Investigation of optical neuro-monitoring technique for detection of maintenance and emergence states during general anesthesia.
The American Society of Anesthesiologist recommends peripheral physiological monitoring during general anesthesia, which offers no information regarding the effects of anesthetics on the brain. Since no "gold standard" method exists for this evaluation, such a technique is needed to ensure patient c...
| Publicado en: | Journal of Clinical Monitoring & Computing Vol. 32; no. 1; pp. 147 - 164 |
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| Autores principales: | , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Feb2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=127064710&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 127064710 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13871307 OHC jtl: Journal of Clinical Monitoring & Computing issn: 13871307 maglogo: N pubinfo: dt: Feb2018 vid: 32 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 127064710 127064710 144007827 NLM28214930 10.1007/s10877-017-9998-x NLM28214930 127064710 ppf: 147 ppct: 17 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Investigation of optical neuro-monitoring technique for detection of maintenance and emergence states during general anesthesia. aug: au: Hernandez-Meza, Gabriela Izzetoglu, Meltem Osbakken, Mary Green, Michael Abubakar, Hawa Izzetoglu, Kurtulus affil: School of Biomedical Engineering, Science and Health Systems, Drexel University, 3508 Market St, Suite 100, 19104, Philadelphia, PA, USA sug: subj: Brain Physiopathology Spectroscopy, Near-Infrared Methods Anesthesia, General Cerebrovascular Circulation Physiology Young Adult Female Heart Rate Algorithms Hemoglobins Anesthesia Methods Adult Intraoperative Monitoring Middle Age Medical Organizations Frontal Lobe Drug Effects Reproducibility of Results Oxygen Metabolism Time Factors Hemodynamics Male Clinical Assessment Tools Ferrans and Powers Quality of Life Index Questionnaires Adult: 19-44 years Middle Aged: 45-64 years Female Male ab: The American Society of Anesthesiologist recommends peripheral physiological monitoring during general anesthesia, which offers no information regarding the effects of anesthetics on the brain. Since no "gold standard" method exists for this evaluation, such a technique is needed to ensure patient comfort, procedure quality and safety. In this study we investigated functional near infrared spectroscopy (fNIRS) as possible monitor of anesthetic effects on the prefrontal cortex. Anesthetic drugs, such as sevoflurane, suppress the cerebral metabolism and alter the cerebral blood flow. We hypothesize that fNIRS derived features carry information on the effects of anesthetics on the prefrontal cortex (PFC) that can be used for the classification of the anesthetized state. In this study, patients were continuously monitored using fNIRS, BIS and standard monitoring during surgical procedures under sevoflurane general anesthesia. Maintenance and emergence states were identified and fNIRS features were identified and compared between states. Linear and non-linear machine learning algorithms were investigated as methods for the classification of maintenance/emergence. The results show that changes in oxygenated (HbO2) and deoxygenated hemoglobin (HHb) concentration and blood volume measured by fNIRS were associated with the transition between maintenance and emergence that occurs as a result of sevoflurane washout. We observed that during maintenance the signal is relatively more stable than during emergence. Maintenance and emergence states were classified with 94.7% accuracy with a non-linear model using the locally derived mean total hemoglobin, standard deviation of HbO2, minimum and range of HbO2 and HHb as features. These features were found to be correlated with the effects of sevoflurane and to carry information that allows real time and automatic classification of the anesthetized state with high accuracy. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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