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

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.