Evaluation of the 3-Minute Diagnostic Confusion Assessment Method for Identification of Postoperative Delirium in Older Patients.

Importance: Delirium is a common postoperative complication in older patients that often goes undetected and might lead to worse outcomes. The 3-Minute Diagnostic Confusion Assessment Method (3D-CAM) might be a practical tool for routine clinical diagnosis of delirium. Objective: To assess the 3D-CAM for detecting postoperative delirium compared with the long-form CAM used for research purposes. Design, Setting, and Participants: This cohort study of older patients enrolled in ongoing clinical trials between 2015 and 2018 was conducted at a single tertiary US hospital. Included participants were aged 60 years or older undergoing major elective surgical procedures that required at least a 2-day hospital stay. Data were analyzed between February and April 2019. Exposures: Surgical procedures of at least 2 hours in length requiring general anesthesia with planned extubation. Main Outcomes and Measures: Patients were concurrently assessed for delirium using the 3D-CAM assessment and the long-form CAM, scored based on a standardized cognitive assessment. Agreement between these 2 methods was tested using Cohen κ with repeated measures, a generalized linear mixed-effects model, and Bland-Altman analysis. Results: Sixteen raters conducted 471 concurrent CAM and 3D-CAM interviews including 299 patients (mean [SD] age, 69 [6.5] years), the majority of whom were men (152 [50.8%]), were White (263 [88.0%]), and had noncardiac operations (211 [70.6%]). Both instruments had good intraclass correlation (0.84 for the CAM and 0.98 for the 3D-CAM). Cohen κ demonstrated good overall agreement between the CAM and 3D-CAM (κ = 0.71; 95% CI, 0.58 to 0.83). According to the mixed-effects model, there was statistically significant disagreement between the 3D-CAM and CAM (estimated difference in fixed effect, -0.68; 95% CI, -1.32 to -0.05; P = .04). Bland-Altman analysis showed the probability of a delirium diagnosis with the 3D-CAM was more than twice the probability of a delirium diagnosis with the CAM (probability ratio, 2.78; 95% CI, 2.44 to 3.23). Conclusions and Relevance: The 3D-CAM instrument demonstrated agreement with the long-form CAM and might provide a pragmatic and sensitive clinical tool for detecting postoperative delirium, with the caveat that the 3D-CAM might overdiagnose delirium.

Preoperative Cognitive Abnormality, Intraoperative Electroencephalogram Suppression, and Postoperative Delirium: A Mediation Analysis.

BACKGROUND: Postoperative delirium is a common complication that hinders recovery after surgery. Intraoperative electroencephalogram suppression has been linked to postoperative delirium, but it is unknown if this relationship is causal or if electroencephalogram suppression is merely a marker of underlying cognitive abnormalities. The hypothesis of this study was that intraoperative electroencephalogram suppression mediates a nonzero portion of the effect between preoperative abnormal cognition and postoperative delirium. METHODS: This is a prespecified secondary analysis of the Electroencephalography Guidance of Anesthesia to Alleviate Geriatric Syndromes (ENGAGES) randomized trial, which enrolled patients age 60 yr or older undergoing surgery with general anesthesia at a single academic medical center between January 2015 and May 2018. Patients were randomized to electroencephalogram-guided anesthesia or usual care. Preoperative abnormal cognition was defined as a composite of previous delirium, Short Blessed Test cognitive score greater than 4 points, or Eight Item Interview to Differentiate Aging and Dementia score greater than 1 point. Duration of intraoperative electroencephalogram suppression was defined as number of minutes with suppression ratio greater than 1%. Postoperative delirium was detected via Confusion Assessment Method or chart review on postoperative days 1 to 5. RESULTS: Among 1,113 patients, 430 patients showed evidence of preoperative abnormal cognition. These patients had an increased incidence of postoperative delirium (151 of 430 [35%] vs.123 of 683 [18%], P < 0.001). Of this 17.2% total effect size (99.5% CI, 9.3 to 25.1%), an absolute 2.4% (99.5% CI, 0.6 to 4.8%) was an indirect effect mediated by electroencephalogram suppression, while an absolute 14.8% (99.5% CI, 7.2 to 22.5%) was a direct effect of preoperative abnormal cognition. Randomization to electroencephalogram-guided anesthesia did not change the mediated effect size (P = 0.078 for moderation). CONCLUSIONS: A small portion of the total effect of preoperative abnormal cognition on postoperative delirium was mediated by electroencephalogram suppression. Study precision was too low to determine if the intervention changed the mediated effect.

Reliability and accuracy of delirium assessments among investigators at multiple international centres.

INTRODUCTION: Delirium is a common, serious postoperative complication. For clinical studies to generate valid findings, delirium assessments must be standardised and administered accurately by independent researchers. The Confusion Assessment Method (CAM) is a widely used delirium assessment tool. The objective was to determine whether implementing a standardised CAM training protocol for researchers at multiple international sites yields reliable inter-rater assessment and accurate delirium diagnosis. METHODS: Patients consented to video recordings of CAM delirium assessments for research purposes. Raters underwent structured training in CAM administration. Training entailed didactic education, role-playing with intensive feedback, apprenticeship with experienced researchers and group discussions of complex cases. Raters independently viewed and scored nine video-recorded CAM interviews. Inter-rater reliability was determined using Fleiss kappa. Accuracy was judged by comparing raters' scores with those of an expert delirium researcher. RESULTS: Twenty-seven raters from eight international research centres completed the study and achieved almost perfect agreement for overall delirium diagnosis, kappa=0.88 (95% CI 0.85 to 0.92). Agreement of the four core CAM features ranged from fair to substantial. The sensitivity and specificity for identifying delirium were 72% (95% CI 60% to 81%) and 99% (95% CI 96% to 100%), considering an expert rater's scores as the reference standard (delirious, n=3; non-delirious, n=6). Delirium severity ratings were tightly clustered, with most scores within 5% of the median. CONCLUSION: Our results demonstrate that, with appropriate training and ongoing scoring discussions, researchers at multiple sites can reliably detect delirium in postsurgical patients. These results support the premise that methodologically rigorous multi-centre studies can yield standardised and accurate determinations of delirium.