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When is an optimization not an optimization? Evaluation of clinical implications of information content (signal-to-noise ratio) in optimization of cardiac resynchronization therapy, and how to measure and maximize it

机译:什么时候不是最优化?评估信息含量(信噪比)在优化心脏再同步治疗中的临床意义,以及如何测量和最大化它

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Impact of variability in the measured parameter is rarely considered in designing clinical protocols for optimization of atrioventricular (AV) or interventricular (VV) delay of cardiac resynchronization therapy (CRT). In this article, we approach this question quantitatively using mathematical simulation in which the true optimum is known and examine practical implications using some real measurements. We calculated the performance of any optimization process that selects the pacing setting which maximizes an underlying signal, such as flow or pressure, in the presence of overlying random variability (noise). If signal and noise are of equal size, for a 5-choice optimization (60, 100, 140, 180, 220 ms), replicate AV delay optima are rarely identical but rather scattered with a standard deviation of 45 ms. This scatter was overwhelmingly determined (ρ = −0.975, P < 0.001) by Information Content, fractextSignaltextSignal + textNoise {frac{text{Signal}}{{{text{Signal}} + {text{Noise}}}}} , an expression of signal-to-noise ratio. Averaging multiple replicates improves information content. In real clinical data, at resting, heart rate information content is often only 0.2–0.3; elevated pacing rates can raise information content above 0.5. Low information content (e.g. <0.5) causes gross overestimation of optimization-induced increment in VTI, high false-positive appearance of change in optimum between visits and very wide confidence intervals of individual patient optimum. AV and VV optimization by selecting the setting showing maximum cardiac function can only be accurate if information content is high. Simple steps to reduce noise such as averaging multiple replicates, or to increase signal such as increasing heart rate, can improve information content, and therefore viability, of any optimization process.
机译:在设计用于优化心脏再同步治疗(CRT)的房室(AV)或心室(VV)延迟的临床方案时,很少考虑测量参数变化的影响。在本文中,我们使用数学模拟定量地解决了这个问题,在数学模拟中,真正的最优值是已知的,并使用一些实际测量来检验实际含义。我们计算了任何优化过程的性能,这些过程选择了在存在过度的随机变异性(噪声)的情况下,使基本信号(例如流量或压力)最大化的起搏设置。如果信号和噪声大小相等,则对于5选择优化(60、100、140、180、220 ms),复制AV延迟优化很少是相同的,而是以45 ms的标准偏差分散。此分散由信息内容fractextSignaltextSignal + textNoise {frac {text {Signal}} {{{text {Signal}} + {text {Noise}}}}}绝对确定(ρ= −0.975,P <0.001)信噪比的表达式。平均多个副本可改善信息内容。在实际的临床数据中,静息时,心率信息的含量通常仅为0.2-0.3;较高的起搏率可将信息含量提高到0.5以上。信息含量低(例如<0.5)会导致高估了优化诱导的VTI增量,两次就诊之间最佳变化的高假阳性表象以及各个患者的最佳置信区间非常大。只有在信息含量高的情况下,通过选择显示最大心功能的设置进行的AV和VV优化才能准确。减少噪声(例如平均多个重复样本)或增加信号(例如增加心率)的简单步骤可以改善任何优化过程的信息内容,从而提高生存能力。

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