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Record W2228750271 · doi:10.4103/2348-0548.173244

Comparison of bispectral index and entropy monitoring in patients undergoing internalisation of deep brain stimulators

2016· article· en· W2228750271 on OpenAlexaff
Suparna Bharadwaj, Mahesh Nagappa, Audrey Tan, Jigesh Mehta, Pirjo Manninen, Lashmi Venkatraghavan

Bibliographic record

VenueJournal of Neuroanaesthesiology and Critical Care · 2016
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Sedative Agents
Canadian institutionsToronto Western HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineBispectral indexDeep brain stimulationAnesthesiaElectroencephalographyDystoniaParkinson's diseaseDiseasePropofolInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Abstract Introduction: Depth of anaesthesia (DOA) monitors are shown to reduce the intra-operative dose of anaesthetic agents, provide haemodynamic stability and shorten emergence times. Electroencephalography (EEG) based DOA monitors such as bispectral index (BIS) and entropy have been calibrated and validated in healthy subjects. Hence the clinical effectiveness of these monitors may be affected when monitoring patients with neurological disorders (e.g., epilepsy, dystonia, dementia and Parkinson’s disease). The aim of this study was to determine whether BIS and entropy correlate with each other and with clinical indices of DOA in patients with movement disorders under general anaesthesia (GA). Materials and Methods: We conducted a prospective, observational study in patients with movement disorders undergoing internalization of deep brain stimulators. All patients received standard GA with age-adjusted mean alveolar concentration (aaMAC) of an inhalational agent between 0.7 and 1.1. BIS and entropy sensors were applied on the patient’s left forehead. Data collected included clinical parameters and EEG-based DOA indices. Correlation analysis was performed between entropy, BIS and the clinical indices of DOA. Bland Altman analysis was performed to determine the agreement between BIS and entropy. Results: Thirty patients were studied (mean age was 58.4 ± 11 years, male: female 18:12 and weight 79.2 ± 17 kg). Indications for deep brain stimulation were Parkinson’s disease (n = 25), essential tremors (n = 2) and dystonia (n = 3). There was a very strong positive correlation between BIS and response entropy (RE) (r = 0.932) and BIS and state entropy (SE) (r = 0.950) and a strong negative correlation among aaMAC and BIS, RE and SE with r values of −0.686, −0.788 and −0.732, respectively. However, there was no correlation between BIS, RE, SE and haemodynamic values. Conclusion: Our study showed that BIS and entropy perform well in patients with movement disorders. There was a good correlation between the BIS and entropy devices. Haemodynamic parameters were not reliable indicators of DOA in these patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.207

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.337
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2016
Admission routes1
Has abstractyes

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