Delirium as an acute brain injury in hospital inpatients: can clinical features and biomarkers predict outcomes?

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Background Delirium is an acute-onset, severe neuropsychiatric syndrome that affects 1 in 8 hospitalised patients. Delirium is associated with higher mortality, new long-term cognitive impairment and worsening of existing neurodegeneration. However, the mechanisms of delirium remains poorly understood. Some studies have suggested a role for inflammation, with raised CSF and inflammatory biomarkers frequently observed. In recent years new clinical tools have been developed to improve the recognition and ascertainment of delirium, such as 4AT and NEWS2. There is also growth in the use of routine data to assess risk and outcomes of delirium, with application of machine learning and AI. These developments allow for new research addressing at unprecedented scale relationships between delirium as coded in routine data and other clinical variables such as markers of inflammation and physiological measurements. What I aim to achieve within the PhD research project: 1) To explore the frequency and representation of reported delirium coding in healthcare discharge summaries via a systematic review 2) Perform research studies examining risks and associated outcomes for delirium using electronic health records that have utilised delirium assessment tools (e.g. NEWS2 and 4AT) o Risk factors including inflammation (via clinical biomarkers), abnormal physiological parameters (such as hypotension and hypoxia) and increased brain atrophy. o Outcomes include 30-day mortality, length of stay, readmission, development of dementia (or new cognitive impairment) and functional decline. References: Davis D. H., Muniz-Terrera G., Keage H. A., Stephan B. C., Fleming J., Ince P. G., Matthews F. E., Cunningham C., Ely E. W., MacLullich A. M., Brayne C. Epidemiological Clinicopathological Studies in Europe (EClipSE) Collaborative Members. Association of Delirium With Cognitive Decline in Late Life: A Neuropathologic Study of 3 Population-Based Cohort Studies. JAMA Psychiatry. 2017; 74(3):244-251.Hall R. J., Watne L. O., Cunningham E., Zetterberg H., Shenkin S. D., Wyller T. B., MacLullich A. M. J. CSF biomarkers in delirium: a systematic review. Int J Geriatr Psychiatry. 2018; 33(11):1479-1500. Lee A., Mu J. L., Joynt G. M., Chiu C. H., W. Lai V. K., Gin T., Underwood M. J. Risk prediction models for delirium in the intensive care unit after cardiac surgery: a systematic review and independent external validation, BJA: British Journal of Anaesthesia. 2017; 118(3):391-399. MacLullich A. M. J., Shenkin SD, Goodacre S., et al. The 4 'A's test for detecting delirium in acute medical patients: a diagnostic accuracy study. NIHR Journals Library; 2019 Aug. (Health Technology Assessment, No. 23.40.) Chapter 5, Diagnostic accuracy of the 4AT. Available from: https://www.ncbi.nlm.nih.gov/books/NBK544921/ Witlox J., Eurelings L. S. M., De Jonghe J. F. M., Kalisvaart K. J., Eikelenboom P., et al. Delirium in elderly patients and the risk of post-discharge mortality, institutionalization, and dementia: A meta-analysis. JAMA. 2010; 304:443-451. NHS England approves use of National Early Warning Score (NEWS) 2 to improve detection of acutely ill patients. (2018, February 05). Retrieved October 11, 2020, from https://www.rcplondon.ac.uk/news/nhs-england-approves-use-national-early-warning-score-news-2-improve-detection-acutely-ill.