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 E., Ngo L., O'Connor M., Jones R., Crane P., Metzger E., Inouye S.; 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
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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.
1. Rex Wilford, DO, RPh, FACP, 2. Sue Fosnight, RPh, CGP, BCPS, 3. Kyle Allen, DO, AGSF, Vice President for Clinical Integration and Medical Director Geriatric Medicine & Lifelong Health Division
1. Core Faculty, Internal Medicine Residency; Summa Health System; Akron, Ohio; 2. Clinical Lead Pharmacist-Geriatrics; Summa Health System; Akron, Ohio; 3. Vice President for Clinical Integration an
October 28, 2014
3D-CAM: Derivation and Validation of a 3-Minute Diagnostic Interview for CAM-Defined Delirium Letter to Editor
TO THE EDITOR: We read the article by Marcantonio and colleagues (1) with great interest. The early recognition of delirium across all hospital settings is a very important factor in patient safety and care. Nurses caring for patients have the best opportunity to recognize a disorder that fluctuations over time such as delirium. The ultimate goal of having a brief and accurate tool to aid nurses in the early detection of delirium, without adding excess burden to ever increasing nurse charting time, is quite significant. Marcantonio et al. did indeed show the 3D CAM shortens the time to complete delirium assessment to 3 minutes, while maintaining high sensitivity and specificity. In the discussion the authors comment “We currently have no brief instrument that is well-suited for widespread use across clinical settings”; we would argue that the Nursing Delirium Screening Scale (Nu-DESC ) is such an instrument. The Nu-DESC is an observational five-item delirium screening scale that can be completed in about 1 minute (2). When studied in medical units (2), surgical units (3), and intensive care units the Nu-DESC took less time and had clinically comparable sensitivity and specificity to other instruments such as the CAM, and also demonstrated efficacy in identification of hypoactive delirium. The Nu-DESC has been successfully implemented hospital wide among medical-surgical patients as a major part of a delirium protocol at our institutions (4). Nursing staff have favored this delirium screening tool due to short administration time and ease of use. The ability to quickly train nurses to use this tool has also been viewed as an advantage. The Nu-DESC is not perfect and indeed problems with nurse accuracy of assessment, despite high investigator accuracy, have been reported (5). In our experience for a delirium screening test to be accepted by nurses, it must be quick, accurate, and perceived valuable. The difference between 1 minute and 3 minutes can become quite significant when applied to multiple patients cared for each shift. If the delirium assessment tool does not have work-flow efficiency, then sustainability of its use is put in jeopardy. The Nu-DESC should be considered for broader clinical use in hospitals, and should certainly be considered in any future comparative research trials.References1. Marcantonio ER, Ngo LH, O’Connor M, Jones RN, Crane P, Metzger ED, Inouye SK. 3D-CAM: Derivation and Validation of a 3-Minute Diagnostic Inverview for CAM-Defined Delirium. Ann Intern Med. 2014; 161: 554-561.2. Gaudreau JD, Gagnon P, Harel F, Tremblay A, Roy MA. Fast, Systematic, and Continuous Delirium Assessment in Hospitalized Patients: The Nursing Delirium Screening Scale. J Pain Symptom Manage. 2005; 29: 368-375.3. Radtke FM, Franck M, Schust S, Boehme L, Pascher A, Bail HJ, Seeling M, Luetz A, Wernecke KD, Heinz A, Spies CD. A Comparison of Three Scores to Screen for Delirium on the Surgical Ward. World Journal of Surgery. 2010; 34: 487-489.4. Allen KR, Fosnight SM, Wilford R, Benedict LM, Sabo A, Holder C, Jackovitz DS, Germano SA, Gleespen L, Baum E, Wilber ST, Hazelett S. Implementation of a System-Wide Quality Improvement Project to Prevent Delirium in Hospitalized Patients. Journal of Clinical Outcomes Management. 2011; 18: 253-258.5. Solberg LM, Plummer CE, May KN, Mion LC. A quality improvement program to increase nurses’ detection of delirium on an acute medical unit. Geriatric Nursing. 2013; 34: 75-79.
Edward R. Marcantonio, MD, SM, Sharon K. Inouye, MD, MPH
Beth Israel Deaconess Medical Center
December 31, 2014
We appreciate Wilford et. al.’s letter regarding our recent paper 3D-CAM: Derivation and Validation of a 3-Minute Diagnostic Interview for Confusion Assessment Method (CAM)-Defined Delirium (1). The authors describe their experience with the Nu-DESC (2), a brief delirium screening instrument that assesses 5 features—disorientation, inappropriate behavior, inappropriate communication, illusions/hallucinations, and psychomotor retardation. Each feature is rated 0, 1, or 2, and a total score of ≥ 2 out of 10 is considered a positive screen for delirium. Importantly, Nu-DESC scoring is based on routine nursing observations, and requires no formal interviewing or cognitive testing. Therefore, it can be completed very quickly—in 1 minute or less. In the references provided by the authors, the Nu-DESC has excellent test characteristics relative to a reference standard. However, other publications report worse performance, such as a recent study of surgical patients that reported sensitivities of 29-32% (3), indicating that 7 out of 10 cases of delirium were missed. Key to delirium assessment is the quality of data that goes into determining the presence or absence of core diagnostic features of delirium. In modern hospital care, physicians and nurses do not routinely interact with patients in ways that reliably elicit delirium features. For instance, when the CAM algorithm was completed by nurses solely based on observations from routine care, its sensitivity was 30% relative to a reference standard (4). Information provided by structured testing is essential, particularly for patients with hypoactive delirium. The 3D-CAM incorporates patient symptom probes (e.g. “Have you felt confused today?”) and cognitive testing (e.g. days of the week backwards), in addition to observational items. Structured testing enhances sensitivity so cases will not be missed, ensures that all key features of delirium are assessed, and enhances reliability by collecting a uniform set of data. It also provides an objective measure of cognitive function that facilitates assessment of change in future days. Defining a brief yet informative set of cognitive items is a key contribution of the 3D-CAM.The 3D-CAM, when administered in full, can be completed in 3 minutes. Using skip patterns or up-front screening items, it may be possible to shorten the 3D-CAM further while retaining excellent performance. Our group is actively developing and testing methods to enhance feasibility of delirium identification in clinical practice. For the time being, we urge clinicians to incorporate structured testing, such as the items in the 3D-CAM, into their routine assessment of delirium.References1. Marcantonio ER, Ngo LH, O’Connor M, Jones RN, Crane P, Metzger ED, Inouye SK. 3D-CAM: Derivation and Validation of a 3-Minute Diagnostic Inverview for CAM-Defined Delirium. Ann Intern Med. 2014; 161: 554-561.2. Gaudreau JD, Gagnon P, Harel F, Tremblay A, Roy MA. Fast, Systematic, and Continuous Delirium Assessment in Hospitalized Patients: The Nursing Delirium Screening Scale. J Pain Symptom Manage. 2005; 29: 368-375.3. Neufeld KJ, Leoutsakos JS, Sieber FE, Joshi D, Wanamaker BL, Rios-Robels J, Needhma DM. Evaluation of two delirium screening tools for detecting post-operative delirium in the elderly. Brit J of Anesth. 2013; 111: 612-8.4. Inouye SK, Foreman MD, Mion LC, Katz KH, Cooney LM, Jr. Nurses' recognition of delirium and its symptoms: comparison of nurse and researcher ratings. Arch Intern Med. 2001;161(20):2467-73.
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Geriatric Medicine, Neurology, Delirium.
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