Person:

Marcantonio, Edward

Background: Delirium (acute confusion), is a common, morbid, and costly complication of acute illness in older adults. Yet, researchers and clinicians lack short, efficient, and sensitive case identification tools for delirium. Though the Confusion Assessment Method (CAM) is the most widely used algorithm for delirium, the existing assessments that operationalize the CAM algorithm may be too long or complicated for routine clinical use. Item response theory (IRT) models help facilitate the development of short screening tools for use in clinical applications or research studies. This study utilizes IRT to identify a reduced set of optimally performing screening indicators for the four CAM features of delirium. Methods: Older adults were screened for enrollment in a large scale delirium study conducted in Boston-area post-acute facilities (n = 4,598). Trained interviewers conducted a structured delirium assessment that culminated in rating the presence or absence of four features of delirium based on the CAM. A pool of 135 indicators from established cognitive testing and delirium assessment tools were assigned by an expert panel into two indicator sets per CAM feature representing (a) direct interview questions, including cognitive testing, and (b) interviewer observations. We used IRT models to identify the best items to screen for each feature of delirium. Results: We identified 10 dimensions and chose up to five indicators per dimension. Preference was given to items with peak psychometric information in the latent trait region relevant for screening for delirium. The final set of 48 indicators, derived from 39 items, maintains fidelity to clinical constructs of delirium and maximizes psychometric information relevant for screening. Conclusions: We identified optimal indicators from a large item pool to screen for delirium. The selected indicators maintain fidelity to clinical constructs of delirium while maximizing psychometric information important for screening. This reduced item set facilitates development of short screening tools suitable for use in clinical applications or research studies. This study represents the first step in the establishment of an item bank for delirium screening with potential questions for clinical researchers to select from and tailor according to their research objectives.

Background: Difficulties with performance of functional activities may result from cognitive and/or physical impairments. To date, there has not been a clear delineation of the physical and cognitive demands of activities of daily living. Objectives: To quantify the relative physical and cognitive demands required to complete typical functional activities in older adults. Design: Expert panel survey. Setting: Web-based platform. Participants: Eleven experts from eight academic medical centers and 300 community dwelling elderly adults age 70 and older scheduled for elective non-cardiac surgery from two academic medical centers. Methods: Sum scores of expert ratings were calculated and then validated against objective data collected from a prospective longitudinal study. Main Outcome Measurements Correlation between expert ratings and objective neuropsychological tests (memory, language, complex attention) and physical measures (gait speed and grip strength) for performance-based tasks. Results: Managing money, self-administering medications, using the telephone, and preparing meals were rated as requiring significantly more cognitive demand, while walking and transferring, moderately strenuous activities, and climbing stairs were assessed as more physically demanding. Largely cognitive activities correlated with objective neuropsychological performance (r=0.13–0.23, p<.05) and largely physical activities correlated with physical performance (r=0.15–0.46, p<.05). Conclusions: Quantifying the degree of cognitive and/or physical demand for completing a specific task adds an additional dimension to standard measures of functional assessment. This additional information may significantly influence decisions about rehabilitation, post-acute care needs, treatment plans, and caregiver education.

Deficits in cholinergic function have been postulated to cause delirium and cognitive decline. This review examines current understanding of the cholinergic deficiency hypothesis in delirium by synthesizing evidence on potential pathophysiological pathways. Acetylcholine synthesis involves various precursors, enzymes, and receptors, and dysfunction in these components can lead to delirium. Insults to the brain, like ischemia and immunological stressors, can precipitously alter acetylcholine levels. Imbalances between cholinergic and other neurotransmitter pathways may result in delirium. Furthermore, genetic, enzymatic, and immunological overlaps exist between delirium and dementia related to the cholinergic pathway. Important areas for future research include identifying biomarkers, determining genetic contributions, and evaluating response to cholinergic drugs in delirium. Understanding how the cholinergic pathway relates to delirium may yield innovative approaches in the diagnosis, prevention, and treatment of this common, costly, and morbid condition.

Background: Unplanned hospitalization often represents a costly and hazardous event for the older population. Objectives: To develop and validate a predictive model for unplanned medical hospitalization from administrative data. Research Design: Model development and validation. Subjects: A total of 3919 patients aged >=70 years who were followed for at least 1 year in primary care clinics of an academic medical center. Measures: Risk factor data and the primary outcome of unplanned medical hospitalization were obtained from administrative data. Results: Of 1932 patients in the development cohort, 299 (15%) were hospitalized during 1 year follow up. Five independent risk factors were identified in the preceding year: Deyo-Charlson comorbidity score >=2 [adjusted relative risk (RR) = 1.8; 95% confidence interval (CI): 1.4–2.2], any prior hospitalization (RR = 1.8; 95% CI: 1.5–2.3), 6 or more primary care visits (RR = 1.6; 95% CI: 1.3–2.0), age >=85 years (RR = 1.4; 95% CI: 1.1–1.7), and unmarried status (RR = 1.4; 95% CI: 1.1–1.7). A risk stratification system was created by adding 1 point for each factor present. Rates of hospitalization for the low- (0 factor), intermediate- (1–2 factors), and high-risk (>=3 factors) groups were 5%, 15%, and 34% (P < 0.0001). The corresponding rates in the validation cohort, where 328/1987 (17%) were hospitalized, were 6%, 16%, and 36% (P < 0.0001). Conclusions: A predictive model based on administrative data has been successfully validated for prediction of unplanned hospitalization. This model will identify patients at high risk for hospitalization who may be candidates for preventive interventions.

OBJECTIVES: To identify barriers and motivators to participation in long-term clinical research by high-risk elderly people and to develop procedures to maximize recruitment and retention. DESIGN: Quantitative and qualitative survey. SETTING: Academic primary care medicine and pre-anesthesia testing clinics. PARTICIPANTS: Fifty patients aged 70 and older, including 25 medical patients at high risk of hospitalization and 25 patients with planned major surgery. MEASUREMENTS: Fifteen- to 20-minute interviews involved open- and closed-ended questions guided by an in-depth script. Two planned study protocols were presented to each participant. Both involved serial neuropsychological assessments, blood testing, and magnetic resonance brain imaging (MRI); one added lumbar puncture (LP). Participants were asked whether they would be willing to participate in these protocols, rated barriers and incentives to participation, and were probed with open-ended questions. RESULTS: Of 50 participants (average age 78, 44% male, 40% nonwhite), 32 (64%) expressed willingness to participate in the LP-containing protocol, with LP cited as the strongest disincentive. Thirty-eight (76%) expressed willingness to participate in the protocol without LP, with phlebotomy and long interviews cited as the strongest disincentives. Altruism was a strong motivator for participation, whereas transportation was a major barrier. Study visits at home, flexible appointment times, assessments shorter than 75 minutes, and providing transportation and free parking were strategies developed to maximize study participation. CONCLUSION: Vulnerable elderly people expressed a high rate of willingness to participate in an 18-month prospective study. Participants identified incentives and barriers that enabled investigators to develop procedures to maximize recruitment and retention.

The purpose of this analysis was to determine if postoperative delirium was associated with early postoperative cognitive dysfunction (at 7 days) and long-term postoperative cognitive dysfunction (at 3 months). The International Study of Postoperative Cognitive Dysfunction recruited 1218 subjects ≥ 60 years old undergoing elective, non-cardiac surgery. Postoperatively, subjects were evaluated for delirium using the criteria of the Diagnostic and Statistical Manual. Subjects underwent neuropsychological testing pre-operatively and postoperatively at 7 days (n = 1018) and 3 months (n = 946). Postoperative cognitive dysfunction was defined as a composite Z-score > 2 across tests or at least two individual test Z-scores > 2. Subjects with delirium were significantly less likely to participate in postoperative testing. Delirium was associated with an increased incidence of early postoperative cognitive dysfunction (adjusted risk ratio 1.6, 95% CI 1.1–2.1), but not long-term postoperative cognitive dysfunction (adjusted risk ratio 1.3, 95% CI 0.6–2.4). Delirium was associated with early postoperative cognitive dysfunction, but the relationship of delirium to long-term postoperative cognitive dysfunction remains unclear.