Literature DB >> 25466976

Amplitude spectrum area to guide defibrillation: a validation on 1617 patients with ventricular fibrillation.

Giuseppe Ristagno1, Tommaso Mauri2, Giancarlo Cesana2, Yongqin Li2, Andrea Finzi2, Francesca Fumagalli2, Gianpiera Rossi2, Niccolò Grieco2, Maurizio Migliori2, Aida Andreassi2, Roberto Latini2, Carla Fornari2, Antonio Pesenti2.   

Abstract

BACKGROUND: This study sought to validate the ability of amplitude spectrum area (AMSA) to predict defibrillation success and long-term survival in a large population of out-of-hospital cardiac arrests. METHODS AND
RESULTS: ECGs recorded by automated external defibrillators from different manufacturers were obtained from patients with cardiac arrests occurring in 8 city areas. A database, including 2447 defibrillations from 1050 patients, was used as the derivation group, and an additional database, including 1381 defibrillations from 567 patients, served as validation. A 2-second ECG window before defibrillation was analyzed, and AMSA was calculated. Univariable and multivariable regression analyses and area under the receiver operating characteristic curve were used for associations between AMSA and study end points: defibrillation success, sustained return of spontaneous circulation, and long-term survival. Among the 2447 defibrillations of the derivation database, 26.2% were successful. AMSA was significantly higher before a successful defibrillation than a failing one (13 ± 5 versus 6.8 ± 3.5 mV-Hz) and was an independent predictor of defibrillation success (odds ratio, 1.33; 95% confidence interval, 1.20-1.37) and sustained return of spontaneous circulation (odds ratio, 1.22; 95% confidence interval, 1.17-1.26). Area under the receiver operating characteristic curve for defibrillation success prediction was 0.86 (95% confidence interval, 0.85-0.88). AMSA was also significantly associated with long-term survival. The following AMSA thresholds were identified: 15.5 mV-Hz for defibrillation success and 6.5 mV-Hz for defibrillation failure. In the validation database, AMSA ≥ 15.5 mV-Hz had a positive predictive value of 84%, whereas AMSA ≤ 6.5 mV-Hz had a negative predictive value of 98%.
CONCLUSIONS: In this large derivation-validation study, AMSA was validated as an accurate predictor of defibrillation success. AMSA also appeared as a predictor of long-term survival.
© 2014 American Heart Association, Inc.

Entities:  

Keywords:  cardiac arrest; defibrillation, electric; survival; ventricular fibrillation

Mesh:

Year:  2014        PMID: 25466976     DOI: 10.1161/CIRCULATIONAHA.114.010989

Source DB:  PubMed          Journal:  Circulation        ISSN: 0009-7322            Impact factor:   29.690


  19 in total

1.  Value of capnography to predict defibrillation success in out-of-hospital cardiac arrest.

Authors:  Beatriz Chicote; Elisabete Aramendi; Unai Irusta; Pamela Owens; Mohamud Daya; Ahamed Idris
Journal:  Resuscitation       Date:  2019-03-02       Impact factor: 5.262

2.  Predictive value of amplitude spectrum area of ventricular fibrillation waveform in patients with acute or previous myocardial infarction in out-of-hospital cardiac arrest.

Authors:  Michiel Hulleman; David D Salcido; James J Menegazzi; Patrick C Souverein; Hanno L Tan; Marieke T Blom; Rudolph W Koster
Journal:  Resuscitation       Date:  2017-08-24       Impact factor: 5.262

3.  Effects of intra-resuscitation antiarrhythmic administration on rearrest occurrence and intra-resuscitation ECG characteristics in the ROC ALPS trial.

Authors:  David D Salcido; Robert H Schmicker; Noah Kime; Jason E Buick; Sheldon Cheskes; Brian Grunau; Stephanie Zellner; Dana Zive; Tom P Aufderheide; Allison C Koller; Heather Herren; Jack Nuttall; Matthew L Sundermann; James J Menegazzi
Journal:  Resuscitation       Date:  2018-05-24       Impact factor: 5.262

4.  Cardioplegia defibrillation of circulatory and metabolic phase ventricular fibrillation in a swine model.

Authors:  Keith A Marill; David D Salcido; Matthew L Sundermann; Allison C Koller; James J Menegazzi
Journal:  Resuscitation       Date:  2019-09-18       Impact factor: 5.262

5.  Energy conserving chemical defibrillation of ventricular fibrillation: A randomized two phase controlled blinded trial.

Authors:  Keith A Marill; David D Salcido; Matthew L Sundermann; Allison C Koller; James J Menegazzi
Journal:  Resuscitation       Date:  2016-03-31       Impact factor: 5.262

Review 6.  Towards individualised treatment of out-of-hospital cardiac arrest patients: an update on technical innovations in the prehospital chain of survival.

Authors:  J Thannhauser; J Nas; R A Waalewijn; N van Royen; J L Bonnes; M A Brouwer; M J de Boer
Journal:  Neth Heart J       Date:  2021-08-09       Impact factor: 2.854

7.  Validation of spectral energy for the quantitative analysis of ventricular fibrillation waveform to guide defibrillation in a porcine model of cardiac arrest and resuscitation.

Authors:  Qiyu Yang; Ming Li; Zhaolan Huang; Zhuoyan Xie; Yue Wang; Qin Ling; Xuefen Liu; Wanchun Tang; Longyuan Jiang; Zhengfei Yang
Journal:  J Thorac Dis       Date:  2019-09       Impact factor: 2.895

Review 8.  [Adult advanced life support].

Authors:  Jasmeet Soar; Bernd W Böttiger; Pierre Carli; Keith Couper; Charles D Deakin; Therese Djärv; Carsten Lott; Theresa Olasveengen; Peter Paal; Tommaso Pellis; Gavin D Perkins; Claudio Sandroni; Jerry P Nolan
Journal:  Notf Rett Med       Date:  2021-06-08       Impact factor: 0.826

9.  Electrocardiographic recording direction impacts ventricular fibrillation waveform measurements: A potential pitfall for VF-waveform guided defibrillation protocols.

Authors:  Jos Thannhauser; Joris Nas; Priya Vart; Joep L R M Smeets; Menko-Jan de Boer; Niels van Royen; Judith L Bonnes; Marc A Brouwer
Journal:  Resusc Plus       Date:  2021-04-02

10.  Time boundaries of the three-phase time-sensitive model for ventricular fibrillation cardiac arrest.

Authors:  Yoshikazu Goto; Akira Funada; Tetsuo Maeda; Yumiko Goto
Journal:  Resusc Plus       Date:  2021-03-02
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