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http://dx.doi.org/10.22722/KJPM.2019.27.2.101

A Study on Clinical Variables Contributing to Differentiation of Delirium and Non-Delirium Patients in the ICU  

Ko, Chanyoung (Department of Psychiatry and Institute of Behavioral Science in Medicine, Yonsei University College of Medicine)
Kim, Jae-Jin (Department of Psychiatry and Institute of Behavioral Science in Medicine, Yonsei University College of Medicine)
Cho, Dongrae (Deepmedi Research Institute of Technology, Deepmedi Inc.)
Oh, Jooyoung (Department of Psychiatry and Institute of Behavioral Science in Medicine, Yonsei University College of Medicine)
Park, Jin Young (Department of Psychiatry and Institute of Behavioral Science in Medicine, Yonsei University College of Medicine)
Publication Information
Korean Journal of Psychosomatic Medicine / v.27, no.2, 2019 , pp. 101-110 More about this Journal
Abstract
Objectives : It is not clear which clinical variables are most closely associated with delirium in the Intensive Care Unit (ICU). By comparing clinical data of ICU delirium and non-delirium patients, we sought to identify variables that most effectively differentiate delirium from non-delirium. Methods : Medical records of 6,386 ICU patients were reviewed. Random Subset Feature Selection and Principal Component Analysis were utilized to select a set of clinical variables with the highest discriminatory capacity. Statistical analyses were employed to determine the separation capacity of two models-one using just the selected few clinical variables and the other using all clinical variables associated with delirium. Results : There was a significant difference between delirium and non-delirium individuals across 32 clinical variables. Richmond Agitation Sedation Scale (RASS), urinary catheterization, vascular catheterization, Hamilton Anxiety Rating Scale (HAM-A), Blood urea nitrogen, and Acute Physiology and Chronic Health Examination II most effectively differentiated delirium from non-delirium. Multivariable logistic regression analysis showed that, with the exception of vascular catheterization, these clinical variables were independent risk factors associated with delirium. Separation capacity of the logistic regression model using just 6 clinical variables was measured with Receiver Operating Characteristic curve, with Area Under the Curve (AUC) of 0.818. Same analyses were performed using all 32 clinical variables;the AUC was 0.881, denoting a very high separation capacity. Conclusions : The six aforementioned variables most effectively separate delirium from non-delirium. This highlights the importance of close monitoring of patients who received invasive medical procedures and were rated with very low RASS and HAM-A scores.
Keywords
Delirium; Intensive care unit; Electronic medical record; Discriminatory analysis;
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1 Martinez F, Tobar C, Hill N. Preventing delirium: should non-pharmacological, multicomponent interventions be used? A systematic review and meta-analysis of the literature. Age Ageing 2015;44:196-204.   DOI
2 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;19:178-186.   DOI
3 Simons KS, Laheij RJ, van den Boogaard M, Moviat MA, Paling AJ, Polderman FN, Rozendaal FW, Salet GA, van der Hoeven JG, Pickkers P, de Jager CP. Dynamic light application therapy to reduce the incidence and duration of delirium in intensive-care patients: a randomised controlled trial. Lancet Respir Med 2016;4:194-202.   DOI
4 Wong A, Young AT, Liang AS, Gonzales R, Douglas VC, Hadley D. Development and Validation of an Electronic Health Record-Based Machine Learning Model to Estimate Delirium Risk in Newly Hospitalized Patients Without Known Cognitive Impairment. JAMA Netw Open 2018;1:e181018.   DOI
5 Douglas VC, Hessler CS, Dhaliwal G, Betjemann JP, Fukuda KA, Alameddine LR, Lucatorto R, Johnston SC, Josephson SA. The AWOL tool: derivation and validation of a delirium prediction rule. J Hosp Med 2013;8:493-499.   DOI
6 Lundstrom M, Edlund A, Karlsson S, Brannstrom B, Bucht G, Gustafson Y. A multifactorial intervention program reduces the duration of delirium, length of hospitalization, and mortality in delirious patients. J Am Geriatr Soc 2005;53:622-628.   DOI
7 Ahn JS, Oh J, Park J, Kim JJ, Park JY. Incidence and Procedure-Related Risk Factors of Delirium in Patients Admitted to an Intensive Care Unit. Korean J Psychosomatic Med 2019;27:35-41.   DOI
8 Ahmed S, Leurent B, Sampson EL. Risk factors for incident delirium among older people in acute hospital medical units: a systematic review and meta-analysis. Age Ageing 2014;43:326-333.   DOI
9 Chanques G, Ely EW, Garnier O, Perrigault F, Eloi A, Carr J, Rowan CM, Prades A, de Jong A, Moritz-Gasser S, Molinari N, Jaber S. The 2014 updated version of the Confusion Assessment Method for the Intensive Care Unit compared to the 5th version of the Diagnostic and Statistical Manual of Mental Disorders and other current methods used by intensivists. Ann Intensive Care 2018;8:33.   DOI
10 Adamis D, Meagher D, Rooney S, Mulligan O, McCarthy G. A comparison of outcomes according to different diagnostic systems for delirium (DSM-5, DSM-IV, CAM, and DRS-R98). Int Psychogeriatr 2018;30:591-596.   DOI
11 McNicoll L, Pisani MA, Zhang Y, Ely EW, Siegel MD, Inouye SK. Delirium in the intensive care unit: occurrence and clinical course in older patients. J Am Geriatr Soc 2003;51: 591-598.   DOI
12 Haviland A, Nagin DS, Rosenbaum PR. Combining propensity score matching and group-based trajectory analysis in an observational study. Psychol Methods 2007;12:247-267.   DOI
13 Ross ME, Kreider AR, Huang YS, Matone M, Rubin DM, Localio AR. Propensity Score Methods for Analyzing Observational Data Like Randomized Experiments: Challenges and Solutions for Rare Outcomes and Exposures. Am J Epidemiol 2015;181:989-995.   DOI
14 Khan BA, Guzman O, Campbell NL, Walroth T, Tricker JL, Hui SL, Perkins A, Zawahiri M, Buckley JD, Farber MO, Ely EW, Boustani MA. Comparison and agreement between the Richmond Agitation-Sedation Scale and the Riker Sedation-Agitation Scale in evaluating patients' eligibility for delirium assessment in the ICU. Chest 2012;142:48-54.   DOI
15 Pohjalainen J, Rasanen O, Kadioglu S. Feature selection methods and their combinations in high-dimensional classification of speaker likability, intelligibility and personality traits. Computer Speech and Language 2015;29:145-171.   DOI
16 Han JH, Vasilevskis EE, Schnelle JF, Shintani A, Dittus RS, Wilson A, Ely EW. The Diagnostic Performance of the Richmond Agitation Sedation Scale for Detecting Delirium in Older Emergency Department Patients. Acad Emerg Med 2015;22:878-882.   DOI
17 Hamilton M. The assessment of anxiety states by rating. Br J Med Psychol 1959;32:50-55.   DOI
18 Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of disease classification system. Crit Care Med 1985;13:818-829.   DOI
19 Samani A, Kawczynski A, Chmura J, Madeleine P. Principle component analysis of exposure variation analysis during computer work at presence of delayed onset muscle soreness. Work 2012;41 Suppl 1:2387-2391.   DOI
20 Peritogiannis V, Bolosi M, Lixouriotis C, Rizos DV. Recent Insights on Prevalence and Corelations of Hypoactive Delirium. Behav Neurol 2015;2015:416792.   DOI
21 Marklew A. Urinary catheter care in the intensive care unit. Nurs Crit Care 2004;9:21-27.   DOI
22 Gershengorn HB, Garland A, Kramer A, Scales DC, Rubenfeld G, Wunsch H. Variation of arterial and central venous catheter use in United States intensive care units. Anesthesiology 2014;120:650-664.   DOI
23 Cole MG, Ciampi A, Belzile E, Zhong L. Persistent delirium in older hospital patients: a systematic review of frequency and prognosis. Age Ageing 2009;38:19-26.   DOI
24 Cavallazzi R, Saad M, Marik PE. Delirium in the ICU: an overview. Ann Intensive Care 2012;2:49.   DOI
25 Girard TD, Pandharipande PP, Ely EW. Delirium in the intensive care unit. Crit Care 2008;12 Suppl 3:S3.
26 Brummel NE, Girard TD. Preventing delirium in the intensive care unit. Crit Care Clin 2013;29:51-65.   DOI
27 Inouye SK. Prevention of delirium in hospitalized older patients: risk factors and targeted intervention strategies. Ann Med 2000;32:257-263.   DOI
28 Marcantonio ER, Goldman L, Orav EJ, Cook EF, Lee TH. The association of intraoperative factors with the development of postoperative delirium. Am J Med 1998;105:380-384.   DOI
29 Francis J, Martin D, Kapoor WN. A prospective study of delirium in hospitalized elderly. JAMA 1990;263:1097-1101.   DOI
30 Inouye SK. Predisposing and precipitating factors for delirium in hospitalized older patients. Dement Geriatr Cogn Disord 1999;10:393-400.   DOI
31 Kamel HK, Iqbal MA, Mogallapu R, Maas D, Hoffmann RG. Time to ambulation after hip fracture surgery: relation to hospitalization outcomes. J Gerontol A Biol Sci Med Sci 2003;58:1042-1045.   DOI
32 Oh J, Cho D, Park J, Na SH, Kim J, Heo J, Shin CS, Kim JJ, Park JY, Lee B. Prediction and early detection of delirium in the intensive care unit by using heart rate variability and machine learning. Physiol Meas 2018;39:035004.   DOI
33 Hshieh TT, Yue J, Oh E, Puelle M, Dowal S, Travison T, Inouye SK. Effectiveness of multicomponent nonpharmacological delirium interventions: a meta-analysis. JAMA Intern Med 2015;175:512-520.   DOI