Biomarkers of neurodegeneration and neural injury as potential predictors for delirium.

OBJECTIVES: Determine if biomarkers of Alzheimer's disease and neural injury may play a role in the prediction of delirium risk. METHODS: In a cohort of older adults who underwent elective surgery, delirium case-no delirium control pairs (N = 70, or 35 matched pairs) were matched by age, sex and vascular comorbidities. Biomarkers from CSF and plasma samples collected prior to surgery, including amyloid beta (Aß)42 , Aß40 , total (t)-Tau, phosphorylated (p)-Tau181 , neurofilament-light (NfL), and glial fibrillary acid protein (GFAP) were measured in cerebrospinal fluid (CSF) and plasma using sandwich enzyme-linked immunosorbent assays (ELISAs) or ultrasensitive single molecule array (Simoa) immunoassays. RESULTS: Plasma GFAP correlated significantly with CSF GFAP and both plasma and CSF GFAP values were nearly two-fold higher in delirium cases. The median paired difference between delirium case and control without delirium for plasma GFAP was not significant (p = 0.074) but higher levels were associated with a greater risk for delirium (odds ratio 1.52, 95% confidence interval 0.85, 2.72 per standard deviation increase in plasma GFAP concentration) in this small study. No matched pair differences or associations with delirium were observed for NfL, p-Tau 181, Aß40 and Aß42 . CONCLUSIONS: These preliminary findings suggest that plasma GFAP, a marker of astroglial activation, may be worth further investigation as a predictive risk marker for delirium.

Now showing: The presentation. Using video recording to enhance Balint leadership training.

Review of video recorded sessions is a powerful teaching tool in medical education, helping students appreciate both spoken and unspoken communications not fully appreciated in the moment. For many years, the American Balint Society has used video review in its Leadership Training Intensive courses, however technical challenges around setting up and operating the equipment have led some faculty to question whether the benefits are worth the effort and anxiety. We describe here an approach to video review in Intensives with a focus on the case presentation. Close attention to the case presentation can uncover important clues about a presenter's feelings and conflicts in a case, clues that may easily be missed on first pass. The Balint group leader listens for clues and cues to the patient's state of mind, and how the clinician is being distracted or deflected from their authentic role. Focusing the video review at an Intensive on the case presentation highlights for novice leaders the importance of maintaining keen focus on this initial section of the Balint group process for information on "what this case is about." Finally, we predict that Balint group leaders who emerge from an Intensive with this new appreciation for close listening to the presentation will not only be more effective Balint group leaders but will also be in a better position to serve as clinical role models, teaching by example to their Balint group members the importance of attending closely to the patient's communications in the patient - clinician encounter.

Identifying Delirium in Persons With Moderate or Severe Dementia: Review of Challenges and an Illustrative Approach.

Delirium and dementia are common causes of cognitive impairment among older adults, which often coexist. Delirium is associated with poor clinical outcomes, and is more frequent and more severe in patients with dementia. Identifying delirium in the presence of dementia, also described as delirium superimposed on dementia (DSD), is particularly challenging, as symptoms of delirium such as inattention, cognitive dysfunction, and altered level of consciousness, are also features of dementia. Because DSD is associated with poorer clinical outcomes than dementia alone, detecting delirium is important for reducing morbidity and mortality in this population. We review a number of delirium screening instruments that have shown promise for use in DSD, including the 4-DSD, combined Six Item Cognitive Impairment Test (6-CIT) and 4 'A's Test (4AT), Confusion Assessment Method (CAM), and the combined UB2 and 3D-CAM (UB-CAM). Each has advantages and disadvantages. We then describe the operationalization of a CAM-based approach in a current ECT in dementia project as an example of modifying an existing instrument for patients with moderate to severe dementia. Ultimately, any instrument modified will need to be validated against a standard clinical reference, in order to fully establish its sensitivity and specificity in the moderate to severe dementia population. Future work is greatly needed to advance the challenging area of accurate identification of delirium in moderate or severe dementia.

Delirium Item Bank: Utilization to Evaluate and Create Delirium Instruments.

INTRODUCTION: The large number of heterogeneous instruments in active use for identification of delirium prevents direct comparison of studies and the ability to combine results. In a recent systematic review we performed, we recommended four commonly used and well-validated instruments and subsequently harmonized them using advanced psychometric methods to develop an item bank, the Delirium Item Bank (DEL-IB). The goal of the present study was to find optimal cut-points on four existing instruments and to demonstrate use of the DEL-IB to create new instruments. METHODS: We used a secondary analysis and simulation study based on data from three previous studies of hospitalized older adults (age 65+ years) in the USA, Ireland, and Belgium. The combined dataset included 600 participants, contributing 1,623 delirium assessments, and an overall incidence of delirium of about 22%. The measurements included the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition diagnostic criteria for delirium, Confusion Assessment Method (long form and short form), Delirium Observation Screening Scale, Delirium Rating Scale-Revised-98 (total and severity scores), and Memorial Delirium Assessment Scale (MDAS). RESULTS: We identified different cut-points for each existing instrument to optimize sensitivity or specificity, and compared instrument performance at each cut-point to the author-defined cut-point. For instance, the cut-point on the MDAS that maximizes both sensitivity and specificity was at a sum score of 6 yielding 89% sensitivity and 79% specificity. We then created four new example instruments (two short forms and two long forms) and evaluated their performance characteristics. In the first example short form instrument, the cut-point that maximizes sensitivity and specificity was at a sum score of 3 yielding 90% sensitivity, 81% specificity, 30% positive predictive value, and 99% negative predictive value. DISCUSSION/CONCLUSION: We used the DEL-IB to better understand the psychometric performance of widely used delirium identification instruments and scorings, and also demonstrated its use to create new instruments. Ultimately, we hope that the DEL-IB might be used to create optimized delirium identification instruments and to spur the development of a unified approach to identify delirium.

Psychometric Properties of a Delirium Severity Score for Older Adults and Association With Hospital and Posthospital Outcomes.

Importance: The ability to rate delirium severity is key to providing optimal care for older adults, and such ratings would allow clinicians to target patients with severe delirium and monitor response to treatment, recovery time, and prognosis; assess nursing burden and staffing needs; and, ultimately, provide more appropriate patient-centered care. Current delirium severity measures have been limited in their content, gradations, and measurement characteristics. Objective: To examine the internal consistency, reliability, and validity for clinical outcomes of the DEL-S delirium severity score, a measure of delirium severity that was developed using advanced psychometric approaches, analogous to those of the Patient-Reported Outcomes Measurement Information System initiative. Design, Setting, and Participants: This prospective cohort study was conducted at a large academic medical center in Boston, Massachusetts. Adults aged 70 years or older who were admitted or transferred to medical or surgical services as either emergency or elective admissions were enrolled between October 20, 2015, and March 15, 2017, and were monitored for 1 year. Data analysis was performed from June 2020 to August 2021. Exposures: Delirium severity, measured by scores on the delirium severity score short-form (SF; 6 items, scored 0-13, with higher scores indicating more severe delirium) and long-form (LF; 17 items, scored 0-21), considered continuously and grouped into 5 categories. Main Outcomes and Measures: The primary outcomes were in-hospital outcomes, including length of stay and hospital costs, and posthospital (30, 90, and 365 days) outcomes, including death, health care costs, and rehospitalization. Results: The 352 participants had a median (IQR) age of 79.7 (74.6-85.5) years, 204 (58.0%) were women, and they were highly educated (median [IQR] duration of education, 14 [7-20] years). Patients in the highest delirium severity score SF group (scores 6-9) had a longer length of stay (13.3 vs 6.9 days; P for trend < .001), greater in-hospital costs ($57 700 vs $34 200), greater cumulative health care costs ($168 700 vs $106 500; P for trend = .01), and increased mortality at 1 year (50% vs 17%; P for trend = .02) compared with patients in the lowest delirium severity score SF group (score 0). Similar trends and significant findings were demonstrated for the delirium severity score LF. Conclusions and Relevance: These findings suggest that the delirium severity score provides an approach for measuring delirium severity that is associated with adverse clinical outcomes in a direct exposure-response association and that the delirium severity score may help advance patient-centered care for delirium.

Harmonization of Four Delirium Instruments: Creating Crosswalks and the Delirium Item-Bank (DEL-IB).

OBJECTIVES: Over 30 instruments are in current, active use for delirium identification. In a recent systematic review, we recommended 4 commonly used and well-validated instruments for clinical and research use. The goal of this study is to harmonize the four instruments on the same metric using modern methods in psychometrics. DESIGN: Secondary data analysis from 3 studies, and a simulation study based on the observed data. SETTING: Hospitalized (non-ICU) adults over 65 years old in the United States, Ireland, and Belgium. PARTICIPANTS: The total sample comprised 600 participants, contributing 1,623 assessments. MEASUREMENTS: Confusion Assessment Method (long-form and short-form), Delirium Observation Screening Scale, Delirium Rating Scale-Revised-98 (DRS-R-98) (total and severity scores), and Memorial Delirium Assessment Scale. RESULTS: Using item response theory, we linked scores across instruments, placing all four instruments and their separate scorings on the same metric (the propensity to delirium). Kappa statistics comparing agreement in delirium identification among the instruments ranged from 0.37 to 0.75, with the highest agreement between the DRS-R-98 total score and MDAS. After linking scores, we created a harmonized item bank, called the Delirium Item Bank (DEL-IB), consisting of 50 items. The DEL-IB allowed us to create six crosswalks, to allow scores to be translated across instruments. CONCLUSIONS: With our results, individual instrument scores can be directly compared to aid in clinical decision-making, and quantitatively combined in meta-analyses.

Development and internal validation of a predictive model of cognitive decline 36 months following elective surgery.

INTRODUCTION: Our goal was to determine if features of surgical patients, easily obtained from the medical chart or brief interview, could be used to predict those likely to experience more rapid cognitive decline following surgery. METHODS: We analyzed data from an observational study of 560 older adults (≥70 years) without dementia undergoing major elective non-cardiac surgery. Cognitive decline was measured using change in a global composite over 2 to 36 months following surgery. Predictive features were identified as variables readily obtained from chart review or a brief patient assessment. We developed predictive models for cognitive decline (slope) and predicting dichotomized cognitive decline at a clinically determined cut. RESULTS: In a hold-out testing set, the regularized regression predictive model achieved a root mean squared error (RMSE) of 0.146 and a model r-square (R2 ) of .31. Prediction of "rapid" decliners as a group achieved an area under the curve (AUC) of .75. CONCLUSION: Some of our models could predict persons with increased risk for accelerated cognitive decline with greater accuracy than relying upon chance, and this result might be useful for stratification of surgical patients for inclusion in future clinical trials.

Targeted metabolomics analysis of postoperative delirium.

Postoperative delirium is the most common complication among older adults undergoing major surgery. The pathophysiology of delirium is poorly understood, and no blood-based, predictive markers are available. We characterized the plasma metabolome of 52 delirium cases and 52 matched controls from the Successful Aging after Elective Surgery (SAGES) cohort (N = 560) of patients ≥ 70 years old without dementia undergoing scheduled major non-cardiac surgery. We applied targeted mass spectrometry with internal standards and pooled controls using a nested matched case-control study preoperatively (PREOP) and on postoperative day 2 (POD2) to identify potential delirium risk and disease markers. Univariate analyses identified 37 PREOP and 53 POD2 metabolites associated with delirium and multivariate analyses achieved significant separation between the two groups with an 11-metabolite prediction model at PREOP (AUC = 83.80%). Systems biology analysis using the metabolites with differential concentrations rendered "valine, leucine, and isoleucine biosynthesis" at PREOP and "citrate cycle" at POD2 as the most significantly enriched pathways (false discovery rate < 0.05). Perturbations in energy metabolism and amino acid synthesis pathways may be associated with postoperative delirium and suggest potential mechanisms for delirium pathogenesis. Our results could lead to the development of a metabolomic delirium predictor.

Detecting Delirium: A Systematic Review of Identification Instruments for Non-ICU Settings.

BACKGROUND/OBJECTIVES: Delirium manifests clinically in varying ways across settings. More than 40 instruments currently exist for characterizing the different manifestations of delirium. We evaluated all delirium identification instruments according to their psychometric properties and frequency of citation in published research. DESIGN: We conducted the systematic review by searching Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane Library, Excerpta Medica Database (Embase), PsycINFO, PubMed, and Web of Science from January 1, 1974, to January 31, 2020, with the keywords "delirium" and "instruments," along with their known synonyms. We selected only systematic reviews, meta-analyses, or narrative literature reviews including multiple delirium identification instruments. MEASUREMENTS: Two reviewers assessed the eligibility of articles and extracted data on all potential delirium identification instruments. Using the original publication on each instrument, the psychometric properties were examined using the Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) framework. RESULTS: Of 2,542 articles identified, 75 met eligibility criteria, yielding 30 different delirium identification instruments. A count of citations was determined using Scopus for the original publication for each instrument. Each instrument underwent methodological quality review of psychometric properties using COSMIN definitions. An expert panel categorized key domains for delirium identification based on criteria from the Diagnostic and Statistical Manual of Mental Disorders (DSM)-III through DSM-5. Four instruments were notable for having at least two of three of the following: citation count of 200 or more, strong validation methodology in their original publication, and fulfillment of DSM-5 criteria. These were, alphabetically, Confusion Assessment Method, Delirium Observation Screening Scale, Delirium Rating Scale-Revised-98, and Memorial Delirium Assessment Scale. CONCLUSION: Four commonly used and well-validated instruments can be recommended for clinical and research use. An important area for future investigation is to harmonize these measures to compare and combine studies on delirium.

Machine Learning to Develop and Internally Validate a Predictive Model for Post-operative Delirium in a Prospective, Observational Clinical Cohort Study of Older Surgical Patients.

BACKGROUND: Our objective was to assess the performance of machine learning methods to predict post-operative delirium using a prospective clinical cohort. METHODS: We analyzed data from an observational cohort study of 560 older adults (≥ 70 years) without dementia undergoing major elective non-cardiac surgery. Post-operative delirium was determined by the Confusion Assessment Method supplemented by a medical chart review (N = 134, 24%). Five machine learning algorithms and a standard stepwise logistic regression model were developed in a training sample (80% of participants) and evaluated in the remaining hold-out testing sample. We evaluated three overlapping feature sets, restricted to variables that are readily available or minimally burdensome to collect in clinical settings, including interview and medical record data. A large feature set included 71 potential predictors. A smaller set of 18 features was selected by an expert panel using a consensus process, and this smaller feature set was considered with and without a measure of pre-operative mental status. RESULTS: The area under the receiver operating characteristic curve (AUC) was higher in the large feature set conditions (range of AUC, 0.62-0.71 across algorithms) versus the selected feature set conditions (AUC range, 0.53-0.57). The restricted feature set with mental status had intermediate AUC values (range, 0.53-0.68). In the full feature set condition, algorithms such as gradient boosting, cross-validated logistic regression, and neural network (AUC = 0.71, 95% CI 0.58-0.83) were comparable with a model developed using traditional stepwise logistic regression (AUC = 0.69, 95% CI 0.57-0.82). Calibration for all models and feature sets was poor. CONCLUSIONS: We developed machine learning prediction models for post-operative delirium that performed better than chance and are comparable with traditional stepwise logistic regression. Delirium proved to be a phenotype that was difficult to predict with appreciable accuracy.

New Delirium Severity Indicators: Generation and Internal Validation in the Better Assessment of Illness (BASIL) Study.

BACKGROUND: Delirium is a common and preventable geriatric syndrome. Moving beyond the binary classification of delirium present/absent, delirium severity represents a potentially important outcome for evaluating preventive and treatment interventions and tracking the course of patients. Although several delirium severity assessment tools currently exist, most have been developed in the absence of advanced measurement methodology and have not been evaluated with rigorous validation studies. OBJECTIVE: We aimed to report our development of new delirium severity items and the results of item reduction and selection activities guided by psychometric analysis of data derived from a field study. METHODS: Building on our literature review of delirium instruments and expert panel process to identify domains of delirium severity, we adapted items from existing delirium severity instruments and generated new items. We then fielded these items among a sample of 352 older hospitalized patients. RESULTS: We used an expert panel process and psychometric data analysis techniques to narrow a set of 303 potential items to 17 items for use in a new delirium severity instrument. The 17-item set demonstrated good internal validity and favorable psychometric characteristics relative to comparator instruments, including the Confusion Assessment Method - Severity (CAM-S) score, the Delirium Rating Scale Revised 98, and the Memorial Delirium Assessment Scale. CONCLUSION: We more fully conceptualized delirium severity and identified characteristics of an ideal delirium severity instrument. These characteristics include an instrument that is relatively quick to administer, is easy to use by raters with minimal training, and provides a severity rating with good content validity, high internal consistency reliability, and broad domain coverage across delirium symptoms. We anticipate these characteristics to be represented in the subsequent development of our final delirium severity instrument.

Does Alzheimer's Disease and Related Dementias Modify Delirium Severity and Hospital Outcomes?

OBJECTIVES: We examined the association between delirium severity and outcomes of delirium among persons with and without Alzheimer's disease and related dementias (ADRD). DESIGN: Prospective cohort study. SETTING: Academic tertiary medical center. PARTICIPANTS: A total of 352 medical and surgical patients. MEASUREMENTS: Delirium incidence and severity were rated daily using the Confusion Assessment Method (CAM) and CAM-Severity (CAM-S) score during hospitalization. Severe delirium was defined as a CAM-S Short Form score in the highest tertile (3-7 points out of 7). ADRD status was determined by a clinical consensus process. Clinical outcomes included prolonged length of stay (>6 d), discharge to post-acute nursing facility, any decline in activities of daily living (ADLs) at 1 month from prehospital baseline, ongoing nursing facility stay, and mortality. RESULTS: Patients with ADRD (n = 85 [24%]) had a significantly higher relative risk (RR) for incident delirium (RR = 2.31; 95% confidence interval [CI] = 1.64-3.28) and higher peak CAM-S scores (mean difference = 1.24 points; CI = .83-1.65; P < .001). Among patients with ADRD, severe delirium significantly increased the RR for nursing facility stay (RR = 2.22; CI = 1.05-4.69; P = .04) and increased the RR for mortality (RR = 2.10; CI = .89-4.98; P = .09). Among patients without ADRD, severe delirium was associated with a significantly increased risk for all poor outcomes except mortality including prolonged length of stay in the hospital (RR = 1.47; CI = 1.18-1.82) and discharge to a post-acute nursing facility (RR = 2.17; CI = 1.58-2.98) plus decline in ADLs (RR = 1.30; CI = 1.05-1.60) and nursing facility stay at 1 month (RR = 1.93; CI = 1.31-2.83). CONCLUSION: Severe delirium is associated with increased risk for poor clinical outcomes in patients with and without ADRD. In both groups, severe delirium increased risk of nursing home placement. In patients with ADRD, delirium was more severe and associated with a trend toward increased mortality at 1 month. Although the increased risk remains substantial by RR, the study had limited power to examine the rarer outcome of death. J Am Geriatr Soc 68:1722-1730, 2020.

Assessment of Instruments for Measurement of Delirium Severity: A Systematic Review.

Importance: Measurement of delirium severity has been recognized as highly important for tracking prognosis, monitoring response to treatment, and estimating burden of care for patients both during and after hospitalization. Rather than simply rating delirium as present or absent, the ability to quantify its severity would enable development and monitoring of more effective treatment approaches for the condition. Objectives: To present a comprehensive review of delirium severity instruments, conduct a methodologic quality rating of the original validation study of the most commonly used instruments, and select a group of top-rated instruments. Evidence Review: This systematic review was conducted using literature from Embase, PsycINFO, PubMed, Web of Science, and Cumulative Index to Nursing and Allied Health Literature, from January 1, 1974, through March 31, 2017, with the key words delirium, severity, tests, measures, and intensity. Inclusion criteria were original articles assessing delirium severity and using a delirium-specific severity instrument. Final listings of articles were supplemented with hand searches of reference listings to ensure completeness. At least 2 reviewers independently completed each step of the review process: article selection, data extraction, and methodologic quality assessment of relevant articles using a validated rating scale. All discrepancies between raters were resolved by consensus. Findings: Of 9409 articles identified, 228 underwent full text review, and we identified 42 different instruments of delirium severity. Eleven of the 42 tools were multidomain, delirium-specific instruments providing a quantitative rating of delirium severity; these instruments underwent a methodologic quality review. Applying prespecified criteria related to frequency of use, methodologic quality, construct or predictive validity, and broad domain coverage, an expert panel used an iterative modified Delphi process to select 6 final high-quality instruments meeting these criteria: the Confusion Assessment Method-Severity Score, Confusional State Examination, Delirium-O-Meter, Delirium Observation Scale, Delirium Rating Scale, and Memorial Delirium Assessment Scale. Conclusions and Relevance: The 6 instruments identified may enable accurate measurement of delirium severity to improve clinical care for patients with this condition. This work may stimulate increased usage and head-to-head comparison of these instruments.

Consensus Approaches to Identify Incident Dementia in Cohort Studies: Systematic Review and Approach in the Successful Aging after Elective Surgery Study.

OBJECTIVES: To survey the current methods used to ascertain dementia and mild cognitive impairment (MCI) in longitudinal cohort studies, to categorize differences in approaches and to identify key components of expert panel methodology in current use. METHODS: We searched PubMed for the past 10 years, from March 6, 2007 to March 6, 2017 using a combination of controlled vocabulary and keyword terms to identify expert panel consensus methods used to diagnose MCI or dementia in large cohort studies written in English. From these results, we identified a framework for reporting standards and describe as an exemplar the clinical consensus procedure used in an ongoing study of elective surgery patients (the Successful Aging after Elective Surgery study). RESULTS: Thirty-one articles representing unique cohorts were included. Among published methods, membership of experts panel varied significantly. There was more similarity in what types of information was use to ascertain disease status. However, information describing the diagnostic decision process and resolution of disagreements was often lacking. CONCLUSIONS: Methods used for expert panel diagnosis of MCI and dementia in large cohort studies are widely variable, and there is a need for more standardized reporting of these approaches. By describing the procedure in which our expert panel achieved consensus diagnoses, we hope to encourage the development and publication of well-founded and reproducible methods for diagnosis of MCI and dementia in longitudinal studies.

High C-Reactive Protein Predicts Delirium Incidence, Duration, and Feature Severity After Major Noncardiac Surgery.

OBJECTIVES: To examine associations between the inflammatory marker C-reactive protein (CRP) measured preoperatively and on postoperative day 2 (POD2) and delirium incidence, duration, and feature severity. DESIGN: Prospective cohort study. SETTING: Two academic medical centers. PARTICIPANTS: Adults aged 70 and older undergoing major noncardiac surgery (N = 560). MEASUREMENTS: Plasma CRP was measured using enzyme-linked immunosorbent assay. Delirium was assessed from Confusion Assessment Method (CAM) interviews and chart review. Delirium duration was measured according to number of hospital days with delirium. Delirium feature severity was defined as the sum of CAM-Severity (CAM-S) scores on all postoperative hospital days. Generalized linear models were used to examine independent associations between CRP (preoperatively and POD2 separately) and delirium incidence, duration, and feature severity; prolonged hospital length of stay (LOS, >5 days); and discharge disposition. RESULTS: Postoperative delirium occurred in 24% of participants, 12% had 2 or more delirium days, and the mean ± standard deviation sum CAM-S was 9.3 ± 11.4. After adjusting for age, sex, surgery type, anesthesia route, medical comorbidities, and postoperative infectious complications, participants with preoperative CRP of 3 mg/L or greater had a risk of delirium that was 1.5 times as great (95% confidence interval (CI) = 1.1-2.1) as that of those with CRP less than 3 mg/L, 0.4 more delirium days (P < .001), more-severe delirium (3.6 CAM-S points higher, P < .001), and a risk of prolonged LOS that was 1.4 times as great (95% CI = 1.1-1.8). Using POD2 CRP, participants in the highest quartile (≥235.73 mg/L) were 1.5 times as likely to develop delirium (95% CI = 1.0-2.4) as those in the lowest quartile (≤127.53 mg/L), had 0.2 more delirium days (P < .05), and had more severe delirium (4.5 CAM-S points higher, P < .001). CONCLUSION: High preoperative and POD2 CRP were independently associated with delirium incidence, duration, and feature severity. CRP may be useful to identify individuals who are at risk of developing delirium.

Higher C-Reactive Protein Levels Predict Postoperative Delirium in Older Patients Undergoing Major Elective Surgery: A Longitudinal Nested Case-Control Study.

BACKGROUND: Delirium is a common, morbid, and costly postoperative complication. We aimed to identify blood-based postoperative delirium markers in a nested case-control study of older surgical patients using a proteomics approach followed by enzyme-linked immunosorbent assay (ELISA) validation. METHODS: The Successful Aging after Elective Surgery study enrolled dementia-free adults ≥70 years old undergoing major scheduled noncardiac surgery (N = 566; 24% delirium). Plasma was collected at four time points: preoperative, postanesthesia care unit, postoperative day 2, and 1 month postoperative. Matched pairs were selected for the independent discovery (39 pairs) and replication cohorts (36 pairs), which were subsequently combined into the pooled cohort (75 pairs). Isobaric tags for relative and absolute quantitation-based relative quantitation mass spectrometry proteomics were performed to identify the strongest delirium-related protein, which was selected for ELISA validation. Using the ELISA results, statistical analyses using nonparametric signed rank tests were performed in all cohorts examining the association between the identified protein and delirium. RESULTS: C-reactive protein emerged from the proteomics analysis as the strongest delirium-related protein. Validation by ELISA confirmed that compared with controls, cases had significantly higher C-reactive protein levels in the discovery, replication, and pooled cohorts at the preoperative (median paired difference [MPD] 1.97 mg/L [p < .05], 0.29 mg/L, 1.56 mg/L [p < .01]), postanesthesia care unit (MPD 2.83 mg/L, 2.22 mg/L [p < .05], 2.53 mg/L [p < .01]) and postoperative day 2 (MPD 71.97 mg/L [p < .01], 35.18 mg/L [p < .05], 63.76 mg/L [p < .01]) time points, but not 1 month postoperative (MPD 2.72 mg/L, -0.66 mg/L, 1.10 mg/L). CONCLUSIONS: Elevated preoperative and postoperative plasma levels of C-reactive protein were associated with delirium, suggesting that a preinflammatory state and heightened inflammatory response to surgery are potential pathophysiologic mechanisms of delirium.

3D-CAM: derivation and validation of a 3-minute diagnostic interview for CAM-defined delirium: a cross-sectional diagnostic test study.

BACKGROUND: Delirium is common, leads to other adverse outcomes, and is costly. However, it often remains unrecognized in most clinical settings. The Confusion Assessment Method (CAM) is the most widely used diagnostic algorithm, and operationalizing its features would be a substantial advance for clinical care. OBJECTIVE: To derive the 3D-CAM, a new 3-minute diagnostic assessment for CAM-defined delirium, and validate it against a clinical reference standard. DESIGN: Derivation and validation study. SETTING: 4 general medicine units in an academic medical center. PARTICIPANTS: 201 inpatients aged 75 years or older. MEASUREMENTS: 20 items that best operationalized the 4 CAM diagnostic features were identified to create the 3D-CAM. For prospective validation, 3D-CAM assessments were administered by trained research assistants. Clinicians independently did an extensive assessment, including patient and family interviews and medical record reviews. These data were considered by an expert panel to determine the presence or absence of delirium and dementia (reference standard). The 3D-CAM delirium diagnosis was compared with the reference standard in all patients and subgroups with and without dementia. RESULTS: The 201 participants in the prospective validation study had a mean age of 84 years, and 28% had dementia. The expert panel identified 21% with delirium, 88% of whom had hypoactive or normal psychomotor features. Median administration time for the 3D-CAM was 3 minutes (interquartile range, 2 to 5 minutes), sensitivity was 95% (95% CI, 84% to 99%), and specificity was 94% (CI, 90% to 97%). The 3D-CAM did well in patients with dementia (sensitivity, 96% [CI, 82% to 100%]; specificity, 86% [CI, 67% to 96%]) and without dementia (sensitivity, 93% [CI, 66% to 100%]; specificity, 96% [CI, 91% to 99%]). LIMITATION: Limited to single-center, cross-sectional, and medical patients only. CONCLUSION: The 3D-CAM operationalizes the CAM algorithm using a 3-minute structured assessment with high sensitivity and specificity relative to a reference standard and could be an important tool for improving recognition of delirium. PRIMARY FUNDING SOURCE: National Institute on Aging.

Cognitive and Brain Reserve and the Risk of Postoperative Delirium in Older Patients.

BACKGROUND: Cognitive and brain reserve theories suggest that aspects of neural architecture or cognitive processes modify the impact of neuropathological processes on cognitive outcomes. While frequently studied in the context of dementia, reserve in delirium is relatively understudied. METHODS: We examined the association of three markers of brain reserve (head circumference, MRI-derived brain volume, and leisure time physical activity) and five markers of cognitive reserve (education, vocabulary, cognitive activities, cognitive demand of lifetime occupation, and interpersonal demand of lifetime occupation) and the risk of postoperative delirium in a prospective observational study of 566 older adults free of dementia undergoing scheduled surgery. FINDINGS: Twenty four percent of patients (135/566) developed delirium during the postoperative hospitalization period. Of the reserve markers examined, only the Wechsler Test of Adult Reading (WTAR) was significantly associated with the risk of delirium. A one-half standard deviation better performance on the WTAR was associated with a 38% reduction in delirium risk (P = 0·01); adjusted relative risk of 0·62, 95% confidence interval 0·45-0·85. INTERPRETATION: In this relatively large and well-designed study, most markers of reserve fail to predict delirium risk. The exception to this is the WTAR. Our findings suggest that the reserve markers that are important for delirium may be different from those considered to be important for dementia.