Comparison of bispectral index and entropy monitoring in patients undergoing internalisation of deep brain stimulators
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".