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

• Autores: Sarinnapha Vasunilashorn, Long H. Ngo, Donna M. Fick, Richard N. Jones, Eva Schmitt, Cyrus M. Kosar, Jane S. Saczynski, Thomas Travison, Sharon K. Inouye, Edward R. Marcantonio
• Localización: Journal of the American Geriatrics Society, ISSN 0002-8614, Vol. 64, Nº. 8, 2016, págs. 1684-1689
• Idioma: inglés
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• Resumen

  • 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.