Cognition has been identified as an area of priority in examining health impacts of COVID-19 infection, and evidence suggests the virus invades the brain, with potential for long-term cognitive impact. Studies utilizing screening measures have reported cognitive sequelae (e.g., attention disorder, executive dysfunction) of the post-COVID-19 condition (i.e., long-haulers). More extensive examination of cognitive difficulties via comprehensive neuropsychological assessment is critical to informing treatment for those experiencing cognitive or functional difficulties post-infection. We aimed to comprehensively evaluate cognitive resiliencies and vulnerabilities of acutely recovered COVID-19 patients, across key domains (i.e., attention, processing speed, language, visuospatial abilities, memory, executive functioning), compared to healthy controls.

Adults (N=103; aged 19-85; 69.2% female) who had COVID-19 at least three months prior (n=50) and those with no history of infection (n=53) completed demographic and health questionnaires via Qualtrics, along with measures of depressive (CES-D) and anxiety (GAD-7) symptoms, the Lawton-Brody Instrumental Activities of Daily Living (IADL) Scale, and a measure of subjective cognitive difficulties (SCD-Q). Participants (n=84) completed a teleneuropsychology assessment including a short interview and battery of neuropsychological tests assessing attention (BTA, Digit Span Forward), processing speed (DKEFS Colour Naming & Word Reading, SDMT), language (FAS, Animals, NAB Naming), visuospatial abilities (JLO, RCFT Copy), verbal and visual memory (HVLT-R, NAB Shape Learning, RCFT), and executive function (DKEFS Color-Word Interference & Switching, Digit Span Backward & Sequencing, BRIEF), and including multiple measures of cognitive effort/assessment validity (RFIT, RDS), and a self-report measure of symptom validity (SIMS). T-tests were used to examine demographic and health variables between COVID-19 and control groups. MANCOVA were used to examine group differences across each cognitive domain assessed, and across cognitive effort and symptom validity tasks, while controlling for English language status.

Group comparisons indicated that the COVID-19 group was slightly older (mean age = 40 vs. 34 yrs.; f=-2.101, p=0.04). Those who had COVID-19 reported more difficulties completing IADLs (f=2.204; p=0.03), more depressive symptoms (f=-2.299; p=0.02), and more subjective cognitive difficulties (f=-3.886; p<0.01). Examination of cognitive performance indicated a main effect of prior infection on executive function, controlling for language status (Wilks’ /\=0.817, F(6,73)=2.733, p=0.02). Specifically, having COVID-19 was associated with worse DKEFS Colour-Word Switching performance (p=0.01) and slightly higher selfreported difficulties on the BRIEF MI (p=0.04). No other significant group differences were seen across cognitive domains. There was also a main effect of COVID-19 infection on effort and symptom validity task performance (Wilks’ /\=0.705, F(10,70)=2.923, p<0.01). Specifically, prior infection was associated with higher SIMS Neurologic Impairment (p<0.01) and Amnestic Disorders (p<0.01) subscale scores, and paradoxically, slightly higher RFIT combined scores (p=0.02).

Interestingly, results indicate a significant role for subjective cognitive complaints and potential exaggeration of cognitive symptoms post-COVID-19 infection, in the absence of differences in objective performance in most cognitive domains. While subtle differences are seen on some executive function measures, mean group differences are small, and in the context of higher SIMS subscale scores, may not be readily interpretable. Studies employing similarly comprehensive neuropsychological assessments including validity measures in larger samples are needed to further disambiguate potential objective cognitive performance decrements from subjectively experienced difficulties.

This study aimed to determine how modifiable risk factors, such as physical exercise and social support, and non-modifiable risk factors, such as genetic risk may affect cognitive function over time in older adults. As well, the study explored how changes in modifiable risk factors (i.e., increase in exercise) may affect cognitive function over time. This research question was shaped with the help of a patient partner team.

The study used UK Biobank data, and patient partners were involved in shaping research questions/goals. The UK Biobank study had participants complete comprehensive baseline assessments (2006-2010), with subgroups also completing repeat assessments (2012-2013), imaging assessments (2014-ongoing) and/or repeat imaging assessments (2019-ongoing; i.e., 2-4 data points per participant). Age, sex, education, ethnicity, and apolipoprotein E (APOE) e4 status (at least one e4 allele present) data were collected at baseline. Employment, physical activity, social support, and recent depressive symptom data were collected across timepoints. A Fluid intelligence score was obtained at each timepoint via a series of thirteen 1-pt. reasoning tasks (range: 0-13). Participants who did not complete cognitive testing at baseline and at least one other time point, and those with neurological conditions or events (e.g., stroke, epilepsy, dementia) were excluded (final N=17,409).

Multi-Level Modeling (with Maximum Likelihood) was utilized, with fluid intelligence as the primary outcome measure. We ran Model 1: fully unconditioned, Model 2: with time predictor in years (baseline= 0), and Model 3: with baseline physical activity, social support and APOE e-4 predictors and covariates (mean-centered as appropriate), time-varying physical activity and social support predictors, and interaction terms. Nonsignificant interaction terms were trimmed from Model 3 to facilitate interpretation.

Model 1 was significant (p<.001) with an intraclass correlation (ICC) of 0.64, suggesting that 64% of the total variance in fluid intelligence in this sample is due to interindividual differences. Model 2 revealed that the average fluid intelligence score at baseline mean age (55.85) was 6.79 and significantly decreased with each year increase since baseline. Results from Model 3 (trimmed) revealed that being male, white, and having at least a university degree were associated with higher score at baseline, while being older and having more recent depressive symptoms were associated with lower scores. Higher social support quality was associated with higher scores while higher social support quantity was associated with lower scores at baseline; however, higher social support quantity at baseline was associated with less decline in scores over time. Surprisingly, having at least one e4 allele was associated with higher scores. Engaging in more moderate physical activity was associated with lower scores at baseline, however, individuals who increased the length of their moderate physical activity sessions over time showed higher timepoint-specific fluid intelligence scores. Additional significant interactions will be elaborated.

Results suggest that increases in the length of moderate physical activity exercise sessions were associated with better cognitive function over time. Having better social support quality was also associated with better cognitive function, while higher social support quantity was associated with less cognitive decline over time. These findings suggest that positive lifestyle changes in older adulthood may slow cognitive decline.

Growing evidence indicates that COVID-19 infection adversely impacts cognitive functioning, with COVID-19 patients demonstrating high rates of objective and subjective cognitive impairments (Daroische et al., 2020; Miskowiak et al., 2021). Given the prevalence and potentially debilitating nature of post-COVID-19 cognitive symptoms, understanding factors that mitigate the impact of COVID-19 infection on cognitive functioning is paramount to developing interventions that facilitate recovery. Resilience, the ability to cope with and grow from challenges, has been associated with improved cognitive performance in healthy adults and linked to decreased perceived cognitive difficulties in post-COVID-19 patients (Connor & Davidson, 2003; Deng et al., 2018; Jung et al., 2021). However, resilience has not yet been examined as a potential attenuator of the relationship between COVID-19 and either perceived or objective cognitive function. This study aims to investigate the role of resilience as a protective factor against experience of cognitive function difficulties in COVID-19 patients by probing the role of resilience as a moderator of the relationship between COVID-19 diagnosis and cognitive functioning (both perceived and objective).

Participants (mean age=36.93, 30.10% male) were recruited from British Columbia and Ontario. The sample included 53 adults who had never been diagnosed with COVID-19 and 50 adults diagnosed with symptomatic COVID-19 at least three months prior and not ventilated. Participants completed online questionnaires (n=103) to assess depression (the Center for Epidemiological Studies Depression Scale), anxiety (7-item Generalized Anxiety Disorder Scale), subjective cognitive functioning (The Subjective Cognitive Decline Questionnaire), and resilience (2-item Connor-Davidson Resilience Scale). Participants then completed neuropsychological tests (n=82) measuring attention, processing speed, memory, language, visuospatial skills, and executive function via teleconference, with scores averaged to create a global objective cognition score. Moderated multiple regression was employed to assess the impact of resilience on the relationship between COVID-19 diagnosis and both objective and perceived cognition, controlling for gender, ethnicity, income, age, anxiety, and depression.

Average scores in the COVID-19 group exceeded diagnostic cut-offs for clinical depression (M=16.67, SD=10.77) and mild anxiety (M=5.27, SD=4.99), while the control group scored below diagnostic thresholds for depression (M=11.96, SD=9.76) and mild anxiety (M=4.48, SD=5.07). Controlling for sociodemographic and mental health characteristics, COVID-19 diagnosis was not associated with objective global cognitive functioning (b=-.07, se=1.71, p=.624) or subjective cognitive functioning (b=.16, se=1.32, p=.12), nor was resilience associated with objective global cognitive functioning (b=.19, se=1.50, p=.44) or subjective cognitive functioning (b=-.02, se=1.09, p=.89).

Findings indicate that COVID-19 patients may be at risk for depression and anxiety. Results of this study fail to support a relationship between COVID-19 and cognitive functioning beyond the impact of sociodemographic and mental health variables. Thus, the role of resilience as a protective factor against COVID-19 related cognitive difficulties could not be fully explored. However, findings should be considered in the context of study limitations, including a small sample size. Future research should employ larger samples to further examine the relationship between COVID-19 infection and cognition, focusing on mental health characteristics and resilience as potential risk and protective factors.

Many individuals with COVID-19 develop mild to moderate physical symptoms that can last days to months. In addition to physical symptoms, individuals with COVID-19 have reported depressive symptoms and cognitive decline, posing a long-term threat to mental health and functional outcomes. Few studies have examined the presence of co-occurring depression and subjective cognitive decline in individuals who tested positive for COVID-19. The current study examined whether having COVID-19 is subsequently associated with greater depressive symptoms and subjective cognitive decline when compared to healthy individuals. Our study also examined differential associations between symptoms of depression and subjective cognitive decline between individuals who have and have never had COVID-19.

Adults (N = 104; mean age = 37 years, 69% female) were recruited online from Ontario and British Columbia, Canada. Participants were categorized into two groups: (1) persons who tested positive for COVID-19 at least three months prior, had been symptomatic, and had not been ventilated (N = 50); and (2) persons who have never been suspected of having COVID-19 (N = 54). The Center for Epidemiological Studies Depression Scale (CES-D) and the Subjective Cognitive Decline Questionnaire (SCD-Q) were administered to both groups as part of a larger clinical neuropsychological evaluation. Two separate linear regression analyses were conducted to examine the association of COVID-19 with depressive symptoms and subjective cognitive decline. A moderation analysis was performed to examine whether depressive symptoms were associated with subjective cognitive decline and the extent to which this differed by group (COVID-19 and controls). Participants’ age, self-reported sex, and history of depression were included as covariates.

The first regression model explained 17.2% of the variance in CES-D scores. It was found that the COVID-19 group had significantly higher CES-D scores (ß = .20, p = .03). The second regression model explained 35.9% of the variance in SCD-Q scores. Similar to the previous model, it was found that the COVID-19 group had significantly higher SCD-Q scores compared to healthy controls (ß = .22 p = .01). Lastly, the moderation model indicated that higher CES-D scores were associated with higher SCD-Q scores (ß = .43, p < .01), but there was no statistically significant group X CES-D score interaction.

These findings suggest that individuals who previously experienced a mild to moderate symptomatic COVID-19 infection report greater depressive symptom severity as well as greater subjective cognitive decline. Additionally, while more severe depressive symptoms predicted greater subjective cognitive decline in our sample, the magnitude of this association did not vary between those with and without a previous COVID-19 infection. While the underlying neurobiological and social mechanisms of cognitive difficulties and depressive symptoms in persons who have had COVID-19 have yet to be fully elucidated, our findings highlight treatment for depression and cognitive rehabilitation as potentially useful intervention targets for the post COVID-19 condition.

Recent research has found associations between the Five Factor Model (FFM) personality traits (Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism) and risk of developing subjective cognitive decline (SCD), mild cognitive impairment (MCI), and/or dementia. It has therefore been proposed that personality should be incorporated into conceptual models of dementia risk, as personality assessments have utility as readily available, low-cost measures to predict who is at greater risk for developing pathological cognitive decline. The objective of the present study was to explore the relationship between FFM personality traits and predementia cognitive syndromes including SCD, amnestic MCI (aMCI), and non-amnestic MCI (naMCI). The first aim was to compare baseline personality traits between participants who transitioned from healthy cognition or SCD to aMCI vs. naMCI. The second aim was to determine the relationship between FFM personality traits and risk of transition between predementia cognitive states. The third aim was to explore relationships between levels of FFM personality traits and performance on a comprehensive cognitive battery.

The participants for this study were 562 (Aim 3; Mean Age = 78.90) older adults from the Einstein Aging Study, 378 of which had at least one follow-up assessment (Aims 1 & 2; Mean Age = 78.60). Baseline levels of FFM personality traits were measured in the EAS using the 50-item International Personality Item Pool (IPIP) version of the NEO-Personality Inventory. Baseline levels of anxiety and depressive symptoms, medical history, performance on a cognitive battery and age sex, and years of education were also collected. A multistate Markov approach was used to model the risk of transition across the four predementia states (cognitively healthy, SCD, aMCI, and naMCI) with each FFM personality trait as covariates.

Regarding Aim 1, Mann-Whitney U tests revealed no differences in levels of FFM personality traits between participants who developed aMCI compared to those who developed naMCI. Regarding Aim 2, the multistate Markov model revealed that higher levels of conscientiousness were protective against developing SCD while higher levels of neuroticism resulted in an increased risk of developing SCD. Further, the model revealed that higher levels of extraversion were protective against developing naMCI. Finally, regarding Aim 3, exploratory correlations revealed many positive associations between levels of openness to experience and performance on neuropsychological tests. Few associations were found for the other FFM personality traits.

Results from this study suggest that premorbid personality traits may play a predictive role in the risk for or protection against specific predementia syndromes. Thus, FFM personality traits may be useful in improving predictions of who is at greatest risk for developing specific predementia syndromes. These personality measures could be used (in addition to other established risk factors for cognitive decline) to enrich clinical trials by targeting individuals who are at greatest risk for developing specific forms of cognitive decline. Such measures may also be useful in diagnostic prediction models for predementia syndromes. These results should be replicated in future studies with larger sample sizes and younger participants.

To examine the effectiveness of antimicrobial and antithrombogenic materials incorporated into peripherally inserted central catheters (PICCs) to prevent bloodstream infection, thrombosis, and catheter occlusion.

Prospective cohort study involving 52 hospitals participating in the Michigan Hospital Medicine Safety Consortium. Sample included adult hospitalized medical patients who received a PICC between January 2013 and October 2019. Coated and impregnated catheters were identified by name, brand, and device marketing or regulatory materials. Multivariable Cox proportional hazards models with robust sandwich standard error estimates accounting for the clustered nature of data were used to identify factors associated with PICC complications in coated versus noncoated devices across general care, intensive care unit (ICU), and oncology patients. Results were expressed as hazard ratios (HRs) with corresponding 95% confidence intervals (CIs).

Of 42,562 patients with a PICC, 39,806 (93.5%) were plain polyurethane, 2,263 (5.3%) incorporated antimicrobial materials, and 921 (2.2%) incorporated antithrombogenic materials. Most were inserted in general ward settings (n = 28,111, 66.0%), with 12, 078 (28.4%) and 1,407 (3.3%) placed in ICU and oncological settings, respectively. Within the entire cohort, 540 (1.3%) developed thrombosis, 745 (1.8%) developed bloodstream infection, and 4,090 (9.6%) developed catheter occlusion. Adjusting for known risk factors, antimicrobial PICCs were not associated with infection reduction (HR, 1.16; 95% CI, 0.82–1.64), and antithrombogenic PICCs were not associated with reduction in thrombosis and occlusion (HR, 1.15; 95% CI, 0.92–1.44). Results were consistent across populations and care settings.

Antimicrobial and antithrombogenic PICCs were not associated with a reduction in major catheter complications. Guidance aimed at informing use of these devices, balancing benefits against cost, appear necessary.

The national implementation of competency-based medical education (CBME) has prompted an increased interest in identifying and tracking clinical and educational outcomes for emergency medicine training programs. For the 2019 Canadian Association of Emergency Physicians (CAEP) Academic Symposium, we developed recommendations for measuring outcomes in emergency medicine training in the context of CBME to assist educational leaders and systems designers in program evaluation.

We conducted a three-phase study to generate educational and clinical outcomes for emergency medicine (EM) education in Canada. First, we elicited expert and community perspectives on the best educational and clinical outcomes through a structured consultation process using a targeted online survey. We then qualitatively analyzed these responses to generate a list of suggested outcomes. Last, we presented these outcomes to a diverse assembly of educators, trainees, and clinicians at the CAEP Academic Symposium for feedback and endorsement through a voting process.

Academic Symposium attendees endorsed the measurement and linkage of CBME educational and clinical outcomes. Twenty-five outcomes (15 educational, 10 clinical) were derived from the qualitative analysis of the survey results and the most important short- and long-term outcomes (both educational and clinical) were identified. These outcomes can be used to help measure the impact of CBME on the practice of Emergency Medicine in Canada to ensure that it meets both trainee and patient needs.

The Canadian Resident Matching Service (CaRMS) selection process has come under scrutiny due to the increasing number of unmatched medical graduates. In response, we outline our residency program's selection process including how we have incorporated best practices and novel techniques.

We selected file reviewers and interviewers to mitigate gender bias and increase diversity. Four residents and two attending physicians rated each file using a standardized, cloud-based file review template to allow simultaneous rating. We interviewed applicants using four standardized stations with two or three interviewers per station. We used heat maps to review rating discrepancies and eliminated rating variance using Z-scores. The number of person-hours that we required to conduct our selection process was quantified and the process outcomes were described statistically and graphically.

We received between 75 and 90 CaRMS applications during each application cycle between 2017 and 2019. Our overall process required 320 person-hours annually, excluding attendance at the social events and administrative assistant duties. Our preliminary interview and rank lists were developed using weighted Z-scores and modified through an organized discussion informed by heat mapped data. The difference between the Z-scores of applicants surrounding the interview invitation threshold was 0.18-0.3 standard deviations. Interview performance significantly impacted the final rank list.

We describe a rigorous resident selection process for our emergency medicine training program which incorporated simultaneous cloud-based rating, Z-scores, and heat maps. This standardized approach could inform other programs looking to adopt a rigorous selection process while providing applicants guidance and reassurance of a fair assessment.