Zheng Jingyi, Li Yuexin, Billor Nedret, Ahmed Mustafa I, Fang Yu-Hua Dean, Pat Betty, Denney Thomas S, Dell'Italia Louis J
Department of Mathematics and Statistics, Auburn University, Auburn, AL, United States.
Division of Cardiovascular Disease, University of Alabama at Birmingham, Birmingham, AL, United States.
Front Cardiovasc Med. 2023 Apr 21;10:1112797. doi: 10.3389/fcvm.2023.1112797. eCollection 2023.
Class I echocardiographic guidelines in primary mitral regurgitation (PMR) risks left ventricular ejection fraction (LVEF) < 50% after mitral valve surgery even with pre-surgical LVEF > 60%. There are no models predicting LVEF < 50% after surgery in the complex interplay of increased preload and facilitated ejection in PMR using cardiac magnetic resonance (CMR).
Use regression and machine learning models to identify a combination of CMR LV remodeling and function parameters that predict LVEF < 50% after mitral valve surgery.
CMR with tissue tagging was performed in 51 pre-surgery PMR patients (median CMR LVEF 64%), 49 asymptomatic (median CMR LVEF 63%), and age-matched controls (median CMR LVEF 64%). To predict post-surgery LVEF < 50%, least absolute shrinkage and selection operator (LASSO), random forest (RF), extreme gradient boosting (XGBoost), and support vector machine (SVM) were developed and validated in pre-surgery PMR patients. Recursive feature elimination and LASSO reduced the number of features and model complexity. Data was split and tested 100 times and models were evaluated stratified cross validation to avoid overfitting. The final RF model was tested in asymptomatic PMR patients to predict post-surgical LVEF < 50% if they had gone to mitral valve surgery.
Thirteen pre-surgery PMR had LVEF < 50% after mitral valve surgery. In addition to LVEF ( = 0.005) and LVESD ( = 0.13), LV sphericity index ( = 0.047) and LV mid systolic circumferential strain rate ( = 0.024) were predictors of post-surgery LVEF < 50%. Using these four parameters, logistic regression achieved 77.92% classification accuracy while RF improved the accuracy to 86.17%. This final RF model was applied to asymptomatic PMR and predicted 14 (28.57%) out of 49 would have post-surgery LVEF < 50% if they had mitral valve surgery.
These preliminary findings call for a longitudinal study to determine whether LV sphericity index and circumferential strain rate, or other combination of parameters, accurately predict post-surgical LVEF in PMR.
原发性二尖瓣反流（PMR）的I类超声心动图指南提示，即便术前左心室射血分数（LVEF）>60%，二尖瓣手术后左心室射血分数仍可能<50%。在PMR患者中，前负荷增加与射血增强之间存在复杂的相互作用，目前尚无利用心脏磁共振成像（CMR）预测术后LVEF<50%的模型。
使用回归模型和机器学习模型，识别能够预测二尖瓣手术后LVEF<50%的CMR左心室重构和功能参数组合。
对51例二尖瓣手术前的PMR患者（CMR LVEF中位数为64%）、49例无症状患者（CMR LVEF中位数为63%）以及年龄匹配的对照组（CMR LVEF中位数为64%）进行组织标记CMR检查。为预测术后LVEF<50%，在二尖瓣手术前的PMR患者中开发并验证了最小绝对收缩和选择算子（LASSO）、随机森林（RF）、极端梯度提升（XGBoost）和支持向量机（SVM）模型。递归特征消除和LASSO减少了特征数量和模型复杂性。数据被分割并测试100次，采用分层交叉验证评估模型以避免过度拟合。最终的RF模型在无症状PMR患者中进行测试，以预测如果他们接受二尖瓣手术，术后LVEF<50%的情况。
13例二尖瓣手术前的PMR患者术后LVEF<50%。除LVEF（P=0.005）和左心室舒张末期内径（LVESD，P=0.13）外，左心室球形指数（P=0.047）和左心室收缩中期圆周应变率（P=0.024）是术后LVEF<50%的预测因素。使用这四个参数，逻辑回归的分类准确率为77.92%，而RF将准确率提高到86.17%。将这个最终的RF模型应用于无症状PMR患者，预测49例中有14例（28.57%）如果接受二尖瓣手术，术后LVEF会<50%。
这些初步研究结果需要进行纵向研究，以确定左心室球形指数和圆周应变率或其他参数组合是否能准确预测PMR患者的术后LVEF。
