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Clinical Trial Summary

In this trial, the investigators seek to demonstrate the feasibility of a system in continuously detecting 'inattention' as a subset of CAM-ICU in a small representative sample of patients in the Intensive Care Unit (ICU) at Chelsea & Westminster NHS Foundation Trust.


Clinical Trial Description

Delirium is an acute confusional state that affects many patients admitted to the hospital, especially intensive care. The current diagnosis of delirium is through the use of the Confusional Assessment Method in Intensive Care Unit (CAM-ICU) task based questionnaire. The core prinicipal to CAM-ICU is inattention; this is tested through asking the patient to remember a task and execute it on demand, e.g. squeezing the operator's hand everytime the letter A is said and then spelling CASABLANCA. The aim of this study is to find correlates to inattention. Eye-gaze data is ideally suited for this task as eyes move to pay attention to the environment. A video camera based eye-tracker has been developed that sits at the end of the bed (head-camera) and another behind the patient (scene-camera). The head-camera uses machine learning to measure the gaze of the patient's eyes while the scene-camera finds what the patient is looking at. Simulations are then run from the scene camera and the patient's gaze is then compared to find whether the patient is paying attention to what is simulated. Once per day, a member of the local research team will fill in a non-validated questionnaire based on work by MacMurchy et al. M. MacMurchy, S. Stemler, M. Zander, C. P. Bonafide, Acceptability, Feasibility, and Cost of Using Video to Evaluate Alarm Fatigue, Biomedical Instrumentation & Technology 51 (2017) 25-33. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT04589169
Study type Observational
Source Chelsea and Westminster NHS Foundation Trust
Contact Research Delivery Operations Manager
Phone 020 3315 6825
Email research.development@chelwest.nhs.uk
Status Recruiting
Phase
Start date December 7, 2020
Completion date October 12, 2021

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