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Calculation of the Respiratory Modulation of the Photoplethysmogram (DPOP) Incorporating a Correction for Low Perfusion

机译:结合低灌注校正的光体积描记图(DPOP)呼吸调节的计算

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摘要

DPOP quantifies respiratory modulations in the photoplethysmogram. It has been proposed as a noninvasive surrogate for pulse pressure variation (PPV) used in the prediction of the response to volume expansion in hypovolemic patients. The correlation between DPOP and PPV may degrade due to low perfusion effects. We implemented an automated DPOP algorithm with an optional correction for low perfusion. These two algorithm variants (DPOPa and DPOPb) were tested on data from 20 mechanically ventilated OR patients split into a benign "stable region" subset and a whole record "global set." Strong correlation was found between DPOP and PPV for both algorithms when applied to the stable data set: R = 0.83/0.85 for DPOPa/DPOPb. However, a marked improvement was found when applying the low perfusion correction to the global data set: R = 0.47/0.73 for DPOPa/DPOPb. Sensitivities, Specificities, and AUCs were 0.86, 0.70, and 0.88 for DPOPa/stable region; 0.89, 0.82, and 0.92 for DPOPb/stable region; 0.81,0.61, and 0.73 for DPOPa/global region; 0.83,0.76, and 0.86 for DPOPb/global region. An improvement was found in all results across both data sets when using the DPOPb algorithm. Further, DPOPb showed marked improvements, both in terms of its values, and correlation with PPV, for signals exhibiting low percent modulations.
机译:DPOP量化了光电体积描记图中的呼吸调制。已提出作为脉搏压变化(PPV)的一种非侵入性替代方法,用于预测低血容量患者对体积膨胀的反应。 DPOP和PPV之间的相关性可能会由于低灌注效应而降低。我们实现了自动DPOP算法,并具有针对低灌注的可选校正。对这两种算法的变体(DPOPa和DPOPb)进行了测试,这些数据来自20位机械通气的OR患者,这些患者分为良性“稳定区域”子集和完整记录“全局集”。当将两种算法应用于稳定数据集时,发现DPOP和PPV之间存在很强的相关性:DPOPa / DPOPb的R = 0.83 / 0.85。但是,将低灌注校正应用于全局数据集时,发现了显着的改进:DPOPa / DPOPb的R = 0.47 / 0.73。 DPOPa /稳定区域的敏感性,特异性和AUC分别为0.86、0.70和0.88; DPOPb /稳定区域为0.89、0.82和0.92; DPOPa /全球区域分别为0.81,0.61和0.73; DPOPb /全球区域分别为0.83、0.76和0.86。使用DPOPb算法时,两个数据集的所有结果均得到改善。此外,对于显示低百分比调制的信号,DPOPb在其值以及与PPV的相关性方面均显示出显着的改进。

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