Edward R. Marcantonio, MD, SM; Long H. Ngo, PhD; Margaret O'Connor, PhD; Richard N. Jones, ScD; Paul K. Crane, MD, MPH; Eran D. Metzger, MD; Sharon K. Inouye, MD, MPH
Acknowledgment: The authors thank the patients and families at Beth Israel Deaconess Medical Center who participated in this study; clinical assessors Tracee Francis, Leo Waterston, Meghan Collier, and Laura Branford-White; and research assistants Kerry Palihnich, Jacqueline Gallagher, Aleksandra Kuczmarska, Ariel Hodara, Benjamin Helfand, Mary Michaels, and Li-Wen Huang.
Grant Support: By the National Institute of Aging grants R01AG030618 and K24AG035075 (Dr. Marcantonio) and P01AG031720 and K07AG041835 (Dr. Inouye). Dr. Inouye holds the Milton and Shirley F. Levy Family Chair.
Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M14-0865.
Reproducible Research Statement:Study protocol, statistical code, and data set: Limited availability; please contact the principal investigator, Dr. Marcantonio (e-mail, firstname.lastname@example.org).
Requests for Single Reprints: Edward R. Marcantonio, MD, SM, Harvard Medical School, Division of General Medicine and Primary Care, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, CO-216, Boston, MA 02215; e-mail, email@example.com.
Current Author Addresses: Drs. Marcantonio and Ngo: Division of General Medicine and Primary Care, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA 02215.
Dr. O'Connor: Department of Neurology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA 02215.
Dr. Jones: Department of Psychiatry and Human Behavior, Warren Alpert School of Medicine at Brown University, Providence, RI 02903.
Dr. Crane: Division of General Internal Medicine, Department of Medicine, University of Washington, Box 35978, 325 Ninth Avenue, Seattle, WA 98104.
Drs. Metzger and Inouye: Aging Brain Center, Institute for Aging Research, Hebrew SeniorLife, 1200 Centre Street, Boston, MA 02131.
Author Contributions: Conception and design: E.R. Marcantonio, L.H. Ngo, R.N. Jones, S.K. Inouye.
Analysis and interpretation of the data: E.R. Marcantonio, L.H. Ngo, M. O'Connor, R.N. Jones, P.K. Crane, E.D. Metzger, S.K. Inouye.
Drafting of the article: E.R. Marcantonio, L.H. Ngo.
Critical revision of the article for important intellectual content: L.H. Ngo, M. O'Connor, R.N. Jones, P.K. Crane, E.D. Metzger, S.K.Inouye.
Final approval of the article: E.R. Marcantonio, L.H. Ngo, M. O'Connor, R.N. Jones, P.K. Crane, E.D. Metzger, S.K. Inouye.
Provision of study materials or patients: E.D. Metzger.
Statistical expertise: L.H. Ngo, R.N. Jones, P.K. Crane.
Obtaining of funding: E.R. Marcantonio.
Administrative, technical, or logistic support: S.K. Inouye.
Collection and assembly of data: E.R. Marcantonio, M. O'Connor, E.D. Metzger
Marcantonio ER, Ngo LH, O'Connor M, Jones RN, Crane PK, Metzger ED, et al. 3D-CAM: Derivation and Validation of a 3-Minute Diagnostic Interview for CAM-Defined Delirium: A Cross-sectional Diagnostic Test Study. Ann Intern Med. 2014;161:554-561. doi: 10.7326/M14-0865
Download citation file:
Published: Ann Intern Med. 2014;161(8):554-561.
This article has been corrected. The original version (PDF) is appended to this article as a Supplement.
Delirium is common, leads to other adverse outcomes, and is costly. However, it often remains unrecognized in most clinical settings. The Confusion Assessment Method (CAM) is the most widely used diagnostic algorithm, and operationalizing its features would be a substantial advance for clinical care.
To derive the 3D-CAM, a new 3-minute diagnostic assessment for CAM-defined delirium, and validate it against a clinical reference standard.
Derivation and validation study.
4 general medicine units in an academic medical center.
201 inpatients aged 75 years or older.
20 items that best operationalized the 4 CAM diagnostic features were identified to create the 3D-CAM. For prospective validation, 3D-CAM assessments were administered by trained research assistants. Clinicians independently did an extensive assessment, including patient and family interviews and medical record reviews. These data were considered by an expert panel to determine the presence or absence of delirium and dementia (reference standard). The 3D-CAM delirium diagnosis was compared with the reference standard in all patients and subgroups with and without dementia.
The 201 participants in the prospective validation study had a mean age of 84 years, and 28% had dementia. The expert panel identified 21% with delirium, 88% of whom had hypoactive or normal psychomotor features. Median administration time for the 3D-CAM was 3 minutes (interquartile range, 2 to 5 minutes), sensitivity was 95% (95% CI, 84% to 99%), and specificity was 94% (CI, 90% to 97%). The 3D-CAM did well in patients with dementia (sensitivity, 96% [CI, 82% to 100%]; specificity, 86% [CI, 67% to 96%]) and without dementia (sensitivity, 93% [CI, 66% to 100%]; specificity, 96% [CI, 91% to 99%]).
Limited to single-center, cross-sectional, and medical patients only.
The 3D-CAM operationalizes the CAM algorithm using a 3-minute structured assessment with high sensitivity and specificity relative to a reference standard and could be an important tool for improving recognition of delirium.
National Institute on Aging.
to gain full access to the content and tools.
Learn more about subscription options.
Register Now for a free account.
Geriatric Medicine, Neurology, Delirium.
Results provided by:
Copyright © 2016 American College of Physicians. All Rights Reserved.
Print ISSN: 0003-4819 | Online ISSN: 1539-3704
Conditions of Use
This PDF is available to Subscribers Only