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Quantitative Validation of a Simplified 4-Lead Electroencephalogram Montage for Neuromonitoring in Post-Cardiac
Zhengsong Shi1, Ming Li2, Hongguang Li3
1Department of Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Science, Beijing, China; Department of Surgical Intensive Care Unit, The First People's Hospital of Zhengzhou, Zhengzhou, China.
Objective:
Neurologic complications after cardiac surgery are common and associated with high morbidity and mortality. Continuous electroencephalography (cEEG) provides the reference standard for brain monitoring, but the standard 19-lead setup is difficult to implement routinely in the intensive care unit (ICU). Simplified EEG montages derived from high-density recordings were computationally evaluated to identify a configuration that preserves quantitative EEG (qEEG) fidelity for global brain state trend assessment at the bedside.
Design:
A retrospective, observational validation study.
Setting:
Single-center cardiac surgical ICU.
Participants:
Twenty-six patients admitted to the ICU for at least 24 hours following cardiac surgery with cardiopulmonary bypass, all under deep sedation (Richmond Agitation-Sedation Scale -4) during EEG recording.
Interventions:
Computational extraction of reduced-lead configurations (2-lead, three 4-lead combinations, and 6-lead) from 16-lead reference EEG recordings.
Measurements And Main Results:
Both 4-lead and 6-lead configurations showed good to excellent agreement with the reference. The 4-lead F3+F4+F7+F8 montage achieved excellent reliability intraclass coefficient (>0.9) for 9 of 10 qEEG parameters, with performance comparable to the 6-lead configuration. Bland-Altman analysis showed small bias and acceptable 95% limits of agreement for key parameters.
Conclusions:
A computationally derived 4-electrode montage (F3, F4, F7, and F8) demonstrates close agreement with the 16-electrode reference for global qEEG trend parameters in deeply sedated post-cardiac surgery patients. These findings provide a computational basis for designing a future standalone reduced-electrode acquisition system. Prospective validation with independent hardware is required before clinical deployment, and diagnostic performance for focal events remains to be established.
