Historically, psychiatric conditions and neurodegenerative diseases have been considered differential diagnoses in older adults with cognitive impairment. However, recent evidence has shown that neuropsychiatric symptoms may be prodromal for neurodegenerative disease. Subjective Cognitive Decline (SCD) is a potential marker for pre-clinical Alzheimer’s Disease (AD) that is frequently related to mood disturbances. Delineating the relationship between neuropsychiatric symptoms, SCD, and cognitive impairment will help to define both the independent and combined utility of SCD and neuropsychiatric symptoms as markers of preclinical AD. This abstract uses the DSM-5 Cross-Cutting Measure (DSM-5 CC), a novel comprehensive screening tool for psychiatric symptoms, to examine the relationship between objective and subjective measures of cognition as they relate to neuropsychiatric symptoms.

27 community dwelling, cognitively diverse older adults (78% female, mean age 71.9 ± 7) were enrolled in the Concerns about Memory Problems (CAMP) study. Inclusion criteria included the expressed concern about memory functioning by participants on a 5-item screener, while exclusion criteria were defined as previous diagnosis of neurodegenerative diseases and/or major stroke. All participants completed neuropsychological testing and study surveys including the DSM-5 CC. Participants completed Level 1 and all Level 2 (L2) forms of the DSM-5 CC. Spearman two-tailed non-parametric correlations and independent samples t-tests were conducted to examine the relationship between the DSM-5 CC and the 5-item subjective cognition screener, as well as the DSM-5 CC and objective cognition results.

Subjective measures of cognition, as measured by answers to the 5-item screening measure, were significantly associated with DSM-5 CC measures. Question 1 on the SCD screener which asks, “Compared to others your age, do you have difficulty with memory or thinking abilities?” was associated with anger (p=.033) and depression (p=.018) L2 forms. Question 3, “Do any difficulties with memory or thinking abilities make it difficult for you to do things in daily life?)” was associated with the L2 forms for somatic symptoms (p=.016) and repetitive thoughts and behaviors (p<.001). Objective measures of cognition from neuropsychological testing also correlated with DSM-5 CC sub-scores. Digits Backwards Length (DBL) correlated with DSM-5 CC Level 1 Sum (r= -.57, p=.002). DBL (r=-.59 p=.001) and Digits Backwards Total Correct (DBTC) (r=-.47, p=.013) associated with somatic symptoms L2 and sleep L2 (DBL: r=,-.45 p=.019; DBTC: r=-.39, p=.044). Category Naming (animals) was also associated with anxiety L2 (r=-.42, p=.030).

Subjective and objective measures of cognition were each related to sub-scores of the DSM-5 CC. Interestingly, the associations were largely non-overlapping. These results highlight the importance of considering a wide range of neuropsychiatric symptoms in the assessment of SCD and cognitive impairment. Findings contribute to the growing body of literature suggesting that neuropsychiatric symptoms should be studied in conjunction with cognitive symptoms among older adults as co-occurring phenomena. Future directions will need to include longitudinal studies that can examine the prodromal nature of SCD and neuropsychiatric symptoms for Alzheimer’s and other neurodegenerative disorders.

The aim of this study is to assess prevalence of major depressive disorder (MDD), generalized anxiety disorder (GAD), and posttraumatic stress disorder (PTSD) in students of Keyano College 18 months after a wildfire and to determine the predictors of likely MDD, GAD, and PTSD in the respondents.

A quantitative cross-sectional survey was used to collect data through self-administered, paper-based questionnaires to determine likely MDD, GAD, and PTSD using the PHQ 9, GAD-7, and the PTSD Checklist for DSM 5, Part 3, respectively. Data were analyzed with SPSS version 20 (IBM Corp, Armonk, NY) using univariate analysis with chi-square tests.

Eighteen months after the wildfire, the 1-month prevalence rates for MDD, GAD, and PTSD among the college students were 23.4%, 18.7%, and 11.0%, respectively. There were statistically significant associations between multiple sociodemographic variables and the likelihood respondents presented with MDD, GAD, and PTSD 18 months after the wildfire. There were also associations between the likely MDD, GAD, and PTSD and abuse/dependence on alcohol and substances in respondents at 18 months.

Our study has established prevalence rates for MDD, GAD, and PTDS among college students 18 months after the Fort McMurray wildfires. Further studies are needed to explore the impact of college-based mental health interventions on the long-term mental health effects of the wildfires.

Studies suggest that alcohol consumption and alcohol use disorders have distinct genetic backgrounds.

We examined whether polygenic risk scores (PRS) for consumption and problem subscales of the Alcohol Use Disorders Identification Test (AUDIT-C, AUDIT-P) in the UK Biobank (UKB; N = 121 630) correlate with alcohol outcomes in four independent samples: an ascertained cohort, the Collaborative Study on the Genetics of Alcoholism (COGA; N = 6850), and population-based cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC; N = 5911), Generation Scotland (GS; N = 17 461), and an independent subset of UKB (N = 245 947). Regression models and survival analyses tested whether the PRS were associated with the alcohol-related outcomes.

In COGA, AUDIT-P PRS was associated with alcohol dependence, AUD symptom count, maximum drinks (R2 = 0.47–0.68%, p = 2.0 × 10−8–1.0 × 10−10), and increased likelihood of onset of alcohol dependence (hazard ratio = 1.15, p = 4.7 × 10−8); AUDIT-C PRS was not an independent predictor of any phenotype. In ALSPAC, the AUDIT-C PRS was associated with alcohol dependence (R2 = 0.96%, p = 4.8 × 10−6). In GS, AUDIT-C PRS was a better predictor of weekly alcohol use (R2 = 0.27%, p = 5.5 × 10−11), while AUDIT-P PRS was more associated with problem drinking (R2 = 0.40%, p = 9.0 × 10−7). Lastly, AUDIT-P PRS was associated with ICD-based alcohol-related disorders in the UKB subset (R2 = 0.18%, p < 2.0 × 10−16).

AUDIT-P PRS was associated with a range of alcohol-related phenotypes across population-based and ascertained cohorts, while AUDIT-C PRS showed less utility in the ascertained cohort. We show that AUDIT-P is genetically correlated with both use and misuse and demonstrate the influence of ascertainment schemes on PRS analyses.

Previous studies using resting-state functional neuroimaging have revealed alterations in whole-brain images, connectome-wide functional connectivity and graph-based metrics in groups of patients with schizophrenia relative to groups of healthy controls. However, it is unclear which of these measures best captures the neural correlates of this disorder at the level of the individual patient.

Here we investigated the relative diagnostic value of these measures. A total of 295 patients with schizophrenia and 452 healthy controls were investigated using resting-state functional Magnetic Resonance Imaging at five research centres. Connectome-wide functional networks were constructed by thresholding correlation matrices of 90 brain regions, and their topological properties were analyzed using graph theory-based methods. Single-subject classification was performed using three machine learning (ML) approaches associated with varying degrees of complexity and abstraction, namely logistic regression, support vector machine and deep learning technology.

Connectome-wide functional connectivity allowed single-subject classification of patients and controls with higher accuracy (average: 81%) than both whole-brain images (average: 53%) and graph-based metrics (average: 69%). Classification based on connectome-wide functional connectivity was driven by a distributed bilateral network including the thalamus and temporal regions.

These results were replicated across the three employed ML approaches. Connectome-wide functional connectivity permits differentiation of patients with schizophrenia from healthy controls at single-subject level with greater accuracy; this pattern of results is consistent with the ‘dysconnectivity hypothesis’ of schizophrenia, which states that the neural basis of the disorder is best understood in terms of system-level functional connectivity alterations.

Depression is a prevalent long-term condition that is associated with substantial resource use. Telehealth may offer a cost-effective means of supporting the management of people with depression.

To investigate the cost-effectiveness of a telehealth intervention (‘Healthlines’) for patients with depression.

A prospective patient-level economic evaluation conducted alongside a randomised controlled trial. Patients were recruited through primary care, and the intervention was delivered via a telehealth service. Participants with a confirmed diagnosis of depression and PHQ-9 score ≥10 were recruited from 43 English general practices. A series of up to 10 scripted, theory-led, telephone encounters with health information advisers supported participants to effect a behaviour change, use online resources, optimise medication and improve adherence. The intervention was delivered alongside usual care and was designed to support rather than duplicate primary care. Cost-effectiveness from a combined health and social care perspective was measured by net monetary benefit at the end of 12 months of follow-up, calculated from incremental cost and incremental quality-adjusted life years (QALYs). Cost–consequence analysis included cost of lost productivity, participant out-of-pocket expenditure and the clinical outcome.

A total of 609 participants were randomised – 307 to receive the Healthlines intervention plus usual care and 302 to receive usual care alone. Forty-five per cent of participants had missing quality of life data, 41% had missing cost data and 51% of participants had missing data on either cost or utility, or both. Multiple imputation was used for the base-case analysis. The intervention was associated with incremental mean per-patient National Health Service/personal social services cost of £168 (95% CI £43 to £294) and an incremental QALY gain of 0.001 (95% CI −0.023 to 0.026). The incremental cost-effectiveness ratio was £132 630. Net monetary benefit at a cost-effectiveness threshold of £20 000 was –£143 (95% CI –£164 to –£122) and the probability of the intervention being cost-effective at this threshold value was 0.30. Productivity costs were higher in the intervention arm, but out-of-pocket expenses were lower.

The Healthlines service was acceptable to patients as a means of condition management, and response to treatment after 4 months was higher for participants randomised to the intervention. However, the positive average intervention effect size was modest, and incremental costs were high relative to a small incremental QALY gain at 12 months. The intervention is not likely to be cost-effective in its current form.

The objective was to develop a new National Healthcare Safety Network (NHSN) risk model for sternal, deep incisional, and organ/space (complex) surgical site infections (SSIs) following coronary artery bypass graft (CABG) procedures, detected on admission and readmission, consistent with public reporting requirements.

A total of 133,503 CABG procedures with 4,008 associated complex SSIs reported by 293 NHSN hospitals in the United States.

CABG procedures performed from January 1, 2006, through December 31, 2008, were analyzed. Potential SSI risk factors were identified by univariate analysis. Multivariate analysis with forward stepwise logistic regression modeling was used to develop the new model. The c-index was used to compare the predictive power of the new and NHSN risk index models.

Multivariate analysis independent risk factors included ASA score, procedure duration, female gender, age, and medical school affiliation. The new risk model has significantly improved predictive performance over the NHSN risk index (c-index, 0.62 and 0.56, respectively).

Traditionally, the NHSN surveillance system has used a risk index to provide procedure-specific risk-stratified SSI rates to hospitals. A new CABG sternal, complex SSI risk model developed by multivariate analysis has improved predictive performance over the traditional NHSN risk index and is being considered for endorsement as a measure for public reporting.