Non-Invasive Eye Tracking for the Diagnosis of Delirium on ICU (CONfuSED)

Continuous Non-Invasive Eye Tracking for the Early Detection of Delirium on the Intensive Care Unit

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.

Study Overview

• Status: Unknown
• Conditions: Delirium

Detailed 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 Type: Observational
• Enrollment (Anticipated): 30

Contacts and Locations

• Study Contact: Name: Marcela Vizcaychipi, MD, PhD; Phone Number: 02033158024; Email: Marcela.Vizcaychipi@chelwest.nhs.uk

Study Locations

• United Kingdom
  • London, United Kingdom, SW10 9NH
    • Recruiting
    • Chelsea And Westminster Hospital NHS Foundation Trust
    • Contact: Marcela Vizcaychipi, MD, PhD; Phone Number: 02033158024; Email: Marcela.Vizcaychipi@chelwest.nhs.uk
    • Principal Investigator: Ahmed Al-Hindawi

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (ADULT, OLDER_ADULT)
• Accepts Healthy Volunteers: N/A
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

Adult inpatients in ICU

Description

Inclusion Criteria:

1. Aged >18
2. Predicted Delirium as defined by the Early PREdiction of DELIRium in ICU patients (E-PREDELIRIC) score ≥ 20%
3. Expected length of stay ≥ 2 days

Exclusion Criteria:

1. Non-concordant eyes
2. Visual Impairment
3. Dementia
4. Inability for facial recognition and eye tracking to be performed reliably
5. Lack of signed consent form / nominated consultee form
6. In-ability to perform CAM-ICU reliably

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort
Positive cohort; Patients who develop delirium
Experimental control group; Patients who do not develop delirium

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Demonstrate eye gaze correlates with CAM-ICU	Patient's usual clinical care will not be affected by the assessments performed by this study. In our institution, CAM-ICU is performed at least twice daily and more so if there are changes to mental status. The system will be switched on 5 minutes prior to performing CAM-ICU and will record for a duration of 10 minutes following which, the system will be turned off and the cameras covered. This procedure will occur every time CAM-ICU is performed.	8-12 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Acceptance of the use of cameras and artificial intelligence on ICU	Once per day, the research staff will complete an acceptability questionnaire designed to ascertain the acceptability of the use of cameras within this study on day to day activities in ICU.This questionnaire is based on work by MacMurchy et al.; Minimum value is 0, maximum value is 4.; Higher scores indicate that the system affected the nurse's ability to communicate with patients, nurses and doctors and that it affected the nurse's ability to care for them.; A yes answer = 1 point, a No answer = 0 points. Marking will be done per question to gain insights into how the system affected the nurses.	8-12 months

Collaborators and Investigators

• Sponsor: Chelsea and Westminster NHS Foundation Trust
• Collaborators: Westminster Medical School Research Trust; BMA Foundation for Medical Research
• Investigators: Principal Investigator: Ahmed Al-Hindawi, BMBS, MRCA, Chelsea And Westminster Hospital NHS Foundation Trust

Publications and helpful links

General Publications

• McCusker J, Cole M, Abrahamowicz M, Primeau F, Belzile E. Delirium predicts 12-month mortality. Arch Intern Med. 2002 Feb 25;162(4):457-63. doi: 10.1001/archinte.162.4.457.
• Lancaster GA, Dodd S, Williamson PR. Design and analysis of pilot studies: recommendations for good practice. J Eval Clin Pract. 2004 May;10(2):307-12. doi: 10.1111/j..2002.384.doc.x.
• Holt-Lunstad J, Smith TB, Layton JB. Social relationships and mortality risk: a meta-analytic review. PLoS Med. 2010 Jul 27;7(7):e1000316. doi: 10.1371/journal.pmed.1000316.
• Ouimet S, Kavanagh BP, Gottfried SB, Skrobik Y. Incidence, risk factors and consequences of ICU delirium. Intensive Care Med. 2007 Jan;33(1):66-73. doi: 10.1007/s00134-006-0399-8. Epub 2006 Nov 11.
• Miotto R, Li L, Kidd BA, Dudley JT. Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records. Sci Rep. 2016 May 17;6:26094. doi: 10.1038/srep26094.
• M. Sarabia, Y. Demiris, A Humanoid Robot Companion for Wheelchair Users, Social Robotics 8239 (2013) 432-441.
• A. P. A. A. P. Association, et al., DSM-IV-TR: Diagnostic and Statistical Manual of Mental Disorders, Wash ington, DC: American psychiatric association (1994) 143-147.
• Palmu R, Suominen K, Vuola J, Isometsa E. Mental disorders among acute burn patients. Burns. 2010 Nov;36(7):1072-9. doi: 10.1016/j.burns.2010.04.004. Epub 2010 May 18.
• Lundstrom M, Olofsson B, Stenvall M, Karlsson S, Nyberg L, Englund U, Borssen B, Svensson O, Gustafson Y. Postoperative delirium in old patients with femoral neck fracture: a randomized intervention study. Aging Clin Exp Res. 2007 Jun;19(3):178-86. doi: 10.1007/BF03324687.
• Meier-Ruge W, Hunziker O, Iwangoff P. Senile dementia: a threshold phenomenon of normal aging? A contribution to the functional reserve hypothesis of the brain. Ann N Y Acad Sci. 1991;621:104-18. doi: 10.1111/j.1749-6632.1991.tb16973.x.
• Meagher DJ. Delirium: optimising management. BMJ. 2001 Jan 20;322(7279):144-9. doi: 10.1136/bmj.322.7279.144. No abstract available.
• Lin SM, Liu CY, Wang CH, Lin HC, Huang CD, Huang PY, Fang YF, Shieh MH, Kuo HP. The impact of delirium on the survival of mechanically ventilated patients. Crit Care Med. 2004 Nov;32(11):2254-9. doi: 10.1097/01.ccm.0000145587.16421.bb.
• Pisani MA, Araujo KL, Van Ness PH, Zhang Y, Ely EW, Inouye SK. A research algorithm to improve detection of delirium in the intensive care unit. Crit Care. 2006;10(4):R121. doi: 10.1186/cc5027.
• Beedie SA, Benson PJ, St Clair DM. Atypical scanpaths in schizophrenia: evidence of a trait- or state-dependent phenomenon? J Psychiatry Neurosci. 2011 May;36(3):150-64. doi: 10.1503/jpn.090169.
• Loughland CM, Williams LM, Gordon E. Schizophrenia and affective disorder show different visual scanning behavior for faces: a trait versus state-based distinction? Biol Psychiatry. 2002 Aug 15;52(4):338-48. doi: 10.1016/s0006-3223(02)01356-2.
• Trillenberg P, Lencer R, Heide W. Eye movements and psychiatric disease. Curr Opin Neurol. 2004 Feb;17(1):43-7. doi: 10.1097/00019052-200402000-00008.
• Y. Zhang, T. Wilcockson, K. I. Kim, T. Crawford, H. Gellersen, P. Sawyer, Monitoring Dementia with Automatic Eye Movements Analysis, in: I. Czarnowski, A. M. Caballero, R. J. Howlett, L. C. Jain (Eds.), Intelligent Decision Technologies 2016, volume 57, Springer International Publishing, Cham, 2016, pp. 299-309.
• Exton C, Leonard M. Eye tracking technology: a fresh approach in delirium assessment? Int Rev Psychiatry. 2009 Feb;21(1):8-14. doi: 10.1080/09540260802675106.
• Wassenaar A, van den Boogaard M, van Achterberg T, Slooter AJ, Kuiper MA, Hoogendoorn ME, Simons KS, Maseda E, Pinto N, Jones C, Luetz A, Schandl A, Verbrugghe W, Aitken LM, van Haren FM, Donders AR, Schoonhoven L, Pickkers P. Multinational development and validation of an early prediction model for delirium in ICU patients. Intensive Care Med. 2015 Jun;41(6):1048-56. doi: 10.1007/s00134-015-3777-2. Epub 2015 Apr 18.
• MacMurchy M, Stemler S, Zander M, Bonafide CP. Research: Acceptability, Feasibility, and Cost of Using Video to Evaluate Alarm Fatigue. Biomed Instrum Technol. 2017 Jan-Feb;51(1):25-33. doi: 10.2345/0899-8205-51.1.25. No abstract available.

Study record dates

Study Major Dates

• Study Start (ACTUAL): December 7, 2020
• Primary Completion (ANTICIPATED): October 12, 2021
• Study Completion (ANTICIPATED): October 12, 2021

Study Registration Dates

• First Submitted: October 9, 2020
• First Submitted That Met QC Criteria: October 9, 2020
• First Posted (ACTUAL): October 19, 2020

Study Record Updates

• Last Update Posted (ACTUAL): December 8, 2020
• Last Update Submitted That Met QC Criteria: December 7, 2020
• Last Verified: December 1, 2020

More Information

Terms related to this study

• Keywords: ICU; Delirium; Inattention; Eye-gaze
• Additional Relevant MeSH Terms: Mental Disorders; Nervous System Diseases; Neurologic Manifestations; Confusion; Neurobehavioral Manifestations; Neurocognitive Disorders; Delirium
• Other Study ID Numbers: C&W19/064; IRAS number 264759 (OTHER: Integrated Research Application System)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No