Figueroa, Susanne (2025). Quantitative Variables Derived from the Electroencephalographic Signal to Assess Depth of Anesthesia in Animals, a Narrative Review. (Thesis). Universität Bern, Bern
|
Text
25figueroa_s.pdf - Thesis Available under License Creative Commons: Attribution (CC-BY 4.0). Download (1MB) | Preview |
Abstract
Accurately assessing the depth of anaesthesia in animals remains a challenge, as traditional monitoring methods fail to capture subtle changes in brain activity. This review aimed to systematically map and critically evaluate the range of quantitative variables derived from electroencephalography (EEG) used to monitor sedation or anaesthesia in live animals, excluding laboratory rodents, over the past 35 years. Studies were identified through comprehensive searches in major biomedical databases (PubMed, Embase, CAB Abstract). To be included, studies had to report EEG use in relation to anaesthesia or sedation in living animals. A total of 169 studies were selected after screening and data extraction. Information was charted by animal species and reported EEG-derived variables. The most frequently reported variables were spectral edge frequencies, spectral power metrics, suppression ratio, and proprietary indices, such as the Bispectral Index. Methodological variability was high, and no consensus emerged on optimal EEG measures across species. While EEG-derived quantitative variables provide valuable insights, their interpretation remains highly context-dependent. Further research is necessary to refine these methods, explore variable combinations, and improve their clinical relevance in veterinary medicine.
| Item Type: | Thesis |
|---|---|
| Dissertation Type: | Single |
| Date of Defense: | 20 October 2025 |
| Subjects: | 500 Science > 590 Animals (Zoology) 600 Technology > 610 Medicine & health 600 Technology > 630 Agriculture |
| Institute / Center: | 05 Veterinary Medicine > Department of Clinical Veterinary Medicine (DKV) |
| Depositing User: | Hammer Igor |
| Date Deposited: | 23 Dec 2025 15:00 |
| Last Modified: | 23 Dec 2025 15:00 |
| URI: | https://boristheses.unibe.ch/id/eprint/7006 |
Actions (login required)
 |
View Item |