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The Value of the Aperiodic Exponent of the Intraoperative Electroencephalogram for Predicting Postoperative Delirium in Elderly Patients.

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Title: The Value of the Aperiodic Exponent of the Intraoperative Electroencephalogram for Predicting Postoperative Delirium in Elderly Patients.
Authors: Soehle M; From the Department of Anesthesiology and Intensive Care Medicine, University Hospital Bonn, Bonn, Germany., Menzenbach J, Riedel K, Coburn M, Thudium M
Source: Anesthesia and analgesia [Anesth Analg] 2026 Oct 01; Vol. 143 (4), pp. 849-857. Date of Electronic Publication: 2026 Mar 17.
Publication Type: Journal Article; Observational Study
Language: English
Journal Info: Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 1310650 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1526-7598 (Electronic) Linking ISSN: 00032999 NLM ISO Abbreviation: Anesth Analg Subsets: MEDLINE
Imprint Name(s): Publication: 1998- : Baltimore, Md. : Lippincott Williams & Wilkins
Original Publication: Cleveland, International Anesthesia Research Society.
MeSH Terms: Electroencephalography*/methods , Emergence Delirium*/diagnosis , Emergence Delirium*/physiopathology , Emergence Delirium*/psychology , Emergence Delirium*/etiology , Intraoperative Neurophysiological Monitoring*/methods , Delirium*/diagnosis , Delirium*/psychology , Monitoring, Intraoperative*/methods, Humans ; Female ; Prospective Studies ; Predictive Value of Tests ; Male ; Aged ; Risk Factors ; Middle Aged ; Age Factors ; Risk Assessment ; Consciousness Monitors ; Aged, 80 and over
Abstract: Background: Postoperative delirium (POD) is a frequent and serious complication after surgery. Parameters of the electroencephalogram (EEG), such as the Bispectral Index and the occurrence of burst suppression, have been associated with POD. We analyzed the predictive properties of periodic and aperiodic parameters of the EEG power spectrum.
Methods: In a secondary post-hoc analysis of a prospective observational study, patients with an age of at least 60 years undergoing major cardiac or non-cardiac surgery were analyzed. The frontal intraoperative raw EEG was recorded by a BIS monitor and offline analyzed with the FOOOF toolbox, revealing the periodic and aperiodic parameters of the power spectrum. Patients were screened for POD and divided in a 2:1 ratio into a training and a validation cohort. Predictors of POD were identified by uni- and multivariable logistic regression.
Results: Thirty-two out of the 120 training group patients developed POD. These showed a significantly longer median duration of surgery (286 [interquartile range {IQR} 236-391] vs 223 [127-331] min, P = .005), lower median BIS (40.4 [IQR 38.1-43.4] vs 42.7 [39.5-46.0], P = .038), and a higher mean aperiodic exponent (2.09 ± 0.19 vs 1.99 ± 0.17, P = .017). Duration of surgery (odds ratio [OR] = 1.01; 95% confidence interval [CI], 1.00-1.01, P = .005), peak center frequency (OR = 0.79; CI, 0.62-0.97, P = .039) and aperiodic exponent (OR = 23.2; CI, 2.1-318.2, P = .013) were predictors of POD according to univariable logistic regression. At a cutoff of 1.967, the aperiodic exponent had a sensitivity of 0.813 and a specificity of 0.478 for the prediction of POD. A low duration of time spent in burst suppression was observed in both patients with POD (67 [6-363] s) and without POD (173 [4-641] s, P = .30), and cumulative burst suppression time was not a predictor of POD. In a stepwise regression model, age, duration of surgery, peak power, and the aperiodic exponent were associated with POD (AUROC = 0.80 (CI, 0.71-0.89, P < .001). The predictive model was confirmed in the validation group (n = 60) with an AUROC = 0.77 (CI, 0.65-0.90, P = .001).
Conclusions: A higher aperiodic exponent, for example, a less complex EEG signal, is associated with a greater POD risk, especially in combination with known POD predictors such as age and duration of surgery.
(Copyright © 2026 The Author(s). Published by Wolters Kluwer Health, LLC. on behalf of the International Anesthesia Research Society.)
Competing Interests: Conflicts of Interest, Funding: Please see DISCLOSURES at the end of this article.
References: Mangusan RF, Hooper V, Denslow SA, Travis L. Outcomes associated with postoperative delirium after cardiac surgery. Am J Crit Care. 2015;24:156–163.
Menzenbach J, Kirfel A, Guttenthaler V, et al.; PROPDESC Collaboration Group. PRe-Operative Prediction of postoperative DElirium by appropriate SCreening (PROPDESC) development and validation of a pragmatic POD risk screening score based on routine preoperative data. J Clin Anesth. 2022;78:110684.
Shao YR, Kahali P, Houle TT, et al. Low frontal alpha power is associated with the propensity for burst suppression: an electroencephalogram phenotype for a “vulnerable brain.”. Anesth Analg. 2020;131:1529–1539.
Fritz BA, Kalarickal PL, Maybrier HR, et al. Intraoperative electroencephalogram suppression predicts postoperative delirium. Anesth Analg. 2016;122:234–242.
Soehle M, Dittmann A, Ellerkmann RK, Baumgarten G, Putensen C, Guenther U. Intraoperative burst suppression is associated with postoperative delirium following cardiac surgery: a prospective, observational study. BMC Anesthesiol. 2015;15:61.
Sumner M, Deng C, Evered L, et al. Processed electroencephalography-guided general anaesthesia to reduce postoperative delirium: a systematic review and meta-analysis. Br J Anaesth. 2023;130:e243–e253.
Aldecoa C, Bettelli G, Bilotta F, et al. Update of the European Society of Anaesthesiology and Intensive Care Medicine evidence-based and consensus-based guideline on postoperative delirium in adult patients. Eur J Anaesthesiol. 2024;41:81–108.
Donoghue T, Haller M, Peterson EJ, et al. Parameterizing neural power spectra into periodic and aperiodic components. Nat Neurosci. 2020;23:1655–1665.
Lendner JD, Harler U, Daume J, et al. Oscillatory and aperiodic neuronal activity in working memory following anesthesia. Clin Neurophysiol. 2023;150:79–88.
Leroy S, Major S, Bublitz V, Dreier JP, Koch S. Unveiling age-independent spectral markers of propofol-induced loss of consciousness by decomposing the electroencephalographic spectrum into its periodic and aperiodic components. Front Aging Neurosci. 2022;14:1076393.
Kreuzer M, Stern MA, Hight D, et al. Spectral and entropic features are altered by age in the electroencephalogram in patients under sevoflurane anesthesia. Anesthesiology. 2020;132:1003–1016.
Ostertag J, Engelhard A, Nuttall R, et al. Development of postanesthesia care unit delirium is associated with differences in aperiodic and periodic alpha parameters of the electroencephalogram during emergence from general anesthesia: results from a prospective observational cohort study. Anesthesiology. 2024;140:73–84.
Welch P. The use of fast fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms. IEEE Trans Audio Electroacoust. 1967;15:70–73.
Mapleson WW. Effect of age on MAC in humans: a meta-analysis. Br J Anaesth. 1996;76:179–185.
Hastie T, Tibshirani R, Friedman J. Model assessment and selection. In The Elements of Statistical Learning: Data Mining, Inference, and Prediction. 2nd ed. Springer, 2017.
Pollak M, Leroy S, Rohr V, Brown EN, Spies C, Koch S. Electroencephalogram biomarkers from anesthesia induction to identify vulnerable patients at risk for postoperative delirium. Anesthesiology. 2024;140:979–989.
Colombo MA, Napolitani M, Boly M, et al. The spectral exponent of the resting EEG indexes the presence of consciousness during unresponsiveness induced by propofol, xenon, and ketamine. Neuroimage. 2019;189:631–644.
Goldberger AL. Fractal variability versus pathologic periodicity: complexity loss and stereotypy in disease. Perspect Biol Med. 1997;40:543–561.
Soehle M, Czosnyka M, Chatfield DA, Hoeft A, Pena A. Variability and fractal analysis of middle cerebral artery blood flow velocity and arterial blood pressure in subarachnoid hemorrhage. J Cereb Blood Flow Metab. 2008;28:64–73.
Gao R, Peterson EJ, Voytek B. Inferring synaptic excitation/inhibition balance from field potentials. Neuroimage. 2017;158:70–78.
Salvatore SV, Lambert PM, Benz A, et al. Periodic and aperiodic changes to cortical EEG in response to pharmacological manipulation. J Neurophysiol. 2024;131:529–540.
Koch S, Windmann V, Chakravarty S, et al.; BioCog Study Group. Perioperative electroencephalogram spectral dynamics related to postoperative delirium in older patients. Anesth Analg. 2021;133:1598–1607.
Itting PT, Sadlonova M, Santander MJ, et al.; and FINDERI Investigators. Intra- and early postoperative predictors of delirium risk in cardiac surgery: results from the prospective observational FINDERI study. Int J Surg. 2025;111:2872–2885.
Muller J, Nowak S, Weidemeier M, et al. Duration of surgery and intraoperative blood pressure management are modifiable risk factors for postoperative neurocognitive disorders after spine surgery: results of the prospective CONFESS study. Spine. 2023;48:1127–1137.
Ravi B, Pincus D, Choi S, Jenkinson R, Wasserstein DN, Redelmeier DA. Association of duration of surgery with postoperative delirium among patients receiving hip fracture repair. JAMA Netw Open. 2019;2:e190111.
Luo YG, Wu XD, Song YX, et al. Development and validation of a nomogram to predict postoperative delirium in older patients after major abdominal surgery: a retrospective case-control study. Perioper Med (Lond). 2024;13:41.
Aldecoa C, Bettelli G, Bilotta F, et al. European Society of Anaesthesiology evidence-based and consensus-based guideline on postoperative delirium. Eur J Anaesthesiol. 2017;34:192–214.
Evered LA, Chan MTV, Han R, et al. Anaesthetic depth and delirium after major surgery: a randomised clinical trial. Br J Anaesth. 2021;127:704–712.
Koch S, Blankertz B, Windmann V, Spies C, Radtke FM, Röhr V. Desflurane is risk factor for postoperative delirium in older patients’ independent from intraoperative burst suppression duration. Front Aging Neurosci. 2023;15:1067268.
Guay CS, Kafashan M, Huels ER, et al. Postoperative delirium severity and recovery correlate with electroencephalogram spectral features. Anesth Analg. 2023;136:140–151.
Hight D, Ehrhardt A, Lersch F, Luedi MM, Stüber F, Kaiser HA. Lower alpha frequency of intraoperative frontal EEG is associated with postoperative delirium: A secondary propensity-matched analysis. J Clin Anesth. 2024;93:111343.
Numan T, van den Boogaard M, Kamper AM, Rood PJT, Peelen LM, Slooter AJC; Dutch Delirium Detection Study Group. Delirium detection using relative delta power based on 1-minute single-channel EEG: a multicentre study. Br J Anaesth. 2019;122:60–68.
Kochs E. Electrophysiological monitoring and mild hypothermia. J Neurosurg Anesthesiol. 1995;7:222–228.
Entry Date(s): Date Created: 20260317 Date Completed: 20260915 Latest Revision: 20260922
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PubMed Central ID: PMC13541604
DOI: 10.1213/ANE.0000000000008013
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  Label: Abstract
  Group: Ab
  Data: Background: Postoperative delirium (POD) is a frequent and serious complication after surgery. Parameters of the electroencephalogram (EEG), such as the Bispectral Index and the occurrence of burst suppression, have been associated with POD. We analyzed the predictive properties of periodic and aperiodic parameters of the EEG power spectrum.&lt;br /&gt;Methods: In a secondary post-hoc analysis of a prospective observational study, patients with an age of at least 60 years undergoing major cardiac or non-cardiac surgery were analyzed. The frontal intraoperative raw EEG was recorded by a BIS monitor and offline analyzed with the FOOOF toolbox, revealing the periodic and aperiodic parameters of the power spectrum. Patients were screened for POD and divided in a 2:1 ratio into a training and a validation cohort. Predictors of POD were identified by uni- and multivariable logistic regression.&lt;br /&gt;Results: Thirty-two out of the 120 training group patients developed POD. These showed a significantly longer median duration of surgery (286 [interquartile range {IQR} 236-391] vs 223 [127-331] min, P = .005), lower median BIS (40.4 [IQR 38.1-43.4] vs 42.7 [39.5-46.0], P = .038), and a higher mean aperiodic exponent (2.09 &#177; 0.19 vs 1.99 &#177; 0.17, P = .017). Duration of surgery (odds ratio [OR] = 1.01; 95% confidence interval [CI], 1.00-1.01, P = .005), peak center frequency (OR = 0.79; CI, 0.62-0.97, P = .039) and aperiodic exponent (OR = 23.2; CI, 2.1-318.2, P = .013) were predictors of POD according to univariable logistic regression. At a cutoff of 1.967, the aperiodic exponent had a sensitivity of 0.813 and a specificity of 0.478 for the prediction of POD. A low duration of time spent in burst suppression was observed in both patients with POD (67 [6-363] s) and without POD (173 [4-641] s, P = .30), and cumulative burst suppression time was not a predictor of POD. In a stepwise regression model, age, duration of surgery, peak power, and the aperiodic exponent were associated with POD (AUROC = 0.80 (CI, 0.71-0.89, P &amp;lt; .001). The predictive model was confirmed in the validation group (n = 60) with an AUROC = 0.77 (CI, 0.65-0.90, P = .001).&lt;br /&gt;Conclusions: A higher aperiodic exponent, for example, a less complex EEG signal, is associated with a greater POD risk, especially in combination with known POD predictors such as age and duration of surgery.&lt;br /&gt; (Copyright &#169; 2026 The Author(s). Published by Wolters Kluwer Health, LLC. on behalf of the International Anesthesia Research Society.)
– Name: Abstract
  Label: Competing Interests
  Group: Ab
  Data: Conflicts of Interest, Funding: Please see DISCLOSURES at the end of this article.
– Name: Ref
  Label: References
  Group: RefInfo
  Data: Mangusan RF, Hooper V, Denslow SA, Travis L. Outcomes associated with postoperative delirium after cardiac surgery. Am J Crit Care. 2015;24:156–163.&lt;br /&gt;Menzenbach J, Kirfel A, Guttenthaler V, et al.; PROPDESC Collaboration Group. PRe-Operative Prediction of postoperative DElirium by appropriate SCreening (PROPDESC) development and validation of a pragmatic POD risk screening score based on routine preoperative data. J Clin Anesth. 2022;78:110684.&lt;br /&gt;Shao YR, Kahali P, Houle TT, et al. Low frontal alpha power is associated with the propensity for burst suppression: an electroencephalogram phenotype for a “vulnerable brain.”. Anesth Analg. 2020;131:1529–1539.&lt;br /&gt;Fritz BA, Kalarickal PL, Maybrier HR, et al. Intraoperative electroencephalogram suppression predicts postoperative delirium. Anesth Analg. 2016;122:234–242.&lt;br /&gt;Soehle M, Dittmann A, Ellerkmann RK, Baumgarten G, Putensen C, Guenther U. Intraoperative burst suppression is associated with postoperative delirium following cardiac surgery: a prospective, observational study. BMC Anesthesiol. 2015;15:61.&lt;br /&gt;Sumner M, Deng C, Evered L, et al. Processed electroencephalography-guided general anaesthesia to reduce postoperative delirium: a systematic review and meta-analysis. Br J Anaesth. 2023;130:e243–e253.&lt;br /&gt;Aldecoa C, Bettelli G, Bilotta F, et al. Update of the European Society of Anaesthesiology and Intensive Care Medicine evidence-based and consensus-based guideline on postoperative delirium in adult patients. Eur J Anaesthesiol. 2024;41:81–108.&lt;br /&gt;Donoghue T, Haller M, Peterson EJ, et al. Parameterizing neural power spectra into periodic and aperiodic components. Nat Neurosci. 2020;23:1655–1665.&lt;br /&gt;Lendner JD, Harler U, Daume J, et al. Oscillatory and aperiodic neuronal activity in working memory following anesthesia. Clin Neurophysiol. 2023;150:79–88.&lt;br /&gt;Leroy S, Major S, Bublitz V, Dreier JP, Koch S. Unveiling age-independent spectral markers of propofol-induced loss of consciousness by decomposing the electroencephalographic spectrum into its periodic and aperiodic components. Front Aging Neurosci. 2022;14:1076393.&lt;br /&gt;Kreuzer M, Stern MA, Hight D, et al. Spectral and entropic features are altered by age in the electroencephalogram in patients under sevoflurane anesthesia. Anesthesiology. 2020;132:1003–1016.&lt;br /&gt;Ostertag J, Engelhard A, Nuttall R, et al. Development of postanesthesia care unit delirium is associated with differences in aperiodic and periodic alpha parameters of the electroencephalogram during emergence from general anesthesia: results from a prospective observational cohort study. Anesthesiology. 2024;140:73–84.&lt;br /&gt;Welch P. The use of fast fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms. IEEE Trans Audio Electroacoust. 1967;15:70–73.&lt;br /&gt;Mapleson WW. Effect of age on MAC in humans: a meta-analysis. Br J Anaesth. 1996;76:179–185.&lt;br /&gt;Hastie T, Tibshirani R, Friedman J. Model assessment and selection. In The Elements of Statistical Learning: Data Mining, Inference, and Prediction. 2nd ed. Springer, 2017.&lt;br /&gt;Pollak M, Leroy S, Rohr V, Brown EN, Spies C, Koch S. Electroencephalogram biomarkers from anesthesia induction to identify vulnerable patients at risk for postoperative delirium. Anesthesiology. 2024;140:979–989.&lt;br /&gt;Colombo MA, Napolitani M, Boly M, et al. The spectral exponent of the resting EEG indexes the presence of consciousness during unresponsiveness induced by propofol, xenon, and ketamine. Neuroimage. 2019;189:631–644.&lt;br /&gt;Goldberger AL. Fractal variability versus pathologic periodicity: complexity loss and stereotypy in disease. Perspect Biol Med. 1997;40:543–561.&lt;br /&gt;Soehle M, Czosnyka M, Chatfield DA, Hoeft A, Pena A. Variability and fractal analysis of middle cerebral artery blood flow velocity and arterial blood pressure in subarachnoid hemorrhage. J Cereb Blood Flow Metab. 2008;28:64–73.&lt;br /&gt;Gao R, Peterson EJ, Voytek B. Inferring synaptic excitation/inhibition balance from field potentials. Neuroimage. 2017;158:70–78.&lt;br /&gt;Salvatore SV, Lambert PM, Benz A, et al. Periodic and aperiodic changes to cortical EEG in response to pharmacological manipulation. J Neurophysiol. 2024;131:529–540.&lt;br /&gt;Koch S, Windmann V, Chakravarty S, et al.; BioCog Study Group. Perioperative electroencephalogram spectral dynamics related to postoperative delirium in older patients. Anesth Analg. 2021;133:1598–1607.&lt;br /&gt;Itting PT, Sadlonova M, Santander MJ, et al.; and FINDERI Investigators. Intra- and early postoperative predictors of delirium risk in cardiac surgery: results from the prospective observational FINDERI study. Int J Surg. 2025;111:2872–2885.&lt;br /&gt;Muller J, Nowak S, Weidemeier M, et al. Duration of surgery and intraoperative blood pressure management are modifiable risk factors for postoperative neurocognitive disorders after spine surgery: results of the prospective CONFESS study. Spine. 2023;48:1127–1137.&lt;br /&gt;Ravi B, Pincus D, Choi S, Jenkinson R, Wasserstein DN, Redelmeier DA. Association of duration of surgery with postoperative delirium among patients receiving hip fracture repair. JAMA Netw Open. 2019;2:e190111.&lt;br /&gt;Luo YG, Wu XD, Song YX, et al. Development and validation of a nomogram to predict postoperative delirium in older patients after major abdominal surgery: a retrospective case-control study. Perioper Med (Lond). 2024;13:41.&lt;br /&gt;Aldecoa C, Bettelli G, Bilotta F, et al. 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        Value: 10.1213/ANE.0000000000008013
    Languages:
      – Code: eng
        Text: English
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        StartPage: 849
    Subjects:
      – SubjectFull: Humans
        Type: general
      – SubjectFull: Female
        Type: general
      – SubjectFull: Prospective Studies
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      – SubjectFull: Predictive Value of Tests
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      – SubjectFull: Male
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      – SubjectFull: Aged
        Type: general
      – SubjectFull: Risk Factors
        Type: general
      – SubjectFull: Middle Aged
        Type: general
      – SubjectFull: Age Factors
        Type: general
      – SubjectFull: Risk Assessment
        Type: general
      – SubjectFull: Consciousness Monitors
        Type: general
      – SubjectFull: Aged, 80 and over
        Type: general
      – SubjectFull: Electroencephalography methods
        Type: general
      – SubjectFull: Emergence Delirium diagnosis
        Type: general
      – SubjectFull: Emergence Delirium physiopathology
        Type: general
      – SubjectFull: Emergence Delirium psychology
        Type: general
      – SubjectFull: Emergence Delirium etiology
        Type: general
      – SubjectFull: Intraoperative Neurophysiological Monitoring methods
        Type: general
      – SubjectFull: Delirium diagnosis
        Type: general
      – SubjectFull: Delirium psychology
        Type: general
      – SubjectFull: Monitoring, Intraoperative methods
        Type: general
    Titles:
      – TitleFull: The Value of the Aperiodic Exponent of the Intraoperative Electroencephalogram for Predicting Postoperative Delirium in Elderly Patients.
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            – D: 01
              M: 10
              Text: 2026 Oct 01
              Type: published
              Y: 2026
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              Value: 4
          Titles:
            – TitleFull: Anesthesia and analgesia
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