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.

Trends in use of antipsychotics and psychoactive drugs in older patients after major surgery.

BACKGROUND: Professional society guidelines recommend limiting the use of antipsychotics in older patients with postoperative delirium. How these recommendations affected the use of antipsychotics and other psychoactive drugs in the postoperative period has not been studied. METHODS: This retrospective cohort study included patients 65 years or older without psychiatric diagnoses who underwent major surgery in community hospitals (CHs) and academic medical centers (AMCs) in the United States. The outcome was the rate of hospital days exposed to antipsychotics, antidepressants, antiepileptics, benzodiazepines, hypnotics, and selective alpha-2 receptor agonist dexmedetomidine in the postoperative period by hospital type. RESULTS: The study included 4,098,431 surgical admissions from CHs (mean age 75.0 [standard deviation, 7.1] years; 50.8% female) during 2008-2018 and 2,310,529 surgical admissions from AMCs (75.0 [7.4] years; 49.4% female) during 2009-2018. In the intensive care unit (ICU) setting, the number of exposed days per 1000 hospital-days declined for haloperidol (CHs: 33-21 days [p < 0.01]; AMCs: 24-15 days [p < 0.01]) and benzodiazepines (CHs: 261-136 days [p < 0.01]; AMCs: 150-77 days [p < 0.01]). The use of atypical antipsychotics, antidepressants, antiepileptics, and dexmedetomidine increased, while hypnotic use varied by the hospital type. In the non-ICU setting, the rate declined for haloperidol in CHs but not in AMCs (CHs: 10-6 days [p < 0.01]; AMCs: 4-3 days [p = 0.52]) and for benzodiazepines in both settings (CHs: 126-56 days [p < 0.01]; AMCs: 30-27 days [p < 0.01]). The use of antiepileptics and antidepressants increased, while the use of atypical antipsychotics and hypnotics varied by the hospital type. CONCLUSIONS: The use of haloperidol and benzodiazepines in the postoperative period declined at both CHs and AMCs. These trends coincided with the increasing use of other psychoactive drugs.

Comparative Safety Analysis of Oral Antipsychotics for In-Hospital Adverse Clinical Events in Older Adults After Major Surgery : A Nationwide Cohort Study.

BACKGROUND: Antipsychotics are commonly used to manage postoperative delirium. Recent studies reported that haloperidol use has declined, and atypical antipsychotic use has increased over time. OBJECTIVE: To compare the risk for in-hospital adverse events associated with oral haloperidol, olanzapine, quetiapine, and risperidone in older patients after major surgery. DESIGN: Retrospective cohort study. SETTING: U.S. hospitals in the Premier Healthcare Database. PATIENTS: 17 115 patients aged 65 years and older without psychiatric disorders who were prescribed an oral antipsychotic drug after major surgery from 2009 to 2018. INTERVENTIONS: Haloperidol (≤4 mg on the day of initiation), olanzapine (≤10 mg), quetiapine (≤150 mg), and risperidone (≤4 mg). MEASUREMENTS: The risk ratios (RRs) for in-hospital death, cardiac arrhythmia events, pneumonia, and stroke or transient ischemic attack (TIA) were estimated after propensity score overlap weighting. RESULTS: The weighted population had a mean age of 79.6 years, was 60.5% female, and had in-hospital death of 3.1%. Among the 4 antipsychotics, quetiapine was the most prescribed (53.0% of total exposure). There was no statistically significant difference in the risk for in-hospital death among patients treated with haloperidol (3.7%, reference group), olanzapine (2.8%; RR, 0.74 [95% CI, 0.42 to 1.27]), quetiapine (2.6%; RR, 0.70 [CI, 0.47 to 1.04]), and risperidone (3.3%; RR, 0.90 [CI, 0.53 to 1.41]). The risk for nonfatal clinical events ranged from 2.0% to 2.6% for a cardiac arrhythmia event, 4.2% to 4.6% for pneumonia, and 0.6% to 1.2% for stroke or TIA, with no statistically significant differences by treatment group. LIMITATION: Residual confounding by delirium severity; lack of untreated group; restriction to oral low-to-moderate dose treatment. CONCLUSION: These results suggest that atypical antipsychotics and haloperidol have similar rates of in-hospital adverse clinical events in older patients with postoperative delirium who receive an oral low-to-moderate dose antipsychotic drug. PRIMARY FUNDING SOURCE: National Institute on Aging.

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.

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.

Perioperative Gabapentin Use and In-Hospital Adverse Clinical Events Among Older Adults After Major Surgery.

Importance: Gabapentin has been increasingly used as part of a multimodal analgesia regimen to reduce opioid use in perioperative pain management. However, the safety of perioperative gabapentin use among older patients remains uncertain. Objective: To examine in-hospital adverse clinical events associated with perioperative gabapentin use among older patients undergoing major surgery. Design, Setting, and Participants: This retrospective cohort study using data from the Premier Healthcare Database included patients aged 65 years or older who underwent major surgery at US hospitals within 7 days of hospital admission from January 1, 2009, to March 31, 2018, and did not use gabapentin before surgery. Data were analyzed from June 14, 2021, to May 23, 2022. Exposures: Gabapentin use within 2 days after surgery. Main Outcomes and Measures: The primary outcome was delirium, identified using diagnosis codes, and secondary outcomes were new antipsychotic use, pneumonia, and in-hospital death between postoperative day 3 and hospital discharge. To reduce confounding, 1:1 propensity score matching was performed. Risk ratios (RRs) and risk differences (RDs) with 95% CIs were estimated. Results: Among 967 547 patients before propensity score matching (mean [SD] age, 76.2 [7.4] years; 59.6% female), the rate of perioperative gabapentin use was 12.3% (119 087 patients). After propensity score matching, 237 872 (118 936 pairs) gabapentin users and nonusers (mean [SD] age, 74.5 [6.7] years; 62.7% female) were identified. Compared with nonusers, gabapentin users had increased risk of delirium (4040 [3.4%] vs 3148 [2.6%]; RR, 1.28 [95% CI, 1.23-1.34]; RD, 0.75 [95% CI, 0.75 [0.61-0.89] per 100 persons), new antipsychotic use (944 [0.8%] vs 805 [0.7%]; RR, 1.17 [95% CI, 1.07-1.29]; RD, 0.12 [95% CI, 0.05-0.19] per 100 persons), and pneumonia (1521 [1.3%] vs 1368 [1.2%]; RR, 1.11 [95% CI, 1.03-1.20]; RD, 0.13 [95% CI, 0.04-0.22] per 100 persons), but there was no difference in in-hospital death (362 [0.3%] vs 354 [0.2%]; RR, 1.02 [95% CI, 0.88-1.18]; RD, 0.00 [95% CI, -0.04 to 0.05] per 100 persons). Risk of delirium among gabapentin users was greater in subgroups with high comorbidity burden than in those with low comorbidity burden (combined comorbidity index <4 vs ≥4: RR, 1.20 [95% CI, 1.13-1.27] vs 1.40 [95% CI, 1.30-1.51]; RD, 0.41 [95% CI, 0.28-0.53] vs 2.66 [95% CI, 2.08-3.24] per 100 persons) and chronic kidney disease (absence vs presence: RR, 1.26 [95% CI, 1.19-1.33] vs 1.38 [95% CI, 1.27-1.49]; RD, 0.56 [95% CI, 0.42-0.69] vs 1.97 [95% CI, 1.49-2.46] per 100 persons). Conclusion and Relevance: In this cohort study, perioperative gabapentin use was associated with increased risk of delirium, new antipsychotic use, and pneumonia among older patients after major surgery. These results suggest careful risk-benefit assessment before prescribing gabapentin for perioperative pain management.

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.

Transcranial magnetic stimulation (TMS) for geriatric depression.

BACKGROUND: The prevalence of treatment-resistant geriatric depression (GD) highlights the need for treatments that preserve cognitive functions and recognize polypharmacy in elderly, yet effectively reduce symptom burden. Transcranial magnetic stimulation (TMS) is a proven intervention for treatment-resistant depression in younger adults but the efficacy of TMS to treat depressed older adults is still unclear. This review provides an updated view on the efficacy of TMS treatment for GD, discusses methodological differences between trials in TMS application, and explores avenues for optimization of TMS treatment in the context of the ageing brain. METHODS: A systematic review was conducted to identify published literature on the antidepressant efficacy of TMS for GD. Databases PubMed, Embase, and PsycINFO were searched for English language articles in peer-reviewed journals in March 2021. RESULTS: Seven randomized controlled trials (RCTs) (total n = 260, active n = 148, control n = 112) and seven uncontrolled trials (total n = 160) were included. Overall, we found substantial variability in the clinical response, ranging from 6.7% to 54.3%. CONCLUSIONS: The reviewed literature highlights large heterogeneity among studies both in terms of the employed TMS dosage and the observed clinical efficacy. This highlights the need for optimizing TMS dosage by recognizing the unique clinical features of GD. We showcase a set of novel approaches for the optimization of the TMS protocol for depression and discuss the possibility for a standardized TMS protocol tailored for the treatment of GD.

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.

Safety and Feasibility of Tele-Supervised Home-Based Transcranial Direct Current Stimulation for Major Depressive Disorder.

Major depressive disorder (MDD) is a worldwide cause of disability in older age, especially during the covid pandemic. Transcranial direct current stimulation (tDCS) is a non-invasive neuromodulation technique that has shown encouraging efficacy for treatment of depression. Here, we investigate the feasibility of an innovative protocol where tDCS is administered within the homes of older adults with MDD (patient participants) with the help of a study companion (i.e. caregiver). We further analyze the feasibility of a remotely-hosted training program that provides the knowledge and skills to administer tDCS at home, without requiring them to visit the lab. We also employed a newly developed multi-channel tDCS system with real-time monitoring designed to guarantee the safety and efficacy of home-based tDCS. Patient participants underwent a total of 37 home-based tDCS sessions distributed over 12 weeks. The protocol consisted of three phases each lasting four weeks: an acute phase, containing 28 home-based tDCS sessions, a taper phase containing nine home-based tDCS sessions, and a follow up phase, with no stimulation sessions. We found that the home-based, remotely-supervised, study companion administered, multi-channel tDCS protocol for older adults with MDD was feasible and safe. Further, the study introduces a novel training program for remote instruction of study companions in the administration of tDCS. Future research is required to determine the translatability of these findings to a larger sample. Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT04799405?term=NCT04799405&draw=2&rank=1, identifier NCT04799405.

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.

The Psychopharmacology Algorithm Project at the Harvard South Shore Program: An update on management of behavioral and psychological symptoms in dementia.

Geriatric patients with dementia frequently present with agitation, aggression, psychosis, and other behavioral and psychological symptoms of dementia (BPSD). We present an update of our previously published algorithms for the use of psychopharmacologic agents in these patients taking into account more recent studies and findings in meta-analyses, reviews, and other published algorithms. We propose three algorithms: BPSD in an emergent, urgent, and non-urgent setting. In the emergent setting when intramuscular (IM) administration is necessary, the first-line recommendation is for olanzapine (since IM aripiprazole, previously favored, is no longer available) and haloperidol injection is the second choice, followed by possible consideration of an IM benzodiazepine. In the urgent setting, the first line would be oral second-generation antipsychotics (SGAs) aripiprazole and risperidone. Perhaps next could be then prazosin, and lastly electroconvulsive therapy is a consideration. There are risks associated with these agents, and adverse effects can be severe. Dosing strategies, discontinuation considerations, and side effects are discussed. In the non-emergent setting, medications are proposed for use in the following order: trazodone, donepezil and memantine, antidepressants such as escitalopram and sertraline, SGAs, prazosin, and carbamazepine. Other options with less support but potential future promise are discussed.

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.

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.