Characterizing Longitudinal Patterns in Cognition, Mood, And Activity in Depression With 6-Week High-Frequency Wearable Assessment: Observational Study.

BACKGROUND: Cognitive symptoms are an underrecognized aspect of depression that are often untreated. High-frequency cognitive assessment holds promise for improving disease and treatment monitoring. Although we have previously found it feasible to remotely assess cognition and mood in this capacity, further work is needed to ascertain the optimal methodology to implement and synthesize these techniques. OBJECTIVE: The objective of this study was to examine (1) longitudinal changes in mood, cognition, activity levels, and heart rate over 6 weeks; (2) diurnal and weekday-related changes; and (3) co-occurrence of fluctuations between mood, cognitive function, and activity. METHODS: A total of 30 adults with current mild-moderate depression stabilized on antidepressant monotherapy responded to testing delivered through an Apple Watch (Apple Inc) for 6 weeks. Outcome measures included cognitive function, assessed with 3 brief n-back tasks daily; self-reported depressed mood, assessed once daily; daily total step count; and average heart rate. Change over a 6-week duration, diurnal and day-of-week variations, and covariation between outcome measures were examined using nonlinear and multilevel models. RESULTS: Participants showed initial improvement in the Cognition Kit N-Back performance, followed by a learning plateau. Performance reached 90% of individual learning levels on average 10 days after study onset. N-back performance was typically better earlier and later in the day, and step counts were lower at the beginning and end of each week. Higher step counts overall were associated with faster n-back learning, and an increased daily step count was associated with better mood on the same (P<.001) and following day (P=.02). Daily n-back performance covaried with self-reported mood after participants reached their learning plateau (P=.01). CONCLUSIONS: The current results support the feasibility and sensitivity of high-frequency cognitive assessments for disease and treatment monitoring in patients with depression. Methods to model the individual plateau in task learning can be used as a sensitive approach to better characterize changes in behavior and improve the clinical relevance of cognitive data. Wearable technology allows assessment of activity levels, which may influence both cognition and mood.

Visual memory and alcohol use in a middle-aged birth cohort.

Light and moderate alcohol use has been reported to be associated with both impaired and enhanced cognition. The purpose of this study was to explore whether there was a linear relationship between visual memory and alcohol consumption in males and females in a large middle-aged birth cohort population in cross-sectional and longitudinal settings. Data were collected from 5585 participants completing 31-year (1997-1998) and 46-year (2012-2014) follow-ups including Paired Associate Learning (PAL) test at 46-years follow-up. The participants were originally from 12,231 study population of the Northern Finland Birth Cohort 1966 (NFBC1966). The PAL test was conducted to assess visual memory. Reported alcohol use was measured as total daily use of alcohol, beer, wine, and spirits converted into grams and as frequency and amount of use of beer, wine, and spirits. The total daily alcohol use was not associated with reduced visual memory. The frequency of use of beer and wine in males was associated with better visual memory in cross-sectional and longitudinal settings. Using six or more servings of spirits was associated with worse visual memory in males in cross-sectional and longitudinal settings. Using six or more servings of spirits was associated with worse visual memory in males in cross-sectional and longitudinal setting. The study suggested a lack of a linear association between drinking and visual memory in the middle-aged population.

Prediction of mental effort derived from an automated vocal biomarker using machine learning in a large-scale remote sample.

Introduction: Biomarkers of mental effort may help to identify subtle cognitive impairments in the absence of task performance deficits. Here, we aim to detect mental effort on a verbal task, using automated voice analysis and machine learning. Methods: Audio data from the digit span backwards task were recorded and scored with automated speech recognition using the online platform NeuroVocalixTM, yielding usable data from 2,764 healthy adults (1,022 male, 1,742 female; mean age 31.4 years). Acoustic features were aggregated across each trial and normalized within each subject. Cognitive load was dichotomized for each trial by categorizing trials at >0.6 of each participants' maximum span as "high load." Data were divided into training (60%), test (20%), and validate (20%) datasets, each containing different participants. Training and test data were used in model building and hyper-parameter tuning. Five classification models (Logistic Regression, Naive Bayes, Support Vector Machine, Random Forest, and Gradient Boosting) were trained to predict cognitive load ("high" vs. "low") based on acoustic features. Analyses were limited to correct responses. The model was evaluated using the validation dataset, across all span lengths and within the subset of trials with a four-digit span. Classifier discriminant power was examined with Receiver Operating Curve (ROC) analysis. Results: Participants reached a mean span of 6.34 out of 8 items (SD = 1.38). The Gradient Boosting classifier provided the best performing model on test data (AUC = 0.98) and showed excellent discriminant power for cognitive load on the validation dataset, across all span lengths (AUC = 0.99), and for four-digit only utterances (AUC = 0.95). Discussion: A sensitive biomarker of mental effort can be derived from vocal acoustic features in remotely administered verbal cognitive tests. The use-case of this biomarker for improving sensitivity of cognitive tests to subtle pathology now needs to be examined.

A new era for schizophrenia drug development - Lessons for the future.

For many patients and their treating clinicians, the pharmacological management of psychotic symptoms centres on trying to find a regime that balances efficacy and quality of life-impairing side effects associated with dopamine antagonism. Recent reports of a positive Phase III study from Karuna Therapeutics indicate that the first primarily non-dopamine-based treatment for schizophrenia may come to market soon with the potential for substantially reduced or differentiated side effects. Against a background of repeated failures, Karuna's success promises a desperately needed new treatment option for patients. It also reflects some hard-won lessons about the methodology for schizophrenia drug development.

Emotional bias training as a treatment for anxiety and depression: evidence from experimental medicine studies in healthy and medicated samples.

BACKGROUND: Anxiety and depression are leading causes of disability worldwide, yet individuals are often unable to access appropriate treatment. There is a need to develop effective interventions that can be delivered remotely. Previous research has suggested that emotional processing biases are a potential target for intervention, and these may be altered through brief training programs. METHODS: We report two experimental medicine studies of emotional bias training in two samples: individuals from the general population (n = 522) and individuals currently taking antidepressants to treat anxiety or depression (n = 212). Participants, recruited online, completed four sessions of EBT from their own home. Mental health and cognitive functioning outcomes were assessed at baseline, immediately post-training, and at 2-week follow-up. RESULTS: In both studies, our intervention successfully trained participants to perceive ambiguous social information more positively. This persisted at a 2-week follow-up. There was no clear evidence that this change in emotional processing transferred to improvements in symptoms in the primary analyses. However, in both studies, there was weak evidence for improved quality of life following EBT amongst individuals with more depressive symptoms at baseline. No clear evidence of transfer effects was observed for self-reported daily stress, anhedonia or depressive symptoms. Exploratory analyses suggested that younger participants reported greater treatment gains. CONCLUSIONS: These studies demonstrate the effectiveness of delivering a multi-session online training program to promote lasting cognitive changes. Given the inconsistent evidence for transfer effects, EBT requires further development before it can be considered as a treatment for anxiety and depression.

Measuring functional outcomes in schizophrenia in an increasingly digital world.

With an unmet clinical need for effective interventions for cognitive and negative symptoms in patients with schizophrenia, measures of functional status (often a co-primary endpoint) remain key clinical trial outcomes. This review aims to give an overview of the different types of functional assessments commonly used in clinical trials and research involving patients with schizophrenia and highlight pertinent challenges surrounding the use of these as reliable, sensitive, and specific assessments in intervention trials. We provide examples of commonly used functional measures and highlight emerging real-time digital assessment tools. Informant- and clinician-rated functional outcome measures and functional capacity assessments are valid, commonly used measures of functional status that try to overcome the need for often overly ambitious and insensitive 'real world' milestones. The wide range of scientific and practical challenges associated with these different tools leave room for the development of improved functional outcome measures for use in clinical trials. In particular, many existing measures fail to capture small, but meaningful, functional changes that may occur over the course of typically short intervention trials. Adding passive digital data collection and short active real-time digital assessments whilst patients go about their day offers the opportunity to build a more fine-grained picture of functional improvements that, if thoughtfully developed and carefully applied, could provide the sensitivity needed to accurately evaluate functional status in intervention studies, aiding the development of desperately needed treatments.

Comparing performance on the Months of the Year Backwards test in hospitalised patients with delirium, dementia, and no cognitive impairment: an exploratory study.

PURPOSE: To investigate performance of the Months of the Year Backwards (MOTYB) test in older hospitalised patients with delirium, dementia, and no cognitive impairment. METHODS: Secondary analysis of data from a case-control study of 149 hospitalised patients aged ≥ 65 years with delirium [with or without dementia (N = 50)], dementia [without delirium (N = 46)], and no cognitive impairment (N = 53). Verbatim transcripts of MOTYB audio recordings were analysed to determine group differences in response patterns. RESULTS: In the total sample [median age 85y (IQR 80-88), 82% female], patients with delirium were more often unable to recite months backward to November (36/50 = 72%) than patients with dementia (21/46 = 46%; p < 0.01) and both differed significantly from patients without cognitive impairment (2/53 = 4%; p's < 0.001). 121/149 (81%) of patients were able to engage with the test. Patients with delirium were more often unable to engage with MOTYB (23/50 = 46%; e.g., due to reduced arousal) than patients with dementia (5/46 = 11%; p < 0.001); both groups differed significantly (p's < 0.001) from patients without cognitive impairment (0/53 = 0%). There was no statistically significant difference between patients with delirium (2/27 = 7%) and patients with dementia (8/41 = 20%) in completing MOTYB to January, but performance in both groups differed (p < 0.001 and p < 0.02, respectively) from patients without cognitive impairment (35/53 = 66%). CONCLUSION: Delirium was associated with inability to engage with MOTYB and low rates of completion. In patients able to engage with the test, error-free completion rates were low in delirium and dementia. Recording of engagement and patterns of errors may add useful information to MOTYB scoring.

Developing Digital Tools for Remote Clinical Research: How to Evaluate the Validity and Practicality of Active Assessments in Field Settings.

The ability of remote research tools to collect granular, high-frequency data on symptoms and digital biomarkers is an important strength because it circumvents many limitations of traditional clinical trials and improves the ability to capture clinically relevant data. This approach allows researchers to capture more robust baselines and derive novel phenotypes for improved precision in diagnosis and accuracy in outcomes. The process for developing these tools however is complex because data need to be collected at a frequency that is meaningful but not burdensome for the participant or patient. Furthermore, traditional techniques, which rely on fixed conditions to validate assessments, may be inappropriate for validating tools that are designed to capture data under flexible conditions. This paper discusses the process for determining whether a digital assessment is suitable for remote research and offers suggestions on how to validate these novel tools.

Effects of 7.5% Carbon Dioxide and Nicotine Administration on Latent Inhibition.

Stratified medicine approaches have potential to improve the efficacy of drug development for schizophrenia and other psychiatric conditions, as they have for oncology. Latent inhibition is a candidate biomarker as it demonstrates differential sensitivity to key symptoms and neurobiological abnormalities associated with schizophrenia. The aims of this research were to evaluate whether a novel latent inhibition task that is not confounded by alternative learning effects such as learned irrelevance, is sensitive to (1) an in-direct model relevant to psychosis [using 7.5% carbon dioxide (CO2) inhalations to induce dopamine release via somatic anxiety] and (2) a pro-cognitive pharmacological manipulation (via nicotine administration) for the treatment of cognitive impairment associated with schizophrenia. Experiment 1 used a 7.5% CO2 challenge as a model of anxiety-induced dopamine release to evaluate the sensitivity of latent inhibition during CO2 gas inhalation, compared to the inhalation of medical air. Experiment 2 examined the effect of 2 mg nicotine administration vs. placebo on latent inhibition to evaluate its sensitivity to a potential pro-cognitive drug treatment. Inhalation of 7.5% CO2 raised self-report and physiological measures of anxiety and impaired latent inhibition, relative to a medical air control; whereas administration of 2 mg nicotine, demonstrated increased latent inhibition relative to placebo control. Here, two complementary experimental studies suggest latent inhibition is modified by manipulations that are relevant to the detection and treatment of schizophrenia. These results suggest that this latent inhibition task merits further investigation in the context of neurobiological sub-groups suitable for novel treatment strategies.

Postoperative cognitive dysfunction: an acute approach for the development of novel treatments for neuroinflammation.

Inflammation within the central nervous system (CNS; neuroinflammation) is a major contributor to lasting symptoms of traumatic brain injury and stroke, and likely has a casual role Alzheimer's disease (AD) and other neurodegenerative conditions. Therapeutic modulation of the immune processes that initiate and maintain neuroinflammation is of growing scientific interest but neuroinflammatory drug development is hampered by limited reliability and availability of neuroimaging or other biomarkers in humans. Better means of establishing drug efficacy on human neuroinflammation would have great value in accelerating the development of neuroinflammatory compounds for many clinical indications. Here, we discuss the use of postoperative cognitive decline (POCD), which is hypothesised to have a neuroinflammatory basis, as an acute indication to demonstrate the efficacy of novel neuroinflammatory drugs.

Comparing Web-Based and Lab-Based Cognitive Assessment Using the Cambridge Neuropsychological Test Automated Battery: A Within-Subjects Counterbalanced Study.

BACKGROUND: Computerized assessments are already used to derive accurate and reliable measures of cognitive function. Web-based cognitive assessment could improve the accessibility and flexibility of research and clinical assessment, widen participation, and promote research recruitment while simultaneously reducing costs. However, differences in context may influence task performance. OBJECTIVE: This study aims to determine the comparability of an unsupervised, web-based administration of the Cambridge Neuropsychological Test Automated Battery (CANTAB) against a typical in-person lab-based assessment, using a within-subjects counterbalanced design. The study aims to test (1) reliability, quantifying the relationship between measurements across settings using correlational approaches; (2) equivalence, the extent to which test results in different settings produce similar overall results; and (3) agreement, by quantifying acceptable limits to bias and differences between measurement environments. METHODS: A total of 51 healthy adults (32 women and 19 men; mean age 36.8, SD 15.6 years) completed 2 testing sessions, which were completed on average 1 week apart (SD 4.5 days). Assessments included equivalent tests of emotion recognition (emotion recognition task [ERT]), visual recognition (pattern recognition memory [PRM]), episodic memory (paired associate learning [PAL]), working memory and spatial planning (spatial working memory [SWM] and one touch stockings of Cambridge), and sustained attention (rapid visual information processing [RVP]). Participants were randomly allocated to one of the two groups, either assessed in-person in the laboratory first (n=33) or with unsupervised web-based assessments on their personal computing systems first (n=18). Performance indices (errors, correct trials, and response sensitivity) and median reaction times were extracted. Intraclass and bivariate correlations examined intersetting reliability, linear mixed models and Bayesian paired sample t tests tested for equivalence, and Bland-Altman plots examined agreement. RESULTS: Intraclass correlation (ICC) coefficients ranged from ρ=0.23-0.67, with high correlations in 3 performance indices (from PAL, SWM, and RVP tasks; ρ≥0.60). High ICC values were also seen for reaction time measures from 2 tasks (PRM and ERT tasks; ρ≥0.60). However, reaction times were slower during web-based assessments, which undermined both equivalence and agreement for reaction time measures. Performance indices did not differ between assessment settings and generally showed satisfactory agreement. CONCLUSIONS: Our findings support the comparability of CANTAB performance indices (errors, correct trials, and response sensitivity) in unsupervised, web-based assessments with in-person and laboratory tests. Reaction times are not as easily translatable from in-person to web-based testing, likely due to variations in computer hardware. The results underline the importance of examining more than one index to ascertain comparability, as high correlations can present in the context of systematic differences, which are a product of differences between measurement environments. Further work is now needed to examine web-based assessments in clinical populations and in larger samples to improve sensitivity for detecting subtler differences between test settings.

Structural and functional alterations in the brain gray matter among first-degree relatives of schizophrenia patients: A multimodal meta-analysis of fMRI and VBM studies.

OBJECTIVE: We conducted a multimodal coordinate-based meta-analysis (CBMA) to investigate structural and functional brain alterations in first-degree relatives of schizophrenia patients (FRs). METHODS: We conducted a systematic literature search from electronic databases to find studies that examined differences between FRs and healthy controls using whole-brain functional magnetic resonance imaging (fMRI) or voxel-based morphometry (VBM). A CBMA of 30 fMRI (754 FRs; 959 controls) and 11 VBM (885 FRs; 775 controls) datasets were conducted using the anisotropic effect-size version of signed differential mapping. Further, we conducted separate meta-analyses about functional alterations in different cognitive tasks: social cognition, executive functioning, working memory, and inhibitory control. RESULTS: FRs showed higher fMRI activation in the right frontal gyrus during cognitive tasks than healthy controls. In VBM studies, there were no differences in gray matter density between FRs and healthy controls. Furthermore, multi-modal meta-analysis obtained no differences between FRs and healthy controls. By utilizing the BrainMap database, we showed that the brain region which showed functional alterations in FRs (i) overlapped only slightly with the brain regions that were affected in the meta-analysis of schizophrenia patients and (ii) correlated positively with the brain regions that exhibited increased activity during cognitive tasks in healthy individuals. CONCLUSIONS: Based on this meta-analysis, FRs may exhibit only minor functional alterations in the brain during cognitive tasks, and the alterations are much more restricted and only slightly overlapping with the regions that are affected in schizophrenia patients. The familial risk did not relate to structural alterations in the gray matter.

A smartphone-based test for the assessment of attention deficits in delirium: A case-control diagnostic test accuracy study in older hospitalised patients.

BACKGROUND: Delirium is a common and serious acute neuropsychiatric syndrome which is often missed in routine clinical care. Inattention is the core cognitive feature. Diagnostic test accuracy (including cut-points) of a smartphone Delirium App (DelApp) for assessing attention deficits was assessed in older hospital inpatients. METHODS: This was a case-control study of hospitalised patients aged ≥65 years with delirium (with or without pre-existing cognitive impairment), who were compared to patients with dementia without delirium, and patients without cognitive impairment. Reference standard delirium assessment, which included a neuropsychological test battery, was based on Diagnostic and Statistical Manual of Mental Disorders-5 criteria. A separate blinded assessor administered the DelApp arousal assessment (score 0-4) and attention task (0-6) yielding an overall score of 0 to 10 (lower scores indicate poorer performance). Analyses included receiver operating characteristic curves and sensitivity and specificity. Optimal cut-points for delirium detection were determined using Youden's index. RESULTS: A total of 187 patients were recruited, mean age 83.8 (range 67-98) years, 152 (81%) women; n = 61 with delirium; n = 61 with dementia without delirium; and n = 65 without cognitive impairment. Patients with delirium performed poorly on the DelApp (median score = 4/10; inter-quartile range 3.0, 5.5) compared to patients with dementia (9.0; 5.5, 10.0) and those without cognitive impairment (10.0; 10.0, 10.0). Area under the curve for detecting delirium was 0.89 (95% Confidence Interval 0.84, 0.94). At an optimal cut-point of ≤8, sensitivity was 91.7% (84.7%, 98.7%) and specificity 74.2% (66.5%, 81.9%) for discriminating delirium from the other groups. Specificity was 68.3% (56.6%, 80.1%) for discriminating delirium from dementia (cut-point ≤6). CONCLUSION: Patients with delirium (with or without pre-existing cognitive impairment) perform poorly on the DelApp compared to patients with dementia and those without cognitive impairment. A cut-point of ≤8/10 is suggested as having optimal sensitivity and specificity. The DelApp is a promising tool for assessment of attention deficits associated with delirium in older hospitalised adults, many of whom have prior cognitive impairment, and should be further validated in representative patient cohorts.

Depressive symptoms as predictors of visual memory deficits in middle-age.

BACKGROUND: Depression has been known to affect memory and other cognitive domains. The objective of this longitudinal cohort study was to investigate longitudinal associations between depressive symptoms at age 31 years and visual memory and new learning at the age of 46 years. We investigated whether depressive symptoms at age 31 predicted visual memory deficits at age 46 years, and whether changes in depressive symptoms between 31 and 46 years predicted visual memory at age 46. METHODS: Participants were members of the Northern Finland Birth Cohort 1966. Depressive symptoms were assessed with the Symptom Checklist-25 (SCL-25) on both occasions. Visual memory and new learning were assessed using Paired Associative Learning (PAL) test at the age 46 follow-up. PAL total errors adjusted and first trial memory score were used as outcomes and basic educational level, relationship status, physical activity and diet at baseline were considered as confounding factors in linear regression analysis. RESULTS: A total of 5029 (57% female) participants were included in the main analysis. No associations were found between depressive symptoms or change in depressive symptoms and visual memory and new learning scores. The result did not change following cut-offs 1.55 and 1.75 for depression. LIMITATIONS: SCL-25 only measures symptoms during the past week. Only one cognitive domain was assessed. CONCLUSIONS: Contrary to our hypothesis, neither baseline depressive symptoms nor change in depressive symptoms predicted visual memory scores 15 years later. It appears that sub-clinical depressive symptoms do not effect this cognitive domain in the middle-aged population.

Wearable Technology for High-Frequency Cognitive and Mood Assessment in Major Depressive Disorder: Longitudinal Observational Study.

BACKGROUND: Cognitive symptoms are common in major depressive disorder and may help to identify patients who need treatment or who are not experiencing adequate treatment response. Digital tools providing real-time data assessing cognitive function could help support patient treatment and remediation of cognitive and mood symptoms. OBJECTIVE: The aim of this study was to examine feasibility and validity of a wearable high-frequency cognitive and mood assessment app over 6 weeks, corresponding to when antidepressant pharmacotherapy begins to show efficacy. METHODS: A total of 30 patients (aged 19-63 years; 19 women) with mild-to-moderate depression participated in the study. The new Cognition Kit app was delivered via the Apple Watch, providing a high-resolution touch screen display for task presentation and logging responses. Cognition was assessed by the n-back task up to 3 times daily and depressed mood by 3 short questions once daily. Adherence was defined as participants completing at least 1 assessment daily. Selected tests sensitive to depression from the Cambridge Neuropsychological Test Automated Battery and validated questionnaires of depression symptom severity were administered on 3 occasions (weeks 1, 3, and 6). Exploratory analyses examined the relationship between mood and cognitive measures acquired in low- and high-frequency assessment. RESULTS: Adherence was excellent for mood and cognitive assessments (95% and 96%, respectively), did not deteriorate over time, and was not influenced by depression symptom severity or cognitive function at study onset. Analyses examining the relationship between high-frequency cognitive and mood assessment and validated measures showed good correspondence. Daily mood assessments correlated moderately with validated depression questionnaires (r=0.45-0.69 for total daily mood score), and daily cognitive assessments correlated moderately with validated cognitive tests sensitive to depression (r=0.37-0.50 for mean n-back). CONCLUSIONS: This study supports the feasibility and validity of high-frequency assessment of cognition and mood using wearable devices over an extended period in patients with major depressive disorder.

The Use of Cognitive Screening in Pharmacotherapy Trials for Cognitive Impairment Associated With Schizophrenia.

There are currently no regulatory approved pharmacological treatments for cognitive impairment associated with schizophrenia (CIAS). One possibility is that trial methodology itself is hindering their development. Emerging evidence suggests that patients with schizophrenia may show limited benefit from pro-cognitive interventions if they already exhibit intact cognitive performance, relative to normative thresholds. The aim of this report was to examine the extent to which objectively assessed cognitive performance has been used as an eligibility and/or stratification criterion in CIAS pharmacotherapy trials. On 16th January 2019, we conducted a systematic search of studies listed on ClinicalTrials.gov to identify randomized, double-blind, placebo-controlled, add-on pharmacotherapy trials conducted in patients with a diagnosis of schizophrenia, in which a paper-and-pencil or computerized cognitive task (or battery) was specified as a primary outcome measure. Of the 87 trials that met our inclusion criteria, 10 (11.5%) required the presence of an objectively assessed cognitive deficit as part of their patient eligibility criteria. No studies reported stratifying patients according to the presence or degree of cognitive impairment they exhibited. These results suggest that the vast majority of CIAS trials may have been underpowered due to the inclusion of cognitively "normal" patients. Purposive screening for cognitive impairment could increase CIAS trial success.

Polygenic Risk Score for Schizophrenia and Face-Processing Network in Young Adulthood.

Development of schizophrenia relates to both genetic and environmental factors. Functional deficits in many cognitive domains, including the ability to communicate in social interactions and impaired recognition of facial expressions, are common for patients with schizophrenia and might also be present in individuals at risk of developing schizophrenia. Here we explore whether an individual's polygenic risk score (PRS) for schizophrenia is associated with the degree of interregional similarities in blood oxygen level-dependent (BOLD) signal and gray matter volume of the face-processing network and whether the exposure to early adversity moderates this association. A total of 90 individuals (mean age 22 years, both functional and structural data available) were used for discovery analyses, and 211 individuals (mean age 26 years, structural data available) were used for replication of the structural findings. Both samples were drawn from the Northern Finland Birth Cohort 1986. We found that the degree of interregional similarities in BOLD signal and gray matter volume vary as a function of PRS; lowest interregional correlation (both measures) was observed in individuals with high PRS. We also replicated the gray matter volume finding. We did not find evidence for an interaction between early adversity and PRS on the interregional correlation of BOLD signal and gray matter volume. We speculate that the observed group differences in PRS-related correlations in both modalities may result from differences in the concurrent functional engagement of the face-processing regions over time, eg, via differences in exposure to social interaction with other people.

Diagnostic test accuracy of a novel smartphone application for the assessment of attention deficits in delirium in older hospitalised patients: a prospective cohort study protocol.

BACKGROUND: Delirium is a common and serious clinical syndrome which is often missed in routine clinical care. The core cognitive feature is inattention. We developed a novel bedside neuropsychological test for assessing inattention in delirium implemented on a smartphone platform (DelApp). We aim to evaluate the diagnostic performance of the DelApp in a representative cohort of older hospitalised patients. METHODS: This is a prospective study of older non-scheduled hospitalised patients (target n = 500, age ≥ 65), recruited from elderly care and acute orthopaedic wards. Exclusion criteria are: non-English speakers; severe vision or hearing impairment; photosensitive epilepsy. A structured reference standard delirium assessment based on DSM-5 criteria will be used, which includes a cognitive test battery administered by a trained assessor (Orientation-Memory-Concentration Test, Abbreviated Mental Test-10, Delirium Rating Severity Scale-Revised-98, digit span, months and days backwards, Vigilance A' test) and assessment of arousal (Observational Scale of Level of Arousal, Richmond Agitation Sedation Scale). Prior change in cognition will be documented using the Informant Questionnaire on Cognitive Decline in the Elderly. Patients will be categorized as delirium (with/without dementia), possible delirium, dementia, no cognitive impairment, or undetermined. A separate assessor (blinded to diagnosis and assessments) will administer the DelApp index test within 3 h of the reference standard assessment. The DelApp comprises assessment of arousal (score 0-4) and sustained attention (score 0-6), yielding a total score between 0 and 10 (higher score = better performance). Outcomes (length of stay, mortality and discharge location) will be collected at 12 weeks. We will evaluate a priori cutpoints derived from a previous case-control study. Measures of the accuracy of DelApp will include sensitivity, specificity, positive and negative predictive values, and area under the ROC curve. We plan repeat assessments on up to 4 occasions in a purposive subsample of 30 patients (15 delirium, 15 no delirium) to examine changes over time. DISCUSSION: This study evaluates the diagnostic test accuracy of a novel smartphone test for delirium in a representative cohort of older hospitalised patients, including those with dementia. DelApp has the potential to be a convenient, objective method of improving delirium assessment for older people in acute care. TRIAL REGISTRATION: Clinical trials.gov, NCT02590796 . Registered on 29 Oct 2015. Protocol version 5, dated 25 July 2016.