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Background Quantifying the severity of delirium is essential to advance clinical care through improved understanding of delirium impact, prognosis, pathophysiology, and response to treatment. Objectives To develop and validate a new delirium severity measure (CAM-S) based on the Confusion Assessment Method Design Validation analysis in two independent cohorts. Setting Three academic medical centers Patients First cohort included 300 patients age ≥ 70 years scheduled for major surgery; second included 919 medicine admissions age ≥ 70 years. Measurements A 4-item short form and 10-item long-form were developed. The association of the maximal CAM-S score during hospitalization with hospital and post-hospital outcomes related to delirium was evaluated. Results CAM-S scores demonstrated strong associations with all clinical outcomes examined, with significant gradients across severity categories in adjusted analyses, adding substantively to delirium diagnoses alone. Representative results included adjusted mean length of stay (LOS), which increased across levels of CAM-S short form severity from 6.5 (95% confidence interval, CI, 6.2-6.9) to 12.7 days (95% CI, 11.2-14.3)(Ptrend < 0.001). Comparable results across increasing levels of the CAM-S long form severity were 5.6 (95% CI, 5.1-6.1) to 11.9 days (95% CI, 10.8-12.9) (Ptrend < 0.001). Representative results for the composite outcome of adjusted relative risk of death or nursing home residence at 90 days increased across levels of CAM-S short form severity from 1.0 (referent) to 2.5 (95% CI, 1.9-3.3)(Ptrend < 0.001). Comparable results for the CAM-S long form severity were 1.0 (referent) to 2.5 (95% CI, 1.6-3.7) (Ptrend < 0.001). Limitations Data on clinical outcomes were drawn from an older dataset involving patients age 70 years and older. Conclusions CAM-S provides a new delirium severity measure with strong psychometric properties and strong associations with important clinical outcomes.

Background Interview and chart-based methods for identifying delirium have been validated. However, relative strengths and limitations of each method have not been described, nor has a combined approach (using both interviews and chart), been systematically examined. Objectives To compare chart and interview-based methods for identification of delirium. Design, Setting and Participants Participants were 300 patients aged 70+ undergoing major elective surgery (majority were orthopedic surgery) interviewed daily during hospitalization for delirium using the Confusion Assessment Method (CAM; interview-based method) and whose medical charts were reviewed for delirium using a validated chart-review method (chart-based method). We examined rate of agreement on the two methods and patient characteristics of those identified using each approach. Predictive validity for clinical outcomes (length of stay, postoperative complications, discharge disposition) was compared. In the absence of a gold-standard, predictive value could not be calculated. Results The cumulative incidence of delirium was 23% (n= 68) by the interview-based method, 12% (n=35) by the chart-based method and 27% (n=82) by the combined approach. Overall agreement was 80%; kappa was 0.30. The methods differed in detection of psychomotor features and time of onset. The chart-based method missed delirium in CAM-identified patients laacking features of psychomotor agitation or inappropriate behavior. The CAM-based method missed chart-identified cases occurring during the night shift. The combined method had high predictive validity for all clinical outcomes. Conclusions Interview and chart-based methods have specific strengths for identification of delirium. A combined approach captures the largest number and the broadest range of delirium cases.

Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New Background Postoperative delirium and postoperative cognitive dysfunction share risk factors and may co-occur, but their relationship is not well established. The primary goals of this study were to describe the prevalence of postoperative cognitive dysfunction and to investigate its association with in-hospital delirium. The authors hypothesized that delirium would be a significant risk factor for postoperative cognitive dysfunction during follow-up. Methods This study used data from an observational study of cognitive outcomes after major noncardiac surgery, the Successful Aging after Elective Surgery study. Postoperative delirium was evaluated each hospital day with confusion assessment method–based interviews supplemented by chart reviews. Postoperative cognitive dysfunction was determined using methods adapted from the International Study of Postoperative Cognitive Dysfunction. Associations between delirium and postoperative cognitive dysfunction were examined at 1, 2, and 6 months. Results One hundred thirty-four of 560 participants (24%) developed delirium during hospitalization. Slightly fewer than half (47%, 256 of 548) met the International Study of Postoperative Cognitive Dysfunction-defined threshold for postoperative cognitive dysfunction at 1 month, but this proportion decreased at 2 months (23%, 123 of 536) and 6 months (16%, 85 of 528). At each follow-up, the level of agreement between delirium and postoperative cognitive dysfunction was poor (kappa less than .08) and correlations were small (r less than .16). The relative risk of postoperative cognitive dysfunction was significantly elevated for patients with a history of postoperative delirium at 1 month (relative risk = 1.34; 95% CI, 1.07–1.67), but not 2 months (relative risk = 1.08; 95% CI, 0.72–1.64), or 6 months (relative risk = 1.21; 95% CI, 0.71–2.09). Conclusions Delirium significantly increased the risk of postoperative cognitive dysfunction in the first postoperative month; this relationship did not hold in longer-term follow-up. At each evaluation, postoperative cognitive dysfunction was more common among patients without delirium. Postoperative delirium and postoperative cognitive dysfunction may be distinct manifestations of perioperative neurocognitive deficits.

Background Electronic medical records (EMRs) offer the potential opportunity to streamline the search for patients with possible delirium. However, the identification of key words is a necessary first step in the effective and systematic use of EMRs for both clinical and research purposes. Objective To identify words and phrases commonly noted in charts of patients with delirium. Design, Setting, and Participants Participants were 67 patients aged 70+ undergoing major elective surgery with evidence of confusion in their medical charts nested within a cohort study of 300 patients. We report the rate of common words and phrases associated with symptoms of delirium and report positive predictive value compared with a reference standard delirium diagnosis. Results Eight key words or phrases (altered mental status, delirium, disoriented, hallucination, confusion, reorient, disorient and encephalopathy) had positive predictive values (PPVs) of 60–100% for diagnosis of delirium. Key words were charted more often in nursing notes compared with physician notes. For example, in patients with delirium, nursing notes had an average of 6.4 notes containing a one of the 8 key words for delirium compared with an average of 2.8 in physician charts. Conclusions A brief list of key words or phrases may serve as building blocks for a methodology to screen for possible delirium from charts and large databases for research and real-time clinical decision making.