Predicting Delirium in Hospitalized Older Patients
Am Fam Physician. 2007 Nov 15;76(10):1527-1529.
Is it possible to predict the likelihood of delirium and overall prognosis in hospitalized older patients?
Delirium is a common complication in hospitalized older patients, particularly in those in the intensive care unit.1 Several interventions can prevent delirium or reduce its duration in at-risk patients. These interventions are aimed at reducing cognitive impairment, sleep deprivation, immobility, visual and hearing impairment, and dehydration.2
The first step in preventing delirium is identifying at-risk patients; therefore, researchers have tried to determine the risk factors for the condition. Inouye and colleagues studied 107 consecutive hospitalized patients older than 70 years who had no signs of delirium at admission; the average age of patients was 79 years.3 Patients with severe dementia were excluded, although those with mild-to-moderate dementia were considered for inclusion. About one fourth of patients in the study were diagnosed with delirium during their hospitalization. The Confusion Assessment Method questionnaire, which was administered by a single physician within 24 hours of onset of suspected delirium, was the reference standard for diagnosis. Four independent predictors of delirium were identified,3 making up a simple four-point clinical decision rule (see part I of the accompanying encounter form).4–6
The rule was validated in a prospective group of 171 inpatients at the same hospital as the original cohort.3 Although the rule includes the APACHE II (Acute Physiology and Chronic Health Evaluation) score,4 a nurse's assessment of severe illness can be substituted. The rule was also prospectively validated in a group of more than 600 Dutch patients older than 70 years who were undergoing hip surgery. In this group, the rule performed almost identically to the original cohort.5
Inouye and colleagues noted that a significant percentage of patients had persistent delirium at hospital discharge, which was an important risk factor for death or nursing home placement.3 Therefore, they developed and validated a second clinical decision rule to predict persistent delirium at hospital discharge.7
This second rule was developed in a group of 491 consecutively hospitalized patients 70 years or older who did not have delirium at admission. Five risk factors for persistent delirium were identified. The five-point rule (see part II of the accompanying encounter form7,8) was prospectively validated in a second group of 461 hospitalized patients older than 70 years. Sixty-three patients (14 percent) developed delirium during hospitalization, and 6 percent had delirium that persisted to discharge.7
Applying the Evidence
A 78-year-old woman is hospitalized for hip surgery. She has moderate cognitive impairment, a blood urea nitrogen (BUN)/creatinine ratio of 30, and moderate visual impairment (20/80); however, the admitting nurse determines that she is not severely ill. The patient needs assistance cleaning her home and preparing meals, but has no significant comorbidities. What is the likelihood that she will develop delirium during this hospitalization?
Answer: Using part I of the accompanying encounter form,4–6 she receives 3 points (one point each for visual impairment, BUN/creatinine ratio, and cognitive impairment). This gives her a 37 percent risk of delirium during this hospitalization. Despite preventive measures, she develops delirium, but restraints are not used. Using part II of the accompanying encounter form,7,8 you assess her risk of persistent delirium at hospital discharge. She receives 3 points (one point each for visual impairment, dementia, and impairment in activities of daily living), giving her a 14 percent risk.
REFERENCESshow all references
1. Francis J, Martin D, Kapoor WN. A prospective study of delirium in hospitalized elderly. JAMA. 1990;263:1097–101....
2. Inouye SK, Bogardus ST Jr, Charpentier PA, Leo-Summers L, Acampora D, Holford TR, et al. A multicomponent intervention to prevent delirium in hospitalized older patients. N Engl J Med. 1999;340:669–76.
3. Inouye SK, Viscoli CM, Horwitz RI, Hurst LD, Tinetti ME. A predictive model for delirium in hospitalized elderly medical patients based on admission characteristics. Ann Intern Med. 1993;119:474–81.
4. Knaus WA, Draper EA, Wanger DP, Zimmerman JE. APACHE II: a severity of disease classification system. Crit Care Med. 1985;13:818–29.
5. Kalisvaart KJ, Vreeswijk R, de Jonghe JF, van der Ploeg T, van Gool WA, Eikelenboom P. Risk factors and prediction of postoperative delirium in elderly hip-surgery patients: implementation and validation of a medical risk factor model. J Am Geriatr Soc. 2006;54:817–22.
6. Folstein MF, Folstein SE, McHugh PR. Mini-Mental State. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12:189–98.
7. Inouye SK, Zhang Y, Jones RN, Kiely DK, Yang F, Marcantonio ER. Risk factors for delirium at discharge: development and validation of a predictive model. Arch Intern Med. 2007;167:1406–13.
8. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40:373–83.
This guide is one in a series that offers evidence-based tools to assist family physicians in improving their decision making at the point of care.
Copyright © 2007 by the American Academy of Family Physicians.
This content is owned by the AAFP. A person viewing it online may make one printout of the material and may use that printout only for his or her personal, non-commercial reference. This material may not otherwise be downloaded, copied, printed, stored, transmitted or reproduced in any medium, whether now known or later invented, except as authorized in writing by the AAFP. Contact firstname.lastname@example.org for copyright questions and/or permission requests.
Want to use this article elsewhere? Get Permissions
More in AFP
MOST RECENT ISSUE
Feb 15, 2018
Access the latest issue of American Family Physician