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VE-CAM-S: Visual EEG-Based Grading of Delirium Severity and Associations With Clinical Outcomes
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 20...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8769081/ https://www.ncbi.nlm.nih.gov/pubmed/35072078 http://dx.doi.org/10.1097/CCE.0000000000000611 |
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author | Tesh, Ryan A. Sun, Haoqi Jing, Jin Westmeijer, Mike Neelagiri, Anudeepthi Rajan, Subapriya Krishnamurthy, Parimala V. Sikka, Pooja Quadri, Syed A. Leone, Michael J. Paixao, Luis Panneerselvam, Ezhil Eckhardt, Christine Struck, Aaron F. Kaplan, Peter W. Akeju, Oluwaseun Jones, Daniel Kimchi, Eyal Y. Westover, M. Brandon |
author_facet | Tesh, Ryan A. Sun, Haoqi Jing, Jin Westmeijer, Mike Neelagiri, Anudeepthi Rajan, Subapriya Krishnamurthy, Parimala V. Sikka, Pooja Quadri, Syed A. Leone, Michael J. Paixao, Luis Panneerselvam, Ezhil Eckhardt, Christine Struck, Aaron F. Kaplan, Peter W. Akeju, Oluwaseun Jones, Daniel Kimchi, Eyal Y. Westover, M. Brandon |
author_sort | Tesh, Ryan A. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8769081 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-87690812022-01-20 VE-CAM-S: Visual EEG-Based Grading of Delirium Severity and Associations With Clinical Outcomes Tesh, Ryan A. Sun, Haoqi Jing, Jin Westmeijer, Mike Neelagiri, Anudeepthi Rajan, Subapriya Krishnamurthy, Parimala V. Sikka, Pooja Quadri, Syed A. Leone, Michael J. Paixao, Luis Panneerselvam, Ezhil Eckhardt, Christine Struck, Aaron F. Kaplan, Peter W. Akeju, Oluwaseun Jones, Daniel Kimchi, Eyal Y. Westover, M. Brandon Crit Care Explor Original Clinical Report 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. Lippincott Williams & Wilkins 2022-01-18 /pmc/articles/PMC8769081/ /pubmed/35072078 http://dx.doi.org/10.1097/CCE.0000000000000611 Text en Copyright © 2022 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. |
spellingShingle | Original Clinical Report Tesh, Ryan A. Sun, Haoqi Jing, Jin Westmeijer, Mike Neelagiri, Anudeepthi Rajan, Subapriya Krishnamurthy, Parimala V. Sikka, Pooja Quadri, Syed A. Leone, Michael J. Paixao, Luis Panneerselvam, Ezhil Eckhardt, Christine Struck, Aaron F. Kaplan, Peter W. Akeju, Oluwaseun Jones, Daniel Kimchi, Eyal Y. Westover, M. Brandon VE-CAM-S: Visual EEG-Based Grading of Delirium Severity and Associations With Clinical Outcomes |
title | VE-CAM-S: Visual EEG-Based Grading of Delirium Severity and Associations With Clinical Outcomes |
title_full | VE-CAM-S: Visual EEG-Based Grading of Delirium Severity and Associations With Clinical Outcomes |
title_fullStr | VE-CAM-S: Visual EEG-Based Grading of Delirium Severity and Associations With Clinical Outcomes |
title_full_unstemmed | VE-CAM-S: Visual EEG-Based Grading of Delirium Severity and Associations With Clinical Outcomes |
title_short | VE-CAM-S: Visual EEG-Based Grading of Delirium Severity and Associations With Clinical Outcomes |
title_sort | ve-cam-s: visual eeg-based grading of delirium severity and associations with clinical outcomes |
topic | Original Clinical Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8769081/ https://www.ncbi.nlm.nih.gov/pubmed/35072078 http://dx.doi.org/10.1097/CCE.0000000000000611 |
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