Dataset Information

ECG waveform dataset for predicting defibrillation outcome in out-of-hospital cardiac arrested patients.

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.

SUBMITTER: Benini S

PROVIDER: S-EPMC7753135 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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ECG waveform dataset for predicting defibrillation outcome in out-of-hospital cardiac arrested patients.

Benini Sergio S Ivanovic Marija D MD Savardi Mattia M Krsic Jelena J Hadžievski Ljupco L Baronio Fabio F

Data in brief 20201209

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 includ ...[more]

PMID: 33364270

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Project description:Background: Early prognostication is a major challenge after out-of-hospital cardiac arrest (OHCA). Aims: We hypothesized that a genome-wide analysis of blood gene expression could offer new prognostic tools and lines of research. Methods: Sixty-nine patients were enrolled from an ancillary study of the clinical trial NCT00999583 that tested the effect of erythropoietin (EPO) after OHCA. Blood samples were collected in comatose survivors of OHCA at hospital admission and 1 and 3 days after resuscitation. Gene expression profiles were analyzed (Illumina HumanHT-12 V4 BeadChip; >34,000 genes). Patients were classified into two categories representing neurologically favorable outcome (Cerebral Performance Category [CPC] = 1-2) vs unfavorable outcome (CPC>2) at Day 60 after OHCA. Differential and functional enrichment analyses were performed to compare transcriptomic profiles between these two categories. Results: Among the 69 enrolled patients, 33 and 36 patients were treated or not by EPO, respectively. Among them, 42% had a favorable neurological outcome in both groups. EPO did not affect the transcriptomic response at Day-0 and 1 after OHCA. In contrast, 76 transcripts differed at Day-0 between patients with unfavorable vs favorable neurological outcome. This signature persisted at Day-1 after OHCA. Functional enrichment analysis revealed a down-regulation of adaptive immunity with concomitant up-regulation of innate immunity and inflammation in patients with unfavorable vs favorable neurological outcome. The transcription of many genes of the HLA family was decreased in patients with unfavorable vs favorable neurological outcome. Concomitantly, neutrophil activation and inflammation were observed. Up-stream regulators analysis showed the implication of numerous factors involved in cell cycle and damages. A logistic regression including a set of genes allowed a reliable prediction of the clinical outcomes (Specificity=88%; Hit Rate=83%). Conclusions: A transcriptomic signature involving a counterbalance between adaptive and innate immune responses is able to predict neurological outcome very early after hospital admission after OHCA. This deserves confirmation in a larger population.

Dataset Information

ECG waveform dataset for predicting defibrillation outcome in out-of-hospital cardiac arrested patients.

Publications

ECG waveform dataset for predicting defibrillation outcome in out-of-hospital cardiac arrested patients.

Similar Datasets

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