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Clarifying Confusion: The Confusion Assessment Method: A New Method for Detection of Delirium

Sharon K. Inouye, MD, MPH; Christopher H. van Dyck, MD; Cathy A. Alessi, MD; Sharyl Balkin, MD; Alan P. Siegal, MD; and Ralph I. Horwitz, MD
[+] Article, Author, and Disclosure Information

Grant Support: In part by the American Federation for Aging Research.

Requests for Reprints: Sharon K. Inouye, MD, MPH, Yale-New Haven Hospital, 20 York Street, Tompkins Basement 15, New Haven, CT 06504.

Current Author Addresses: Dr. Inouye: Yale-New Haven Hospital, 20 York Street, Tompkins Basement 15, New Haven, CT 06504.

Drs. van Dyck and Siegal: Adler Geriatric Assessment Center, Yale-New Haven Hospital, 20 York Street, New Haven, CT 06504.

Dr. Alessi: UCLA Department of Geriatric Medicine and Gerontology, GRECC, Sepulveda VA Medical Center, HE, Building 4, Room A 241, 16111 Plummer Street, Sepulveda, CA 91343.

Dr. Balkin: HCA Riveredge Hospital, 8311 West Roosevelt Road, Forest Park, IL 60130.

Dr. Horwitz: Yale University School of Medicine, P. O. Box 3333, 333 Cedar Street, IE-61 SHM, New Haven, CT 06510.

© 1990 American College of PhysiciansAmerican College of Physicians

Ann Intern Med. 1990;113(12):941-948. doi:10.7326/0003-4819-113-12-941
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Objective: To develop and validate a new standardized confusion assessment method (CAM) that enables nonpsychiatric clinicians to detect delirium quickly in high-risk settings.

Design: Prospective validation study.

Setting: Conducted in general medicine wards and in an outpatient geriatric assessment center at Yale University (site 1) and in general medicine wards at the University of Chicago (site 2).

Patients: The study included 56 subjects, ranging in age from 65 to 98 years. At site 1, 10 patients with and 20 without delirium participated; at site 2, 16 patients with and 10 without delirium participated.

Measurements and Main Results: An expert panel developed the CAM through a consensus building process. The CAM instrument, which can be completed in less than 5 minutes, consists of nine operationalized criteria from the Diagnostic and Statistical Manual of Mental Disorders (DSM-III-R). An a priori hypothesis was established for the diagnostic value of four criteria: acute onset and fluctuating course, inattention, disorganized thinking, and altered level of consciousness. The CAM algorithm for diagnosis of delirium required the presence of both the first and the second criteria and of either the third or the fourth criterion. At both sites, the diagnoses made by the CAM were concurrently validated against the diagnoses made by psychiatrists. At sites 1 and 2 values for sensitivity were 100% and 94%, respectively; values for specificity were 95% and 90%; values for positive predictive accuracy were 91% and 94%; and values for negative predictive accuracy were 100% and 90%. The CAM algorithm had the highest predictive accuracy for all possible combinations of the nine features of delirium. The CAM was shown to have convergent agreement with four other mental status tests, including the Mini-Mental State Examination. The interobserver reliability of the CAM was high (kappa = 0.81 - 1.0).

Conclusions: The CAM is sensitive, specific, reliable, and easy to use for identification of delirium.





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