Trial reportJournal of clinical monitoring and computing2014
Multi-scale sample entropy of electroencephalography during sevoflurane anesthesia.
Trial report in Journal of clinical monitoring and computing, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
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.
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Who cites it
5 citing papers in PubMed, 17 citations in OpenAlex.
- Non-Monotonic Complexity of Stochastic Model of the Channel Gating Dynamics.Entropy (Basel, Switzerland) · 2023Article
- Consciousness is supported by near-critical slow cortical electrodynamics.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Electroencephalogram-Based Complexity Measures as Predictors of Post-operative Neurocognitive Dysfunction.Frontiers in systems neuroscience · 2021Article
- Consciousness and complexity: a consilience of evidence.Neuroscience of consciousness · 2021Review
- Long-Range Temporal Correlations of Patients in Minimally Conscious State Modulated by Spinal Cord Stimulation.Frontiers in physiology · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The electroencephalogram (EEG) has been widely applied in the assessment of depth of anesthesia (DoA). Recent research has found that multi-scale EEG analysis describes brain dynamics better than traditional non-linear methods. In this study, we have adopted a modified sample entropy (MSpEn) method to analyze anesthetic EEG series as a measure of DoA. EEG data from a previous study consisting of 19 adult subjects undergoing sevoflurane anesthesia were used in the present investigation. In addition to the modified sample entropy method, the well-established EEG indices approximate entropy (ApEn), response entropy (RE), and state entropy (SE) were also computed for comparison. Pharmacokinetic/pharmacodynamic modeling and prediction probability (P k ) were used to assess and compare the performance of the four methods for tracking anesthetic concentration. The influence of the number of scales on MSpEn was also investigated using a linear regression model. MSpEn correlated closely with anesthetic effect. The P k (0.83 ± 0.05, mean ± SD) and the coefficient of determination R (2) (0.87 ± 0.21) for the relationship between MSpEn and sevoflurane effect site concentration were highest for MSpEn (P k : RE = 0.73 ± 0.08, SE = 0.72 ± 0.07, ApEn = 0.81 ± 0.04; R (2): RE = 0.75 ± 0.08, SE = 0.64 ± 0.09, ApEn = 0.81 ± 0.10). Scales 1, 3 and 5 tended to make the greatest contribution to MSpEn. For this data set, the MSpEn is superior to the ApEn, the RE and the SE for tracking drug concentration change during sevoflurane anesthesia. It is suggested that the MSpEn may be further studied for application in clinical monitoring of DoA.
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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.