Derivation and Validation of a Severity Scoring Method for the 3-Minute Diagnostic Interview for Confusion Assessment Method--Defined Delirium

Sarinnapha M. Vasunilashorn, Jamey Guess, Long Ngo, Donna Fick, Richard N. Jones, Eva M. Schmitt, Cyrus M. Kosar, Jane S. Saczynski, Thomas G. Travison, Sharon K. Inouye, Edward R. Marcantonio

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Objectives: To derive and validate a method for scoring delirium severity using a recently validated, brief, structured diagnostic interview for Confusion Assessment Method (CAM)-defined delirium (3D-CAM) and to demonstrate its agreement with the CAM Severity short form (CAM-S SF) as the reference standard. Design: Derivation and validation analysis in a prospective cohort study. Setting: Two academic medical centers. Participants: Individuals aged 70 and older enrolled in the Successful Aging after Elective Surgery Study undergoing major elective noncardiac surgery (N = 566). Measurements: The sample was randomly divided into a derivation dataset (n = 377) and an independent validation dataset (n = 189). These datasets were used to develop a severity scoring method using the 3D-CAM based on the four-item CAM-S SF (3D-CAM-S) and evaluate agreement between the 3D-CAM-S and the traditional CAM-S SF using weighted kappa statistics. Results: A method for scoring severity using 3D-CAM items was developed that achieved good agreement with the CAM-S SF in the derivation dataset (κ = 0.94, 95% confidence interval (CI) = 0.93–0.95). The 3D-CAM-S achieved nearly identical agreement in the independent validation dataset (κ = 0.93, 95% CI = 0.92–0.95), and 100% of 3D-CAM-S scores were within 1 point of the CAM-S SF score in both datasets. The 3D-CAM-S also strongly predicts clinical outcomes. Conclusion: A newly developed method for scoring delirium severity using the 3D-CAM (the 3D-CAM-S) has excellent agreement with the CAM-S SF. This new methodology enables clinicians and researchers using the 3D-CAM for surveillance to measure delirium severity and monitor its course simultaneously by tracking changes over time. The 3D-CAM-S expands the utility of the 3D-CAM as an important tool for delirium recognition and management.

Original languageEnglish (US)
Pages (from-to)1684-1689
Number of pages6
JournalJournal of the American Geriatrics Society
Volume64
Issue number8
DOIs
StatePublished - Aug 1 2016

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Confusion
Delirium
Research Design
Interviews
Confidence Intervals

All Science Journal Classification (ASJC) codes

  • Geriatrics and Gerontology

Cite this

Vasunilashorn, Sarinnapha M. ; Guess, Jamey ; Ngo, Long ; Fick, Donna ; Jones, Richard N. ; Schmitt, Eva M. ; Kosar, Cyrus M. ; Saczynski, Jane S. ; Travison, Thomas G. ; Inouye, Sharon K. ; Marcantonio, Edward R. / Derivation and Validation of a Severity Scoring Method for the 3-Minute Diagnostic Interview for Confusion Assessment Method--Defined Delirium. In: Journal of the American Geriatrics Society. 2016 ; Vol. 64, No. 8. pp. 1684-1689.
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title = "Derivation and Validation of a Severity Scoring Method for the 3-Minute Diagnostic Interview for Confusion Assessment Method--Defined Delirium",
abstract = "Objectives: To derive and validate a method for scoring delirium severity using a recently validated, brief, structured diagnostic interview for Confusion Assessment Method (CAM)-defined delirium (3D-CAM) and to demonstrate its agreement with the CAM Severity short form (CAM-S SF) as the reference standard. Design: Derivation and validation analysis in a prospective cohort study. Setting: Two academic medical centers. Participants: Individuals aged 70 and older enrolled in the Successful Aging after Elective Surgery Study undergoing major elective noncardiac surgery (N = 566). Measurements: The sample was randomly divided into a derivation dataset (n = 377) and an independent validation dataset (n = 189). These datasets were used to develop a severity scoring method using the 3D-CAM based on the four-item CAM-S SF (3D-CAM-S) and evaluate agreement between the 3D-CAM-S and the traditional CAM-S SF using weighted kappa statistics. Results: A method for scoring severity using 3D-CAM items was developed that achieved good agreement with the CAM-S SF in the derivation dataset (κ = 0.94, 95{\%} confidence interval (CI) = 0.93–0.95). The 3D-CAM-S achieved nearly identical agreement in the independent validation dataset (κ = 0.93, 95{\%} CI = 0.92–0.95), and 100{\%} of 3D-CAM-S scores were within 1 point of the CAM-S SF score in both datasets. The 3D-CAM-S also strongly predicts clinical outcomes. Conclusion: A newly developed method for scoring delirium severity using the 3D-CAM (the 3D-CAM-S) has excellent agreement with the CAM-S SF. This new methodology enables clinicians and researchers using the 3D-CAM for surveillance to measure delirium severity and monitor its course simultaneously by tracking changes over time. The 3D-CAM-S expands the utility of the 3D-CAM as an important tool for delirium recognition and management.",
author = "Vasunilashorn, {Sarinnapha M.} and Jamey Guess and Long Ngo and Donna Fick and Jones, {Richard N.} and Schmitt, {Eva M.} and Kosar, {Cyrus M.} and Saczynski, {Jane S.} and Travison, {Thomas G.} and Inouye, {Sharon K.} and Marcantonio, {Edward R.}",
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Vasunilashorn, SM, Guess, J, Ngo, L, Fick, D, Jones, RN, Schmitt, EM, Kosar, CM, Saczynski, JS, Travison, TG, Inouye, SK & Marcantonio, ER 2016, 'Derivation and Validation of a Severity Scoring Method for the 3-Minute Diagnostic Interview for Confusion Assessment Method--Defined Delirium', Journal of the American Geriatrics Society, vol. 64, no. 8, pp. 1684-1689. https://doi.org/10.1111/jgs.14234

Derivation and Validation of a Severity Scoring Method for the 3-Minute Diagnostic Interview for Confusion Assessment Method--Defined Delirium. / Vasunilashorn, Sarinnapha M.; Guess, Jamey; Ngo, Long; Fick, Donna; Jones, Richard N.; Schmitt, Eva M.; Kosar, Cyrus M.; Saczynski, Jane S.; Travison, Thomas G.; Inouye, Sharon K.; Marcantonio, Edward R.

In: Journal of the American Geriatrics Society, Vol. 64, No. 8, 01.08.2016, p. 1684-1689.

Research output: Contribution to journalArticle

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T1 - Derivation and Validation of a Severity Scoring Method for the 3-Minute Diagnostic Interview for Confusion Assessment Method--Defined Delirium

AU - Vasunilashorn, Sarinnapha M.

AU - Guess, Jamey

AU - Ngo, Long

AU - Fick, Donna

AU - Jones, Richard N.

AU - Schmitt, Eva M.

AU - Kosar, Cyrus M.

AU - Saczynski, Jane S.

AU - Travison, Thomas G.

AU - Inouye, Sharon K.

AU - Marcantonio, Edward R.

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N2 - Objectives: To derive and validate a method for scoring delirium severity using a recently validated, brief, structured diagnostic interview for Confusion Assessment Method (CAM)-defined delirium (3D-CAM) and to demonstrate its agreement with the CAM Severity short form (CAM-S SF) as the reference standard. Design: Derivation and validation analysis in a prospective cohort study. Setting: Two academic medical centers. Participants: Individuals aged 70 and older enrolled in the Successful Aging after Elective Surgery Study undergoing major elective noncardiac surgery (N = 566). Measurements: The sample was randomly divided into a derivation dataset (n = 377) and an independent validation dataset (n = 189). These datasets were used to develop a severity scoring method using the 3D-CAM based on the four-item CAM-S SF (3D-CAM-S) and evaluate agreement between the 3D-CAM-S and the traditional CAM-S SF using weighted kappa statistics. Results: A method for scoring severity using 3D-CAM items was developed that achieved good agreement with the CAM-S SF in the derivation dataset (κ = 0.94, 95% confidence interval (CI) = 0.93–0.95). The 3D-CAM-S achieved nearly identical agreement in the independent validation dataset (κ = 0.93, 95% CI = 0.92–0.95), and 100% of 3D-CAM-S scores were within 1 point of the CAM-S SF score in both datasets. The 3D-CAM-S also strongly predicts clinical outcomes. Conclusion: A newly developed method for scoring delirium severity using the 3D-CAM (the 3D-CAM-S) has excellent agreement with the CAM-S SF. This new methodology enables clinicians and researchers using the 3D-CAM for surveillance to measure delirium severity and monitor its course simultaneously by tracking changes over time. The 3D-CAM-S expands the utility of the 3D-CAM as an important tool for delirium recognition and management.

AB - Objectives: To derive and validate a method for scoring delirium severity using a recently validated, brief, structured diagnostic interview for Confusion Assessment Method (CAM)-defined delirium (3D-CAM) and to demonstrate its agreement with the CAM Severity short form (CAM-S SF) as the reference standard. Design: Derivation and validation analysis in a prospective cohort study. Setting: Two academic medical centers. Participants: Individuals aged 70 and older enrolled in the Successful Aging after Elective Surgery Study undergoing major elective noncardiac surgery (N = 566). Measurements: The sample was randomly divided into a derivation dataset (n = 377) and an independent validation dataset (n = 189). These datasets were used to develop a severity scoring method using the 3D-CAM based on the four-item CAM-S SF (3D-CAM-S) and evaluate agreement between the 3D-CAM-S and the traditional CAM-S SF using weighted kappa statistics. Results: A method for scoring severity using 3D-CAM items was developed that achieved good agreement with the CAM-S SF in the derivation dataset (κ = 0.94, 95% confidence interval (CI) = 0.93–0.95). The 3D-CAM-S achieved nearly identical agreement in the independent validation dataset (κ = 0.93, 95% CI = 0.92–0.95), and 100% of 3D-CAM-S scores were within 1 point of the CAM-S SF score in both datasets. The 3D-CAM-S also strongly predicts clinical outcomes. Conclusion: A newly developed method for scoring delirium severity using the 3D-CAM (the 3D-CAM-S) has excellent agreement with the CAM-S SF. This new methodology enables clinicians and researchers using the 3D-CAM for surveillance to measure delirium severity and monitor its course simultaneously by tracking changes over time. The 3D-CAM-S expands the utility of the 3D-CAM as an important tool for delirium recognition and management.

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