Department of Communications Engineering, University of the Basque Country, UPV/EHU, 48013 Bilbao, Spain.
Department of Communications Engineering, University of the Basque Country, UPV/EHU, 48013 Bilbao, Spain.
Resuscitation. 2018 Dec;133:53-58. doi: 10.1016/j.resuscitation.2018.09.024. Epub 2018 Sep 29.
Current resuscitation guidelines emphasize the use of waveform capnography to help guide rescuers during cardiopulmonary resuscitation (CPR). However, chest compressions often cause oscillations in the capnogram, impeding its reliable interpretation, either visual or automated. The aim of the study was to design an algorithm to enhance waveform capnography by suppressing the chest compression artefact.
Monitor-defibrillator recordings from 202 patients in out-of-hospital cardiac arrest were analysed. Capnograms were classified according to the morphology of the artefact. Ventilations were annotated using the transthoracic impedance signal acquired through defibrillation pads. The suppression algorithm is designed to operate in real-time, locating distorted intervals and restoring the envelope of the capnogram. We evaluated the improvement in automated ventilation detection, estimation of ventilation rate, and detection of excessive ventilation rates (over-ventilation) using the capnograms before and after artefact suppression.
A total of 44 267 ventilations were annotated. After artefact suppression, sensitivity (Se) and positive predictive value (PPV) of the ventilation detector increased from 91.9/89.5% to 98.0/97.3% in the distorted episodes (83/202). Improvement was most noticeable for high-amplitude artefact, for which Se/PPV raised from 77.6/73.5% to 97.1/96.1%. Estimation of ventilation rate and detection of over-ventilation also upgraded. The suppression algorithm had minimal impact in non-distorted data.
Ventilation detection based on waveform capnography improved after chest compression artefact suppression. Moreover, the algorithm enhances the capnogram tracing, potentially improving its clinical interpretation during CPR. Prospective research in clinical settings is needed to understand the feasibility and utility of the method.
目前的复苏指南强调使用波形二氧化碳描记术来帮助指导心肺复苏（CPR）期间的抢救者。然而，胸部按压常常会导致二氧化碳描记图中的振荡，从而阻碍其可靠的解释，无论是视觉解释还是自动解释。本研究的目的是设计一种算法来抑制胸部按压伪影，从而增强波形二氧化碳描记术。
分析了 202 例院外心脏骤停患者的监护除颤器记录。根据伪影的形态对二氧化碳描记图进行分类。使用通过除颤垫获得的经胸廓阻抗信号对通气进行注释。抑制算法旨在实时运行，定位失真间隔并恢复二氧化碳描记图的包络。我们评估了使用抑制伪影前后的二氧化碳描记图，在自动通气检测、通气率估计和检测过度通气（通气过度）方面的改进。
总共注释了 44267 次通气。在抑制伪影后，在失真的通气中，通气检测器的灵敏度（Se）和阳性预测值（PPV）从 91.9/89.5%提高到 98.0/97.3%（83/202）。对于高振幅伪影，改进最为明显，其 Se/PPV 从 77.6/73.5%提高到 97.1/96.1%。通气率的估计和通气过度的检测也得到了改善。抑制算法对非失真数据的影响最小。
在抑制胸部按压伪影后，基于波形二氧化碳描记术的通气检测得到了改善。此外，该算法增强了二氧化碳描记图的追踪，可能会改善 CPR 期间的临床解释。需要在临床环境中进行前瞻性研究，以了解该方法的可行性和实用性。
