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Can We Really Associate Alpha Power with Mortality?

Recently, I read an interesting article:

Mather et al. «Intraoperative Frontal Electroencephalogram Alpha Power Is Associated with Postoperative Mortality and Other Adverse Outcomes.» Anesthesiology 2025; 142:500–10.

The study suggests that lower intraoperative alpha power in the EEG is independently associated with increased postoperative mortality. While this is an intriguing hypothesis, I believe we must be cautious with these conclusions.


Critical Points to Consider

1. Lack of Information on Consciousness State Titration

The study reports anaesthetic doses, including

  • Propofol median total dose: 200 mg (IQR 150-260 mg)
  • Sevoflurane mean end-tidal concentration: 1.00% (IQR 0.00-1.39%)
  • Nitrous oxide use: 60.3% of patients (a lot)
  • Propofol mean total dose: 200 mg (IQR 150-260 mg)
  • Sevoflurane mean end-tidal concentration: 1.00% (IQR 0.00-1.39%)
  • Use of nitrous oxide: 60.3% of patients.

    However, it is not specified how the anaesthesia was titrated for each patient.
  • No mention of burst suppression, a key indicator of excessive anaesthetic titration.
  • No BIS, Entropy, Narcotrend, Conox monitoring, making it impossible to compare alpha power with other validated EEG monitoring data.
  • No analysis of mean arterial pressure (MAP), so we cannot rule out cerebral hypoperfusion as a cause of reduced alpha power.

Without data on titration strategies, we cannot determine whether lower alpha power reflects patient frailty or simply excessive anesthesia administration.


2. Retrospective Study Design and Selection Bias

  • This was a retrospective observational study, meaning it cannot establish causality, only statistical associations.
  • Only patients with artifact-free EEG recordings were included, introducing selection bias.
  • Other critical confounders (e.g., opioid use, neuromuscular blockade, ventilatory parameters) were not considered.

A prospective study is needed to validate these findings before drawing clinical conclusions.


3. Failure to Differentiate Between Patient Frailty and Over-Titration of Anesthesia

Low intraoperative alpha power could result from:
1. Pre-existing neurological frailty ? reduced cortical connectivity and baseline EEG activity.
2. Inadequate titration of consciousness state ? deeper hypnotic states leading to EEG suppression.
3. Cerebral hypoperfusion ? low MAP causing decreased cortical activity.

The study does not provide enough data to distinguish between these scenarios.


4 Unusual Anesthetic Practice: Predominance of Volatile Agents & Nitrous Oxide

One striking aspect of this study is the low use of total intravenous anesthesia (TIVA) and the high prevalence of volatile agents and nitrous oxide:

  • 98.9% of patients received propofol, but only as an induction agent.
  • 72.1% received sevoflurane as the primary anesthetic.
  • 60.3% received nitrous oxide, a practice that has largely declined in LATAM and Europe due to concerns about environmental impact and neurotoxicity.

The study did not investigate whether the choice of anaesthesia influenced the EEG findings, and it could be questioned whether the findings would be the same in a cohort with predominantly intravenous anaesthesia.


5 No Comparison with Established Risk Prediction Models

  • Several validated models predict postoperative mortality (ASA, POSSUM, ACS-NSQIP).
  • This study does not compare alpha power with these models, making it unclear whether it adds predictive value.


Final Thoughts

At this stage, it is premature to consider intraoperative alpha power as an independent biomarker for mortality.
More rigorous, prospective studies are needed, incorporating Raw EEG/DSA, MAP, burst suppression analysis, and direct comparisons with existing risk models.

Additionally, the high use of volatile agents and nitrous oxide raises the question of whether these findings would hold true in a TIVA-based anesthesia protocol.

What are your thoughts on this? Have you encountered similar discussions in your practice?

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? EEG Interpretation in Anesthesia: A Key to Personalized Anesthesia

In modern anesthesia practice, electroencephalogram (EEG) interpretation has become an essential tool for achieving personalized anesthesia and improving patient safety. While automated indices derived from EEG provide a simplified measure of anesthetic depth, understanding raw EEG signals and spectral density allows for a more precise and individualized approach.

Why Is Learning EEG Interpretation Essential for Personalized Anesthesia?

1?? Optimized Drug Dosing for Each Patient

  • EEG interpretation helps to adjust the anaesthetic to each patient’s needs, reducing the risk of under-dosing, which can lead to patient movement or inadequate anaesthesia, and over-sedation, which can delay recovery and increase complications.

2?? Preventing Postoperative Delirium and Cognitive Dysfunction

  • Over-sedation, particularly in older adults, is strongly associated with postoperative delirium and long-term cognitive impairment.
  • EEG-guided anaesthetic titration helps prevent brain suppression (e.g. burst suppression patterns), reducing the risk of delirium and prolonging neurocognitive recovery..

3?? Understanding the Effect of GABAergic Drugs on Thalamocortical Circuits

  • Most general anaesthetics enhance GABAergic inhibition, which suppresses thalamocortical circuits and produces characteristic EEG changes.
  • Moderate doses of anaesthetic often induce frontal alpha oscillations (8-12 Hz) reflecting synchronised inhibition of corticothalamic loops. This pattern is associated with stable unconsciousness.
  • Deeper anaesthesia, particularly with excessive GABAergic activity, leads to high amplitude slow delta waves (0.5-4 Hz) and burst suppression, indicating profound cortical suppression and a greater risk of neurotoxicity and postoperative delirium.
  • Understanding these variations in thalamocortical dynamics allows anaesthetists to assess whether a patient is adequately anaesthetised or receiving excessive suppression, which could affect postoperative recovery.

 4?? Beyond Numerical Indices: A Deeper Understanding of EEG Data

  • EEG-derived indices provide a numerical estimation of anesthetic depth, but their reliability varies based on factors such as age, medication type, and patient physiology.
  • Complementing these indices with direct EEG interpretation enhances clinical decision-making, particularly in complex cases.
  • Additional parameters, such as the Burst Suppression Index (BSI) and Alpha/Delta Ratio, can offer deeper insights into brain activity and help refine anesthetic management.

5?? Personalized Anesthesia Through Neurophysiological Monitoring

  • Each patient’s brain reacts uniquely to anesthesia. Real-time EEG monitoring allows for dynamic adjustments, reducing risks such as neurotoxicity in elderly patientspostoperative delirium, or insufficient sedation in younger populations.

The Future of EEG-Guided Personalized Anesthesia

Advancements in neuroscience and EEG technology are transforming anesthesia into a more precise and individualized practiceLearning to interpret EEG signals in real-time empowers anesthesiologists to fine-tune drug administration, optimize patient outcomes, and enhance overall surgical safety.

Are you integrating EEG interpretation into your anesthesia practice? Let’s discuss how real-time brain monitoring is shaping the future of personalized anesthesia.

Would you like to learn more about EEG in anesthesia? Share your thoughts and experiences in the comments! Let’s keep learning together.

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The alpha band power.

In previous posts, we discussed the synergy between propofol, remifentanil, and dexmedetomidine, and the impact of dexmedetomidine on alpha band power over time. The tendency that I have observed in my patients is a progressive decrease in alpha band power, which is more accentuated in fragile brains.
The big question remains as to why this happening?
Is this an indirect effect of dexmedetomidine on oscillatory states? or
This means that when the Cp of propofol decreases due to the synergistic effect of dexmedetomidine, the activation of GABAergic neurons in the anterior thalamic reticular nucleus promotes arousal from propofol.
Recently I read an article related to the topic, where they compared the perioperative EEG signatures, drug-induced changes, and neurocognitive outcomes between two anesthetic regimens in geriatric patients (Propofol-Remifentanil vs Propofol-Remifentanil-Dexmedetomidine), and at the end, they proposed the following question: “alpha band power per se is a valid predictor of frailty or is that only in the case of GABAergic anesthetics1.”
Two days ago, I had two 48-year-old patients. The first one was a female ASA I patient, under general anesthesia with Propofol-Remifentanil and Dexmedetomidine (0.2 mcg/kg/hour), with a typical DSA signature of propofol (“rail pattern”), adequate alpha power.
The second, female ASA II patient with history of breast cancer, autoimmune hypothyroidism being treated with tamoxifen and euthirox, ex-smoker, under general anesthesia with Propofol-Remifentanil and Dexmedetomidine (0.2 mcg/kg/hour), with a DSA typical of a fragil brain. After the first hour of anesthesia, the alpha band power decreased even more, with doses of propofol (5.5 mg/kg/hour and remifentanil (0.18 mcg/kg/hour). I decided to perform a 30 mg bolus of propofol at 12:35 (see DSA case 2), and a few seconds later, I recovered the alpha power that I had after LOC. The patient had adequate NMB, adequate analgesia, SEF trend towards 20 Hz, and after the bolus, it decreased to 16 Hz.
Although there is much left to know, I am still thinking that the most important thing is to titrate appropriately and not lose the power of alpha.
I have attached the DSAs processed with Python and the DSAs downloaded from the BIS monitor.
Reference
1.Mehler DM, Kreuzer M, Obert DP, Cardenas LF, Barra I, Zurita F, Lobo FA, Kratzer S, Schneider G, Sepúlveda PO. Electroencephalographic guided propofol-remifentanil TCI anesthesia with and without dexmedetomidine in a geriatric population: electroencephalographic signatures and clinical evaluation. J Clin Monit Comput. 2024 Mar 7. doi: 10.1007/s10877-024-01127-4. Epub ahead of print. PMID: 38451341.

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Me considero pro TIVA, sin embargo luego de leer este paper pienso que faltan datos para llegar a esta conclusión.

Por ejemplo:
«Hypnotic depth was targeted to a bispectral index (BIS) of 40-60, or to clinical judgement when BIS monitoring was unavailable». Me gustaría saber ¿en cuantos casos no se uso BIS? ¿Usaron matriz de densidad espectral (DSA/SEF/MF? No veo correlación entre Burst suppression e incidencia de Delirium. Sabemos que no debemos desestimar los indices derivados del EEG, pero no son suficientes para titular adecuadamente la hipnosis, y también sabemos que muchos estudios han demostrado que a mayor Burst suppression mayor incidencia de delirium.
Con respecto al propofol, ¿que modelo TCI usaron?, sabemos que los modelos no son perfectos y fueron diseñados para una población particular, las diferencias las encontraremos en la inducción, pero las fases de mantenimiento se parecen. ¿Cuanta masa de droga dieron en la inducción? ¿como ocurrió la desconexión de los circuitos corticales y cortico-talámicos?
No usaron dexmedetomidine ni bloqueos neuroaxiales/AR, sabemos que la combinacion TIVA y Regional es ideal en este tipo de pacientes ya que el dolor es uno de los desencadenantes de delirium, fué suficiente la analgesia?
Sigo creyendo que podemos hacer bien ambas técnicas, TIVA o Inhalatoria, tomando en cuenta todas las variables necesarias y aprendiendo a usar los monitores adecuadamente.

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