Clarifying confusion: the confusion assessment method. A new method for detection of delirium.
OBJECTIVE
To develop and validate a new standardized confusion assessment method (CAM) that enables nonpsychiatric clinicians to detect delirium quickly in high-risk settings.


METHODS
Prospective validation study.


METHODS
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).


METHODS
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.


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.
Inouye
S K
SK
Yale University School of Medicine, New Haven, Connecticut.
van Dyck
C H
CH
Alessi
C A
CA
Balkin
S
S
Siegal
A P
AP
Horwitz
R I
RI
D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D003221:Confusion / Q000175:diagnosis*; D003693:Delirium / Q000175:diagnosis*; D005260:Female; D006801:Humans; D008297:Male; D011446:Prospective Studies; D011569:Psychiatric Status Rating Scales; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D011795:Surveys and Questionnaires