Evidence mapPaperPMID 34858144Full record

ArticleFrontiers in systems neuroscience2021

Electroencephalogram-Based Complexity Measures as Predictors of Post-operative Neurocognitive Dysfunction.

Leah Acker, Christine Ha, Junhong Zhou, Brad Manor, Charles M Giattino, Ken Roberts, Miles Berger, Mary Cooter Wright, Cathleen Colon-Emeric, Michael Devinney and 4 more

Abstract read
In one paragraph

Article in Frontiers in systems neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
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

11 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
  4. Observational
  5. A Real-Time Neurophysiologic Stress Test for the Aging Brain: Novel Perioperative and ICU Applications of EEG in Older Surgical Patients.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2023
    Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. 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

14 authors.

Leah AckerDepartment of Anesthesiology, Duke University School of Medicine, Durham, NC, United States.
Christine HaDuke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, United States.
Junhong ZhouHinda and Arthur Marcus Institute for Aging Research, Hebrew Senior Life and Harvard Medical School, Boston, MA, United States.
Brad ManorHinda and Arthur Marcus Institute for Aging Research, Hebrew Senior Life and Harvard Medical School, Boston, MA, United States.
Charles M GiattinoCenter for Cognitive Neuroscience, Duke University, Durham, NC, United States.
Ken RobertsCenter for Cognitive Neuroscience, Duke University, Durham, NC, United States.
Miles BergerDepartment of Anesthesiology, Duke University School of Medicine, Durham, NC, United States.
Mary Cooter WrightDepartment of Anesthesiology, Duke University School of Medicine, Durham, NC, United States.
Cathleen Colon-EmericDuke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, United States.
Michael DevinneyDepartment of Anesthesiology, Duke University School of Medicine, Durham, NC, United States.
Sandra AuDuke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, United States.
Marty G WoldorffCenter for Cognitive Neuroscience, Duke University, Durham, NC, United States.
Lewis A LipsitzHinda and Arthur Marcus Institute for Aging Research, Hebrew Senior Life and Harvard Medical School, Boston, MA, United States.
Heather E WhitsonDuke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, United States.

Funding

Research EducationP30AG031679 · BRIGHAM AND WOMEN'S HOSPITAL · 2025 to 2025
$1.4M
NIA NIH HHS P30 AG031679
6 · The paper itself

Abstract

Physiologic signals such as the electroencephalogram (EEG) demonstrate irregular behaviors due to the interaction of multiple control processes operating over different time scales. The complexity of this behavior can be quantified using multi-scale entropy (MSE). High physiologic complexity denotes health, and a loss of complexity can predict adverse outcomes. Since postoperative delirium is particularly hard to predict, we investigated whether the complexity of preoperative and intraoperative frontal EEG signals could predict postoperative delirium and its endophenotype, inattention. To calculate MSE, the sample entropy of EEG recordings was computed at different time scales, then plotted against scale; complexity is the total area under the curve. MSE of frontal EEG recordings was computed in 50 patients ≥ age 60 before and during surgery. Average MSE was higher intra-operatively than pre-operatively (

Indexed as

anesthesiaattentioncognitioncomplexitydeliriumelectroencephalogram (EEG)perioperative medicineresilience

Identifiers

PMID34858144
PMCPMC8631543

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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 Socratic graph.