Evidence map›Paper›PMID 30946055›Full record

ArticleAnesthesiology2019

Dynamic Cortical Connectivity during General Anesthesia in Healthy Volunteers.

Duan Li, Phillip E Vlisides, Max B Kelz, Michael S Avidan, George A Mashour, ReCCognition Study Group

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in Anesthesiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
14.9field-weighted citation impact, top 1% of its field
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

35 citing papers in PubMed, 69 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Duan LiFrom the Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan (D.L., P.E.V., G.A.M.) the Department of Anesthesiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania (M.B.K.) the Department of Anesthesiology, Washington University School of Medicine, St. Louis, Missouri (M.S.A.). From the Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan From the Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan From the Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan From the Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan From the Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan From the Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan From the Department of Anesthesiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania From the Department of Anesthesiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania From the Department of Anesthesiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania From the Department of Anesthesiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania From the Department of Anesthesiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania From the Department of Anesthesiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania From the Department of Anesthesiology, Washington University School of Medicine, St. Louis, Missouri From the Department of Anesthesiology, Washington University School of Medicine, St. Louis, Missouri From the Department of Anesthesiology, Washington University School of Medicine, St. Louis, Missouri.
Phillip E Vlisides
Max B Kelz
Michael S Avidan
George A Mashour
ReCCognition Study Group
University of Michigan–Ann Arbor · US

Funding

Neurophysiological Mechanisms of Recovery of ConsciousnessR01GM124023 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI PROEKT, ALEXANDER · 2018 to 2022
$1.8M
NIGMS NIH HHS R01 GM124023
6 · The paper itself

Abstract

what we already know about this topicAnesthetic-induced loss of consciousness is accompanied by changes in functional connectivity within and between brain networks. WHAT THIS ARTICLE TELLS US THAT IS NEW: Despite a stable surgical level of anesthesia and the absence of noxious stimuli, connectivity patterns are not static but rather fluctuate dynamically and nonrandomly over time. These results suggest that single or static connectivity patterns may not be able to discriminate levels of consciousness.

backgroundRecent studies of anesthetic-induced unconsciousness in healthy volunteers have focused on functional brain connectivity patterns, but the protocols rarely parallel the depth and duration of surgical anesthesia. Furthermore, it is unknown whether there is a single functional connectivity pattern that correlates with general anesthesia for the duration of prolonged anesthetic exposure.

methodsThe authors analyzed electroencephalographic data in 30 healthy participants who underwent induction of anesthesia with propofol followed by 3 h of isoflurane anesthesia at age-adjusted 1.3 minimum alveolar concentration. Functional connectivity was assessed by frequency-resolved weighted phase lag index between frontal and parietal channels and between prefrontal and frontal channels, which were classified into a discrete set of states through k-means cluster analysis. Temporal dynamics were evaluated by the occurrence rate and dwell time distribution for each state as well as the transition probabilities between states.

resultsBurst suppression was present, with mean suppression ratio reducing from 44.8 ± 32.3% to 14.0 ± 20.2% (mean ± SD) during isoflurane anesthesia (P < 0.001). Aside from burst suppression, eight connectivity states were classified by optimizing the reproducibility of clustering solutions, with each characterized by distinct properties. The temporal progression of dominant states revealed a successive shifting trajectory from the state associated with alpha frontal-parietal connectivity to those associated with delta and alpha prefrontal-frontal connectivity during induction, which was reversed during emergence. Cortical connectivity was dynamic during maintenance period, and it was more probable to remain in the same state (82.0 ± 8.3%) than to switch to a different state (P < 0.001). However, transitions to other states were structured, i.e., occurred more frequently than expected by chance.

conclusionsAnesthesia-induced alterations of functional connectivity are dynamic despite the stable and prolonged administration of isoflurane, in the absence of any noxious stimuli. Changes in connectivity over time will likely yield more information as a marker or mechanism of surgical anesthesia than any single pattern.

Indexed as

Anesthesia, GeneralAdultAnesthetics, InhalationAnesthetics, IntravenousCerebral CortexElectroencephalographyFemaleHealthy VolunteersHumansIsofluraneMaleNerve NetPropofolYoung AdultAnesthetics, InhalationAnesthetics, IntravenousIsofluranePropofol

Identifiers

PMID30946055
OpenAlexW2925812302

What OpenQuestion holds

Textmetadata
Read underepoch 390

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 OpenQuestion graph.