VE-CAM-S: Visual EEG-Based Grading of Delirium Severity and Associations With Clinical Outcomes

Ryan A Tesh; Haoqi Sun; Jin Jing; Mike Westmeijer; Anudeepthi Neelagiri; Subapriya Rajan; Parimala V Krishnamurthy; Pooja Sikka; Syed A Quadri; Michael J Leone; Luis Paixao; Ezhil Panneerselvam; Christine Eckhardt; Aaron F Struck; Peter W Kaplan; Oluwaseun Akeju; Daniel Jones; Eyal Y Kimchi; M Brandon Westover

doi:10.1097/CCE.0000000000000611

VE-CAM-S: Visual EEG-Based Grading of Delirium Severity and Associations With Clinical Outcomes

Crit Care Explor. 2022 Jan 18;4(1):e0611. doi: 10.1097/CCE.0000000000000611. eCollection 2022 Jan.

Authors

Ryan A Tesh^{1

2}, Haoqi Sun^{1

2}, Jin Jing^{1

2}, Mike Westmeijer, Anudeepthi Neelagiri¹, Subapriya Rajan^{1

2

3}, Parimala V Krishnamurthy^{1

2

4}, Pooja Sikka^{1

2

5}, Syed A Quadri^{1

2}, Michael J Leone^{1

2

6}, Luis Paixao^{1

2

7}, Ezhil Panneerselvam^{1

2

8}, Christine Eckhardt¹, Aaron F Struck⁴, Peter W Kaplan⁹, Oluwaseun Akeju¹⁰, Daniel Jones^{1

2}, Eyal Y Kimchi¹, M Brandon Westover^{1

2}

Affiliations

¹ Department of Neurology, Massachusetts General Hospital (MGH), Boston, MA.
² Clinical Data Animation Center (CDAC), MGH, Boston, MA.
³ Department of Neurology, West Virginia University, Morgantown, WV.
⁴ Department of Neurology, University of Wisconsin School of Medicine, William S. Middleton Veterans Memorial Hospital, Madison, WI.
⁵ Tufts University School of Medicine, Boston, MA.
⁶ University of Pittsburgh School of Medicine, Pittsburgh, PA.
⁷ Department of Neurology, Washington University School of Medicine in St. Louis, St. Louis, MO.
⁸ Department of Medicine, Texas Tech University Health Sciences Center El Paso, El Paso, TX.
⁹ Department of Neurology, Johns Hopkins Bayview Medical Center, Baltimore, MD.
¹⁰ Department of Anesthesia, Critical Care and Pain Medicine, MGH, Boston, MA.

Abstract

To develop a physiologic grading system for the severity of acute encephalopathy manifesting as delirium or coma, based on EEG, and to investigate its association with clinical outcomes.

Design: This prospective, single-center, observational cohort study was conducted from August 2015 to December 2016 and October 2018 to December 2019.

Setting: Academic medical center, all inpatient wards.

Patients/subjects: Adult inpatients undergoing a clinical EEG recording; excluded if deaf, severely aphasic, developmentally delayed, non-English speaking (if noncomatose), or if goals of care focused primarily on comfort measures. Four-hundred six subjects were assessed; two were excluded due to technical EEG difficulties.

Interventions: None.

Measurements and main results: A machine learning model, with visually coded EEG features as inputs, was developed to produce scores that correlate with behavioral assessments of delirium severity (Confusion Assessment Method-Severity [CAM-S] Long Form [LF] scores) or coma; evaluated using Spearman R correlation; area under the receiver operating characteristic curve (AUC); and calibration curves. Associations of Visual EEG Confusion Assessment Method Severity (VE-CAM-S) were measured for three outcomes: functional status at discharge (via Glasgow Outcome Score [GOS]), inhospital mortality, and 3-month mortality. Four-hundred four subjects were analyzed (mean [sd] age, 59.8 yr [17.6 yr]; 232 [57%] male; 320 [79%] White; 339 [84%] non-Hispanic); 132 (33%) without delirium or coma, 143 (35%) with delirium, and 129 (32%) with coma. VE-CAM-S scores correlated strongly with CAM-S scores (Spearman correlation 0.67 [0.62-0.73]; p < 0.001) and showed excellent discrimination between levels of delirium (CAM-S LF = 0 vs ≥ 4, AUC 0.85 [0.78-0.92], calibration slope of 1.04 [0.87-1.19] for CAM-S LF ≤ 4 vs ≥ 5). VE-CAM-S scores were strongly associated with important clinical outcomes including inhospital mortality (AUC 0.79 [0.72-0.84]), 3-month mortality (AUC 0.78 [0.71-0.83]), and GOS at discharge (0.76 [0.69-0.82]).

Conclusions: VE-CAM-S is a physiologic grading scale for the severity of symptoms in the setting of delirium and coma, based on visually assessed electroencephalography features. VE-CAM-S scores are strongly associated with clinical outcomes.

Keywords: EEG; delirium; delirium severity; encephalopathy; prognosis.

Abstract

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