de Baat Esmée C, Merkx Remy, Leerink Jan M, Boerhout Coen, van der Pal Heleen J H, van Dalen Elvira C, Loonen Jacqueline, Bresters Dorine, van Dulmen-den Broeder Eline, van der Heiden-van der Loo Margriet, van den Heuvel Marry M, Kok Judith L, Louwerens Marloes, Neggers Sebastian J C M M, Ronckers Cecline M, Teepen Jop C, Tissing Wim J E, de Vries Andrica C, Kapusta Livia, Kremer Leontien C M, Mavinkurve-Groothuis Annelies M C, Kok Wouter E M, Feijen Elizabeth A M
Princess Maxima Center for Pediatric Oncology, Utrecht, The Netherlands
Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
Heart. 2024 Apr 25;110(10):726-734. doi: 10.1136/heartjnl-2023-323474.
We assessed the prevalence and diagnostic value of ECG abnormalities for cardiomyopathy surveillance in childhood cancer survivors.
In this cross-sectional study, 1381 survivors (≥5 years) from the Dutch Childhood Cancer Survivor Study part 2 and 272 siblings underwent a long-term follow-up ECG and echocardiography. We compared ECG abnormality prevalences using the Minnesota Code between survivors and siblings, and within biplane left ventricular ejection fraction (LVEF) categories. Among 880 survivors who received anthracycline, mitoxantrone or heart radiotherapy, logistic regression models using least absolute shrinkage and selection operator identified ECG abnormalities associated with three abnormal LVEF categories (<52% in male/<54% in female, <50% and <45%). We assessed the overall contribution of these ECG abnormalities to clinical regression models predicting abnormal LVEF, assuming an absence of systolic dysfunction with a <1% threshold probability.
16% of survivors (52% female, mean age 34.7 years) and 14% of siblings had major ECG abnormalities. ECG abnormalities increased with decreasing LVEF. Integrating selected ECG data into the baseline model significantly improved prediction of sex-specific abnormal LVEF (c-statistic 0.66 vs 0.71), LVEF <50% (0.66 vs 0.76) and LVEF <45% (0.80 vs 0.86). While no survivor met the preset probability threshold in the first two models, the third model used five ECG variables to predict LVEF <45% and was applicable for ruling out (sensitivity 93%, specificity 56%, negative predictive value 99.6%). Calibration and internal validation tests performed well.
A clinical prediction model with ECG data (left bundle branch block, left atrial enlargement, left heart axis, Cornell's criteria for left ventricular hypertrophy and heart rate) may aid in ruling out LVEF <45%.
我们评估了心电图异常在儿童癌症幸存者心肌病监测中的患病率及诊断价值。
在这项横断面研究中,荷兰儿童癌症幸存者研究第2部分的1381名幸存者(≥5岁)和272名同胞接受了长期随访心电图和超声心动图检查。我们使用明尼苏达编码比较了幸存者和同胞之间以及双平面左心室射血分数(LVEF)类别内的心电图异常患病率。在880名接受蒽环类药物、米托蒽醌或心脏放疗的幸存者中,使用最小绝对收缩和选择算子的逻辑回归模型确定了与三个异常LVEF类别(男性<52%/女性<54%、<50%和<45%)相关的心电图异常。我们评估了这些心电图异常对预测异常LVEF的临床回归模型的总体贡献,假设收缩功能障碍不存在且阈值概率<1%。
16%的幸存者(52%为女性,平均年龄34.7岁)和14%的同胞有主要心电图异常。心电图异常随LVEF降低而增加。将选定的心电图数据纳入基线模型显著改善了对性别特异性异常LVEF(c统计量0.66对0.71)、LVEF<50%(0.66对0.76)和LVEF<45%(0.80对0.86)的预测。在前两个模型中没有幸存者达到预设概率阈值,而第三个模型使用五个心电图变量预测LVEF<45%,适用于排除(敏感性93%,特异性56%,阴性预测值99.6%)。校准和内部验证测试表现良好。
包含心电图数据(左束支传导阻滞、左心房扩大、左心轴、康奈尔左心室肥厚标准和心率)的临床预测模型可能有助于排除LVEF<45%。