An automated EEG algorithm to detect polymorphic delta activity in acute encephalopathy presenting as postoperative delirium

Abstract

Aim Delirium, a clinical manifestation of acute encephalopathy, is often unrecognised. An important electroencephalography (EEG) characteristic of acute encephalopathy is polymorphic delta activity (PDA), which can be detected automatically. We aimed to study whether automated assessment of PDA in unselected EEG could detect acute encephalopathy that presents clinically as delirium. Methods We assessed PDA in 145 elderly patients using the first 96 seconds of unselected single-channel EEG (Fp2,Pz). We compared fully automated PDA detection with visual inspection by EEG experts. Additionally, we tested its performance as a delirium monitor by comparing PDA detection with a standardized delirium assessment by a clinical expert panel. Results PDA detection showed an area under the receiver operating characteristic (AUC) of 0.86 compared to EEG experts. When compared with the delirium classification of clinical experts, PDA detection achieved an AUC of 0.78. PDA detection correlated with the likelihood of delirium, its severity and the levels of attention and consciousness (all p<0.001). Conclusion Automated PDA detection in unselected, single-channel EEG can classify acute encephalopathy clinically presenting as delirium. Significance A fully automated EEG algorithm can assist in the recognition of delirium.

Competing Interest Statement

Arjen JC Slooter is a non-salaried advisor for Prolira, a start-up company that develops an EEG-based delirium monitor. Any (future) profits from EEG-based delirium monitoring will be used for future scientific research only. Frans SS Leijten is also a non-salaried advisor and holds shares in Prolira. None of the other authors reports any conflicts of interest. The sponsor and Prolira, had no role in the study design, data analysis, data interpretation, or the decision to submit for publication.

Clinical Trial

NCT02404181

Funding Statement

This work was funded by European Union Horizon 2020 [grant number 820555].

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The study design was approved prior to patient enrolment by the local ethical committee of University Medical Center Utrecht (protocol 13-634)

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.

Yes

Data Availability

All data produced in the present study are available upon reasonable request to the authors

留言 (0)

沒有登入
gif