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.

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.

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.

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.

Core Competencies for Chronic Disease Prevention Practice.

Chronic disease prevention practice is an important specialization within public health and health care that connects chronic conditions, causes, prevention tactics, and population-based health promotion modalities. Required competencies for successful chronic disease prevention and health promotion encompass leadership, epidemiology, program practice, and evaluation, among others. In 2007, the National Association of Chronic Disease Directors (NACDD) developed and codified the Core Chronic Disease Prevention Competencies (Competencies), a standard set of competencies for professionals in chronic disease prevention and control. NACDD also devised support tools to assist individuals and managers in increasing capacity and opportunities for member growth, thereby benefitting the agencies they serve. In revisiting the Competencies in 2015 through 2018, the NACDD Professional Development Committee reviewed uses, conducted member surveys, polled NACDD councils, and produced recommendations. The goal of this process was to recognize rapid changes in the environments, practices, and characteristics that affect chronic disease prevention, both at the population level and for individual groups at risk during the past 10 years. In addition, opportunities existed to benefit from the changes in technology that have increased demands on health professionals, who as a result have had to adapt to these changes. We worked with the NACDD Learning and Professional Development Committee and reviewed learning offerings, other related competency sets, and tools for performance assessment. The results of the review include a final set of Competencies and subcompetencies, a guide to using the competencies, and a fully integrated interactive assessment tool used by individuals, managers, and teams. Going forward, NACDD's strategic focus includes a regular review of the Competencies and building chronic disease learning assets.

Cognition, psychosis risk and metabolic measures in two adolescent birth cohorts.

BACKGROUND: Psychoses, especially schizophrenia, are often preceded by cognitive deficits and psychosis risk states. Altered metabolic profiles have been found in schizophrenia. However, the associations between metabolic profiles and poorer cognitive performance and psychosis risk in the population remain to be determined. METHODS: Detailed molecular profiles were measured for up to 8976 individuals from two general population-based prospective birth cohorts: the Northern Finland Birth Cohort 1986 (NFBC 1986) and the Avon Longitudinal Study of Parents and Children (ALSPAC). A high-throughput nuclear magnetic resonance spectroscopy platform was used to quantify 70 metabolic measures at age 15-16 years in the NFBC 1986 and at ages 15 and 17 years in ALSPAC. Psychosis risk was assessed using the PROD-screen questionnaire at age 15-16 years in the NFBC 1986 or the psychotic-like symptoms assessment at age 17 years in ALSPAC. Cognitive measures included academic performance at age 16 years in both cohorts and general intelligence and executive function in ALSPAC. Logistic regression measured cross-sectional and longitudinal associations between metabolic measures and psychosis risk and cognitive performance, controlling for important covariates. RESULTS: Seven metabolic measures, primarily fatty acid (FA) measures, showed cross-sectional associations with general cognitive performance, four across both cohorts (low density lipoprotein diameter, monounsaturated FA ratio, omega-3 ratio and docosahexaenoic acid ratio), even after controlling for important mental and physical health covariates. Psychosis risk showed minimal metabolic associations. CONCLUSIONS: FA ratios may be important in marking risk for cognitive deficits in adolescence. Further research is needed to clarify whether these biomarkers could be causal and thereby possible targets for intervention.

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.

Early adversity and brain response to faces in young adulthood.

Early stressors play a key role in shaping interindividual differences in vulnerability to various psychopathologies, which according to the diathesis-stress model might relate to the elevated glucocorticoid secretion and impaired responsiveness to stress. Furthermore, previous studies have shown that individuals exposed to early adversity have deficits in emotion processing from faces. This study aims to explore whether early adversities associate with brain response to faces and whether this association might associate with the regional variations in mRNA expression of the glucocorticoid receptor gene (NR3C1). A total of 104 individuals drawn from the Northern Finland Brith Cohort 1986 participated in a face-task functional magnetic resonance imaging (fMRI) study. A large independent dataset (IMAGEN, N = 1739) was utilized for reducing fMRI data-analytical space in the NFBC 1986 dataset. Early adversities were associated with deviant brain response to fearful faces (MANCOVA, P = 0.006) and with weaker performance in fearful facial expression recognition (P = 0.01). Glucocorticoid receptor gene expression (data from the Allen Human Brain Atlas) correlated with the degree of associations between early adversities and brain response to fearful faces (R2 = 0.25, P = 0.01) across different brain regions. Our results suggest that early adversities contribute to brain response to faces and that this association is mediated in part by the glucocorticoid system. Hum Brain Mapp 38:4470-4478, 2017. © 2017 Wiley Periodicals, Inc.

Smoking in pregnancy, adolescent mental health and cognitive performance in young adult offspring: results from a matched sample within a Finnish cohort.

BACKGROUND: The association between prenatal exposure to maternal cigarette smoking (PEMCS) and adult cognition is debated, including if there are differences according to sex. We aimed to determine if there are associations between PEMCS and cognition in early adulthood in men and women and examine if observed associations were mediated by adolescent mental health factors that are associated with cognition, namely psychotic-like experiences (PLEs), inattention and hyperactivity, and other externalizing behaviors. METHODS: Participants were 471 individuals drawn from the general population-based Northern Finland 1986 Birth Cohort (NFBC 1986) followed up from pregnancy and birth to early adulthood; individuals with PEMCS were matched with those without PEMCS by socioeconomic and demographic factors. Cognitive performance in adulthood was assessed with a range of tests and their association with PEMCS was measured by sex using hierarchical linear regression, unadjusted and then controlling for potential confounders, mediators and moderators, including adolescent mental health factors. RESULTS: There were no associations between PEMCS and cognitive scores in females. In males, there were associations with vocabulary (beta = -0.444, 95% CI: -0.783, -0.104) and matrix reasoning (beta = -0.379, 95% CI: -0.711, -0.047). CONCLUSIONS: While associations between PEMCS and cognition were limited, observed findings with measures of general intelligence in males contribute to suggestions of differences in response to PEMCS by sex. Furthermore, observed associations may be partly mediated by earlier inattention and hyperactivity. Findings add support to efforts aimed to eliminate smoking in pregnancy.

Brain structural deficits and working memory fMRI dysfunction in young adults who were diagnosed with ADHD in adolescence.

When adolescents with ADHD enter adulthood, some no longer meet disorder diagnostic criteria but it is unknown if biological and cognitive abnorma lities persist. We tested the hypothesis that people diagnosed with ADHD during adolescence present residual brain abnormalities both in brain structure and in working memory brain function. 83 young adults (aged 20-24 years) from the Northern Finland 1986 Birth Cohort were classified as diagnosed with ADHD in adolescence (adolescence ADHD, n = 49) or a control group (n = 34). Only one patient had received medication for ADHD. T1-weighted brain scans were acquired and processed in a voxel-based analysis using permutation-based statistics. A sub-sample of both groups (ADHD, n = 21; controls n = 23) also performed a Sternberg working memory task whilst acquiring fMRI data. Areas of structural difference were used as a region of interest to evaluate the implications that structural abnormalities found in the ADHD group might have on working memory function. There was lower grey matter volume bilaterally in adolescence ADHD participants in the caudate (p < 0.05 FWE corrected across the whole brain) at age 20-24. Working memory was poorer in adolescence ADHD participants, with associated failure to show normal load-dependent caudate activation. Young adults diagnosed with ADHD in adolescence have structural and functional deficits in the caudate associated with abnormal working memory function. These findings are not secondary to stimulant treatment, and emphasise the importance of taking a wider perspective on ADHD outcomes than simply whether or not a particular patient meets diagnostic criteria at any given point in time.

Early intervention in Alzheimer's disease: a health economic study of the effects of diagnostic timing.

BACKGROUND: Intervention and treatment in Alzheimer's disease dementia (AD-dementia) can be cost effective but the majority of patients are not diagnosed in a timely manner. Technology is now available that can enable the earlier detection of cognitive loss associated with incipient dementia, offering the potential for earlier intervention in the UK health care system. This study aimed to determine to what extent the timing of an intervention affects its cost-effectiveness. METHODS: Using published data describing cognitive decline in the years prior to an AD diagnosis, we modelled the effects on healthcare costs and quality-adjusted life years of hypothetical symptomatic and disease-modifying interventions. Early and standard interventions were assumed to have equal clinical effects, but the early intervention could be applied up to eight years prior to standard diagnosis. RESULTS: A symptomatic treatment which immediately improved cognition by one MMSE point and reduced in efficacy over three years, would produce a maximum net benefit when applied at the earliest timepoint considered, i.e. eight years prior to standard diagnosis. In this scenario, the net benefit was reduced by around 17% for every year that intervention was delayed. In contrast, for a disease-modifying intervention which halted cognitive decline for one year, economic benefits would peak when treatment effects were applied two years prior to standard diagnosis. In these models, the maximum net benefit of the disease modifying intervention was fifteen times larger than that of the symptomatic treatment. CONCLUSION: Timeliness of intervention is likely to have an important impact on the cost-effectiveness of both current and future treatments. Healthcare policy should aim to optimise the timing of AD-dementia diagnosis, which is likely to necessitate detecting and treating patients several years prior to current clinical practice.

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.

PsyCog: A computerised mini battery for assessing cognition in psychosis.

Despite the functional impact of cognitive deficit in people with psychosis, objective cognitive assessment is not typically part of routine clinical care. This is partly due to the length of traditional assessments and the need for a highly trained administrator. Brief, automated computerised assessments could help to address this issue. We present data from an evaluation of PsyCog, a computerised, non-verbal, mini battery of cognitive tests. Healthy Control (HC) (N = 135), Clinical High Risk (CHR) (N = 233), and First Episode Psychosis (FEP) (N = 301) participants from a multi-centre prospective study were assessed at baseline, 6 months, and 12 months. PsyCog was used to assess cognitive performance at baseline and at up to two follow-up timepoints. Mean total testing time was 35.95 min (SD = 2.87). Relative to HCs, effect sizes of performance impairments were medium to large in FEP patients (composite score G = 1.21, subtest range = 0.52-0.88) and small to medium in CHR patients (composite score G = 0.59, subtest range = 0.18-0.49). Site effects were minimal, and test-retest reliability of the PsyCog composite was good (ICC = 0.82-0.89), though some practice effects and differences in data completion between groups were found. The present implementation of PsyCog shows it to be a useful tool for assessing cognitive function in people with psychosis. Computerised cognitive assessments have the potential to facilitate the evaluation of cognition in psychosis in both research and in clinical care, though caution should still be taken in terms of implementation and study design.

Cognitive health begins at conception: addressing dementia as a lifelong and preventable condition.

BACKGROUND: Dementia is a major public health problem that poses an increasing burden on the health and wealth of societies worldwide. Because the efficacy of current treatments is limited, increasing efforts are required to prevent the diseases that cause dementia. DISCUSSION: We consider the evidence that lifelong prevention strategies may be an effective way to tackle the national burden of dementia in the absence of a cure. The links between lifestyle and cardiovascular disease are widely understood and accepted, but health professionals and patients remain unconvinced about the extent to which risk for dementia can be modified. However, there is strong evidence that at least half of risk for dementia is attributable to lifestyle factors such as diet, exercise and smoking. Moreover, the disease processes that result in dementia develop over several decades, implying that attempts to ameliorate them need to start early in life. Some modifiable risk factors for dementia act from the earliest stages of life, including in utero. SUMMARY: Rebalancing efforts from the development of treatments to increased emphasis on prevention may be an alternative means to reducing the impact of dementia on society.

Genetic predictors of risk and resilience in psychiatric disorders: a cross-disorder genome-wide association study of functional impairment in major depressive disorder, bipolar disorder, and schizophrenia.

Functional impairment is one of the most enduring, intractable consequences of psychiatric disorders and is both familial and heritable. Previous studies have suggested that variation in functional impairment can be independent of symptom severity. Here we report the first genome-wide association study (GWAS) of functional impairment in the context of major mental illness. Participants of European-American descent (N = 2,246) were included from three large treatment studies of bipolar disorder (STEP-BD) (N = 765), major depressive disorder (STAR*D) (N = 1091), and schizophrenia (CATIE) (N = 390). At study entry, participants completed the SF-12, a widely used measure of health-related quality of life. We performed a GWAS and pathway analysis of the mental and physical components of health-related quality of life across diagnosis (∼1.6 million single nucleotide polymorphisms), adjusting for psychiatric symptom severity. Psychiatric symptom severity was a significant predictor of functional impairment, but it accounted for less than one-third of the variance across disorders. After controlling for diagnostic category and symptom severity, the strongest evidence of genetic association was between variants in ADAMTS16 and physical functioning (P = 5.87 × 10(-8) ). Pathway analysis did not indicate significant enrichment after correction for gene clustering and multiple testing. This study illustrates a phenotypic framework for examining genetic contributions to functional impairment across psychiatric disorders.

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.

The Influence of Comorbidities, General Health Status, and Self-Care Self-Efficacy on COVID-19 Symptoms During the Omicron Wave.

Background The emergence of the less virulent COVID-19 strains such as Omicron and its subvariants shifted the paradigm of COVID-19 treatment from inpatient treatment to regular outpatient care. The individual health determinants affecting COVID-19 disease severity among vulnerable adults treated in outpatient settings are an under-researched area. Methods This study conducted in an outpatient COVID-19 antibody infusion center employed a cross-sectional survey design to explore the impact of comorbidities, general health status, and self-care self-efficacy on COVID-19 symptom severity. We recruited 120 COVID-19-positive participants over 40 years of age, of which 117 completed the study with 87 providing complete data. After the screening and consenting process, the participants completed the following surveys in a secure REDCap survey software (Vanderbilt University, Nashville, USA) on an iPad (Apple Inc., Cupertino, USA): 1) sociodemographic questionnaire, 2) Charlson Comorbidity Index (CCI) to capture comorbidities, 3) Medical Outcomes Study Short-Form (SF-12) to assess general health including physical (PCS) and mental (MCS) health subscales, 4) Self-Care Self-Efficacy Scale (SCSES) to measure self-care self-efficacy, and 5) the COVID-19 Symptom rating scale (COVID-19 SRS). Statistical analysis used were Chi-square and Pearson correlations.  Results As evidenced by CCI, the top five comorbidities were hypertension (42%), diabetes mellitus (31%), pulmonary disease (19%), depression (14%), and solid tumors (11%). Age was statistically significantly correlated to comorbidity burden (p<0.0001). Severe COVID-19 symptoms reported were fatigue, myalgia, cough, runny nose, and sore throat. The general health status measure (SF-12) subscales showed that the patient's mental component summary (MCS) was more statistically significant to COVID-19 symptom severity than the physical component summary (PCS). The MCS demonstrated a statistically significant correlation with fatigue and myalgia (p<0.0001), headache and breathing difficulties (p<0.001), nausea/vomiting (p<0.01), and abdominal pain/diarrhea (p<0.05). The PCS showed a lesser statistically significant correlation with fatigue, myalgia, headaches (p<0.01), fever/chills, cough, congestion/runny nose, night sweats, breathing difficulties, nausea/vomiting, and abdominal pain/diarrhea (p<0.05). Interestingly, the 'loss of smell' which is the hallmark symptom of COVID-19 was the only symptom that showed a statically significant correlation with the Charlson Comorbidity Index (p<0.05), and it did not show any association with either mental (SF-12 MCS) or physical (SF-12 PCS) health status. The SF-12 MCS also showed a statistically significant correlation with a diagnosis of depression (p< 0.01), validating it as a true measure of mental health among vulnerable adults. The SCSES was not correlated with any of the COVID-19 symptoms. Conclusions The patient's general health status, especially mental health was more statistically significant to COVID-19 symptoms. The COVID-19 hallmark symptom of 'loss of smell' was the only symptom that showed statistical significance with comorbidities. Within the limitations of a cross-sectional survey design and convenient sampling methods, this study calls to tailor general health status, especially mental health, and cumulative comorbidity burden to risk assessment/risk stratification of COVID-19 care.

Perioperative Risk Assessment for Skin Injury.

Hospital-acquired pressure injuries create a tremendous cost to health care organizations and negatively affect quality and patient safety. Surgical patients are at an increased risk for skin injury, particularly a pressure injury, because of a lack of sensation and immobility during a procedure. An interprofessional team at our facility identified factors that place surgical patients at risk for skin injury. We developed a risk assessment protocol in March 2021 using the Six Sigma DMAIC (define, measure, analyze, improve, and control) method. After data review and analysis, we identified age of 65 years or older, existence of a skin condition, and procedural duration greater than four hours as significant predictors for postoperative skin injury. Our findings reinforce the benefit of using an appropriate risk assessment protocol that alerts the perioperative team members to at-risk patients.