Abstract 127: The Effect of Cutoff Frequency Range on Amplitude Spectrum Area Performance in Predicting Defibrillation Outcome

Circulation ◽  
2018 ◽  
Vol 138 (Suppl_2) ◽  
Author(s):  
Xiaobo Wu ◽  
Weilun Quan ◽  
Jennifer Bradley ◽  
Mary Ann Peberdy ◽  
Joseph Ornato ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Sensitivity And Specificity ◽  
Characteristic Curve ◽  
Amplitude Spectrum ◽  
Sampling Rate ◽  
Cutoff Frequency ◽  
Experimental Studies ◽  
High Sensitivity ◽  
Frequency Range ◽  
Spectrum Area

Introduction: Both clinical and experimental studies have demonstrated that ventricular fibrillation (VF) waveform-based amplitude spectrum area (AMSA) predicts defibrillation outcome with high sensitivity and specificity. A commonly used cutoff frequency range for calculation of AMSA is 4-48 Hz, but the median VF frequency in patients is less than 7 Hz. In the present study, we investigated whether the AMSA performance in predicting defibrillation outcome may be affected by different cutoff frequency ranges. Hypothesis: A selected cutoff frequency range would affect AMSA performance in predicting defibrillation outcome in patients. Methods: A total of 450 segments (179-defibrillation success and 271-defibrillation failure) of VF waveforms from patients with out-of-hospital cardiac arrest were analyzed. Each 4.096-s segment prior to defibrillation was acquired with a sampling rate of 250 Hz. Using MATLAB (MathWorks, Natck, MA), the AMSA of each segment of VF waveform was calculated with five cutoff frequency ranges (Shown in Figure 1). Sensitivity and specificity were calculated when defibrillation success rate was 50% which was estimated by a logistic regression curve. Area under the receiver operating characteristic curve (AUC) was used to evaluate AMSA performance within different cutoff frequency ranges. Results: AMSA threshold was decreased from 20.5 to 6.5 mV·Hz when the cutoff frequency range was changed from 3-48 Hz to 3-10 Hz (Figure 1). Sensitivity of AMSA in 3-10 Hz was increased by 81.3% compared with that of AMSA in 3-48 Hz. Specificity of AMSA in 3-10 Hz was decreased by 8.1% compared with that of AMSA in 3-48 Hz. The corresponding AUC was increased from 0.724 (3-48 Hz) to 0.768 (3-10 Hz). Conclusions: A cutoff frequency range of 3-10 Hz significantly increases the sensitivity of AMSA for predicting defibrillation success in patients with cardiac arrest with a slight decrease in specificity.

Abstract 309: A Novel Method to Predict Survival From Ventricular Fibrillation Arrest During Chest Compressions

Circulation ◽  
2018 ◽  
Vol 138 (Suppl_2) ◽  
Author(s):  
Jason Coult ◽  
Lawrence D Sherman ◽  
Jennifer Blackwood ◽  
Heemun Kwok ◽  
Peter J Kudenchuk ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Ventricular Fibrillation ◽  
Characteristic Curve ◽  
Amplitude Spectrum ◽  
Support Vector ◽  
Chest Compressions ◽  
Time Frequency ◽  
Model Combining ◽  
Spectrum Area ◽  
Care Guidelines

Background: Quantitative measures of the ventricular fibrillation (VF) electrocardiogram (ECG) such as Amplitude Spectrum Area (AMSA) assess myocardial physiology and predict cardiac arrest outcomes, offering the potential to guide resuscitation care. Guidelines recommend minimally-interrupted chest compressions (CCs) during resuscitation, but CCs corrupt the ECG and must be paused for analysis. We therefore sought to develop a novel measure to predict survival without requiring CC pause. Methods and Results: Five-second VF ECG segments were collected with CCs and without CCs prior to 2755 defibrillation shocks in 1151 patients with out-of-hospital cardiac arrest. The cohort was divided into a training set to develop the measure and a test set to evaluate performance. Using segments from 460 training patients, we designed an adaptive filter to remove CC artifacts based on chest impedance and ECG characteristics, derived novel time-frequency and amplitude features of the filtered VF ECG, and trained a Support Vector Machine (SVM) model combining these novel features to predict survival with favorable neurologic status. In 691 test cases, area under the receiver operating characteristic curve (AUC) for predicting survival using the SVM was 0.74 (95% CI: 0.71-0.77) with CCs and 0.74 (95% CI: 0.71-0.76) without CCs (Figure 1). By comparison, AUC for predicting survival using AMSA was 0.70 (95% CI: 0.67-0.73) with CCs (p=0.001 for difference versus SVM) and 0.73 (95% CI: 0.71-0.76) without CCs (p=0.68 for difference versus SVM). Conclusions: VF waveform measures such as AMSA predict functional survival when obtained during ongoing CCs, but prognostic performance is reduced compared to CC-free analysis. However, an SVM-based measure combining novel VF waveform features enabled similar prediction with and without CCs. Machine learning combinations of features optimized for use during CCs may thus afford a means for VF prognosis during uninterrupted CCs.

Abstract 16924: Initial AMSA and Increased AMSA After CPR Predict Second Shock Success in Initially Shock-resistant VF During Out-of-hospital Cardiac Arrest

Circulation ◽  
2015 ◽  
Vol 132 (suppl_3) ◽  
Author(s):  
Ulrich Herken ◽  
Weilun Quan
Keyword(s):  
Logistic Regression ◽  
Cardiac Arrest ◽  
Ventricular Fibrillation ◽  
Success Rate ◽  
Fourier Transformation ◽  
Amplitude Spectrum ◽  
Fast Fourier Transformation ◽  
Shock Delivery ◽  
Spectrum Area ◽  
Hospital Cardiac Arrest

Purpose: Amplitude spectrum area (AMSA), which is calculated from the ventricular fibrillation (VF) waveform using fast Fourier transformation, has been recognized as a predictor of successful defibrillation (DF) and as an index of myocardial perfusion and viability during resuscitation. In this study, we investigated whether a change in AMSA occurring during CPR would predict DF outcome for subsequent DF attempts after a failed DF. We hypothesized that a patient responding to CPR with an increase in AMSA would have an increased likelihood of DF success. Methods: This was a retrospective analysis of out-of-hospital cardiac arrest patients who received a second DF due to initially shock-resistant VF. A total of 193 patients with an unsuccessful first DF were identified in a manufacturer database of electrocardiographic defibrillator records. AMSA was calculated for the first DF (AMSA1) and the second DF (AMSA2) during a 2.1 sec window ending 0.5 sec prior to DF. A successful DF attempt was defined as the presence of an organized rhythm with a rate ≥ 40 / min starting within 60 sec from the DF and lasting for > 30 sec. After the failed first DF, all patients received CPR for 2 to 3 minutes before delivery of the second DF. Change in AMSA (dAMSA) was calculated as dAMSA = AMSA2 - AMSA1. Results: The overall second DF success rate was 14.5%. Multivariable logistic regression showed that both AMSA1 and dAMSA were independent predictors of second DF success with odds ratios of 1.24 (95% CI 1.12 - 1.38, p<0.001) and 1.27 (95% CI 1.16 - 1.41, p<0.001) for each mVHz change in AMSA or dAMSA, respectively. Conclusions: In initially DF-resistant VF, a high initial AMSA value predicted an increased likelihood of second shock success. An increase of AMSA in response to CPR also predicted a higher second shock success rate. Monitoring of AMSA during resuscitation therefore may be useful to guide CPR efforts, possibly including timing of second shock delivery. These findings also further support the value of AMSA as indicator of myocardial viability.

scholarly journals Insights From the Ventricular Fibrillation Waveform Into the Mechanism of Survival Benefit From Bystander Cardiopulmonary Resuscitation

2021 ◽  
Vol 10 (19) ◽  
Author(s):  
Brooke Bessen ◽  
Jason Coult ◽  
Jennifer Blackwood ◽  
Cindy H. Hsu ◽  
Peter Kudenchuk ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Ventricular Fibrillation ◽  
Cardiopulmonary Resuscitation ◽  
Survival Benefit ◽  
Amplitude Spectrum ◽  
Peak Frequency ◽  
Spectrum Area ◽  
Bystander Cardiopulmonary Resuscitation ◽  
Bystander Cpr ◽  
Hospital Cardiac Arrest

Background The mechanism by which bystander cardiopulmonary resuscitation (CPR) improves survival following out‐of‐hospital cardiac arrest is unclear. We hypothesized that ventricular fibrillation (VF) waveform measures, as surrogates of myocardial physiology, mediate the relationship between bystander CPR and survival. Methods and Results We performed a retrospective cohort study of adult, bystander‐witnessed patients with out‐of‐hospital cardiac arrest with an initial rhythm of VF who were treated by a metropolitan emergency medical services system from 2005 to 2018. Patient, resuscitation, and outcome variables were extracted from emergency medical services and hospital records. A total of 3 VF waveform measures (amplitude spectrum area, peak frequency, and median peak amplitude) were computed from a 3‐second ECG segment before the initial shock. Multivariable logistic regression estimated the association between bystander CPR and survival to hospital discharge adjusted for Utstein elements. Causal mediation analysis quantified the proportion of survival benefit that was mediated by each VF waveform measure. Of 1069 patients, survival to hospital discharge was significantly higher among the 814 patients who received bystander CPR than those who did not (0.52 versus 0.43, respectively; P <0.01). The multivariable‐adjusted odds ratio for bystander CPR and survival was 1.6 (95% CI, 1.2, 2.1), and each VF waveform measure attenuated this association. Depending on the specific waveform measure, the proportion of mediation varied: 53% for amplitude spectrum area, 31% for peak frequency, and 29% for median peak amplitude. Conclusions Bystander CPR correlated with more robust initial VF waveform measures, which in turn mediated up to one‐half of the survival benefit associated with bystander CPR. These results provide insight into the biological mechanism of bystander CPR in VF out‐of‐hospital cardiac arrest.

Abstract 289: Relationship Between Myocardial Glycogen Concentrations and Amplitude Spectrum Area During Ventricular Fibrillation in a Rat Model of Cardiac Arrest and Resuscitation

Circulation ◽  
2018 ◽  
Vol 138 (Suppl_2) ◽  
Author(s):  
Qiaohua Hu ◽  
Xiangshao Fang ◽  
Zhengfei Yang ◽  
Wanchun Tang
Keyword(s):  
Cardiac Arrest ◽  
Energy Metabolism ◽  
Ventricular Fibrillation ◽  
Rat Model ◽  
Glycogen Content ◽  
Amplitude Spectrum ◽  
High Energy ◽  
Myocardial Energy Metabolism ◽  
Spectrum Area ◽  
The Relationship

Introduction: Myocardial high-energy phosphate (ATP) levels has been demonstrated correlating with amplitude spectrum area (AMSA) during ventricular fibrillation (VF) in previous experimental studies. In the present study, we investigated the relationship between AMSA and myocardial glycogen content (MGC),which can be used to reflect the status of myocardial energy metabolism indirectly during VF. Hypothesis: AMSA has a significantly correlation with MGC during VF in a rat model of cardiac arrest and resuscitation. Methods: Twenty male Sprague-Dawley rats weighing 350 to 450 g were utilized and randomized into two groups: VF and cardiopulmonary resuscitation (CPR) (VF/CPR group) or untreated VF (VF group). 5 mins of CPR was performed after 10 mins of untreated VF in VF/CPR animals. Amplitude spectrum area (AMSA) at VF 5, 10 and 15 mins were calculated from ECG signals. The rats’ hearts were quickly removed at the predetermined time of 15 min for determines the glycogen contents by the anthrone reagent method using a glycogen assay kit. Results: AMSA values significantly decreased during untreated VF in both VF and VF/CPR animals. However, much greater AMSA during CPR was achieved by the VF/CPR group in comparison with the VF group. There was a marked and negative relationship between AMSA at VF 15 min and MGC. (Figure). Conclusion: MGC was significantly and negatively correlated with AMSA during VF in this rat model of cardiac arrest and resuscitation. In clinical practice, we can use AMSA to reflect the state of myocardial energy metabolism indirectly. Figure The changes of AMSA and relationship between AMSA and glycogen content:(A) The change of AMSA between VF/CRP group and VF group;(B) The relationship between AMSA and glycogen content. AMSA, amplitude spectrum area; V, time of ventricular fibrillation; # p <0.05 vs. V4.

scholarly journals PP12 New ‘nature of call’ telephone screening tool, employed prior to nhs pathways triage, can accurately identify those later treated for out of hospital cardiac arrest: analysis of sensitivity and specificity using routine ambulance service data

2019 ◽  
Vol 36 (1) ◽  
pp. e5.2-e5
Author(s):  
Jonathan Green ◽  
Sean Ewings ◽  
Richard Wortham ◽  
Bronagh Walsh
Keyword(s):  
Cardiac Arrest ◽  
Sensitivity And Specificity ◽  
Screening Tool ◽  
Early Recognition ◽  
High Sensitivity ◽  
Ambulance Service ◽  
Current Function ◽  
Ambulance Dispatch ◽  
Clinical Records ◽  
Hospital Cardiac Arrest

BackgroundA new pre-triage emergency medical call screening tool, Nature of Call (NoC), has been introduced into UK ambulance services which employ the NHS Pathways (NHSP) triage system. Its current function is to provide a rapid sieve, differentiating between patients who may need treatment for Out-of-Hospital Cardiac Arrest (OHCA), and therefore require immediate ambulance dispatch, and all other calls, for which ambulance dispatch is withheld whilst further triage is undertaken.ObjectiveTo evaluate the accuracy of NoC in identifying patients with potentially treatable OHCA or peri-arrest conditions.MethodsStudy of diagnostic accuracy. The sample was a retrospective cohort of consecutive calls to a UK ambulance service, taken over a four-month period. Sensitivity and specificity were determined, comparing allocated priority dispositions with an OHCA Treatment Registry. Context was supplied by the evaluation of subsequent categorisation by NHSP. The accuracy of the combined NoC and NHSP allocations was also investigated.ResultsA total of 1 87 419 emergency calls were received. Of these, 71 373 were allocated both NoC and NHSP priority dispositions and were associated with electronic Patient Clinical Records. 590 (0.8%) of these patients received treatment for OHCA. NoC, sensitivity=77.6% (95% CI 74.1 to 80.8); specificity=86.9% (95% CI 86.6 to 87.1). NHSP, sensitivity=79.2% (95% CI 75.7 to 82.2); specificity=93.4% (93.2 to 93.6). NoC and NHSP combined, sensitivity=84.1% (95% CI 80.9 to 86.8); specificity=95.0% (95% CI 94.8 to 95.3).ConclusionsNoC and subsequent NHSP call categorisation each achieved relatively high sensitivity for the identification of treated OHCA, predicting similar groups of registry patients (although 6% were identified by NoC alone). Overall accuracy was enhanced when NoC and subsequent NHSP Results were combined. The unidentified group of treated OHCA patients (16%) present a challenge to the current dispatch system which relies on the early recognition of patients who may require treatment for OHCA.

Pattern of Intraoperative Parathyroid Hormone and Calcium in the Treatment of Tertiary Hyperparathyroidism

2019 ◽  
Vol 161 (6) ◽  
pp. 954-959 ◽  
Author(s):  
André Luís Maion Casarim ◽  
Fernando Antonio Maria Claret Arcadipane ◽  
Antonio Santos Martins ◽  
André Del Negro ◽  
André Afonso Nimtz Rodrigues ◽  
...  
Keyword(s):  
Parathyroid Hormone ◽  
Sensitivity And Specificity ◽  
Medical Center ◽  
Characteristic Curve ◽  
Treatment Success ◽  
Case Series ◽  
High Sensitivity ◽  
Total Parathyroidectomy ◽  
Tertiary Hyperparathyroidism ◽  
Intraoperative Pth

Objective Tertiary hyperparathyroidism, an autonomous hyperproduction of parathyroid hormone (PTH), has a challenge in its treatment. This study asked whether the intraoperative PTH and calcium drop can confirm the resection of all parathyroid tissues. Study Design Case series with planned data collection. Setting Tertiary referral medical center. Subjects and Methods The study assessed patients with tertiary hyperparathyroidism who were treated at the Hospital of the State University of Campinas from 2007 to 2015. All patients underwent total parathyroidectomy with autotransplantation of parathyroid fragments. PTH and calcium were collected during the preoperative period; at 10, 20, and 240 minutes after resection of the glands; and at 1 year after the procedure. Data were analyzed by analysis of variance and logistic regression analysis with statistical values of P < .05. Results Thirty-five patients were assessed: 17 women (48.57%) and 18 men (51.43%). The percentage of PTH drop was statistically significant at all times, unlike the calcium analysis, but only PTH collected at 20 minutes was able to confirm the removal of all parathyroid tissues ( P = .029). Based on the receiver operating characteristic curve, the 71.2% drop obtained high sensitivity and specificity ( P = .028). Conclusions Treatment success can be predicted by analyzing the decrease of intraoperative PTH and not by calcium. The 71.2% PTH drop at 20 minutes after parathyroidectomy had high sensitivity and specificity to predict surgical cure.

Prediction of Countershock Success in Patients Using the Autoregressive Spectral Estimation

2012 ◽  
Vol 51 (01) ◽  
pp. 13-20 ◽  
Author(s):  
A. Neurauter ◽  
L. Wieser ◽  
V. Wenzel ◽  
B. Abella ◽  
H. Myklebust ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Spectral Estimation ◽  
Amplitude Spectrum ◽  
Diagnostic Odds Ratio ◽  
Dominant Frequency ◽  
Fast Fourier Transformation ◽  
Optimal Timing ◽  
Spectrum Area ◽  
Life Threatening ◽  
Hospital Cardiac Arrest

SummaryObjectives: Ventricular fibrillation (VF) is a life-threatening cardiac arrhythmia and within of minutes of its occurrence, optimal timing of countershock therapy is highly warranted to improve the chance of survival. This study was designed to investigate whether the autoregressive (AR) estimation technique was capable to reliably predict countershock success in VF cardiac arrest patients.Methods: ECG data of 1077 countershocks applied to 197 cardiac arrest patients with out-of-hospital and in-hospital cardiac arrest between March 2002 and July 2004 were retrospectively analyzed. The ECG from the 2.5 s interval of the precountershock VF ECG was used for computing the AR based features Spectral Pole Power (SPP) and Spectral Pole Power with Dominant Frequency weighing (SPPDF) and Centroid Frequency (CF) and Amplitude Spectrum Area (AMSA) based on Fast Fourier Transformation (FFT).Results: With ROC AUC values up to 84.1 % and diagnostic odds ratio up to 19.12 AR based features SPP and SPPDF have better prediction power than the FFT based features CF (80.5 %; 6.56) and AMSA (82.1 %; 8.79).Conclusions: AR estimation based features are promising alternatives to FFT based features for countershock outcome when analyzing human data.

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