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Zuo F, Ding Y, Dai C, Wei L, Gong Y, Wang J, Shen Y, Li Y. Estimating the amplitude spectrum area of ventricular fibrillation during cardiopulmonary resuscitation using only ECG waveform. Ann Transl Med 2021; 9:619. [PMID: 33987317 PMCID: PMC8106002 DOI: 10.21037/atm-20-7166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Background Amplitude spectrum area (AMSA) calculated from ventricular fibrillation (VF) can be used to monitor the effectiveness of chest compression (CC) and optimize the timing of defibrillation. However, reliable AMSA can only be obtained during CC pause because of artifacts. In this study, we sought to develop a method for estimating AMSA during cardiopulmonary resuscitation (CPR) using only the electrocardiogram (ECG) waveform. Methods Intervals of 8 seconds ECG and CC-related references, including 4 seconds during CC and an adjacent 4 seconds without CC, were collected before 1,008 defibrillation shocks from 512 out-of-hospital cardiac arrest patients. Signal quality was analyzed based on the irregularity of autocorrelation of VF. If signal quality index (SQI) was high, AMSA would be calculated from the original signal. Otherwise, CC-related artifacts would be constructed and suppressed using the least mean square filter from VF before calculation of AMSA. The algorithm was optimized using 480 training shocks and evaluated using 528 independent testing shocks. Results Overall, CC resulted in lower SQI [0.15 (0.04-0.61) with CC vs. 0.75 (0.61-0.83) without CC, P<0.01] and higher AMSA [11.2 (7.7-16.2) with CC vs. 7.2 (4.9-10.6) mVHz without CC, P<0.01] values. The predictive accuracy (49.2% vs. 66.5%, P<0.01) and area under the receiver operating characteristic curve (AUC) (0.647 vs. 0.734, P<0.01) were significantly decreased during CC. Using the proposed method, the estimated AMSA was 7.1 (5.0-15.2) mVHz, the predictive accuracy was 67.0% and the AUC was 0.713, which were all comparable with those calculated without CC. Conclusions Using the signal quality-based artifact suppression method, AMSA can be reliably estimated and continuously monitored during CPR.
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Affiliation(s)
- Feng Zuo
- Department of Biomedical Engineering and Imaging Medicine, Army Medical University, Chongqing, China.,Department of Information Technology, Southwest Hospital, Army Medical University, Chongqing, China
| | - Youde Ding
- Department of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China
| | - Chenxi Dai
- Department of Biomedical Engineering and Imaging Medicine, Army Medical University, Chongqing, China
| | - Liang Wei
- Department of Biomedical Engineering and Imaging Medicine, Army Medical University, Chongqing, China
| | - Yushun Gong
- Department of Biomedical Engineering and Imaging Medicine, Army Medical University, Chongqing, China
| | - Juan Wang
- Department of Emergency, Southwest Hospital, Army Medical University, Chongqing, China
| | - Yiming Shen
- Department of Emergency, Chongqing Emergency Medical Center, Chongqing, China
| | - Yongqin Li
- Department of Biomedical Engineering and Imaging Medicine, Army Medical University, Chongqing, China
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Frigerio L, Baldi E, Aramendi E, Chicote B, Irusta U, Contri E, Palo A, Compagnoni S, Fracchia R, Iotti G, Oltrona Visconti L, Savastano S. End-tidal carbon dioxide (ETCO 2) and ventricular fibrillation amplitude spectral area (AMSA) for shock outcome prediction in out-of-hospital cardiac arrest. Are they two sides of the same coin? Resuscitation 2020; 160:142-149. [PMID: 33181229 DOI: 10.1016/j.resuscitation.2020.10.032] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 09/15/2020] [Accepted: 10/19/2020] [Indexed: 11/15/2022]
Abstract
AIM Ventricular fibrillation amplitude spectral area (AMSA) and end-tidal carbon dioxide (ETCO2) are predictors of shock success, understood as restoration of an organized rhythm, and return of spontaneous circulation (ROSC). However, little is known about their combined use. We aimed to assess the prediction accuracy when combined, and to clarify if they are correlated in out of hospital cardiac arrest' victims. MATERIALS AND METHODS Records acquired by external defibrillators in out-of-hospital cardiac arrest patients of the Lombardia Cardiac Arrest registry were processed. The 1-min pre-shock ETCO2 median value (METCO2) was computed from the capnogram and AMSA (2-48 mV.Hz range) computed applying the Fast Fourier Transform to a 2-second pre-shock filtered ECG interval (0.5-30 Hz). Support Vector Machine (SVM) predictive models based on METCO2, AMSA and their combination were fit; results were given as the area under the curve (AUC) of the receiver operating characteristic (ROC) curves. RESULTS We considered 112 patients with 391 shocks delivered. METCO2 and AMSA were predictors of shock success [AUC (IQR) of the ROC curve: 0.59 (0.56-0.62); 0.68 (0.65-0.72), respectively] and of ROSC [0.56 (0.53-0.59); 0.74 (0.71-0.78),]. Their combination in a SVM model increased the accuracy for predicting shock success [AUC (IQR) of the ROC curve: 0.71 (0.68-0.75)] and ROSC [0.77 (0.73-0.8)]. AMSA and METCO2 were significantly correlated only in patients who achieved ROSC (rho = 0.33 p = 0.03). CONCLUSIONS AMSA and ETCO2 predict shock success and ROSC after every shock, and their predictive power increases if combined. Notably, they were correlated only in patients who achieved ROSC.
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Affiliation(s)
- Laura Frigerio
- Division of Cardiology, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Enrico Baldi
- Cardiac Intensive Care Unit, Arrhythmia and Electrophysiology and Experimental Cardiology, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy; Department of Molecular Medicine, Section of Cardiology, University of Pavia, Pavia, Italy
| | - Elisabete Aramendi
- Communications Engineering Department, University of the Basque Country UPV/EHU, Bilbao, Spain
| | - Beatriz Chicote
- Communications Engineering Department, University of the Basque Country UPV/EHU, Bilbao, Spain
| | - Unai Irusta
- Communications Engineering Department, University of the Basque Country UPV/EHU, Bilbao, Spain
| | - Enrico Contri
- AREU Azienda Regionale Emergenza Urgenza - AAT Pavia c/o Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Alessandra Palo
- AREU Azienda Regionale Emergenza Urgenza - AAT Pavia c/o Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Sara Compagnoni
- Division of Cardiology, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy; Department of Molecular Medicine, Section of Cardiology, University of Pavia, Pavia, Italy
| | - Rosa Fracchia
- Division of Cardiology, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Giorgio Iotti
- Intensive Care Unit, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | | | - Simone Savastano
- Division of Cardiology, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy.
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Chicote B, Aramendi E, Irusta U, Owens P, Daya M, Idris A. Value of capnography to predict defibrillation success in out-of-hospital cardiac arrest. Resuscitation 2019; 138:74-81. [PMID: 30836170 PMCID: PMC6504568 DOI: 10.1016/j.resuscitation.2019.02.028] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Revised: 02/12/2019] [Accepted: 02/18/2019] [Indexed: 11/21/2022]
Abstract
BACKGROUND AND AIM Unsuccessful defibrillation shocks adversely affect survival from out-of-hospital cardiac arrest (OHCA). Ventricular fibrillation (VF) waveform analysis is the tool-of-choice for the non-invasive prediction of shock success, but surrogate markers of perfusion like end-tidal CO2 (EtCO2) could improve the prediction. The aim of this study was to evaluate EtCO2 as predictor of shock success, both individually and in combination with VF-waveform analysis. MATERIALS AND METHODS In total 514 shocks from 214 OHCA patients (75 first shocks) were analysed. For each shock three predictors of defibrillation success were automatically calculated from the device files: two VF-waveform features, amplitude spectrum area (AMSA) and fuzzy entropy (FuzzyEn), and the median EtCO2 (MEtCO2) in the minute before the shock. Sensitivity, specificity, receiver operating characteristic (ROC) curves and area under the curve (AUC) were calculated, for each predictor individually and for the combination of MEtCO2 and VF-waveform predictors. Separate analyses were done for first shocks and all shocks. RESULTS MEtCO2 in first shocks was significantly higher for successful than for unsuccessful shocks (31mmHg/25mmHg, p<0.05), but differences were not significant for all shocks (32mmHg/29mmHg, p>0.05). MEtCO2 predicted shock success with an AUC of 0.66 for first shocks, but was not a predictor for all shocks (AUC 0.54). AMSA and FuzzyEn presented AUCs of 0.76 and 0.77 for first shocks, and 0.75 and 0.75 for all shocks. For first shocks, adding MEtCO2 improved the AUC of AMSA and FuzzyEn to 0.79 and 0.83, respectively. CONCLUSIONS MEtCO2 predicted defibrillation success only for first shocks. Adding MEtCO2 to VF-waveform analysis in first shocks improved prediction of shock success. VF-waveform features and MEtCO2 were automatically calculated from the device files, so these methods could be introduced in current defibrillators adding only new software.
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Affiliation(s)
- Beatriz Chicote
- Communications Engineering Department, University of the Basque Country UPV/EHU, Ingeniero Torres Quevedo Plaza, 1, 48013 Bilbao, Spain.
| | - Elisabete Aramendi
- Communications Engineering Department, University of the Basque Country UPV/EHU, Ingeniero Torres Quevedo Plaza, 1, 48013 Bilbao, Spain
| | - Unai Irusta
- Communications Engineering Department, University of the Basque Country UPV/EHU, Ingeniero Torres Quevedo Plaza, 1, 48013 Bilbao, Spain
| | - Pamela Owens
- Department of Emergency Medicine, University of Texas Southwesterm Medical Center (UTSW), 5323 Harry Hines Blvd, Dallas, TX, USA
| | - Mohamud Daya
- Department of Emergency Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR 97239-3098, USA
| | - Ahamed Idris
- Department of Emergency Medicine, University of Texas Southwesterm Medical Center (UTSW), 5323 Harry Hines Blvd, Dallas, TX, USA
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Zhang G, Wu T, Wan Z, Song Z, Yu M, Wang D, Li L, Chen F, Xu X. A method to differentiate between ventricular fibrillation and asystole during chest compressions using artifact-corrupted ECG alone. Comput Methods Programs Biomed 2017; 141:111-117. [PMID: 28241962 DOI: 10.1016/j.cmpb.2017.01.015] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2016] [Accepted: 01/29/2017] [Indexed: 06/06/2023]
Abstract
In recent years, numerous adaptive filtering techniques have been developed to suppress the chest compression (CC) artifact for reliable analysis of the electrocardiogram (ECG) rhythm without CC interruption. Unfortunately, the result of rhythm diagnosis during CCs is still unsatisfactory in many studies. The misclassification between corrupted asystole (ASY) and corrupted ventricular fibrillation (VF) is generally regarded as one of the major reasons for the poor performance of reported methods. In order to improve the diagnosis of VF/ASY corrupted by CCs, a novel method combining a least mean-square (LMS) filter and an amplitude spectrum area (AMSA) analysis was developed based only on the analysis of the surface of the corrupted ECG episode. This method was tested on 253 VF and 160 ASY ECG samples from subjects who experienced cardiac arrest using a porcine model and was compared with six other algorithms. The validation results indicated that this method, which yielded a satisfactory result with a sensitivity of 93.3%, a specificity of 96.3% and an accuracy of 94.8%, is superior to the other reported techniques. After improvement using the human ECG records in real cardiopulmonary resuscitation (CPR) scenarios, the algorithm is promising for corrupted VF/ASY detection with no hardware alterations in clinical practice.
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Affiliation(s)
- Guang Zhang
- Institute of Medical Equipment, National Biological Protection Engineering Centre, Tianjin, China
| | - Taihu Wu
- Institute of Medical Equipment, National Biological Protection Engineering Centre, Tianjin, China
| | - Zongming Wan
- Department of Pharmacology, Logistics University of Chinese People's Armed Police Forces, Tianjin, China
| | - Zhenxing Song
- Institute of Medical Equipment, National Biological Protection Engineering Centre, Tianjin, China
| | - Ming Yu
- Institute of Medical Equipment, National Biological Protection Engineering Centre, Tianjin, China
| | - Dan Wang
- Institute of Medical Equipment, National Biological Protection Engineering Centre, Tianjin, China
| | - Liangzhe Li
- Institute of Medical Equipment, National Biological Protection Engineering Centre, Tianjin, China
| | - Feng Chen
- Institute of Medical Equipment, National Biological Protection Engineering Centre, Tianjin, China.
| | - Xinxi Xu
- Institute of Medical Equipment, National Biological Protection Engineering Centre, Tianjin, China.
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