ECG waveform dataset for predicting defibrillation outcome in out-of-hospital cardiac arrested patients
Аутори
Benini, SergioIvanović, Marija D.
Savardi, Mattia
Kršić, Jelena
Hadžievski, Ljupčo
Baronio, Fabio
Чланак у часопису (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
The provided database of 260 ECG signals was collected from patients with out-of-hospital cardiac arrest while treated by the emergency medical services. Each ECG signal contains a 9 second waveform showing ventricular fibrillation, followed by 1 min of post-shock waveform. Patients’ ECGs are made available in multiple formats. All ECGs recorded during the prehospital treatment are provided in PFD files, after being anonymized, printed in paper, and scanned. For each ECG, the dataset also includes the whole digitized waveform (9 s pre- and 1 min post-shock each) and numerous features in temporal and frequency domain extracted from the 9 s episode immediately prior to the first defibrillation shock. Based on the shock outcome, each ECG file has been annotated by three expert cardiologists, - using majority decision -, as successful (56 cases), unsuccessful (195 cases), or indeterminable (9 cases). The code for preprocessing, for feature extraction, and for limiting the investigation to ...different temporal intervals before the shock is also provided. These data could be reused to design algorithms to predict shock outcome based on ventricular fibrillation analysis, with the goal to optimize the defibrillation strategy (immediate defibrillation versus cardiopulmonary resuscitation and/or drug administration) for enhancing resuscitation. © 2020
Кључне речи:
cardiac arrest / Defibrillation / ECG / Prediction / resuscitation / Shock outcome / Ventricular fibrillation (VF) / waveformИзвор:
Data in Brief, 2021, 34, 106635-Финансирање / пројекти:
- Capturing and quantitative analysis of multi-scale multi-channel diagnostic data. (EU-H2020-691051)
- Фотоника микро и нано структурних материјала (RS-MESTD-Integrated and Interdisciplinary Research (IIR or III)-45010)
Повезане информације:
- Повезани садржај
https://doi.org/10.1016/j.artmed.2020.101963 - Повезани садржај
https://doi.org/10.17632/wpr5nzyn2z.1 - Повезани садржај
https://vinar.vin.bg.ac.rs/handle/123456789/9549
DOI: 10.1016/j.dib.2020.106635
ISSN: 2352-3409
PubMed: 33364270
WoS: 000617525400025
Scopus: 2-s2.0-85099497948
Институција/група
VinčaTY - JOUR AU - Benini, Sergio AU - Ivanović, Marija D. AU - Savardi, Mattia AU - Kršić, Jelena AU - Hadžievski, Ljupčo AU - Baronio, Fabio PY - 2021 UR - https://vinar.vin.bg.ac.rs/handle/123456789/9547 AB - The provided database of 260 ECG signals was collected from patients with out-of-hospital cardiac arrest while treated by the emergency medical services. Each ECG signal contains a 9 second waveform showing ventricular fibrillation, followed by 1 min of post-shock waveform. Patients’ ECGs are made available in multiple formats. All ECGs recorded during the prehospital treatment are provided in PFD files, after being anonymized, printed in paper, and scanned. For each ECG, the dataset also includes the whole digitized waveform (9 s pre- and 1 min post-shock each) and numerous features in temporal and frequency domain extracted from the 9 s episode immediately prior to the first defibrillation shock. Based on the shock outcome, each ECG file has been annotated by three expert cardiologists, - using majority decision -, as successful (56 cases), unsuccessful (195 cases), or indeterminable (9 cases). The code for preprocessing, for feature extraction, and for limiting the investigation to different temporal intervals before the shock is also provided. These data could be reused to design algorithms to predict shock outcome based on ventricular fibrillation analysis, with the goal to optimize the defibrillation strategy (immediate defibrillation versus cardiopulmonary resuscitation and/or drug administration) for enhancing resuscitation. © 2020 T2 - Data in Brief T1 - ECG waveform dataset for predicting defibrillation outcome in out-of-hospital cardiac arrested patients VL - 34 SP - 106635 DO - 10.1016/j.dib.2020.106635 ER -
@article{ author = "Benini, Sergio and Ivanović, Marija D. and Savardi, Mattia and Kršić, Jelena and Hadžievski, Ljupčo and Baronio, Fabio", year = "2021", abstract = "The provided database of 260 ECG signals was collected from patients with out-of-hospital cardiac arrest while treated by the emergency medical services. Each ECG signal contains a 9 second waveform showing ventricular fibrillation, followed by 1 min of post-shock waveform. Patients’ ECGs are made available in multiple formats. All ECGs recorded during the prehospital treatment are provided in PFD files, after being anonymized, printed in paper, and scanned. For each ECG, the dataset also includes the whole digitized waveform (9 s pre- and 1 min post-shock each) and numerous features in temporal and frequency domain extracted from the 9 s episode immediately prior to the first defibrillation shock. Based on the shock outcome, each ECG file has been annotated by three expert cardiologists, - using majority decision -, as successful (56 cases), unsuccessful (195 cases), or indeterminable (9 cases). The code for preprocessing, for feature extraction, and for limiting the investigation to different temporal intervals before the shock is also provided. These data could be reused to design algorithms to predict shock outcome based on ventricular fibrillation analysis, with the goal to optimize the defibrillation strategy (immediate defibrillation versus cardiopulmonary resuscitation and/or drug administration) for enhancing resuscitation. © 2020", journal = "Data in Brief", title = "ECG waveform dataset for predicting defibrillation outcome in out-of-hospital cardiac arrested patients", volume = "34", pages = "106635", doi = "10.1016/j.dib.2020.106635" }
Benini, S., Ivanović, M. D., Savardi, M., Kršić, J., Hadžievski, L.,& Baronio, F.. (2021). ECG waveform dataset for predicting defibrillation outcome in out-of-hospital cardiac arrested patients. in Data in Brief, 34, 106635. https://doi.org/10.1016/j.dib.2020.106635
Benini S, Ivanović MD, Savardi M, Kršić J, Hadžievski L, Baronio F. ECG waveform dataset for predicting defibrillation outcome in out-of-hospital cardiac arrested patients. in Data in Brief. 2021;34:106635. doi:10.1016/j.dib.2020.106635 .
Benini, Sergio, Ivanović, Marija D., Savardi, Mattia, Kršić, Jelena, Hadžievski, Ljupčo, Baronio, Fabio, "ECG waveform dataset for predicting defibrillation outcome in out-of-hospital cardiac arrested patients" in Data in Brief, 34 (2021):106635, https://doi.org/10.1016/j.dib.2020.106635 . .