回归分析
Figure 2. LASSO regression analysis. A: LASSO regression algorithm variable screening; B: Cross-validation parameter λ selection.
图 3 CMR参数预测DCM患者MACE的列线图模型
Figure 3. Nomogram model of CMR parameters predicting MACE in patients with DCM.
图 4 列线图模型的评估及验证
Figure 4. Evaluation and validation of the nomogram model. A: Training set calibration plot; B: Training set ROC curve; C: Training set DCA curve; D: Test set calibration plot; E: Test set ROC curve; F: Test set DCA curve.
图 5 DCM患者的Kaplan-Meier生存曲线
Figure 5. Kaplan-Meier survival curves for DCM patients. A: Training set; B: Test set.
表 1 训练集与测试集临床及CMR临床特征比较
Table 1. Comparison of clinical and CMR clinical characteristics between the training and test sets
Characteristics Training set (n=104) Test set (n=69) t/χ2 P Age (year, Mean±SD) 65.48±3.09 65.41±3.41 0.150 0.881 Male [n(%)] 87（83.7） 58（84.1） 0.005 0.944 BMI (kg/m2, Mean±SD) 25.04±2.98 24.57±2.80 1.035 0.302 NYHA Ⅲ-Ⅳ [n(%)] 50（48.1） 43（62.3） 3.384 0.066 Dyspnea [n(%)] 76（73.1） 51（73.9） 0.015 0.903 Tachycardia [n(%)] 45（43.3） 35（50.7） 0.927 0.336 Hypertension [n(%)] 40（38.5） 31（44.9） 0.717 0.397 Hypercholesterolemia [n(%)] 32（30.8） 21（30.4） 0.002 0.963 Diabetes [n(%)] 20（19.2） 15（21.7） 0.162 0.688 Smoking [n(%)] 32（30.8） 19（27.5） 0.209 0.648 SBP (mmHg, Mean±SD) 114.18±9.20 113.43±9.03 0.528 0.598 DBP (mmHg, Mean±SD) 74.26±3.97 74.57±4.32 -0.479 0.633 NT-ProBNP (pg/mL, Mean±SD) 2364.18±932.57 2506.40±923.47 -0.992 0.323 Beta-blocker [n(%)] 63（60.6） 38（51.1） 0.517 0.472 LAD (mm, Mean±SD) 41.39±8.07 39.82±7.52 1.282 0.201 LVD (mm, Mean±SD) 72.16±9.13 73.45±9.42 -0.895 0.372 LVEF (%, Mean±SD) 35.19±8.40 33.39±6.93 1.475 0.142 LVEDVI (mL/m2, Mean±SD) 158.56±39.07 162.93±38.51 -0.725 0.469 LVESVI (mL/m2, Mean±SD) 108.60±20.11 107.84±20.22 0.240 0.811 LVMI (g/m2, Mean±SD) 64.38±16.00 64.18±15.37 0.080 0.936 Mitral regurgitation [n(%)] 72（69.2） 42（60.9） 1.290 0.256 Tricuspid regurgitation [n(%)] 40（38.5） 22（31.9） 0.780 0.377 LGE [n(%)] 53（51.0） 40（58.0） 0.820 0.365 LVGLS (%, Mean±SD) -8.51±2.60 -8.56±2.82 -0.132 0.895 LVGCS (%, Mean±SD) -8.90±3.00 -9.36±2.77 1.030 0.305 LVGRS (%, Mean±SD) 16.41±4.34 16.68±3.59 -0.426 0.670 NYHA: New York Heart Association; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; NT-ProBNP: N-Terminal probrain natriuretic peptide; LAD: Left atrial diameter; LVD: Left ventricular diameter; LVEF: Left ventricular ejection fraction; LVEDVI: Left ventricular end-diastolic volume index; LVESVI: Left ventricular end-systolic volume index; LVMI: Left ventricular mass index; LGE: Late gadolinium enhancement; LVGLS: Left ventricular global longitudinal strain; LVGCS: Left ventricular global circumferential strain; LVGRS: Left ventricular global radial strain. 
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表 2 多因素Cox回归分析
Table 2. Multifactor Cox regression analysis
Variant B SE Wald χ2 P HR（95% CI） NYHA Class Ⅲ-Ⅳ 0.750 0.226 10.998 0.001 2.118（1.359-3.299） NT-ProBNP 0.000 0.000 15.036 ＜0.001 1.000（1.000-1.001） Beta-blocker -0.908 0.219 17.224 ＜0.001 0.403（0.263-0.619） LGE 0.599 0.224 7.142 0.008 1.820（1.173-2.823） LVGLS 0.530 0.045 137.154 ＜0.001 1.699（1.555-1.856） NT-ProBNP: N-Terminal pro-brain natriuretic peptide.
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