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.

Association of Loneliness With Change in Physical and Emotional Health of Older Adults During the COVID-19 Shutdown.

OBJECTIVES: To examine factors influencing loneliness and the effect of loneliness on physical and emotional health, in the context of the COVID-19 pandemic. DESIGN: Prospective, observational cohort. SETTING: Community-dwelling participants. PARTICIPANTS: Older adults (n = 238) enrolled in a longitudinal study. MEASUREMENTS: Interviews were completed July-December 2020. Loneliness was measured with the UCLA 3-item loneliness scale. Data including age, marriage, education, cognitive functioning, functional impairment, vision or hearing impairment, depression, anxiety, medical comorbidity, social network size, technology use, and activity engagement were collected. Health outcomes included self-rated health, and physical and mental composites from the 12-item Short Form Survey. Physical function was measured by a PROMIS-scaled composite score. RESULTS: Thirty-nine (16.4%) participants reported loneliness. Vulnerability factors for loneliness included age (RR = 1.08, 95% CI 1.02-1.14); impairment with instrumental activities of daily living (RR = 2.08, 95% CI 1.14-3.80); vision impairment (RR = 2.09, 95% CI 1.10-3.97); depression (RR = 1.34, 95% CI 1.25-1.43); and anxiety (RR = 1.92, 95% CI 1.55-2.39). Significant resilience factors included high cognitive functioning (RR = 0.88, 95% CI 0.83-0.94); large social network size (RR = 0.92, 95% CI 0.88-0.96); technology use (RR = 0.81, 95% CI 0.73-0.90); and social and physical activity engagement (RR = 0.91, 95% CI 0.85-0.98). Interaction analyses showed that larger social network size moderated the effect of loneliness on physical function (protective interaction effect, RR = 0.64, 95% CI 0.15-1.13, p <.01), and activity engagement moderated the effect of loneliness on mental health (protective interaction effect, RR = 0.65, 95% CI 0.25-1.05, p <.001). CONCLUSIONS: Resilience factors may mitigate the adverse health outcomes associated with loneliness. Interventions to enhance resilience may help to diminish the detrimental effects of loneliness and hold great importance for vulnerable older adults.

Patterns and Persistence of Perioperative Plasma and Cerebrospinal Fluid Neuroinflammatory Protein Biomarkers After Elective Orthopedic Surgery Using SOMAscan.

BACKGROUND: The neuroinflammatory response to surgery can be characterized by peripheral acute plasma protein changes in blood, but corresponding, persisting alterations in cerebrospinal fluid (CSF) proteins remain mostly unknown. Using the SOMAscan assay, we define acute and longer-term proteome changes associated with surgery in plasma and CSF. We hypothesized that biological pathways identified by these proteins would be in the categories of neuroinflammation and neuronal function and define neuroinflammatory proteome changes associated with surgery in older patients. METHODS: SOMAscan analyzed 1305 proteins in blood plasma (n = 14) and CSF (n = 15) samples from older patients enrolled in the Role of Inflammation after Surgery for Elders (RISE) study undergoing elective hip and knee replacement surgery with spinal anesthesia. Systems biology analysis identified biological pathways enriched among the surgery-associated differentially expressed proteins in plasma and CSF. RESULTS: Comparison of postoperative day 1 (POD1) to preoperative (PREOP) plasma protein levels identified 343 proteins with postsurgical changes ( P < .05; absolute value of the fold change [|FC|] > 1.2). Comparing postoperative 1-month (PO1MO) plasma and CSF with PREOP identified 67 proteins in plasma and 79 proteins in CSF with altered levels ( P < .05; |FC| > 1.2). In plasma, 21 proteins, primarily linked to immune response and inflammation, were similarly changed at POD1 and PO1MO. Comparison of plasma to CSF at PO1MO identified 8 shared proteins. Comparison of plasma at POD1 to CSF at PO1MO identified a larger number, 15 proteins in common, most of which are regulated by interleukin-6 (IL-6) or transforming growth factor beta-1 (TGFB1) and linked to the inflammatory response. Of the 79 CSF PO1MO-specific proteins, many are involved in neuronal function and neuroinflammation. CONCLUSIONS: SOMAscan can characterize both short- and long-term surgery-induced protein alterations in plasma and CSF. Acute plasma protein changes at POD1 parallel changes in PO1MO CSF and suggest 15 potential biomarkers for longer-term neuroinflammation that warrant further investigation.

One-year Medicare costs associated with delirium in older hospitalized patients with and without Alzheimer's disease dementia and related disorders.

INTRODUCTION: One-year health-care costs associated with delirium in older hospitalized patients with and without Alzheimer's disease and related dementias (ADRD) have not been examined previously. METHODS: Medicare costs were determined prospectively at discharge, and at 30, 90, and 365 days in a cohort (n = 311) of older adults after hospital admission. RESULTS: Seventy-six (24%) patients had ADRD and were more likely to develop delirium (51% vs. 24%, P < 0.001) and die within 1 year (38% vs. 21%, P = 0.002). In ADRD patients with versus without delirium, adjusted mean difference in costs associated with delirium were $34,828; most of the excess costs were incurred between 90 and 365 days (P = 0.03). In non-ADRD patients, delirium was associated with increased costs at all timepoints. Excess costs associated with delirium in ADRD patients increased progressively over 1 year, whereas in non-ADRD patients the increase was consistent across time periods. DISCUSSION: Our findings highlight the complexity of health-care costs for ADRD patients who develop delirium, a potentially preventable source of expenditures. HIGHLIGHTS: Novel examination of health-care costs of delirium in persons with and without Alzheimer's disease and related dementias (ADRD). Increased 1-year costs of $34,828 in ADRD patients with delirium (vs. without). Increased costs for delirium in ADRD occur later during the 365-day study period. For ADRD patients, cost differences between those with and without delirium increased over 1 year. For non-ADRD patients, the parallel cost differences were consistent over time.

Parental Education and Delirium Risk after Surgery in Older Adults.

OBJECTIVES: Efforts to conceptualize risk factors for postoperative delirium in older adults have focused on the time proximate to the episode, but how early-life exposures influence delirium risk is poorly understood. METHODS: An observational cohort of 547 patients aged 70+undergoing major non-cardiac surgery at two academic medical centers in Boston. Demographic characteristics, cognition, parental education, health, and participation in cognitively stimulating activities were assessed prior to surgery. Delirium incidence and severity were measured daily during hospitalization. RESULTS: Higher paternal education was associated with significantly lower incidence of delirium (X2(1, N =547)=8.35, p <.001; odds ratio OR=.93, 95% CI, .87 to .98) and inversely associated with delirium severity (r(545)=-.13, p <.001). Higher maternal education was associated with lower delirium incidence but did not reach statistical significance. The effect of paternal education on delirium incidence was independent of the patient's education, estimated premorbid intelligence, medical comorbidities, neighborhood disadvantage, and participation in cognitively stimulating activities (X2(2, N =547)=31.22, p <.001). CONCLUSIONS: Examining early-life exposures may yield unique insights into the risks and pathogenesis of delirium. CLINICAL IMPLICATIONS: Evaluating long-term factors that increase vulnerability to delirium may improve our ability to calculate risk. It may guide clinical decision-making and inform pre- and post-operative recommendations.

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.

Identification of Plasma Proteome Signatures Associated With Surgery Using SOMAscan.

OBJECTIVES: To characterize the proteomic signature of surgery in older adults and association with postoperative outcomes. SUMMARY OF BACKGROUND DATA: Circulating plasma proteins can reflect the physiological response to and clinical outcomes after surgery. METHODS: Blood plasma from older adults undergoing elective surgery was analyzed for 1305 proteins using SOMAscan. Surgery-associated proteins underwent Ingenuity Pathways Analysis. Selected surgery-associated proteins were independently validated using Luminex or enzyme-linked immunosorbent assay methods. Generalized linear models estimated correlations with postoperative outcomes. RESULTS: Plasma from a subcohort (n = 36) of the Successful Aging after Elective Surgery (SAGES) study was used for SOMAscan. Systems biology analysis of 110 proteins with Benjamini-Hochberg (BH) corrected P value ≤0.01 and an absolute foldchange (|FC|) ≥1.5 between postoperative day 2 (POD2) and preoperative (PREOP) identified functional pathways with major effects on pro-inflammatory proteins. Chitinase-3-like protein 1 (CHI3L1), C-reactive protein (CRP), and interleukin-6 (IL-6) were independently validated in separate validation cohorts from SAGES (n = 150 for CRP, IL-6; n = 126 for CHI3L1). Foldchange CHI3L1 and IL-6 were associated with increased postoperative complications [relative risk (RR) 1.50, 95% confidence interval (95% CI) 1.21-1.85 and RR 1.63, 95% CI 1.18-2.26, respectively], length of stay (RR 1.35, 95% CI 0.77-1.92 and RR 0.98, 95% CI 0.52-1.45), and risk of discharge to postacute facility (RR 1.15, 95% CI 1.04-1.26 and RR 1.11, 95% CI 1.04-1.18); POD2 and PREOP CRP difference was associated with discharge to postacute facility (RR 1.14, 95% CI 1.04-1.25). CONCLUSION: SOMAscan can identify novel and clinically relevant surgery-induced protein changes. Ultimately, proteomics may provide insights about pathways by which surgical stress contributes to postoperative outcomes.

Plasma and cerebrospinal fluid inflammation and the blood-brain barrier in older surgical patients: the Role of Inflammation after Surgery for Elders (RISE) study.

BACKGROUND: Our understanding of the relationship between plasma and cerebrospinal fluid (CSF) remains limited, which poses an obstacle to the identification of blood-based markers of neuroinflammatory disorders. To better understand the relationship between peripheral and central nervous system (CNS) markers of inflammation before and after surgery, we aimed to examine whether surgery compromises the blood-brain barrier (BBB), evaluate postoperative changes in inflammatory markers, and assess the correlations between plasma and CSF levels of inflammation. METHODS: We examined the Role of Inflammation after Surgery for Elders (RISE) study of adults aged ≥ 65 who underwent elective hip or knee surgery under spinal anesthesia who had plasma and CSF samples collected at baseline and postoperative 1 month (PO1MO) (n = 29). Plasma and CSF levels of three inflammatory markers previously identified as increasing after surgery were measured using enzyme-linked immunosorbent assay: interleukin-6 (IL-6), C-reactive protein (CRP), and chitinase 3-like protein (also known as YKL-40). The integrity of the BBB was computed as the ratio of CSF/plasma albumin levels (Qalb). Mean Qalb and levels of inflammation were compared between baseline and PO1MO. Spearman correlation coefficients were used to determine the correlation between biofluids. RESULTS: Mean Qalb did not change between baseline and PO1MO. Mean plasma and CSF levels of CRP and plasma levels of YKL-40 and IL-6 were higher on PO1MO relative to baseline, with a disproportionally higher increase in CRP CSF levels relative to plasma levels (CRP tripled in CSF vs. increased 10% in plasma). Significant plasma-CSF correlations for CRP (baseline r = 0.70 and PO1MO r = 0.89, p < .01 for both) and IL-6 (PO1MO r = 0.48, p < .01) were observed, with higher correlations on PO1MO compared with baseline. CONCLUSIONS: In this elective surgical sample of older adults, BBB integrity was similar between baseline and PO1MO, plasma-CSF correlations were observed for CRP and IL-6, plasma levels of all three markers (CRP, IL-6, and YKL-40) increased from PREOP to PO1MO, and CSF levels of only CRP increased between the two time points. Our identification of potential promising plasma markers of inflammation in the CNS may facilitate the early identification of patients at greatest risk for neuroinflammation and its associated adverse cognitive outcomes.

Association of Plasma Neurofilament Light with Postoperative Delirium.

OBJECTIVE: To examine the association of the plasma neuroaxonal injury markers neurofilament light (NfL), total tau, glial fibrillary acid protein, and ubiquitin carboxyl-terminal hydrolase L1 with delirium, delirium severity, and cognitive performance. METHODS: Delirium case-no delirium control (n = 108) pairs were matched by age, sex, surgery type, cognition, and vascular comorbidities. Biomarkers were measured in plasma collected preoperatively (PREOP), and 2 days (POD2) and 30 days postoperatively (PO1MO) using Simoa technology (Quanterix, Lexington, MA). The Confusion Assessment Method (CAM) and CAM-S (Severity) were used to measure delirium and delirium severity, respectively. Cognitive function was measured with General Cognitive Performance (GCP) scores. RESULTS: Delirium cases had higher NfL on POD2 and PO1MO (median matched pair difference = 16.2pg/ml and 13.6pg/ml, respectively; p < 0.05). Patients with PREOP and POD2 NfL in the highest quartile (Q4) had increased risk for incident delirium (adjusted odds ratio [OR] = 3.7 [95% confidence interval (CI) = 1.1-12.6] and 4.6 [95% CI = 1.2-18.2], respectively) and experienced more severe delirium, with sum CAM-S scores 7.8 points (95% CI = 1.6-14.0) and 9.3 points higher (95% CI = 3.2-15.5). At PO1MO, delirium cases had continued high NfL (adjusted OR = 9.7, 95% CI = 2.3-41.4), and those with Q4 NfL values showed a -2.3 point decline in GCP score (-2.3 points, 95% CI = -4.7 to -0.9). INTERPRETATION: Patients with the highest PREOP or POD2 NfL levels were more likely to develop delirium. Elevated NfL at PO1MO was associated with delirium and greater cognitive decline. These findings suggest NfL may be useful as a predictive biomarker for delirium risk and long-term cognitive decline, and once confirmed would provide pathophysiological evidence for neuroaxonal injury following delirium. ANN NEUROL 2020;88:984-994.

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.

Predictors of Caregiver Burden in Delirium: Patient and Caregiver Factors.

The current study examined the association of patient factors, patient/caregiver relationships, and living arrangements with caregiver burden due to delirium. The sample included a subset (N = 207) of hospitalized medical and surgical patients (aged >70 years) enrolled in the Better Assessment of Illness Study and their care-givers. The majority of caregivers were female (57%) and married (43%), and 47% reported living with the patient. Delirium occurred in 22% of the sample, and delirium severity, pre-existing cognitive impairment, and impairment of any activities of daily living (ADL) were associated with higher caregiver burden. However, only the ADL impairment of needing assistance with transfers was independently significantly associated with higher burden (p < 0.01). Child, child-in-law, and other relatives living with or apart from the patient reported significantly higher caregiver burden compared to spouse/partners (p < 0.01), indicating caregiver relationship and living arrangement are associated with burden. Future studies should examine additional factors contributing to delirium burden. [Journal of Gerontological Nursing, 47(9), 32-39.].

Preoperative Cognitive Abnormality, Intraoperative Electroencephalogram Suppression, and Postoperative Delirium: A Mediation Analysis.

BACKGROUND: Postoperative delirium is a common complication that hinders recovery after surgery. Intraoperative electroencephalogram suppression has been linked to postoperative delirium, but it is unknown if this relationship is causal or if electroencephalogram suppression is merely a marker of underlying cognitive abnormalities. The hypothesis of this study was that intraoperative electroencephalogram suppression mediates a nonzero portion of the effect between preoperative abnormal cognition and postoperative delirium. METHODS: This is a prespecified secondary analysis of the Electroencephalography Guidance of Anesthesia to Alleviate Geriatric Syndromes (ENGAGES) randomized trial, which enrolled patients age 60 yr or older undergoing surgery with general anesthesia at a single academic medical center between January 2015 and May 2018. Patients were randomized to electroencephalogram-guided anesthesia or usual care. Preoperative abnormal cognition was defined as a composite of previous delirium, Short Blessed Test cognitive score greater than 4 points, or Eight Item Interview to Differentiate Aging and Dementia score greater than 1 point. Duration of intraoperative electroencephalogram suppression was defined as number of minutes with suppression ratio greater than 1%. Postoperative delirium was detected via Confusion Assessment Method or chart review on postoperative days 1 to 5. RESULTS: Among 1,113 patients, 430 patients showed evidence of preoperative abnormal cognition. These patients had an increased incidence of postoperative delirium (151 of 430 [35%] vs.123 of 683 [18%], P < 0.001). Of this 17.2% total effect size (99.5% CI, 9.3 to 25.1%), an absolute 2.4% (99.5% CI, 0.6 to 4.8%) was an indirect effect mediated by electroencephalogram suppression, while an absolute 14.8% (99.5% CI, 7.2 to 22.5%) was a direct effect of preoperative abnormal cognition. Randomization to electroencephalogram-guided anesthesia did not change the mediated effect size (P = 0.078 for moderation). CONCLUSIONS: A small portion of the total effect of preoperative abnormal cognition on postoperative delirium was mediated by electroencephalogram suppression. Study precision was too low to determine if the intervention changed the mediated effect.

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.

Apolipoprotein E genotype and the association between C-reactive protein and postoperative delirium: Importance of gene-protein interactions.

INTRODUCTION: Apolipoprotein E (APOE) status may modify the risk of postoperative delirium conferred by inflammation. METHODS: We tested whether APOE modifies the established association between C-reactive protein (CRP) and delirium incidence, severity, and duration in 553 noncardiac surgical patients aged 70 and older. High postoperative plasma CRP (≥234.12 mg/L) was defined by the highest sample-based quartile. Delirium was determined using the Confusion Assessment Method and chart review, and severity was determined by the Confusion Assessment Method-Severity score. RESULTS: APOE ε4 carrier prevalence was 19%, and postoperative delirium occurred in 24%. The relationship between CRP and delirium incidence, severity, and duration differed by ε4 status. Among ε4 carriers, there was a strong relationship between high CRP (vs. low CRP) and delirium incidence (relative risk [95% confidence interval], 3.0 [1.4-6.7]); however, no significant association was observed among non-ε4 carriers (relative risk [95% CI], 1.2 [0.8-1.7]). DISCUSSION: Our findings raise the possibility that APOE ε4 carrier status may modify the relationship between postoperative day 2 CRP levels and postoperative delirium.

Postoperative Delirium and Postoperative Cognitive Dysfunction: Overlap and Divergence.

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

Use of an expert panel to identify domains and indicators of delirium severity.

PURPOSE: Our purpose was to create a content domain framework for delirium severity to inform item development for a new instrument to measure delirium severity. METHODS: We used an established, multi-stage instrument development process during which expert panelists discussed best approaches to measure delirium severity and identified related content domains. We conducted this work as part of the Better ASsessment of ILlness (BASIL) study, a prospective, observational study aimed at developing and testing measures of delirium severity. Our interdisciplinary expert panel consisted of twelve national delirium experts and four expert members of the core research group. Over a one-month period, experts participated in two rounds of review. RESULTS: Experts recommended that the construct of delirium severity should reflect both the phenomena and the impact of delirium to create an accurate, patient-centered instrument useful to interdisciplinary clinicians and family caregivers. Final content domains were Cognitive, Level of consciousness, Inattention, Psychiatric-Behavioral, Emotional dysregulation, Psychomotor features, and Functional. Themes debated by experts included reconciling clinical geriatrics and psychiatric content, mapping symptoms to one specific domain, and accurate capture of unclear clinical presentations. CONCLUSIONS: We believe this work represents the first application of instrument development science to delirium. The identified content domains are inclusive of various, wide-ranging domains of delirium severity and are reflective of a consistent framework that relates delirium severity to potential clinical outcomes. Our content domain framework provides a foundation for development of delirium severity instruments that can help improve care and quality of life for patients with delirium.

The Better Assessment of Illness Study for Delirium Severity: Study Design, Procedures, and Cohort Description.

BACKGROUND/OBJECTIVES: To describe the design, procedures, and cohort for the Better ASsessment of ILlness -(BASIL) study, which is conducted to develop and test new delirium severity measures, compare them with existing measures, and examine related clinical outcomes. METHODS: Prospective cohort study with 1 year follow-up of study participants at a large teaching hospital in Boston, Massachusetts. After brief cognitive testing and the Delirium Symptom Interview, delirium and delirium severity were rated daily in the hospital using the Confusion Assessment Method (CAM) and CAM-Severity score, the Delirium Rating Scale-Revised-98 (DRS-R-98), and the Memorial Delirium Assessment Scale (MDAS). Other key study variables included comorbidity, physical function (basic and instrumental activities of daily living [ADL]), ratings of subjective health and well-being, and clinical outcomes (length of stay, 30 day rehospitalization, nursing home admission, healthcare utilization). Follow-up interviews occurred at 1- and 12-month with patients and families. In 42 patient interviews, inter-rater reliability for key variables was assessed. RESULTS: Of 768 eligible patients approached, 469 were screened and 352 enrolled, yielding an overall study response rate of 67% for potentially eligible participants. The mean participant was 80.3 years old (SD 6.8) and 203 (58%) were female. The majority of patients were medically complex with Charlson Comorbidity Scores ≥2 (192 patients, 55%), and 102 (29%) met criteria for dementia. Inter-rater reliability assessments (n = 42 pairs) were high for overall ratings of presence or absence of delirium by CAM (κ = 1.0), delirium severity by DRS-R-98 and MDAS (weighted kappa, κ = 1.0 for each) and for ADL impairment (κ = 1.0). For eligible participants at each time point, 278 out of 308 (90%) completed the 1-month follow-up and 132 out of 256 (53%) have completed the 12-month follow-up to date, which is still in progress. Among those who completed interviews, there was only 1-3% missing data on most major outcomes (delirium, basic ADL, and readmission). CONCLUSION: The BASIL study presents an innovative effort to advance the conceptualization and measurement of delirium severity. Unique strengths include the diverse cohort with complete high quality data and longitudinal follow-up, along with detailed collection of multiple delirium measures daily during hospitalization.

Correction for retest effects across repeated measures of cognitive functioning: a longitudinal cohort study of postoperative delirium.

BACKGROUND: Few studies have compared methods to correct for retest effects or practice effects in settings where an acute event could influence test performance, such as major surgery. Our goal in this study was to evaluate the use of different methods to correct for the effects of practice or retest on repeated test administration in the context of an observational study of older adults undergoing elective surgery. METHODS: In a cohort of older surgical patients (N = 560) and a non-surgical comparison group (N = 118), we compared changes on repeated cognitive testing using a summary measure of general cognitive performance (GCP) between patients who developed post-operative delirium and those who did not. Surgical patients were evaluated pre-operatively and at 1, 2, 6, 12, and 18 months following surgery. Inferences from linear mixed effects models using four approaches were compared: 1) no retest correction, 2) mean-difference correction, 3) predicted-difference correction, and 4) model-based correction. RESULTS: Using Approaches 1 or 4, which use uncorrected data, both surgical groups appeared to improve or remain stable after surgery. In contrast, Approaches 2 and 3, which dissociate retest and surgery effects by using retest-adjusted GCP scores, revealed an acute decline in performance in both surgical groups followed by a recovery to baseline. Relative differences between delirium groups were generally consistent across all approaches: the delirium group showed greater short- and longer-term decline compared to the group without delirium, although differences were attenuated after 2 months. Standard errors and model fit were also highly consistent across approaches. CONCLUSION: All four approaches would lead to nearly identical inferences regarding relative mean differences between groups experiencing a key post-operative outcome (delirium) but produced qualitatively different impressions of absolute performance differences following surgery. Each of the four retest correction approaches analyzed in this study has strengths and weakness that should be evaluated in the context of future studies. Retest correction is critical for interpretation of absolute cognitive performance measured over time and, consequently, for advancing our understanding of the effects of exposures such as surgery, hospitalization, acute illness, and delirium.

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.

Effects of arterial transit delay on cerebral blood flow quantification using arterial spin labeling in an elderly cohort.

PURPOSE: To investigate whether measurement of arterial transit time (ATT) can improve the accuracy of arterial spin labeling (ASL) cerebral blood flow (CBF) quantification in an elderly cohort due to the potentially prolonged ATT in the cohort. MATERIALS AND METHODS: We employed a 1-minute, low-resolution (12 mm in-plane), sequential multidelay ATT measurement (both with and without vessel suppression) approach to characterize and correct ATT errors in CBF imaging of an elderly, clinical cohort. In all, 140 nondemented subjects greater than 70 years old were imaged at 3T with a single delay, volumetric continuous ASL sequence and also with the fast ATT measurement method. Nine healthy young subjects (28 ± 6 years old) were also imaged. RESULTS: ATTs measured without vessel suppression (superior frontal: 1.51 ± 0.27 sec) in the elderly were significantly shorter than those with suppression (P < 0.0001). Correction of CBF for ATT significantly increased average CBF in multiple brain regions where ATT was longer than the postlabeling delay (P < 0.01) and decreased intersubject variability of CBF in frontal, parietal, and occipital regions (P < 10-8 ). Measured ATT with vessel suppression was significantly longer in the elderly subjects (eg, superior frontal: 1.76 ± 0.25 sec) compared to the younger adults (superior frontal: 1.59 ± 0.19 sec) in basal ganglia and frontal cortical regions (P < 0.05). CONCLUSION: The ATT measurement is beneficial for imaging of elderly clinical populations. If ATT mapping is not feasible or available, postlabeling delays of 2-2.3 seconds should be used for elderly populations based on longest measured regional ATTs. LEVEL OF EVIDENCE: 1 J. Magn. Reson. Imaging 2017;45:472-481.