Person:

Rudolph, James

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: The Diagnostic and Statistical Manual fifth edition (DSM-5) provides new criteria for delirium diagnosis. We examined delirium diagnosis using these new criteria compared with the Diagnostic and Statistical Manual fourth edition (DSM-IV) in a large dataset of patients assessed for delirium and related presentations. Methods: Patient data (n = 768) from six prospectively collected cohorts, clinically assessed using DSM-IV and the Delirium Rating Scale-Revised-98 (DRS-R98), were pooled. Post hoc application of DRS-R98 item scores were used to rate DSM-5 criteria. ‘Strict’ and ‘relaxed’ DSM-5 criteria to ascertain delirium were compared to rates determined by DSM-IV. Results: Using DSM-IV by clinical assessment, delirium was found in 510/768 patients (66%). Strict DSM-5 criteria categorized 158 as delirious including 155 (30%) with DSM-IV delirium, whereas relaxed DSM-5 criteria identified 466 as delirious, including 455 (89%) diagnosed by DSM-IV (P <0.001). The concordance between the different diagnostic methods was: 53% (ĸ = 0.22) between DSM-IV and the strict DSM-5, 91% (ĸ = 0.82) between the DSM-IV and relaxed DSM-5 criteria and 60% (ĸ = 0.29) between the strict versus relaxed DSM-5 criteria. Only 155 cases were identified as delirium by all three approaches. The 55 (11%) patients with DSM-IV delirium who were not rated as delirious by relaxed criteria had lower mean DRS-R98 total scores than those rated as delirious (13.7 ± 3.9 versus 23.7 ± 6.0; P <0.001). Conversely, mean DRS-R98 score (21.1 ± 6.4) for the 70% not rated as delirious by strict DSM-5 criteria was consistent with suggested cutoff scores for full syndromal delirium. Only 11 cases met DSM-5 criteria that were not deemed to have DSM-IV delirium. Conclusions: The concordance between DSM-IV and the new DSM-5 delirium criteria varies considerably depending on the interpretation of criteria. Overly-strict adherence for some new text details in DSM-5 criteria would reduce the number of delirium cases diagnosed; however, a more ‘relaxed’ approach renders DSM-5 criteria comparable to DSM-IV with minimal impact on their actual application and is thus recommended.

The objective of this analysis was to develop a measure of neuropsychological performance for cardiac surgery and to assess its psychometric properties. Older patients (n = 210) underwent a neuropsychological battery using nine assessments. The number of factors was identified with variable reduction methods. Factor analysis methods based on item response theory were used to evaluate the measure. Modified parallel analysis supported a single factor, and the battery formed an internally consistent set (coefficient alpha = .82). The developed measure provided a reliable, continuous measure (reliability > .90) across a broad range of performance (–1.5 SDs to +1.0 SDs) with minimal ceiling and floor effects.

OBJECTIVES: To determine whether patients who developed delirium after cardiac surgery were at risk of functional decline.

DESIGN: Prospective cohort study.

SETTING: Two academic hospitals and a Veterans Affairs Medical Center.

PARTICIPANTS: One hundred ninety patients aged 60 and older undergoing elective or urgent cardiac surgery.

MEASUREMENTS: Delirium was assessed daily and was diagnosed according to the Confusion Assessment Method. Before surgery and 1 and 12 months postoperatively, patients were assessed for function using the instrumental activities of daily living (IADL) scale. Functional decline was defined as a decrease in ability to perform one IADL at follow-up.

RESULTS: Delirium occurred in 43.1% (n=82) of the patients (mean age 73.7±6.7). Functional decline occurred in 36.3% (n=65/179) at 1 month and in 14.6% (n=26/178) at 12 months. Delirium was associated with greater risk of functional decline at 1 month (relative risk (RR)=1.9, 95% confidence interval (CI)=1.3–2.8) and tended toward greater risk at 12 months (RR=1.9, 95% CI=0.9–3.8). After adjustment for age, cognition, comorbidity, and baseline function, delirium remained significantly associated with functional decline at 1 month (adjusted RR=1.8, 95% CI=1.2–2.6) but not at 12 months (adjusted RR=1.5, 95% CI=0.6–3.3).

CONCLUSION: Delirium was independently associated with functional decline at 1 month and had a trend toward association at 12 months. These findings provide justification for intervention trials to evaluate whether delirium prevention or treatment strategies might improve postoperative functional recovery.

OBJECTIVES: To use an expert consensus process to identify indicators of delirium features to help enhance bedside recognition of delirium. DESIGN: Modified Delphi consensus process to assign existing cognitive and delirium assessment items to delirium features in the Confusion Assessment Method (CAM) diagnostic algorithm. SETTING: Meetings of expert panel. PARTICIPANTS: Panel of seven interdisciplinary clinical experts. MEASUREMENTS: Panelists' assignments of each assessment item to indicate CAM features. RESULTS: From an initial pool of 119 assessment items, the panel assigned 66 items to at least one CAM feature, and many items were assigned to more than one feature. Experts achieved a high level of consensus, with a postmeeting kappa for agreement of 0.98. The study staff compiled the assignment results to create a comprehensive list of CAM feature indicators, consisting of 107 patient interview questions, cognitive tasks, and interviewer observations, with some items assigned to multiple features. A subpanel shortened this list to 28 indicators of important delirium features. CONCLUSION: A systematic, well-described qualitative methodology was used to create a list of indicators for delirium based on the features of the CAM diagnostic algorithm. This indicator list may be useful as a clinical tool for enhancing delirium recognition at the bedside and for aiding in the development of a brief delirium screening instrument.

Background: When a hospitalized older patient falls or develops delirium, there are significant consequences for the patient and the health care system. Assessments of inattention and altered consciousness, markers for delirium, were analyzed to determine if they were also associated with falls. Methods: This retrospective case-control study from a regional tertiary Veterans Affairs referral center identified falls and delirium risk factors from quality databases from 2010 to 2012. Older fallers with complete delirium risk assessments prior to falling were identified. As a control, non-fallers were matched at a 3:1 ratio. Admission risk factors that were compared in fallers and non-fallers included altered consciousness, cognitive performance, attention, sensory deficits, and dehydration. Odds ratio (OR) was reported (95% confidence interval [CI]). Results: After identifying 67 fallers, the control population (n=201) was matched on age (74.4±9.8 years) and ward (83.6% medical; 16.4% intensive care unit). Inattention as assessed by the Months of the Year Backward test was more common in fallers (67.2% versus 50.8%, OR=2.0; 95% CI: 1.1–3.7). Fallers tended to have altered consciousness prior to falling (28.4% versus 12.4%, OR=2.8; 95% CI: 1.3–5.8). Conclusion: In this case-control study, alterations in consciousness and inattention, assessed prior to falling, were more common in patients who fell. Brief assessments of consciousness and attention should be considered for inclusion in fall prediction.

Delirium is a common and morbid condition in elderly hospitalized patients. Its pathophysiology is poorly understood but inflammation has been implicated based on a clinical association with systemic infection and surgery and preclinical data showing that systemic inflammation adversely affects hippocampus-dependent memory. However, clinical manifestations and imaging studies point to abnormalities not in the hippocampus but in cortical circuits. We therefore tested the hypothesis that systemic inflammation impairs prefrontal cortex function by assessing attention and executive function in aged animals. Aged (24-month-old) Fischer-344 rats received a single intraperitoneal injection of lipopolysaccharide (LPS; 50 μg/kg) or saline and were tested on the attentional set-shifting task (AST), an index of integrity of the prefrontal cortex, on days 1–3 post-injection. Plasma and frontal cortex concentrations of the cytokine TNFα and the chemokine CCL2 were measured by ELISA in separate groups of identically treated, age-matched rats. LPS selectively impaired reversal learning and attentional shifts without affecting discrimination learning in the AST, indicating a deficit in attention and cognitive flexibility but not learning globally. LPS increased plasma TNFα and CCL2 acutely but this resolved within 24–48 h. TNFα in the frontal cortex did not change whereas CCL2 increased nearly threefold 2 h after LPS but normalized by the time behavioral testing started 24 h later. Together, our data indicate that systemic inflammation selectively impairs attention and executive function in aged rodents and that the cognitive deficit is independent of concurrent changes in frontal cortical TNFα and CCL2. Because inattention is a prominent feature of clinical delirium, our data support a role for inflammation in the pathogenesis of this clinical syndrome and suggest this animal model could be useful for studying that relationship further.