A novel index for trending sepsis and inflammatory response using processed EEG and Heart Rate Variability

Early detection of systemic inflammation and sepsis is essential for improving patient outcomes. Heart rate variability (HRV) has been proposed as a non-invasive marker of inflammation; however, its specificity is limited, particularly under anesthesia or sedation. This study introduces the Trend of Sepsis and Inflammation (TSI), a novel index combining HRV and electroencephalogram (EEG)-derived parameters to better isolate inflammation-related autonomic changes.A post-hoc observational analysis was conducted in two cohorts: surgical patients undergoing general anesthesia (N = 41) and septic patients admitted to the intensive care unit (N = 21). Continuous EEG and ECG recordings were obtained using a multimodal monitoring system. HRV parameters from time and frequency domains, together with an EEG-derived Brain Activity Index, were integrated using an Adaptive Neuro-Fuzzy Inference System (ANFIS) to compute the TSI. TSI values were compared across three conditions: awake baseline, post-surgical inflammation, and sepsis. Statistical analysis employed non-parametric tests, while discriminative performance was assessed using prediction probability (Pk) and concordance with predefined interpretation ranges.TSI values increased progressively across conditions. Median values were 2.29 (IQR: 0.00-13.74) at baseline, 24.68 (18.50-32.00) post-surgery, and 65.59 (52.38-76.25) in sepsis, with significant differences (p < 0.0001). The TSI demonstrated strong discriminative ability (Pk = 93.58%) and high overall concordance (92.6%). HRV spectrograms and EEG-compensated analyses supported physiological consistency.The TSI distinguishes between baseline, post-surgical inflammatory, and septic states. By compensating for anesthesia-related autonomic suppression, it provides a continuous, non-invasive measure of inflammatory burden, supporting its potential use in perioperative and critical care settings. Further validation against established biomarkers is warranted.

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Journal
Journal of Clinical Monitoring and Computing
Published
2026-07-24
DOI
https://doi.org/10.1007/s10877-026-01472-6
Primary Topic
Heart Rate Variability and Autonomic Control
Type
article
Field-Weighted Citation Impact
0.00

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article

A novel index for trending sepsis and inflammatory response using processed EEG and Heart Rate Variability

Montserrat Vallverdú-Ferrer, Jaume Millán i Ichon, Michel Struys, Gertrude J. Nieuwenhuijs‐Moeke et al.
Journal of Clinical Monitoring and Computing
Heart Rate Variability and Autonomic Control
article

A novel index for trending sepsis and inflammatory response using processed EEG and Heart Rate Variability

Montserrat Vallverdú-Ferrer, Jaume Millán i Ichon, Michel Struys, Gertrude J. Nieuwenhuijs‐Moeke, Erik Weber Jensen, Carolina Frederico Avendaño, J E Nnagbo, Laia Yébenes-Serra
article en

Abstract

Early detection of systemic inflammation and sepsis is essential for improving patient outcomes. Heart rate variability (HRV) has been proposed as a non-invasive marker of inflammation; however, its specificity is limited, particularly under anesthesia or sedation. This study introduces the Trend of Sepsis and Inflammation (TSI), a novel index combining HRV and electroencephalogram (EEG)-derived parameters to better isolate inflammation-related autonomic changes.A post-hoc observational analysis was conducted in two cohorts: surgical patients undergoing general anesthesia (N = 41) and septic patients admitted to the intensive care unit (N = 21). Continuous EEG and ECG recordings were obtained using a multimodal monitoring system. HRV parameters from time and frequency domains, together with an EEG-derived Brain Activity Index, were integrated using an Adaptive Neuro-Fuzzy Inference System (ANFIS) to compute the TSI. TSI values were compared across three conditions: awake baseline, post-surgical inflammation, and sepsis. Statistical analysis employed non-parametric tests, while discriminative performance was assessed using prediction probability (Pk) and concordance with predefined interpretation ranges.TSI values increased progressively across conditions. Median values were 2.29 (IQR: 0.00-13.74) at baseline, 24.68 (18.50-32.00) post-surgery, and 65.59 (52.38-76.25) in sepsis, with significant differences (p < 0.0001). The TSI demonstrated strong discriminative ability (Pk = 93.58%) and high overall concordance (92.6%). HRV spectrograms and EEG-compensated analyses supported physiological consistency.The TSI distinguishes between baseline, post-surgical inflammatory, and septic states. By compensating for anesthesia-related autonomic suppression, it provides a continuous, non-invasive measure of inflammatory burden, supporting its potential use in perioperative and critical care settings. Further validation against established biomarkers is warranted.

Journal of Clinical Monitoring and Computing
University Medical Center Groningen (NL), University of Groningen (NL), Ghent University (BE), National Hospital Abuja (NG), Maresme Health Consortium (ES), Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (ES), Hospital Quirónsalud Barcelona (ES), Hospital de Mataró (ES), Barcelona School of Economics (ES), Universitat Politècnica de Catalunya (ES)
Universitat Politècnica de Catalunya
Reduced inequalities
Openalex Percentile: Top 8%
Heart Rate Variability and Autonomic Control
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