Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Electrocardiogram01:29

Electrocardiogram

5.4K
An electrocardiogram (ECG or EKG) is a critical diagnostic tool that records the electrical signals produced by the heart during each heartbeat. This recording is achieved through electrodes placed strategically on the arms, legs, and chest. The electrocardiograph amplifies these signals and produces 12 distinct tracings, offering a comprehensive understanding of the heart's electrical activity.
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and...
5.4K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

To Cool or Not to Cool in Low- and Middle-Income Countries:? A Call for Resources, Training and Shared Knowledge.

The Journal of pediatrics·2026
Same author

Acute and Long-Term EEG and seizure characteristics in new onset refractory status epilepticus (NORSE).

Epilepsia·2026
Same author

Real-Time Assessment of Factors Impacting Prognostic Predictions After Pediatric Cardiac Arrest: A Single-Center Prospective Study.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies·2026
Same author

Mechanistically informed circulating biomarkers are associated with acquired epilepsy after neonatal brain injury.

Journal of neuroinflammation·2026
Same author

Multimodal MRI of white matter development and selective motor control in preterm infants.

NeuroImage. Clinical·2026
Same author

Autonomic Function and Cerebral Autoregulation in Children Receiving Extracorporeal Life Support.

Children (Basel, Switzerland)·2026
Same journal

Analyses of gender disparities in receipt of bystander cardiopulmonary resuscitation after out-of-hospital cardiac arrests by patient's age group and bystander category.

Resuscitation·2026
Same journal

A scoping review of Support Interventions for Bystanders involved in Out-of-Hospital Cardiac Arrest.

Resuscitation·2026
Same journal

Sedation Early After Return of Spontaneous Circulation and During Pre-Hospital Transport After Out-Of-Hospital Cardiac Arrest: Retrospective Analysis of the AfterROSC1 & 2 Database.

Resuscitation·2026
Same journal

Volume-controlled mechanical ventilation during cardiopulmonary resuscitation: A systematic review and meta-analysis.

Resuscitation·2026
Same journal

Number of community first responders needed for quick response times to cardiac arrest: a nationwide study.

Resuscitation·2026
Same journal

Device damage and malfunction during dual defibrillation or dual electrical cardioversion: a scoping review.

Resuscitation·2026
See all related articles

Related Experiment Video

Updated: Jan 16, 2026

Author Spotlight: A Unique Mouse Model of Asphyxia-Induced Cardiac Arrest
07:18

Author Spotlight: A Unique Mouse Model of Asphyxia-Induced Cardiac Arrest

Published on: April 14, 2023

2.2K

Predicting pediatric cardiac arrest outcomes using early quantitative EEG.

Giulia M Benedetti1, Andrea C Pardo2, LNelson Sanchez-Pinto2

  • 1Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; Division of Pediatric Neurology, Seattle Children's Hospital, University of Washington. Seattle, WA, USA; Department of Pediatrics, Division of Pediatric Neurology, C.S. Mott Children's Hospital, University of Michigan. Ann Arbor, MI, USA.

Resuscitation
|September 26, 2025
PubMed
Summary
This summary is machine-generated.

Quantitative EEG (qEEG) features improve neuroprognostication accuracy after pediatric cardiac arrest (CA). These dynamic biomarkers, alongside clinical data, enhance outcome prediction for children, guiding future neuroprotective strategies.

Keywords:
ElectroencephalographyMachine learningNeurocritical careNeuroprognosticationPrediction model

More Related Videos

Simultaneous Video-EEG-ECG Monitoring to Identify Neurocardiac Dysfunction in Mouse Models of Epilepsy
11:54

Simultaneous Video-EEG-ECG Monitoring to Identify Neurocardiac Dysfunction in Mouse Models of Epilepsy

Published on: January 29, 2018

26.8K
Application of an Amplitude-integrated EEG Monitor Cerebral Function Monitor to Neonates
05:58

Application of an Amplitude-integrated EEG Monitor Cerebral Function Monitor to Neonates

Published on: September 6, 2017

40.5K

Related Experiment Videos

Last Updated: Jan 16, 2026

Author Spotlight: A Unique Mouse Model of Asphyxia-Induced Cardiac Arrest
07:18

Author Spotlight: A Unique Mouse Model of Asphyxia-Induced Cardiac Arrest

Published on: April 14, 2023

2.2K
Simultaneous Video-EEG-ECG Monitoring to Identify Neurocardiac Dysfunction in Mouse Models of Epilepsy
11:54

Simultaneous Video-EEG-ECG Monitoring to Identify Neurocardiac Dysfunction in Mouse Models of Epilepsy

Published on: January 29, 2018

26.8K
Application of an Amplitude-integrated EEG Monitor Cerebral Function Monitor to Neonates
05:58

Application of an Amplitude-integrated EEG Monitor Cerebral Function Monitor to Neonates

Published on: September 6, 2017

40.5K

Area of Science:

  • Pediatric Neurology
  • Neurocritical Care
  • Quantitative Electroencephalography (qEEG)

Background:

  • Accurate neuroprognostication is crucial for pediatric cardiac arrest (CA) care.
  • Current models lack precision and modifiable biomarkers.
  • Quantitative EEG (qEEG) may enhance prognostic accuracy.

Purpose of the Study:

  • To evaluate the accuracy of neuroprognostication models incorporating quantitative EEG (qEEG) features.
  • To assess the predictive value of qEEG in children post-CA.
  • To identify potential modifiable biomarkers for improved outcomes.

Main Methods:

  • Retrospective multicenter cohort study (2010-2016) of children (3mo-18yr) post-CA.
  • EEG data analyzed within 24 hours post-CA.
  • Models included clinical variables, qualitative EEG (qualEEG), and qEEG features.

Main Results:

  • A combined model of clinical, qualEEG, and qEEG features achieved high predictive accuracy (AUC 0.92).
  • qEEG features significantly improved outcome prediction.
  • Increased signal complexity (SR) correlated with disability and unfavorable outcomes.

Conclusions:

  • qEEG features measured within 24 hours post-CA enhance predictive models.
  • Signal complexity (SR) is an objective measure for outcome prediction.
  • qEEG may represent targetable biomarkers for neuroprotective interventions.