Sex differences in the genetic architecture of cognitive resilience to Alzheimer's disease.

Approximately 30% of elderly adults are cognitively unimpaired at time of death despite the presence of Alzheimer's disease neuropathology at autopsy. Studying individuals who are resilient to the cognitive consequences of Alzheimer's disease neuropathology may uncover novel therapeutic targets to treat Alzheimer's disease. It is well established that there are sex differences in response to Alzheimer's disease pathology, and growing evidence suggests that genetic factors may contribute to these differences. Taken together, we sought to elucidate sex-specific genetic drivers of resilience. We extended our recent large scale genomic analysis of resilience in which we harmonized cognitive data across four cohorts of cognitive ageing, in vivo amyloid PET across two cohorts, and autopsy measures of amyloid neuritic plaque burden across two cohorts. These data were leveraged to build robust, continuous resilience phenotypes. With these phenotypes, we performed sex-stratified [n (males) = 2093, n (females) = 2931] and sex-interaction [n (both sexes) = 5024] genome-wide association studies (GWAS), gene and pathway-based tests, and genetic correlation analyses to clarify the variants, genes and molecular pathways that relate to resilience in a sex-specific manner. Estimated among cognitively normal individuals of both sexes, resilience was 20-25% heritable, and when estimated in either sex among cognitively normal individuals, resilience was 15-44% heritable. In our GWAS, we identified a female-specific locus on chromosome 10 [rs827389, ß (females) = 0.08, P (females) = 5.76 × 10-09, ß (males) = -0.01, P(males) = 0.70, ß (interaction) = 0.09, P (interaction) = 1.01 × 10-04] in which the minor allele was associated with higher resilience scores among females. This locus is located within chromatin loops that interact with promoters of genes involved in RNA processing, including GATA3. Finally, our genetic correlation analyses revealed shared genetic architecture between resilience phenotypes and other complex traits, including a female-specific association with frontotemporal dementia and male-specific associations with heart rate variability traits. We also observed opposing associations between sexes for multiple sclerosis, such that more resilient females had a lower genetic susceptibility to multiple sclerosis, and more resilient males had a higher genetic susceptibility to multiple sclerosis. Overall, we identified sex differences in the genetic architecture of resilience, identified a female-specific resilience locus and highlighted numerous sex-specific molecular pathways that may underly resilience to Alzheimer's disease pathology. This study illustrates the need to conduct sex-aware genomic analyses to identify novel targets that are unidentified in sex-agnostic models. Our findings support the theory that the most successful treatment for an individual with Alzheimer's disease may be personalized based on their biological sex and genetic context.

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.

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.

Clinical outcomes in older surgical patients with mild cognitive impairment.

INTRODUCTION: Older adults, including those with mild cognitive impairment (MCI), are increasingly undergoing surgery. METHODS: Relative risks (RRs) of MCI alone or with delirium on adverse outcomes were estimated in an ongoing prospective, observational cohort study of 560 nondemented adults aged ≥70 years. RESULTS: MCI (n = 61, 11%) was associated with increased RR of delirium (RR = 1.9, P < .001) and delirium severity (RR = 4.6, P < .001). Delirium alone (n = 107), but not MCI alone (n = 34), was associated with multiple adverse outcomes including more major postoperative complication(s) (RR = 2.5, P = .002) and longer length of stay (RR = 2.2, P < .001). Patients with concurrent MCI and delirium (n = 27) were more often discharged to a postacute facility (RR = 1.4, P < .001) and had synergistically increased risk for new impairments in cognitive functioning (RR = 3.6, P < .001). DISCUSSION: MCI is associated with increased risk of delirium incidence and severity. Patients with delirium and MCI have synergistically elevated risk of developing new difficulties in cognitively demanding tasks.

Preoperative Cognitive Performance Dominates Risk for Delirium Among Older Adults.

BACKGROUND: Cognitive impairment is a well-recognized risk factor for delirium. Our goal was to determine whether the level of cognitive performance across the nondemented cognitive ability spectrum is correlated with delirium risk and to gauge the importance of cognition relative to other known risk factors for delirium. METHODS: The Successful Aging after Elective Surgery study enrolled 566 adults aged ≥70 years scheduled for major surgery. Patients were assessed preoperatively and daily during hospitalization for the occurrence of delirium using the Confusion Assessment Method. Cognitive function was assessed preoperatively with an 11-test neuropsychological battery combined into a composite score for general cognitive performance (GCP). We examined the risk for delirium attributable to GCP, as well as demographic factors, vocabulary ability, and informant-rated cognitive decline, and compared the strength of association with risk factors identified in a previously published delirium prediction rule for delirium. RESULTS: Delirium occurred in 135 (24%) patients. Lower GCP score was strongly and linearly predictive of delirium risk (relative risk = 2.0 per each half standard deviation difference in GCP score, 95% confidence interval, 1.5-2.5). This effect was not attenuated by statistical adjustment for demographics, vocabulary ability, and informant-rated cognitive decline. The effect was stronger than, and largely independent from, both standard delirium risk factors and comorbidity. CONCLUSION: Risk of delirium is linearly and strongly related to presurgical cognitive performance level even at levels above the population median, which would be considered unimpaired.

The short-term and long-term relationship between delirium and cognitive trajectory in older surgical patients.

INTRODUCTION: As the relationship between delirium and long-term cognitive decline has not been well-explored, we evaluated this association in a prospective study. METHODS: SAGES is an ongoing study involving 560 adults age 70 years or more without dementia scheduled for major surgery. Delirium was assessed daily in the postoperative period using the Confusion Assessment Method. General Cognitive Performance (GCP) and the Informant Questionnaire for Cognitive Decline in the Elderly were assessed preoperatively then repeatedly out to 36 months. RESULTS: On average, patients with postoperative delirium had significantly lower preoperative cognitive performance, greater immediate (1 month) impairment, equivalent recovery at 2 months, and significantly greater long-term cognitive decline relative to the nondelirium group. Proxy reports corroborated the clinical significance of the long-term cognitive decline in delirious patients. DISCUSSION: Cognitive decline after surgery is biphasic and accelerated among persons with delirium. The pace of long-term decline is similar to that seen with mild cognitive impairment.

The CAM-S: development and validation of a new scoring system for delirium severity in 2 cohorts.

BACKGROUND: Quantifying the severity of delirium is essential to advancing clinical care by improved understanding of delirium effect, prognosis, pathophysiology, and response to treatment. OBJECTIVE: To develop and validate a new delirium severity measure (CAM-S) based on the Confusion Assessment Method. DESIGN: Validation analysis in 2 independent cohorts. SETTING: Three academic medical centers. PATIENTS: The first cohort included 300 patients aged 70 years or older scheduled for major surgery. The second included 919 medical patients aged 70 years or older. MEASUREMENTS: A 4-item short form and a 10-item long form were developed. Association of the maximum CAM-S score during hospitalization with hospital and posthospital outcomes related to delirium was evaluated. RESULTS: Representative results included adjusted mean length of stay, which increased across levels of short-form severity from 6.5 days (95% CI, 6.2 to 6.9 days) to 12.7 days (CI, 11.2 to 14.3 days) (P for trend < 0.001) and across levels of long-form severity from 5.6 days (CI, 5.1 to 6.1 days) to 11.9 days (CI, 10.8 to 12.9 days) (P for trend < 0.001). Representative results for the composite outcome of adjusted relative risk of death or nursing home residence at 90 days increased progressively across levels of short-form severity from 1.0 (referent) to 2.5 (CI, 1.9 to 3.3) (P for trend < 0.001) and across levels of long-form severity from 1.0 (referent) to 2.5 (CI, 1.6 to 3.7) (P for trend < 0.001). LIMITATION: Data on clinical outcomes were measured in an older data set limited to patients aged 70 years or older. CONCLUSION: The CAM-S provides a new delirium severity measure with strong psychometric properties and strong associations with important clinical outcomes. PRIMARY FUNDING SOURCE: National Institute on Aging.

Calibration and validation of an innovative approach for estimating general cognitive performance.

OBJECTIVE: To evaluate a new approach for creating a composite measure of cognitive function, we calibrated a measure of general cognitive performance from existing neuropsychological batteries. METHODS: We applied our approach in an epidemiological study and scaled the composite to a nationally representative sample of older adults. Criterion validity was evaluated against standard clinical diagnoses. Convergent validity was evaluated against the Mini-Mental State Examination (MMSE). RESULTS: The general cognitive performance factor was scaled to have a mean of 50 and standard deviation of 10 in a nationally representative sample of older adults. A cutoff point of approximately 45, corresponding to an MMSE of 23/24, optimally discriminated participants with and without dementia (sensitivity = 0.94, specificity = 0.90, area under the curve = 0.97). The general cognitive performance factor was internally consistent (Cronbach's α = 0.91) and provided reliable measures of functional ability across a wide range of cognitive functioning. It demonstrated minimal floor and ceiling effects, which is an improvement over most individual cognitive tests. CONCLUSIONS: The cognitive composite is a highly reliable measure, with minimal floor and ceiling effects. We calibrated it using a nationally representative sample of adults over the age of 70 in the USA and established diagnostically relevant cutoff points. Our methods can be used to harmonize neuropsychological test results across diverse settings and studies.

Coevolution of brain structures in amnestic mild cognitive impairment.

Network accounts of the progression of Alzheimer's disease (AD), based on cross-sectional brain imaging observations, postulate that the biological course of the disease is characterized by coordinated spatial patterns of brain change to distributed cognitive networks. This study tests this conjecture by quantifying inter-regional covariance in cortical gray matter atrophy rates in 317 Alzheimer's Disease Neuroimaging Initiative participants who were clinically diagnosed with amnestic mild cognitive impairment at baseline and underwent serial MRI at 6-month intervals over the course of 2years. A factor analysis model identified five factors (i.e. groupings of regions) that exhibited highly correlated rates of atrophy. Four groupings approximately corresponded to coordinated change within the posterior default mode network, prefrontal cortex, medial temporal lobe, and regions largely spared by the early pathological course of AD (i.e., sensorimotor and occipital cortex), while the fifth grouping represented diffuse, global atrophy. The data-driven observation of "frontal aging" superimposed upon medial temporal atrophy typical of early AD and default mode network changes supports the view that in individuals at high risk of eventual clinical AD, multiple patterns of distributed neuronal death corresponding to multiple biological substrates may be active.

Selecting optimal screening items for delirium: an application of item response theory.

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.

Adverse outcomes after hospitalization and delirium in persons with Alzheimer disease.

BACKGROUND: Hospitalization, frequently complicated by delirium, can be a life-changing event for patients with Alzheimer disease (AD). OBJECTIVE: To determine risks for institutionalization, cognitive decline, or death associated with hospitalization and delirium in patients with AD. DESIGN: Prospective cohort enrolled between 1991 and 2006 into the Massachusetts Alzheimer's Disease Research Center (MADRC) patient registry. SETTING: Community-based. PARTICIPANTS: 771 persons aged 65 years or older with a clinical diagnosis of AD. MEASUREMENTS: Hospitalization, delirium, death, and institutionalization were identified through administrative databases. Cognitive decline was defined as a decrease of 4 or more points on the Blessed Information-Memory-Concentration test score. Multivariate analysis was used to calculate adjusted relative risks (RRs). RESULTS: Of 771 participants with AD, 367 (48%) were hospitalized and 194 (25%) developed delirium. Hospitalized patients who did not have delirium had an increased risk for death (adjusted RR, 4.7 [95% CI, 1.9 to 11.6]) and institutionalization (adjusted RR, 6.9 [CI, 4.0 to 11.7]). With delirium, risk for death (adjusted RR, 5.4 [CI, 2.3 to 12.5]) and institutionalization (adjusted RR, 9.3 [CI, 5.5 to 15.7]) increased further. With hospitalization and delirium, the adjusted RR for cognitive decline for patients with AD was 1.6 (CI, 1.2 to 2.3). Among hospitalized patients with AD, 21% of the incidences of cognitive decline, 15% of institutionalization, and 6% of deaths were associated with delirium. LIMITATIONS: Cognitive outcome was missing in 291 patients. Sensitivity analysis was performed to test the effect of missing data, and a composite outcome was used to decrease the effect of missing data. CONCLUSION: Approximately 1 in 8 hospitalized patients with AD who develop delirium will have at least 1 adverse outcome, including death, institutionalization, or cognitive decline, associated with delirium. Delirium prevention may represent an important strategy for reducing adverse outcomes in this population.

Using Bayesian item response theory for multicohort repeated measure design to estimate individual latent change scores.

Repeated measure data design has been used extensively in a wide range of fields, such as brain aging or developmental psychology, to answer important research questions exploring relationships between trajectory of change and external variables. In many cases, such data may be collected from multiple study cohorts and harmonized, with the intention of gaining higher statistical power and enhanced external validity. When psychological constructs are measured using survey scales, a fundamental psychometric challenge for data harmonization is to create commensurate measures for the constructs of interest across studies. Traditional analysis may fit a unidimensional item response theory model to data from one time point and one cohort to obtain item parameters and fix the same parameters in subsequent analyses. Such a simplified approach ignores item residual dependencies in the repeated measure design on one hand, and on the other hand, it does not exploit accumulated information from different cohorts. Instead, two alternative approaches should serve such data designs much better: an integrative approach using multiple-group two-tier model via concurrent calibration, and if such calibration fails to converge, a Bayesian sequential calibration approach that uses informative priors on common items to establish the scale. Both approaches use a Markov chain Monte Carlo algorithm that handles computational complexity well. Through a simulation study and an empirical study using Alzheimer's diseases neuroimage initiative cognitive battery data (i.e., language and executive functioning), we conclude that latent change scores obtained from these two alternative approaches are more precisely recovered. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Six-Year Cognitive Trajectory in Older Adults Following Major Surgery and Delirium.

Importance: The study results suggest that delirium is the most common postoperative complication in older adults and is associated with poor outcomes, including long-term cognitive decline and incident dementia. Objective: To examine the patterns and pace of cognitive decline up to 72 months (6 years) in a cohort of older adults following delirium. Design, Setting, and Participants: This was a prospective, observational cohort study with long-term follow-up including 560 community-dwelling older adults (older than 70 years) in the ongoing Successful Aging after Elective Surgery study that began in 2010. The data were analyzed from 2021 to 2022. Exposure: Development of incident delirium following major elective surgery. Main Outcomes and Measures: Delirium was assessed daily during hospitalization using the Confusion Assessment Method, which was supplemented with medical record review. Cognitive performance using a comprehensive battery of neuropsychological tests was assessed preoperatively and across multiple points postoperatively to 72 months of follow-up. We evaluated longitudinal cognitive change using a composite measure of neuropsychological performance called the general cognitive performance (GCP), which is scaled so that 10 points on the GCP is equivalent to 1 population SD. Retest effects were adjusted using cognitive test results in a nonsurgical comparison group. Results: The 560 participants (326 women [58%]; mean [SD] age, 76.7 [5.2] years) provided a total of 2637 person-years of follow-up. One hundred thirty-four participants (24%) developed postoperative delirium. Cognitive change following surgery was complex: we found evidence for differences in acute, post-short-term, intermediate, and longer-term change from the time of surgery that were associated with the development of postoperative delirium. Long-term cognitive change, which was adjusted for practice and recovery effects, occurred at a pace of about -1.0 GCP units (95% CI, -1.1 to -0.9) per year (about 0.10 population SD units per year). Participants with delirium showed significantly faster long-term cognitive change with an additional -0.4 GCP units (95% CI, -0.1 to -0.7) or -1.4 units per year (about 0.14 population SD units per year). Conclusions and Relevance: This cohort study found that delirium was associated with a 40% acceleration in the slope of cognitive decline out to 72 months following elective surgery. Because this is an observational study, we cannot be sure whether delirium directly causes subsequent cognitive decline, or whether patients with preclinical brain disease are more likely to develop delirium. Future research is needed to understand the causal pathway between delirium and cognitive decline.

Successful aging after elective surgery II: Study design and methods.

BACKGROUND: The Successful Aging after Elective Surgery (SAGES) II study was designed to increase knowledge of the pathophysiology and linkages between delirium and dementia. We examine novel biomarkers potentially associated with delirium, including inflammation, Alzheimer's disease (AD) pathology and neurodegeneration, neuroimaging markers, and neurophysiologic markers. The goal of this paper is to describe the study design and methods for the SAGES II study. METHODS: The SAGES II study is a 5-year prospective observational study of 400-420 community dwelling persons, aged 65 years and older, assessed prior to scheduled surgery and followed daily throughout hospitalization to observe for development of delirium and other clinical outcomes. Delirium is measured with the Confusion Assessment Method (CAM), long form, after cognitive testing. Cognitive function is measured with a detailed neuropsychologic test battery, summarized as a weighted composite, the General Cognitive Performance (GCP) score. Other key measures include magnetic resonance imaging (MRI), transcranial magnetic stimulation (TMS)/electroencephalography (EEG), and Amyloid positron emission tomography (PET) imaging. We describe the eligibility criteria, enrollment flow, timing of assessments, and variables collected at baseline and during repeated assessments at 1, 2, 6, 12, and 18 months. RESULTS: This study describes the hospital and surgery-related variables, delirium, long-term cognitive decline, clinical outcomes, and novel biomarkers. In inter-rater reliability assessments, the CAM ratings (weighted kappa = 0.91, 95% confidence interval, CI = 0.74-1.0) in 50 paired assessments and GCP ratings (weighted kappa = 0.99, 95% CI 0.94-1.0) in 25 paired assessments. We describe procedures for data quality assurance and Covid-19 adaptations. CONCLUSIONS: This complex study presents an innovative effort to advance our understanding of the inter-relationship between delirium and dementia via novel biomarkers, collected in the context of major surgery in older adults. Strengths include the integration of MRI, TMS/EEG, PET modalities, and high-quality longitudinal data.

Linking self-perceived cognitive functioning questionnaires using item response theory: The subjective cognitive decline initiative.

OBJECTIVE: Self-perceived cognitive functioning, considered highly relevant in the context of aging and dementia, is assessed in numerous ways-hindering the comparison of findings across studies and settings. Therefore, the present study aimed to link item-level self-report questionnaire data from international aging studies. METHOD: We harmonized secondary data from 24 studies and 40 different questionnaires with item response theory (IRT) techniques using a graded response model with a Bayesian estimator. We compared item information curves to identify items with high measurement precision at different levels of the self-perceived cognitive functioning latent trait. Data from 53,030 neuropsychologically intact older adults were included, from 13 English language and 11 non-English (or mixed) language studies. RESULTS: We successfully linked all questionnaires and demonstrated that a single-factor structure was reasonable for the latent trait. Items that made the greatest contribution to measurement precision (i.e., "top items") assessed general and specific memory problems and aspects of executive functioning, attention, language, calculation, and visuospatial skills. These top items originated from distinct questionnaires and varied in format, range, time frames, response options, and whether they captured ability and/or change. CONCLUSIONS: This was the first study to calibrate self-perceived cognitive functioning data of geographically diverse older adults. The resulting item scores are on the same metric, facilitating joint or pooled analyses across international studies. Results may lead to the development of new self-perceived cognitive functioning questionnaires guided by psychometric properties, content, and other important features of items in our item bank. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Cognitive decline in the elderly: an analysis of population heterogeneity.

BACKGROUND: studies of cognitive ageing at the group level suggest that age is associated with cognitive decline; however, there may be individual differences such that not all older adults will experience cognitive decline. OBJECTIVE: to evaluate patterns of cognitive decline in a cohort of older adults initially free of dementia. DESIGN, SETTING AND SUBJECTS: elderly Catholic clergy members participating in the Religious Orders Study were followed for up to 15 years. Cognitive performance was assessed annually. METHODS: performance on a composite global measure of cognition was analysed using random effects models for baseline performance and change over time. A profile mixture component was used to identify subgroups with different cognitive trajectories over the study period. RESULTS: from a sample of 1,049 participants (mean age 75 years), three subgroups were identified based on the distribution of baseline performance and change over time. The majority (65%) of participants belonged to a slow decline class that did not experience substantial cognitive decline over the observation period [-0.04 baseline total sample standard deviation (SD) units/year]. About 27% experienced moderate decline (-0.19 SD/year), and 8% belonged to a class experiencing rapid decline (-0.57 SD/year). A subsample analysis revealed that when substantial cognitive decline does occur, the magnitude and rate of decline is correlated with neuropathological processes. CONCLUSIONS: in this sample, the most common pattern of cognitive decline is extremely slow, perceptible on a time scale measured by decades, not years. While in need of cross validation, these findings suggest that cognitive changes associated with ageing may be minimal and emphasise the importance of understanding the full range of age-related pathologies that may diminish brain function.

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.

Lower practice effects as a marker of cognitive performance and dementia risk: A literature review.

BACKGROUND: Practice effects (PEs) are improvements in performance after repeated exposure to test materials, and typically viewed as a source of bias in repeated cognitive assessments. We aimed to determine whether characterizing PEs could also provide a useful marker of early cognitive decline. METHODS: We conducted a systematic review of the literature, searching PsycInfo (Ebsco) and PubMed databases for articles studying PEs in aging and dementia populations. Articles published between 1920 and 2019 were included. RESULT: We identified 259 articles, of which 27 studied PEs as markers of cognitive performance. These studies consistently showed that smaller, less-robust PEs were associated with current diagnostic status and/or future cognitive decline. In addition, lower PEs were associated with Alzheimer's disease risk factors and neurodegeneration biomarkers. CONCLUSION: PEs provide a potentially useful marker of cognitive decline, and could prove valuable as part of a cost-effective strategy to select individuals who are at-risk for dementia for future interventions.

Development and validation of language and visuospatial composite scores in ADNI.

INTRODUCTION: Composite scores may be useful to summarize overall language or visuospatial functioning in studies of older adults. METHODS: We used item response theory to derive composite measures for language (ADNI-Lan) and visuospatial functioning (ADNI-VS) from the cognitive battery administered in the Alzheimer's Disease Neuroimaging Initiative (ADNI). We evaluated the scores among groups of people with normal cognition, mild cognitive impairment (MCI), and Alzheimer's disease (AD) in terms of responsiveness to change, association with imaging findings, and ability to differentiate between MCI participants who progressed to AD dementia and those who did not progress. RESULTS: ADNI-Lan and ADNI-VS were able to detect change over time and predict conversion from MCI to AD. They were associated with most of the pre-specified magnetic resonance imaging measures. ADNI-Lan had strong associations with a cerebrospinal fluid biomarker pattern. DISCUSSION: ADNI-Lan and ADNI-VS may be useful composites for language and visuospatial functioning in ADNI.