The aim of this pilot study is to determine the pattern of oral anticoagulant and antiplatelet use in patients with permanent atrial fibrillation (AF) in Irish general practice.

Worldwide, AF is the most common sustained cardiac arrhythmia in adults and poses a significant burden to patients, physicians and healthcare systems. There is a five-fold increased risk of stroke with AF, and AF-related strokes are associated with higher levels of both morbidity and mortality compared to other stroke subtypes. Thankfully, appropriate use of oral anticoagulation (OAC) for AF can reduce the risk of stroke by up to 64%. However, we know that patients are commonly undertreated with OAC, prescribed inappropriate doses of OAC and have prolonged use of an antiplatelet agent in addition to OAC without indication.

A descriptive, cross-sectional observational study was undertaken. Proportionate sampling was used across 11 practices from the Ireland East practice-based research network. The general practitioners completed a report form on each patient provided by the research team by undertaking a retrospective chart review.

Eleven practices participated with a total number of 1855 patients with AF. We received data on 153 patients.

The main findings from this pilot project are that:

1. 1. 11% of patients were undertreated with OAC

2. 2. 20 % of patients were on an incorrect non-vitamin K antagonist oral anticoagulant dose

3. 3. 28 patients (18%) were inappropriately prescribed combination antithrombotic therapy

Undertreatment and underdosing of OAC expose patients to higher risk of thromboembolic events, bleeding and all-cause mortality. Prolonged combination antithrombotic therapy is associated with serious increased risk of bleeding with no additional stroke protection. This pilot project highlights several gaps between guidelines and clinical practice. By identifying these areas, we hope to develop a targeted quality improvement intervention using the electronic health records in general practice to improve the care that those with AF receive.

The Stricker Learning Span (SLS) is a computer-adaptive word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). Given recent evidence suggesting the prominence of learning impairment in preclinical Alzheimer’s disease (AD), the SLS places greater emphasis on learning than delayed memory compared to traditional word list memory tests (see Stricker et al., Neuropsychology in press for review and test details). The primary study aim was to establish criterion validity of the SLS by comparing the ability of the remotely-administered SLS and inperson administered Rey Auditory Verbal Learning Test (AVLT) to differentiate biomarkerdefined groups in cognitively unimpaired (CU) individuals on the Alzheimer’s continuum.

Mayo Clinic Study of Aging CU participants (N=319; mean age=71, SD=11; mean education=16, SD=2; 47% female) completed a brief remote cognitive assessment (∼0.5 months from in-person visit). Brain amyloid and brain tau PET scans were available within 3 years. Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (A+, n=110) or not (A-, n=209), and for 2) those with biological AD (A+T+, n=43) vs no evidence of AD pathology (A-T-, n=181). Primary neuropsychological outcome variables were sum of trials for both the SLS and AVLT. Secondary outcome variables examined comparability of learning (1-5 total) and delay performances. Linear model ANOVAs were used to investigate biomarker subgroup differences and Hedge’s G effect sizes were derived, with and without adjusting for demographic variables (age, education, sex).

Both SLS and AVLT performances were worse in the biomarker positive relative to biomarker negative groups (unadjusted p’s<.05). Because biomarker positive groups were significantly older than biomarker negative groups, group differences were attenuated after adjusting for demographic variables, but SLS remained significant for A+ vs A- and for A+T+ vs A-T- comparisons (adjusted p’s<.05) and AVLT approached significance (p’s .05-.10). The effect sizes for the SLS were slightly better (qualitatively, no statistical comparison) for separating biomarker-defined CU groups in comparison to AVLT. For A+ vs A- and A+T+ vs A-T- comparisons, unadjusted effect sizes for SLS were -0.53 and -0.81 and for AVLT were -0.47 and -0.61, respectively; adjusted effect sizes for SLS were -0.25 and -0.42 and for AVLT were -0.19 and -0.26, respectively. In secondary analyses, learning and delay variables were similar in terms of ability to separate biomarker groups. For example, unadjusted effect sizes for SLS learning (-.80) was similar to SLS delay (.76), and AVLT learning (-.58) was similar to AVLT 30-minute delay (-.55) for the A+T+ vs AT- comparison.

Remotely administered SLS performed similarly to the in-person-administered AVLT in its ability to separate biomarker-defined groups in CU individuals, providing evidence of criterion validity. The SLS showed significantly worse performance in A+ and A+T+ groups (relative to A- and A-T-groups) in this CU sample after demographic adjustment, suggesting potential sensitivity to detecting transitional cognitive decline in preclinical AD. Measures emphasizing learning should be given equal consideration as measures of delayed memory in AD-focused studies, particularly in the preclinical phase.

Mayo Test Drive (MTD): Test Development through Rapid Iteration, Validation and Expansion, is a web-based multi-device (smartphone, tablet, personal computer) platform optimized for remote self-administered cognitive assessment that includes a computer-adaptive word list memory test (Stricker Learning Span; SLS; Stricker et al., 2022; Stricker et al., in press) and a measure of processing speed (Symbols Test: Wilks et al., 2021). Study aims were to determine criterion validity of MTD by comparing the ability of the MTD raw composite and in-person administered cognitive measures to differentiate biomarkerdefined groups in cognitively unimpaired (CU) individuals on the Alzheimer’s continuum.

Mayo Clinic Study of Aging CU participants (N=319; mean age=71, SD=11, range=37-94; mean education=16, SD=2, range=6-20; 47% female) completed a brief remote cognitive assessment (∼0.5 months from in-person visit). Brain amyloid and brain tau PET scans were available within 3 years. Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (A+, n=110) or not (A-, n=209), and for 2) those with biological AD (A+T+, n=43) or with no evidence of AD pathology (A-T-, n=181). Primary outcome variables were MTD raw composite (SLS sum of trials + an accuracy-weighted Symbols response time measure), Global-z (average of 9 in-person neuropsychological measures) and an in-person screening measure (Kokmen Short Test of Mental Status, STMS; which is like the MMSE). Linear model ANOVAs were used to investigate biomarker subgroup differences and Hedge’s G effect sizes were derived, with and without adjusting for demographic variables (age, education, sex).

Remotely administered MTD raw composite showed comparable to slightly larger effect sizes compared to Global-z. Unadjusted effect sizes for MTD raw composite for differentiating A+ vs. A- and A+T+ vs. A-T- groups, respectively, were -0.57 and -0.84 and effect sizes for Global-z were -0.54 and -0.73 (all p’s<.05). Because biomarker positive groups were significantly older than biomarker negative groups, group differences were attenuated after adjusting for demographic variables, but MTD raw composite remained significant for A+T+ vs A-T- (adjusted effect size -0.35, p=.007); Global-z did not reach significance for A+T+ vs A-T- (adjusted effect size -0.19, p=.08). Neither composite reached significance for adjusted analyses for the A+ vs A- comparison (MTD raw composite adjusted effect size= -.22, p=.06; Global-z adjusted effect size= -.08, p=.47). Results were the same for an alternative MTD composite using traditional z-score averaging methods, but the raw score method is preferred for comparability to other screening measures. The STMS screening measure did not differentiate biomarker groups in any analyses (unadjusted and adjusted p’s>.05; d’s -0.23 to 0.05).

Remotely administered MTD raw composite shows at least similar ability to separate biomarker-defined groups in CU individuals as a Global-z for person-administered measures within a neuropsychological battery, providing evidence of criterion validity. Both the MTD raw composite and Global-z showed greater ability to separate biomarker positive from negative CU groups compared to a typical screening measure (STMS) that was unable to differentiate these groups. MTD may be useful as a screening measure to aid early detection of Alzheimer’s pathological changes.

To compare performances of matched groups derived from caregiver-reported ethnicity on measures of verbal comprehension and visual-spatial abilities, and to identify factors potentially related to differences.

Participants included 159 English speaking children from 615 years of age who were referred for neuropsychological evaluation at a clinic in the southwestern region of the United States. Participants were matched across four groups based on caregiver-reported ethnicity, including American Indian (n = 41), Hispanic (n= 41), White (n = 41), and Other (i.e., Black, Asian; n = 36) categories. Propensity score matching was used to derive samples, with participants matched on age, caregiver-reported sex assigned at birth, and the full-scale intelligence quotient on the Wechsler Intelligence Scale for Children, Fifth Edition (WISC-V).

Using a dependent variable derived from subtracting the WISC-V Verbal Comprehension Index from the Visual-Spatial Index, significant differences across groups were found via a factorial analysis of variance model (p = .02, eta squared = .06). Achieved power was .82. Post-hoc analysis indicated significantly greater differences between verbal comprehension and visual-spatial abilities amongst participants of American Indian (mean difference = -6.61 standard score points) and Hispanic (mean difference = -6.66 standard score points) ethnicity relative to participants of White ethnicity (mean difference = 2.17 standard score points; p < .01). Differences did not relate to participant age or assigned sex.

Greater differences between visual and verbal intellectual abilities were found amongst Hispanic and American Indian participants relative to White participants. Hispanic and American children tended to perform higher on visual spatial rather than verbal tasks, while the pattern was reversed for White children. Findings are congruent with previous research conducted using older versions of the WISC and continue to highlight potential issues related to the external validity of this measure in certain populations. This study contributes to the existing literature by replicating previous findings with the most recent iteration of the WISC in a referred sample. Current results continue to suggest that the WISC-V Verbal Comprehension Index may function more as a measure of English language ability rather than verbal intellectual ability. Given these findings, it is important that weaknesses in verbal comprehension amongst children of Hispanic or American Indian ethnicity be interpreted in this context when identified in clinical and research settings. Discrepancies between ethnic groups may relate broadly to cultural and systemic factors (e.g., differing patient/examiner characteristics, inequalities in access to education/intervention and healthcare, bilingualism/exposure to the English language).

Identifying youths most at risk to COVID-19-related mental illness is essential for the development of effective targeted interventions.

To compare trajectories of mental health throughout the pandemic in youth with and without prior mental illness and identify those most at risk of COVID-19-related mental illness.

Data were collected from individuals aged 18–26 years (N = 669) from two existing cohorts: IMAGEN, a population-based cohort; and ESTRA/STRATIFY, clinical cohorts of individuals with pre-existing diagnoses of mental disorders. Repeated COVID-19 surveys and standardised mental health assessments were used to compare trajectories of mental health symptoms from before the pandemic through to the second lockdown.

Mental health trajectories differed significantly between cohorts. In the population cohort, depression and eating disorder symptoms increased by 33.9% (95% CI 31.78–36.57) and 15.6% (95% CI 15.39–15.68) during the pandemic, respectively. By contrast, these remained high over time in the clinical cohort. Conversely, trajectories of alcohol misuse were similar in both cohorts, decreasing continuously (a 15.2% decrease) during the pandemic. Pre-pandemic symptom severity predicted the observed mental health trajectories in the population cohort. Surprisingly, being relatively healthy predicted increases in depression and eating disorder symptoms and in body mass index. By contrast, those initially at higher risk for depression or eating disorders reported a lasting decrease.

Healthier young people may be at greater risk of developing depressive or eating disorder symptoms during the COVID-19 pandemic. Targeted mental health interventions considering prior diagnostic risk may be warranted to help young people cope with the challenges of psychosocial stress and reduce the associated healthcare burden.

The Stricker Learning Span (SLS) is a computer-adaptive digital word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). We aimed to establish criterion validity of the SLS by comparing its ability to differentiate biomarker-defined groups to the person-administered Rey’s Auditory Verbal Learning Test (AVLT).

Participants (N = 353; mean age = 71, SD = 11; 93% cognitively unimpaired [CU]) completed the AVLT during an in-person visit, the SLS remotely (within 3 months) and had brain amyloid and tau PET scans available (within 3 years). Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (amyloid PET positive, A+, n = 125) or not (A-, n = 228), and those with biological AD (amyloid and tau PET positive, A+T+, n = 55) vs no evidence of AD pathology (A−T−, n = 195). Analyses were repeated among CU participants only.

The SLS and AVLT showed similar ability to differentiate biomarker-defined groups when comparing AUROCs (p’s > .05). In logistic regression models, SLS contributed significantly to predicting biomarker group beyond age, education, and sex, including when limited to CU participants. Medium (A− vs A+) to large (A−T− vs A+T+) unadjusted effect sizes were observed for both SLS and AVLT. Learning and delay variables were similar in terms of ability to separate biomarker groups.

Remotely administered SLS performed similarly to in-person-administered AVLT in its ability to separate biomarker-defined groups, providing evidence of criterion validity. Results suggest the SLS may be sensitive to detecting subtle objective cognitive decline in preclinical AD.

Considerable literature has examined the COVID-19 pandemic’s negative mental health sequelae. It is recognised that most people experiencing mental health problems present to primary care and the development of interventions to support GPs in the care of patients with mental health problems is a priority. This review examines interventions to enhance GP care of mental health disorders, with a view to reviewing how mental health needs might be addressed in the post-COVID-19 era.

Five electronic databases (PubMed, PsycINFO, Cochrane Library, Google Scholar and WHO ‘Global Research on COVID-19’) were searched from May – July 2021 for papers published in English following Arksey and O’Malley’s six-stage scoping review process.

The initial search identified 148 articles and a total of 29 were included in the review. These studies adopted a range of methodologies, most commonly randomised control trials, qualitative interviews and surveys. Results from included studies were divided into themes: Interventions to improve identification of mental health disorders, Interventions to support GPs, Therapeutic interventions, Telemedicine Interventions and Barriers and Facilitators to Intervention Implementation. Outcome measures reported included the Seven-item Generalised Anxiety Disorder Scale (GAD-7), the Nine-item Patient Health Questionnaire (PHQ-9) and the ‘The Patient Global Impression of Change Scale’.

With increasing recognition of the mental health sequelae of COVID-19, there is a lack of large scale trials researching the acceptability or effectiveness of general practice interventions. Furthermore there is a lack of research regarding possible biological interventions (psychiatric medications) for mental health problems arising from the pandemic.

Identification of treatment-specific predictors of drug therapies for bipolar disorder (BD) is important because only about half of individuals respond to any specific medication. However, medication response in pediatric BD is variable and not well predicted by clinical characteristics.

A total of 121 youth with early course BD (acute manic/mixed episode) were prospectively recruited and randomized to 6 weeks of double-blind treatment with quetiapine (n = 71) or lithium (n = 50). Participants completed structural magnetic resonance imaging (MRI) at baseline before treatment and 1 week after treatment initiation, and brain morphometric features were extracted for each individual based on MRI scans. Positive antimanic treatment response at week 6 was defined as an over 50% reduction of Young Mania Rating Scale scores from baseline. Two-stage deep learning prediction model was established to distinguish responders and non-responders based on different feature sets.

Pre-treatment morphometry and morphometric changes occurring during the first week can both independently predict treatment outcome of quetiapine and lithium with balanced accuracy over 75% (all p < 0.05). Combining brain morphometry at baseline and week 1 allows prediction with the highest balanced accuracy (quetiapine: 83.2% and lithium: 83.5%). Predictions in the quetiapine and lithium group were found to be driven by different morphometric patterns.

These findings demonstrate that pre-treatment morphometric measures and acute brain morphometric changes can serve as medication response predictors in pediatric BD. Brain morphometric features may provide promising biomarkers for developing biologically-informed treatment outcome prediction and patient stratification tools for BD treatment development.

Despite evidence favoring perioperative antibiotic prophylaxis (ABP) use in patients undergoing craniotomy to reduce rates of surgical site infections (SSIs), standardized protocols are lacking. We describe demographic characteristics, risk factors, and ABP choice in patients with craniotomy complicated with SSI.

Retrospective case series from January 1, 2017, through December 31, 2020.

Tertiary-care referral center.

Adults who underwent craniotomy and were diagnosed with an SSI.

Logistic regression to estimate odds ratios and 95% confidence intervals to identify factors associated with SSIs.

In total, 5,328 patients undergoing craniotomy were identified during the study period; 59 (1.1%) suffered an SSI. Compared with non-SSI cases, patients with SSI had a significantly higher frequency of emergency procedures: 13.5% versus 5.8% (P = .02; odds ratio [OR], 2.52; 95% confidene interval [CI], 1.10–5.06; P = .031). Patients with SSI had a higher rate of a dirty (5.1% vs 0.9%) and lower rate of clean-contaminated (3.3% vs 14.5%) wound class than those without infection (P = .002). Nearly all patients received ABP before craniotomy (98.3% in the SSI group vs 99.6% in the non-SSI group; P = .10). Combination of vancomycin and cefazolin as dual therapy was more prevalent in the group of patients without infection (n = 1,761, 34.1%) than those with SSI (n = 4, 6.8%) (P < .001), associated with decreased odds for SSI (OR, 0.17; 95% CI, 0.005–0.42; P ≤ .001).

SSI are frequently seen after an emergent neurosurgical procedure and a dirty wound classification. Combination of prophylactic cefazolin and vancomycin is associated with decreased risk for SSI.