Refining Research Diagnostic Criteria for Catatonia Among Delirium, Medical, Affective, and Psychosis Patient Groups.

OBJECTIVE: The authors proposed catatonia diagnostic criteria that require the presence of three neuropsychiatric symptom clusters, rated over 24 hours; this system differs from other symptom clustering proposals and is intended to increase diagnostic rigor over Bush-Francis Catatonia Rating Scale (BFCRS) or DSM-5 criteria. METHODS: By applying new BFCRS item score thresholds, symptoms were clustered into three categories to comprise the Research Diagnostic Criteria for Catatonia (RDCC): akinesia (criterion A), unusual motor signs (criterion B), and behavioral signs (criterion C). RDCC symptom clusters were analyzed in four prospectively evaluated patient groups (delirium, medical, affective, and psychosis) (N=341). RESULTS: Use of the RDCC, compared with the DSM-5-TR and BFCRS, resulted in far fewer diagnoses of catatonia in the four patient groups: medical, N=1 out of 42 (2%); affective, N=1 out of 45 (2%); psychosis, N=3 out of 53 (6%); and delirium, N=0 out of 201. Permutations of the RDCC with more relaxed criteria were assessed, requiring either symptom thresholds or numbers of symptoms to meet criteria, resulting in catatonia rate gradations between those obtained with the RDCC and those obtained with current systems. The Cochrane Q test found that the DSM-5-TR was not dissimilar to the RDCC, if fulfilling numerical thresholds for criteria A-C, although any level of symptom severity was allowed. Confirmatory factor analysis with three goodness-of-fit indexes validated the RDCC. CONCLUSIONS: The RDCC requires akinetic symptoms on the basis of literature demonstrating their high BFCRS prevalence and exploratory factor analysis co-loadings, plus symptoms from unusual motor and behavioral signs. Compared with current lenient diagnostic approaches, having the symptoms required by the RDCC produced lower catatonia rates in the psychosis, affective, and medical groups and revealed no patients with catatonia in the delirium group. Subdividing DSM-5-TR symptoms into several different criteria may improve diagnosis. RDCC symptom clusters are both research data-based and amenable to further research for validation.

Practical Application of a Battery of Brief Tools to Evaluate Geriatric Medical Inpatients for the Three Ds.

OBJECTIVE: The investigators aimed to identify the clinical characteristics of patients with or without delirium and preexisting depression, dementia, both, or neither by using validated tools easily administered in clinical practice. METHODS: In this cross-sectional prospective observational study conducted in Medellín, Colombia, 200 geriatric inpatients were evaluated with the Delirium Diagnostic Tool-Provisional (DDT-Pro), Informant Questionnaire on Cognitive Decline in the Elderly, Hachinski Ischemic Scale, Cornell Scale for Depression in Dementia, and Charlson Comorbidity Index-short form. Delirium motor subtype, mortality, and length of hospital stay were assessed. RESULTS: The study included 134 patients without delirium (67%), 14 with delirium only (7%), 16 with delirium and dementia (8%), 13 with delirium and depression (7%), and 23 with delirium, dementia, and depression (the three Ds) (12%). Prevalence rates of dementia (59%) and depression (55%) among 66 patients with delirium were higher than prevalence rates among patients without delirium (13% and 28%, respectively), suggesting that both conditions are risk factors. Main medical diagnoses, mortality, and dementia type did not differ among groups. Motor subtypes were similar among delirium groups. Patients in the delirium groups, except those in the delirium and depression group, were older than patients without delirium. Medical burden was highest among the patients with delirium and dementia and those with all three conditions. Delirium and dementia were more severe when comorbid with each other. Depression was most severe among patients with delirium and depression. Patients with all three conditions had a longer length of hospital stay than those without delirium. CONCLUSIONS: Using brief tools to detect dementia and depression in conjunction with the DDT-Pro to assess delirium diagnosis and severity is feasible and enables a more in-depth evaluation of elderly hospitalized patients. Because previous longitudinal research suggests that these comorbid conditions influence prognosis following a delirium episode, better identification of the three Ds offers proactive interventional opportunities. Depression is an underrecognized risk factor for delirium.

Etiologies of Delirium in Consecutive COVID-19 Inpatients and the Relationship Between Severity of Delirium and COVID-19 in a Prospective Study With Follow-Up.

OBJECTIVE: The investigators aimed to describe delirium etiologies and clinical characteristics, as well as the relationship between COVID-19 and delirium severities, at baseline and follow-up after delirium improvement among patients with SARS-CoV-2 infection. METHODS: A longitudinal study of 20 consecutive critically ill, delirious COVID-19 inpatients, assessed with the Charlson Comorbidity Index-Short Form (CCI-SF), COVID-19 Clinical Severity Scale (CCSS), Delirium Etiology Checklist, Delirium Motor Subtype Scale-4, and Delirium Diagnostic Tool-Provisional (DDT-Pro), was conducted. Correlational analysis of delirium severity (DDT-Pro) with each measure of clinical severity (CCI-SF and CCSS) and comparison of baseline DDT-Pro scores between patients who were living and those who were deceased at follow-up were conducted. RESULTS: Participants were 50-90 years old (male, 75%; hypertension, 60%). The prevalence of preexisting medical comorbidities (CCI-SF) was low and not correlated with delirium severity (p=0.193). Eighteen patients were on mechanical or high-flow noninvasive ventilation at baseline in the intensive care unit (ICU; CCSS scores 2-4). Delirium severity (DDT-Pro scores 0-6) correlated with COVID-19 severity (0.459, p=0.021). Delirium motor subtype was hyperactive in 75% of patients. There were three to four etiologies for delirium in each patient, most commonly organ insufficiency (100%), systemic infection (100%), and metabolic and endocrine disturbances (95%). The baseline DDT-Pro score was ≤4 for five (25%) patients who died before the final assessment, with a trend of being lower than that for survivors (χ2=3.398, p=0.065). CONCLUSIONS: Among inpatients with COVID-19, at least three different etiological categories were identified for delirium. ICU staff treating patients with severe cases of COVID-19 should anticipate a greater severity of delirium. Although multivariate analyses with larger study samples are needed, more severe delirium may herald greater risk of death among COVID-19 patients.

Validation of the Delirium Diagnostic Tool-Provisional (DDT-Pro) With Medical Inpatients and Comparison With the Confusion Assessment Method Algorithm.

OBJECTIVE: Delirium remains underdetected as a result of its broad constellation of symptoms and the inadequate neuropsychiatric expertise of most medical-surgical clinicians. Brief, accurate tools are needed to enhance detection. METHODS: The authors extended validation of the Delirium Diagnostic Tool-Provisional (DDT-Pro), originally validated in a study of inpatients with traumatic brain injury for diagnosis of delirium by nonexpert clinicians, for 200 general medical inpatients in Colombia. The three structured, quantitatively rated items in DDT-Pro represent the three core delirium domains. RESULTS: High interrater reliability between physician and nurse (0.873) administrators, internal consistency (>0.81), and content validity were found. Compared with independent reference standard diagnosis with DSM-5 or the Delirium Rating Scale-Revised-98, the area under the receiver operating characteristic (ROC) curve (global diagnostic accuracy) range was 93.8%-96.3%. ROC analysis revealed the same cutoff score (≤6) as that for the original study, with somewhat lower sensitivities of 88.0%-90.0% and specificities of 85.3%-81.2% (independent expert physician or nurse ratings). Even when rated by a trained expert physician, the original version of the Confusion Assessment Method algorithm (CAM-A) performed moderately, with lower sensitivities (61.8%-70.0%) than the DDT-Pro (88.0%-100%) and somewhat higher specificities (84.8%-95.3% versus 67.4%-86.7%), with values depending on dementia status, reference standard, and rater type. Accuracies for the DDT-Pro and CAM-A were comparable (DDT-Pro: 83.0%-87.5% versus CAM-A: 87.5%-88.5%), although lower in the dementia subgroup, especially for CAM-A. However, these tools were significantly discordant, especially in negative cases, which suggests that they do not detect diagnosis of patients in the same way. CONCLUSIONS: The DDT-Pro had high validity and reliability in provisional delirium diagnosis by physicians and nonexpert clinicians, although further validation is warranted before widespread use can be recommended.

Distinguishing characteristics of delirium in a skilled nursing facility in Spain: Influence of baseline cognitive status.

OBJECTIVE: Mild cognitive impairment (MCI) and dementia (DEM) are prevalent in skilled nursing facilities (SNFs), confounding delirium detection. We report characteristics of delirium in an SNF to ascertain distinguishing features for delirium diagnosis, despite challenges of comorbidity with MCI and DEM. METHODS: Cross-sectional study of 200 consecutive patients from an SNF in Catalunya, Spain, assessed within the first 24 to 48 admission hours by independent experts with Spanish-Informant Questionnaire on Cognitive Decline in the Elderly (for MCI-DEM), Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) delirium criteria, and Delirium Rating Scale Revised-98 (DRS-R98) for delirium phenomenology. Delirium characteristics were modeled in successive steps, according to the presence of delirium and MCI-DEM, with analysis of variance (ANOVA), receiver operator characteristic analyses, and conditional logistic regression. RESULTS: The final model produced symptoms that represented each of the three delirium core domains (ie, cognitive, higher order thinking, and circadian). The DRS-R98 items rated these symptoms as moderate-severe attention/vigilance, mild-severe language, and moderate-severe sleep-wake cycle alterations. The delirium discriminant accuracy of the three symptoms together was high: 84.6% in the MCI-DEM group to 92.8% in the No MCI-DEM group. CONCLUSIONS: Impairments of attention, language, and sleep-wake cycle indicate delirium in SNF patients regardless of the underlying MCI-DEM status. Because delirium is underdetected in SNFs, where nursing staff/patient ratios are low, brief simple tools that measure these symptoms could potentially enhance delirium detection.

Delirium Phenotype by Age and Sex in a Pooled Data Set of Adult Patients.

The authors aimed to evaluate whether the clinical phenotype of delirium differs if dichotomized either by sex or age (cutoff age, 65 years old) in a pooled sample of 406 nondemented adult patients with delirium as defined by DSM-IV criteria. Delirium characteristics were measured with the Delirium Rating Scale-Revised-98 (DRS-R-98). DRS-R-98 items were subgrouped to represent subscores representing the three core domains of delirium (cognitive, higher-order thinking, and circadian), noncore accessory symptoms (psychotic and affective), and diagnostic characteristics (temporal onset, fluctuation, and physical disorder). The authors compared means of the DRS-R-98 subscores and medians of individual items. Exploratory factor analyses evaluated delirium characteristics for each subgroup for each of the four groups-male, female, nongeriatric, and geriatric-while taking into account active medical diagnoses. Males had higher scores on motor agitation and affective lability (behavioral), whereas females had a higher frequency of hypoactive delirium. Delirium had a two-factor structure that emerged in all four study groups, and all its core domains loaded (i.e., correlated together) onto some of these two factors and with circadian domain correlating with accessory symptoms. Although the influence of a variety of active diagnoses on delirium was small and complex, traumatic brain injury had a clear influence on cognitive domain and abrupt onset. Age had a mild influence over delirium characteristics for both males and females. In conclusion, the authors confirmed a two-factor structure for delirium phenomenology, regardless of age and sex, with few significant differences between etiological groups.

Relationship of Hippocampal Volume to Amyloid Burden across Diagnostic Stages of Alzheimer's Disease.

AIMS: To assess how hippocampal volume (HV) from volumetric magnetic resonance imaging (vMRI) is related to the amyloid status at different stages of Alzheimer's disease (AD) and its relevance to patient care. METHODS: We evaluated the ability of HV to predict the florbetapir positron emission tomography (PET) amyloid positive/negative status by group in healthy controls (HC, n = 170) and early/late mild cognitive impairment (EMCI, n = 252; LMCI, n = 136), and AD dementia (n = 75) subjects from the Alzheimer's Disease Neuroimaging Initiative Grand Opportunity (ADNI-GO) and ADNI2. Logistic regression analyses, including elastic net classification modeling with 10-fold cross-validation, were used with age and education as covariates. RESULTS: HV predicted amyloid status only in LMCI using either logistic regression [area under the curve (AUC) = 0.71, p < 0.001] or elastic net classification modeling [positive predictive value (PPV) = 72.7%]. In EMCI, age (AUC = 0.70, p < 0.0001) and age and/or education (PPV = 63.1%), but not HV, predicted amyloid status. CONCLUSION: Using clinical neuroimaging, HV predicted amyloid status only in LMCI, suggesting that HV is not a biomarker surrogate for amyloid PET in clinical applications across the full diagnostic spectrum.

Florbetapir F18 PET Amyloid Neuroimaging and Characteristics in Patients With Mild and Moderate Alzheimer Dementia.

BACKGROUND: Clinical diagnosis of Alzheimer disease (AD) is challenging, with a 70.9%-87.3% sensitivity and 44.3%-70.8% specificity, compared with autopsy diagnosis. Florbetapir F18 positron emission tomography (FBP-PET) estimates beta-amyloid plaque density antemortem. METHODS: Of 2052 patients (≥55 years old) clinically diagnosed with mild or moderate AD dementia from 2 solanezumab clinical trials, 390 opted to participate in a FBP-PET study addendum. We analyzed baseline prerandomization characteristics. RESULTS: A total of 22.4% had negative FBP-PET scans, whereas 72.5% of mild and 86.9% of moderate AD patients had positive results. No baseline clinical variable reliably differentiated negative from positive FBP-PET scan groups. CONCLUSIONS: These data confirm the challenges of correctly diagnosing AD without using biomarkers. FBP-PET can aid AD dementia differential diagnosis by detecting amyloid pathology antemortem, even when the diagnosis of AD is made by expert clinicians.

Delirium diagnosis defined by cluster analysis of symptoms versus diagnosis by DSM and ICD criteria: diagnostic accuracy study.

BACKGROUND: Information on validity and reliability of delirium criteria is necessary for clinicians, researchers, and further developments of DSM or ICD. We compare four DSM and ICD delirium diagnostic criteria versions, which were developed by consensus of experts, with a phenomenology-based natural diagnosis delineated using cluster analysis of delirium features in a sample with a high prevalence of dementia. We also measured inter-rater reliability of each system when applied by two evaluators from distinct disciplines. METHODS: Cross-sectional analysis of 200 consecutive patients admitted to a skilled nursing facility, independently assessed within 24-48 h after admission with the Delirium Rating Scale-Revised-98 (DRS-R98) and for DSM-III-R, DSM-IV, DSM-5, and ICD-10 criteria for delirium. Cluster analysis (CA) delineated natural delirium and nondelirium reference groups using DRS-R98 items and then diagnostic systems' performance were evaluated against the CA-defined groups using logistic regression and crosstabs for discriminant analysis (sensitivity, specificity, percentage of subjects correctly classified by each diagnostic system and their individual criteria, and performance for each system when excluding each individual criterion are reported). Kappa Index (K) was used to report inter-rater reliability for delirium diagnostic systems and their individual criteria. RESULTS: 117 (58.5 %) patients had preexisting dementia according to the Informant Questionnaire on Cognitive Decline in the Elderly. CA delineated 49 delirium subjects and 151 nondelirium. Against these CA groups, delirium diagnosis accuracy was highest using DSM-III-R (87.5 %) followed closely by DSM-IV (86.0 %), ICD-10 (85.5 %) and DSM-5 (84.5 %). ICD-10 had the highest specificity (96.0 %) but lowest sensitivity (53.1 %). DSM-III-R had the best sensitivity (81.6 %) and the best sensitivity-specificity balance. DSM-5 had the highest inter-rater reliability (K =0.73) while DSM-III-R criteria were the least reliable. CONCLUSIONS: Using our CA-defined, phenomenologically-based delirium designations as the reference standard, we found performance discordance among four diagnostic systems when tested in subjects where comorbid dementia was prevalent. The most complex diagnostic systems have higher accuracy and the newer DSM-5 have higher reliability. Our novel phenomenological approach to designing a delirium reference standard may be preferred to guide revisions of diagnostic systems in the future.

Confirmatory Factor Analysis of the Delirium Rating Scale Revised-98 (DRS-R98).

Principal components analysis applied to the Delirium Rating Scale-Revised-98 contributes to understanding the delirium construct. Using a multisite pooled international delirium database, the authors applied confirmatory factor analysis to Delirium Rating Scale-Revised-98 scores from 859 adult patients evaluated by delirium experts (delirium, N=516; nondelirium, N=343). Confirmatory factor analysis found all diagnostic features and core symptoms (cognitive, language, thought process, sleep-wake cycle, motor retardation), except motor agitation, loaded onto factor 1. Motor agitation loaded onto factor 2 with noncore symptoms (delusions, affective lability, and perceptual disturbances). Factor 1 loading supports delirium as a single construct, but when accompanied by psychosis, motor agitation's role may not be solely as a circadian activity indicator.

Performance of the Delirium Rating Scale-Revised-98 Against Different Delirium Diagnostic Criteria in a Population With a High Prevalence of Dementia.

BACKGROUND: Delirium diagnosis in elderly is often complicated by underlying dementia. OBJECTIVE: We evaluated performance of the Delirium Rating Scale-Revised-98 (DRS-R98) in patients with high dementia prevalence and also assessed concordance among past and current diagnostic criteria for delirium. METHODS: Cross-sectional analysis of newly admitted patients to a skilled nursing facility over 6 months, who were rated within 24-48 hours after admission. Interview for Diagnostic and Statistical Manual of Mental Disorders, 3rd edition-R (DSM)-III-R, DSM-IV, DSM-5, and International Classification of Diseases 10th edition delirium ratings, administration of the DRS-R98, and assessment of dementia using the Informant Questionnaire on Cognitive Decline in the Elderly were independently performed by 3 researchers. Discriminant analyses (receiver operating characteristics curves) were used to study DRS-R98 accuracy against different diagnostic criteria. Hanley and McNeil test compared the area under the curve for DRS-R98's discriminant performance for all diagnostic criteria. RESULTS: Dementia was present in 85/125 (68.0%) subjects, and 36/125 (28.8%) met criteria for delirium by at least 1 classification system, whereas only 19/36 (52.8%) did by all. DSM-III-R diagnosed the most as delirious (27.2%), followed by DSM-5 (24.8%), DSM-IV-TR (22.4%), and International Classification of Diseases 10th edition (16%). DRS-R98 had the highest AUC when discriminating DSM-III-R delirium (92.9%), followed by DSM-IV (92.4%), DSM-5 (91%), and International Classification of Diseases 10th edition (90.5%), without statistical differences among them. The best DRS-R98 cutoff score was ≥14.5 for all diagnostic systems except International Classification of Diseases 10th edition (≥15.5). CONCLUSIONS: There is a low concordance across diagnostic systems for identification of delirium. The DRS-R98 performs well despite differences across classification systems perhaps because it broadly assesses phenomenology, even in this population with a high prevalence of dementia.

Relationship between the Montreal Cognitive Assessment and Mini-mental State Examination for assessment of mild cognitive impairment in older adults.

BACKGROUND: The Montreal Cognitive Assessment (MoCA) was developed to enable earlier detection of mild cognitive impairment (MCI) relative to familiar multi-domain tests like the Mini-Mental State Exam (MMSE). Clinicians need to better understand the relationship between MoCA and MMSE scores. METHODS: For this cross-sectional study, we analyzed 219 healthy control (HC), 299 MCI, and 100 Alzheimer's disease (AD) dementia cases from the Alzheimer's Disease Neuroimaging Initiative (ADNI)-GO/2 database to evaluate MMSE and MoCA score distributions and select MoCA values to capture early and late MCI cases. Stepwise variable selection in logistic regression evaluated relative value of four test domains for separating MCI from HC. Functional Activities Questionnaire (FAQ) was evaluated as a strategy to separate dementia from MCI. Equi-percentile equating produced a translation grid for MoCA against MMSE scores. Receiver Operating Characteristic (ROC) analyses evaluated lower cutoff scores for capturing the most MCI cases. RESULTS: Most dementia cases scored abnormally, while MCI and HC score distributions overlapped on each test. Most MCI cases scored ≥ 17 on MoCA (96.3%) and ≥ 24 on MMSE (98.3%). The ceiling effect (28-30 points) for MCI and HC was less using MoCA (18.1%) versus MMSE (71.4%). MoCA and MMSE scores correlated most for dementia (r = 0.86; versus MCI r = 0.60; HC r = 0.43). Equi-percentile equating showed a MoCA score of 18 was equivalent to MMSE of 24. ROC analysis found MoCA ≥ 17 as the cutoff between MCI and dementia that emphasized high sensitivity (92.3%) to capture MCI cases. The core and orientation domains in both tests best distinguished HC from MCI groups, whereas comprehension/executive function and attention/calculation were not helpful. Mean FAQ scores were significantly higher and a greater proportion had abnormal FAQ scores in dementia than MCI and HC. CONCLUSIONS: MoCA and MMSE were more similar for dementia cases, but MoCA distributes MCI cases across a broader score range with less ceiling effect. A cutoff of ≥ 17 on the MoCA may help capture early and late MCI cases; depending on the level of sensitivity desired, ≥ 18 or 19 could be used. Functional assessment can help exclude dementia cases. MoCA scores are translatable to the MMSE to facilitate comparison.

Florbetapir positron emission tomography and cerebrospinal fluid biomarkers.

BACKGROUND: We evaluated the relationship between florbetapir-F18 positron emission tomography (FBP PET) and cerebrospinal fluid (CSF) biomarkers. METHODS: Alzheimer's Disease Neuroimaging Initiative-Grand Opportunity and Alzheimer's Disease Neuroimaging Initiative 2 (GO/2) healthy control (HC), mild cognitive impairment (MCI), and Alzheimer's disease (AD) dementia subjects with clinical measures and CSF collected ±90 days of FBP PET data were analyzed using correlation and logistic regression. RESULTS: In HC and MCI subjects, FBP PET anterior and posterior cingulate and composite standard uptake value ratios correlated with CSF amyloid beta (Aß1-42) and tau/Aß1-42 ratios. Using logistic regression, Aß1-42, total tau (t-tau), phosphorylated tau181P (p-tau), and FBP PET composite each differentiated HC versus AD. Aß1-42 and t-tau distinguished MCI versus AD, without additional contribution by FBP PET. Total tau and p-tau added discriminative power to FBP PET when classifying HC versus AD. CONCLUSION: Based on cross-sectional diagnostic groups, both amyloid and tau measures distinguish healthy from demented subjects. Longitudinal analyses are needed.

Concordance between DSM-IV and DSM-5 criteria for delirium diagnosis in a pooled database of 768 prospectively evaluated patients using the delirium rating scale-revised-98.

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

Executive function in adults with attention-deficit/hyperactivity disorder during treatment with atomoxetine in a randomized, placebo-controlled, withdrawal study.

We assessed the executive function in adults with attention-deficit/hyperactivity disorder (ADHD) during atomoxetine treatment in a randomized withdrawal trial. Responders (Conners' ADHD Rating Scale-Investigator Rated: Screening Version [adult prompts] ≥30% reduction from baseline and Clinical Global Impression Scale-ADHD Severity score ≤3) to open-label atomoxetine (40-100 mg/d, 12 weeks) entered a 37-week double-blind maintenance period. Patients who maintained response (double-blind atomoxetine for 12 weeks) were randomized 1:1 to atomoxetine (80-100 mg/d, n = 266) or placebo (n = 258) for 25 weeks (total duration, 1 year). Patients and investigators were blinded to response criteria and randomization timing. Change in executive function was assessed with the Behavior Rating Inventory of Executive Function-Adult Version (BRIEF-A) Self-Report and Informant T scores from the randomization to the last-observation-carried-forward postrandomization week 25 (after week 17). Of the enrolled patients (n = 2017; mean age, 33.2 years; male, 58.7%), 524 responders were randomized. During open-label atomoxetine, subscales and individual items on both BRIEF-A questionnaires showed significant improvement (P < 0.001). After randomization, the following T scores improved significantly (P ≤ 0.05) with patients in the atomoxetine group versus those in the placebo group: global executive composite, behavioral regulation, and metacognition indices; plan/organize, working memory, inhibit, task monitor and shift (both BRIEF-A questionnaires), emotional control and organization of materials (BRIEF-A Informant), and initiate (BRIEF-A Self-Report). Atomoxetine significantly improved the executive function compared with placebo, which was maintained for 25 weeks or more; the executive function of patients in the placebo group worsened but did not return to baseline levels after randomization.

Validation of the delirium diagnostic tool-provisional (DDT-Pro) in geriatric medical inpatients with diagnostic permutations of the 3Ds with and without delirium.

OBJECTIVE: Validations of brief delirium tools have not included analysis of psychiatric disorders comorbidities or control groups. We validated the Delirium Diagnostic Tool-Provisional (DDT-Pro) in 422 geriatric inpatients with high incidence of depression and/or dementia. METHODS: Cross-sectional study using two delirium reference standards, DSM-5-TR and Delirium Rating Scale-Revised-98 (DRS-R98). We assessed concurrent and construct DDT-Pro validity too. RESULTS: There were 117 (27.7%) delirium cases using DDT-Pro, 104 (24.6%) per DSM-5-TR and 93 (22.0%) per DRS-R98; 133 patients (31.5%) had depression and 105 (24.9%) dementia, some comorbid with delirium. DDT-Pro accuracy (AUC under ROC curve) ranges were 88.3-95.9% vs DSM-5-TR and 92.7-95.0% vs DRS-R98 for whole sample and four diagnostic groups, without statistical differences. DDT-Pro ≤6 had the most balanced sensitivity-specificity for delirium diagnosis against both DSM-5-TR and DRS-R98 with similar specificity but higher sensitivity for DRS-R98 than DSM-5-TR delirium, with the highest values in patients with depression and dementia (≥92% sensitivity, ≥81% specificity). Positive and negative likelihood ratios support diagnostic strength. Concurrent validity was high reflected by significant correlations (p < 0.001) of DDT-Pro total and item scores with DRS-R98 and Delirium Frontal Index scores, highest in groups with comorbid depression and/or dementia. The DDT-Pro represented a single construct for delirium demonstrated by one factor with high item loadings and high internal consistency reliability of its items. CONCLUSIONS: The DDT-Pro demonstrated strong performance metrics in general hospital elderly inpatients with preexisting depression and/or dementia, which is unique among brief delirium tools. Its optimized cutoff score was the same as in other populations.

Subscale validation of the neuropsychiatric inventory questionnaire: comparison of Alzheimer's disease neuroimaging initiative and national Alzheimer's coordinating center cohorts.

OBJECTIVE: Neuropsychiatric symptoms are prevalent in mild cognitive impairment (MCI) and Alzheimer disease (AD) and commonly measured using the Neuropsychiatric Inventory (NPI). Based on existing exploratory literature, we report preliminary validation of three NPI Questionnaire (NPI-Q-10) subscales that measure clinically meaningful symptom clusters. METHODS: Cross-sectional results for three subscales (NPI-Q-4-Frontal, NPI-Q-4-Agitation/Aggression, NPI-Q-3-Mood) in amnestic MCI and AD dementia cases from the National Alzheimer's Coordinating Center (NACC) and Alzheimer's Disease Neuroimaging Initiative (ADNI) databases were analyzed using confirmatory unrotated principal component analysis. RESULTS: ADNI contributed 103 MCI, 90 MCI converters, and 112 AD dementia cases, whereas NACC contributed 1,042 MCI, 763 MCI converters, and 3,048 AD dementia cases. NACC had higher baseline mean age (75.7 versus 74.6), and more impaired mean scores (at month 24) on Mini-Mental State Exam (19.5 versus 22.4) and NPI-Q-10 (5.0 versus 4.3), and all NPI-Q subscales than ADNI. Medians were not different between cohorts for NPI-Q-4-Agitation/Aggression, and NPI-Q-3-Mood, however. Each item on all scales/subscales contributed variance in principal component analysis Pareto plots. All items in Factor (F) 1 for each scale/subscale projected in a positive direction on biplots (revealing coherence), whereas F2 and F3 items showed more spatial separation (revealing independence). There were remarkable similarities between cohorts for factor loadings and spatial patterns of item projections, although factor item identities varied somewhat, especially beyond F1. CONCLUSION: The similar pattern of results across two cohorts support validity of these subscales, which are worthy of further psychometric evaluation in MCI and AD patients and preliminary application in clinical settings.

Three core domains of delirium validated using exploratory and confirmatory factor analyses.

OBJECTIVE: To confirm the existence of the proposed three-core symptom domains in delirium by analyzing a dataset of nondemented adults using selected core symptoms as measured by the Delirium Rating Scale-Revised-98 (DRS-R98) scale. METHODS: Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) of proposed delirium core symptoms were conducted in a pooled international dataset of 592 delirious and nondelirious patients using DSM-IV criteria from 14 studies with comparable methodologies. Using DRS-R98 categorization, 445 had either subsyndromal or full delirium and comprised the delirium group. The dataset was divided into three independent random subsamples to perform a stepwise analysis. First we performed EFA in 100 cases to delineate latent factor loadings of DRS-R98 items selected to represent the three-core domains (circadian, higher level thinking, and cognitive). These items were then assessed using CFA-modeling (n = 246) followed by a CFA-validation (n = 246). Reliability and goodness of fit of these two CFA were assessed statistically. RESULTS: DRS-R98 items representing the proposed delirium core symptoms loaded onto one factor in the EFA, supporting their core nature. The two CFA confirmed the nature of this core factor as comprising three core domains where DRS-R98 items each loaded with high values (>0.7) onto their corresponding core domain (circadian, higher level thinking, and cognitive) with good fit and reliability. Attention was DRS-R98 item with the highest loading in CFA, followed by thought process, and then by sleep-wake cycle and motor behavior. CONCLUSIONS: Our EFA and CFA confirm and validate the proposed three-core domains of delirium, where symptoms were highly related to the domain that they were hypothesized to represent. These domains are consistent with delirium being a state of impaired consciousness, and should be considered necessary to assess whether in clinical or research settings.

Mibampator (LY451395) randomized clinical trial for agitation/aggression in Alzheimer's disease.

BACKGROUND: Mibampator, an amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor potentiator, was evaluated for treatment of agitation and aggression (A/A) in Alzheimer's disease (AD). METHODS: Outpatients (n = 132) with probable AD and A/A randomized to 12 weeks of double-blind treatment with 3-mg po mibampator or placebo were assessed using the 4-domain A/A subscale of the Neuropsychiatric Inventory (NPI-4-A/A) derived from the Neuropsychiatric Inventory. Secondary measures included the Cohen-Mansfield Agitation Inventory, Cornell Scale for Depression in Dementia, Frontal Systems Behavior Inventory (FrSBe), and Alzheimer's Disease Assessment Scale-Cognitive. Efficacy was analyzed using mixed-effects model repeated measures from baseline to endpoint. Adverse events (AEs), labs, vital signs, and electrocardiograms were monitored. RESULTS: Baseline characteristics were comparable between groups. Both groups improved on the NPI-4-A/A, but without group differences. Among secondaries, mibampator was significantly better (p = 0.007) than placebo only on the FrSBe. AEs were similar between groups. One death occurred in the placebo group. CONCLUSION: Possible explanations for no significant group differences include caregiver, drug target engagement, and design issues. This trial is registered on ClinicalTrials.gov; ID: NCT00843518.

Frontolimbic atrophy is associated with agitation and aggression in mild cognitive impairment and Alzheimer's disease.

BACKGROUND: The neuroanatomy of agitation and aggression in Alzheimer's disease is not well understood. METHODS: We analyzed 24 months of Alzheimer's Disease Neuroimaging Initiative data for patients with Alzheimer's disease, mild cognitive impairment-stable, and mild cognitive impairment-converter (n = 462) using the Neuropsychiatric Inventory Questionnaire Agitation and Aggression subscale. Magnetic resonance imaging regions of interest that correlated with Neuropsychiatric Inventory Questionnaire Agitation and Aggression subscale raw scores were included in mixed-model, repeated-measures analyses of agitation and aggression over time with age, sex, apolipoprotein E ε4 status, education, and Mini-Mental State Examination score as covariates. RESULTS: Neuropsychiatric Inventory Questionnaire Agitation and Aggression subscale scores worsened in patients with Alzheimer's disease and in mild cognitive impairment-converter (P < .05; trend for mild cognitive impairment, P = .0518). Greater agitation and aggression severity was associated with greater atrophy of frontal, insular, amygdala, cingulate, and hippocampal regions of interest (P < .05). Mini-Mental State Examination score was significant in mixed-effect model repeated measures only in mild cognitive impairment-converters for posterior regions of interest. Demographics and apolipoprotein ε4 were not associated with agitation and aggression. CONCLUSIONS: Agitation and aggression in Alzheimer's disease and mild cognitive impairment is associated with neurodegeneration affecting the anterior salience network that may reduce capacity to process and regulate behaviors properly.