Background: Patients with low cognitive performance are thought to have a higher risk of postoperative neurocognitive disorders. Here we analyzed the relationship between preoperative cognition and anesthesia-induced brain dynamics. We hypothesized that patients with low cognitive performance would be more sensitive to anesthetics and would show differences in electroencephalogram (EEG) activity consistent with a brain anesthesia overdose.

Methods: This is a retrospective analysis from a previously reported observational study. We evaluated cognitive performance using the Montreal cognitive assessment (MoCA) test. All patients received general anesthesia maintained with sevoflurane or desflurane during elective major abdominal surgery. We analyzed the EEG using spectral, coherence, and phase-amplitude modulation analyses.

Results: Patients were separated into a low MoCA group (<26 points, n = 12) and a high MoCA group (n = 23). There were no differences in baseline EEG, nor end-tidal age-corrected minimum alveolar concentration (MACage). However, under anesthesia, the low MoCA group had lower α-β power (high MoCA: 2.9 [interquartile range {IQR}: 0.6-5.8 dB] versus low MoCA: -1.2 [IQR: -2.1 to 0.6 dB], difference 4.1 [1.0-5.7]) and a lower α peak frequency (high MoCA: 9.0 [IQR: 8.3-9.8 Hz] versus low MoCA: 7.5 [IQR: 6.3-9.0 Hz], difference 1.5 [0-2.3]) compared to the high MoCA group. The low MoCA group also had a lower α band coherence and a stronger peak-max phase-amplitude coupling (PAC). Finally, patients in the low MoCA group had longer emergence times (high MoCA 663 ± 345 seconds versus low MoCA: 960 ± 352 seconds, difference 297 [15-578]). Multiple linear regression shows up that both age and MoCA scores are independently associated with intraoperative α-β power.

Conclusions: All these EEG features, together with a prolonged emergence time, are consistent with the possibility that older patients with low cognitive performance are receiving a brain anesthesia overdose compare to cognitive normal patients.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11363876PMC
http://dx.doi.org/10.1213/ANE.0000000000005262DOI Listing

Publication Analysis

Top Keywords

cognitive performance
12
preoperative cognition
8
patients low
8
low cognitive
8
patients
5
association lower
4
lower preoperative
4
cognition intraoperative
4
intraoperative electroencephalographic
4
electroencephalographic features
4

Similar Publications

Effects of the Oral Health Promotion Program on oral health and oral microbiota changes in diabetic elderly individuals: a quasi-experimental study.

BMC Oral Health

January 2025

Innovation Center of Nursing Research, Nursing Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, No.37, Guoxue Lane, Wuhou District, Chengdu, China.

Background: Diabetes with its highly prevalence has become a major contributor to the burden of health care costs worldwide. Recent unequivocal evidence has revealed a bidirectional link between oral health and diabetes. In this study, the effects of the Oral Health Promotion Program (OHPP) on oral hygiene, oral health-related quality of life and glycated haemoglobin (HbA1c) levels in diabetic elderly were examined.

View Article and Find Full Text PDF

Background: Mental disorders are increasingly prevalent, leading to increased medical expenditures. To refine the reimbursement of medical costs for inpatients with mental disorders by health insurance, an accurate prediction model is essential. Per-diem payment is a common internationally implemented payment method for medical insurance of inpatients with mental disorders, necessitating the exploration of advanced machine learning methods for predicting the average daily hospitalization costs (ADHC) based on the characteristics of inpatients with mental disorders.

View Article and Find Full Text PDF

Inter-individual variability in symptoms and the dynamic nature of brain pathophysiology present significant challenges in constructing a robust diagnostic model for migraine. In this study, we aimed to integrate different types of magnetic resonance imaging (MRI), providing structural and functional information, and develop a robust machine learning model that classifies migraine patients from healthy controls by testing multiple combinations of hyperparameters to ensure stability across different migraine phases and longitudinally repeated data. Specifically, we constructed a diagnostic model to classify patients with episodic migraine from healthy controls, and validated its performance across ictal and interictal phases, as well as in a longitudinal setting.

View Article and Find Full Text PDF

The added value of anosmic subtype on motor subtype in Parkinson's disease: a pilot study.

Sci Rep

January 2025

Department of Neurology, Neurological Institute, Taichung Veterans General Hospital, No. 1650, Taiwan Boulevard, Section 4, Taichung, 40705, Taiwan.

This study investigates whether incorporating olfactory dysfunction into motor subtypes of Parkinson's disease (PD) improves associations with clinical outcomes. PD is commonly divided into motor subtypes, such as postural instability and gait disturbance (PIGD) and tremor-dominant PD (TDPD), but non-motor symptoms like olfactory dysfunction remain underexplored. We assessed 157 participants with PD using the University of Pennsylvania Smell Identification Test (UPSIT), Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (M-UPDRS), Montreal Cognitive Assessment (MoCA), 39-item Parkinson's Disease Questionnaire Summary Index (PDQ-39 SI), and 99mTc-TRODAT-1 imaging.

View Article and Find Full Text PDF

Multivariate patterns among multimodal neuroimaging and clinical, cognitive, and daily functioning characteristics in bipolar disorder.

Neuropsychopharmacology

January 2025

Neurocognition and Emotion in Affective Disorders (NEAD) Centre, Psychiatric Centre Copenhagen, Mental Health Services, Capital Region of Denmark, Frederiksberg, Denmark.

Individuals with bipolar disorder (BD) show heterogeneity in clinical, cognitive, and daily functioning characteristics, which challenges accurate diagnostics and optimal treatment. A key goal is to identify brain-based biomarkers that inform patient stratification and serve as treatment targets. The objective of the present study was to apply a data-driven, multivariate approach to quantify the relationship between multimodal imaging features and behavioral phenotypes in BD.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!