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Title:Predicting defibrillation success by "genetic" programming in patients with out-of-hospital cardiac arrest
Authors:ID Podbregar, Matej (Author)
ID Kovačič, Miha (Author)
ID Podbregar-Marš, Aleksandra (Author)
ID Brezočnik, Miran (Author)
Files:URL http://dx.doi.org/10.1016/S0300-9572(03)00030-3
 
Language:English
Work type:Unknown
Typology:1.01 - Original Scientific Article
Organization:FS - Faculty of Mechanical Engineering
Abstract:In some patients with ventricular fibrillation (VF) there may be a better chance of successful defibrillation after a period of chest compression and ventilation before the defibrillation attempt. It is therefore important to know whether a defibrillation attempt will be successful. The predictive powerof a model developed by "genetic" programming (GP) to predict defibrillation success was studied. Methods and Results: 203 defibrillations were administered in 47 patients with out-of-hospital cardiac arrest due to a cardiac cause. Maximal amplitude, a total energy of power spectral density, and the Hurst exponent of the VF electrocardiogram (ECG) signal were included in the model developed by GP. Positive and negative likelihood ratios of the model for testing data were 35.5 and 0.00, respectively. Using a model developed by GP on the complete database, 120 of the 124 unsuccessful defibrillations would have been avoided, whereas all of the 79 successful defibrillations would have been administered. Conclusion: The VF ECG contains information predictive of defibrillation success. The model developed by GP, including data from the time-domain, frequency-domain and nonlinear dynamics, could reduce the incidence of unsuccessful defibrillations.
Keywords:optimisation methods, evolutionary optimisation methods, genetic algorithms, genetic programming, defibrillation, cardiac arrest prediction
Year of publishing:2003
PID:20.500.12556/DKUM-27671 New window
UDC:004.89:611.12
ISSN on article:0300-9572
COBISS.SI-ID:7969814 New window
NUK URN:URN:SI:UM:DK:DY6RUP8D
Publication date in DKUM:01.06.2012
Views:2046
Downloads:105
Metadata:XML DC-XML DC-RDF
Categories:Misc.
:
PODBREGAR, Matej, KOVAČIČ, Miha, PODBREGAR-MARŠ, Aleksandra and BREZOČNIK, Miran, 2003, Predicting defibrillation success by “genetic” programming in patients with out-of-hospital cardiac arrest. Resuscitation [online]. 2003. [Accessed 23 January 2025]. Retrieved from: http://dx.doi.org/10.1016/S0300-9572(03)00030-3
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Record is a part of a journal

Title:Resuscitation
Shortened title:Resuscitation
Publisher:Middlesex Pub. Co.
ISSN:0300-9572
COBISS.SI-ID:537876 New window

Secondary language

Language:English
Keywords:optimizacijske metode, evolucijske optimizacijske metode, genetski algoritmi, genetsko programiranje, defibrilacija, napoved zastoja srca


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