Gregg Richard E, Deluca Daniel C, Chien Cheng-Hao Simon, Helfenbein Eric D, Ariet Mario
Advanced Algorithm Research Center, Philips Healthcare, Andover, MA 01810, USA.
J Electrocardiol. 2012 Nov-Dec;45(6):561-5. doi: 10.1016/j.jelectrocard.2012.07.021. Epub 2012 Sep 18.
Interpretation of a patient's 12-lead ECG frequently involves comparison to a previously recorded ECG. Automated serial ECG comparison can be helpful not only to note significant ECG changes but also to improve the single-ECG interpretation. Corrections from the previous ECG are carried forward by the serial comparison algorithm when measurements do not change significantly.
A sample of patients from three hospitals was collected with two or more 12-lead ECGs from each patient. There were 233 serial comparisons from 143 patients. 41% of patients had two ECGs and 59% of patients had more than two ECGs. ECGs were taken from a difficult population as measured by ECG abnormalities, 197/233 abnormal, 11/233 borderline, 14/233 otherwise-normal and 11/233 normal. ECGs were processed with the Philips DXL algorithm and then in time order for each patient with the Philips serial comparison algorithm. To measure accuracy of interpretation and serial change, an expert cardiologist corrected the ECGs in stages. The first ECG was corrected and used as the reference for the second ECG. The second ECG was then corrected and used as the reference for the third ECG and so on. At each stage, the serial comparison algorithm compared an unedited ECG to an earlier edited ECG. Interpretation accuracy was measured by comparing the algorithm to the cardiologist on a statement by statement basis. The effect of serial comparison was measured by the sum of interpretive statement mismatches between the algorithm and cardiologist. Statement mismatches were measured in two ways, (1) exact match and (2) match within the same diagnostic category.
The cardiologist used 910 statements over 233 ECGs for an average number of 3.9 statements per ECG and a mode of 4 statements. When automated serial comparison was used, the total number of exact statement mismatches decreased by 29% and the total same-category statement mismatches decreased by 47%.
Automated serial comparison improves interpretation accuracy in addition to its main role of noting differences between ECGs.
对患者的12导联心电图进行解读通常需要与之前记录的心电图进行对比。自动连续心电图对比不仅有助于发现显著的心电图变化，还能提高对单次心电图的解读能力。当测量值变化不显著时，连续对比算法会沿用前一次心电图的校正结果。
收集了来自三家医院的患者样本，每位患者有两份或更多份12导联心电图。共进行了143例患者的233次连续对比。41%的患者有两份心电图，59%的患者有两份以上心电图。从心电图异常情况来看，这些心电图取自病情复杂的患者群体，其中197/233例异常，11/233例临界，14/233例其他情况正常，11/233例正常。心电图先用飞利浦DXL算法进行处理，然后对每位患者按时间顺序采用飞利浦连续对比算法。为了测量解读准确性和连续变化情况，一位心脏病专家分阶段对心电图进行校正。先校正第一份心电图并将其作为第二份心电图的参考。然后校正第二份心电图并将其作为第三份心电图的参考，依此类推。在每个阶段，连续对比算法将一份未编辑的心电图与一份更早编辑的心电图进行对比。通过逐句比较算法和心脏病专家的判断来测量解读准确性。通过计算算法与心脏病专家之间解读语句不匹配的总和来测量连续对比的效果。语句不匹配通过两种方式测量，（1）完全匹配，（2）同一诊断类别内匹配。
心脏病专家在233份心电图上使用了910条语句，平均每份心电图3.9条语句，众数为4条语句。使用自动连续对比时，完全语句不匹配的总数减少了29%，同一类别语句不匹配的总数减少了47%。
自动连续对比除了能发现心电图之间的差异这一主要作用外，还能提高解读准确性。
