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应用平均幅度差函数之和分析心电信号对除颤最佳时机的预测价值OACSTPCD

Predictive value of the sum of average magnitude difference function in determining optimal defibrillation timing by analyzing ECG signals

中文摘要英文摘要

目的 应用平均幅度差函数之和(the sum of average magnitude difference function,SAMDF)处理室颤的心电信号,通过与常用预测除颤时间方法振幅谱面积(amplitude spectrum area,AMSA)进行对比找到预测除颤时间更优的方法.方法 应用56头重(40±5)kg雄性家猪,诱导室颤后进行10 min未处理的室颤、6 min的心肺复苏和除颤.在室颤和心肺复苏过程当中会记录每1 min SAMDF和AMSA的数据并记录下来.进而计算受试者工作特征(receiver operating characteristic,ROC)曲线,应用单向方差分析(one-way analyses of variance,one-way ANOVA)以及正负样本散点图的比较,以此说明两者均能优化最佳除颤时间.比较除颤成功组(Group R)和除颤失败组(Group N)的SAMDF和AMSA的数值以说明两者预测除颤成功的能力.结果 散点图显示SAMDF和AMSA均能够区分阳性和负样本(P<0.001).ROC曲线显示SAMDF(AUC=0.801,P<0.001)和AMSA(AUC=0.777,P<0.001)一样有着相同的能力预测最佳除颤时间.两组SAMDF和AMSA数值比较,Group R的SAMDF和AMSA数值明显高于Group N(P<0.001).结论 SAMDF在优化预测除颤时机方面具有很高的潜力,并且可以作为AMSA等现有有效预测除颤时机特征的补充.

Objective To evaluate the efficacy of the sum of average magnitude difference function(SAMDF)in processing ventricular fibrillation(VF)ECG signals for predicting optimal defibrillation timing,and to compare it with the commonly used amplitude spectrum area(AMSA)method.Methods Fifty-six male pigs,each weighing 40±5 kg,were used for the study.VF was induced,followed by 10 minutes of untreated VF,6 minutes of cardiopulmonary resusci-tation(CPR),and subsequent defibrillation.SAMDF and AMSA values were recorded every minute during VF and CPR.Receiver operating characteristic(ROC)curves were calculated,and one-way analyses of variance(one-way ANOVA)and positive-negative sample scatter plots were used to compare the two methods for optimizing defibrillation timing pre-diction.The SAMDF and AMSA values of the successful defibrillation group(Group R)and the unsuccessful defibrillation group(Group N)were compared to evaluate their predictive abilities.Results Scatter plots demonstrated that both SAM-DF and AMSA could differentiate between positive and negative samples(P<0.001).ROC analysis showed that SAMDF(AUC=0.801,P<0.001)and AMSA(AUC=0.777,P<0.001)had similar capabilities in predicting optimal defib-rillation timing.The SAMDF and AMSA values were significantly higher in Group R than in Group N(P<0.001).Conclusion SAMDF shows strong potential for optimizing the prediction of defibrillation timing and could serve as a com-plement to existing effective predictors like AMSA.

刘远山;林帆荣;陈煜嘉;黄子通;蒋龙元;杨正飞

中山大学孙逸仙纪念医院急诊科、中山大学心肺脑复苏研究所(广东广州 510120)

平均幅度差函数之和振幅谱面积心电信号预测除颤时机

the sum of average magnitude difference functionamplitude spectrum areaECG signalpredicting defibrillation timing

《广东医学》 2024 (009)

1106-1112 / 7

广东省基础与应用基础研究基金项目-区域联合基金-地区培育项目(2022A1515140033);广州市科技计划项目(2023A04J2094,2023A03J0714)

10.13820/j.cnki.gdyx.20241851

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