Evidence map›Paper›PMID 39043984›Full record

ArticleNeurocritical care2025

Early Burst Suppression Similarity Association with Structural Brain Injury Severity on MRI After Cardiac Arrest.

Shawn Shivdat, Tiange Zhan, Alessandro De Palma, Wei-Long Zheng, Parimala Krishnamurthy, Ezhil Paneerselvam, Samuel Snider, Matthew Bevers, Una-May O'Reilly, Jong Woo Lee and 2 more

Abstract read
In one paragraph

Article in Neurocritical care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Guideline
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Shawn ShivdatHarvard College, Cambridge, MA, USA.
Tiange ZhanComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.
Alessandro De PalmaComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.
Wei-Long ZhengDepartment of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China.
Parimala KrishnamurthyDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Ezhil PaneerselvamDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Samuel SniderDivision of Neurocritical Care, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA.
Matthew BeversDivision of Neurocritical Care, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA.
Una-May O'ReillyComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.
Jong Woo LeeDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA.
M Brandon Westover *Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Edilberto Amorim *Department of Neurology, Massachusetts General Hospital, Boston, MA, USA. edilbertoamorim@gmail.com.ORCID 0000-0001-6972-5622

Funding

1/2 ICECAP: Influence of Cooling duration on Efficacy in Cardiac Arrest PatientsUH3HL145269 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GEOCADIN, ROMERGRYKO, MEURER, WILLIAM JOSEPH · 2020 to 2024
$21.4M
Late-onset Unexplained Epilepsy as a Risk Factor for DementiaR01NS130119 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI Alice D Lam · 2023 to 2026
$8.7M
Data-Driven Sleep Biomarkers of Brain Health, Heart Health, and MortalityR01HL161253 · NHLBI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI CLIFFORD, GARI DAVID, MIGNOT, EMMANUEL J · 2022 to 2025
$8.3M
Comparative Safety of Seizure Prophylaxis within the Medicare ProgramR01AG073410 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI Lidia Maria Veras Rocha de Moura · 2021 to 2026
$4.1M
Low Neurophysiologic Resistance to Anesthetics as a Marker of Preclinical/Prodromal Alzheimer's Disease and Neurovascular Pathology, Delirium risk and InattentionR01AG073598 · NIA · STANFORD UNIVERSITY · PI Miles Berger · 2022 to 2026
$3.8M
Integrative Motor Activity Biomarker for the Risk of Alzheimer's RiskRF1AG064312 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI HU, KUN · 2019 to 2019
$3.6M
Multimodal Network Connectivity Architecture (MOCA) of the Brain and its Role in the Recovery of Consciousness in Comatose Cardiac Arrest PatientsR01NS102574 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI GREER, DAVID MATTHEW, WU, ONA · 2018 to 2022
$3.4M
Investigation of Sleep in the Intensive Care Unit (ICU-SLEEP)R01NS102190 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI WESTOVER, MICHAEL BRANDON · 2018 to 2022
$3.2M
Prospective Validation of Neurophysiologic Outcome Prediction in Acute Brain InjuryR01NS126282 · NINDS · BETH ISRAEL DEACONESS MEDICAL CENTER · PI Aaron F Struck, Michael Brandon Westover · 2023 to 2026
$2.9M
Big Data and Deep Learning for the Interictal-Ictal-Injury ContiuumR01NS107291 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI WESTOVER, MICHAEL BRANDON · 2018 to 2022
$2.8M
Establishing a Brain Health Index from the Sleep ElectroencephalogramRF1NS120947 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI CASH, SYDNEY S, THOMAS, ROBERT JOSEPH · 2021 to 2021
$2.4M
Establishing a Brain Health IndexR01NS120947 · NINDS · BETH ISRAEL DEACONESS MEDICAL CENTER · PI CASH, SYDNEY S, THOMAS, ROBERT JOSEPH · 2024 to 2025
$1.6M
NHLBI NIH HHS R01 HL161253NHLBI NIH HHS UH3 HL145269NIA NIH HHS R01 AG073410NIA NIH HHS R01 AG073598NIA NIH HHS RF1 AG064312NINDS NIH HHS 1K23NS119794NINDS NIH HHS K23 NS112474NINDS NIH HHS K23 NS119794NINDS NIH HHS R01 NS102190NINDS NIH HHS R01 NS102574NINDS NIH HHS R01 NS107291NINDS NIH HHS R01 NS120947NINDS NIH HHS R01 NS126282NINDS NIH HHS R01 NS130119NINDS NIH HHS RF1 NS120947
6 · The paper itself

Abstract

backgroundIdentical bursts on electroencephalography (EEG) are considered a specific predictor of poor outcomes in cardiac arrest, but its relationship with structural brain injury severity on magnetic resonance imaging (MRI) is not known.

methodsThis was a retrospective analysis of clinical, EEG, and MRI data from adult comatose patients after cardiac arrest. Burst similarity in first 72 h from the time of return of spontaneous circulation were calculated using dynamic time-warping (DTW) for bursts of equal (i.e., 500 ms) and varying (i.e., 100-500 ms) lengths and cross-correlation for bursts of equal lengths. Structural brain injury severity was measured using whole brain mean apparent diffusion coefficient (ADC) on MRI. Pearson's correlation coefficients were calculated between mean burst similarity across consecutive 12-24-h time blocks and mean whole brain ADC values. Good outcome was defined as Cerebral Performance Category of 1-2 (i.e., independence for activities of daily living) at the time of hospital discharge.

resultsOf 113 patients with cardiac arrest, 45 patients had burst suppression (mean cardiac arrest to MRI time 4.3 days). Three study participants with burst suppression had a good outcome. Burst similarity calculated using DTW with bursts of varying lengths was correlated with mean ADC value in the first 36 h after cardiac arrest: Pearson's r: 0-12 h: - 0.69 (p = 0.039), 12-24 h: - 0.54 (p = 0.002), 24-36 h: - 0.41 (p = 0.049). Burst similarity measured with bursts of equal lengths was not associated with mean ADC value with cross-correlation or DTW, except for DTW at 60-72 h (- 0.96, p = 0.04).

conclusionsBurst similarity on EEG after cardiac arrest may be associated with acute brain injury severity on MRI. This association was time dependent when measured using DTW.

Indexed as

Brain InjuriesComaElectroencephalographyHeart ArrestAdultAgedFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedRetrospective StudiesDynamic time-warpingEEGHeart arrestHypoxic-ischemic encephalopathyQuantitative EEGSimilarity

Identifiers

PMID39043984
PMCPMC11757804

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.