Medicare claims are frequently used to study Clostridioides difficile infection (CDI) epidemiology. However, they lack specimen collection and diagnosis dates to assign location of onset. Algorithms to classify CDI onset location using claims data have been published, but the degree of misclassification is unknown.

We linked patients with laboratory-confirmed CDI reported to four Emerging Infections Program (EIP) sites from 2016–2021 to Medicare beneficiaries with fee-for-service Part A/B coverage. We calculated sensitivity of ICD-10-CM codes in claims within ±28 days of EIP specimen collection. CDI was categorized as hospital, long-term care facility, or community-onset using three different Medicare claims-based algorithms based on claim type, ICD-10-CM code position, duration of hospitalization, and ICD-10-CM diagnosis code presence-on-admission indicators. We assessed concordance of EIP case classifications, based on chart review and specimen collection date, with claims case classifications using Cohen’s kappa statistic.

Of 12,671 CDI cases eligible for linkage, 9,032 (71%) were linked to a single, unique Medicare beneficiary. Compared to EIP, sensitivity of CDI ICD-10-CM codes was 81%; codes were more likely to be present for hospitalized patients (93.0%) than those who were not (56.2%). Concordance between EIP and Medicare claims algorithms ranged from 68% to 75%, depending on the algorithm used (κ = 0.56–0.66).

ICD-10-CM codes in Medicare claims data had high sensitivity compared to laboratory-confirmed CDI reported to EIP. Claims-based epidemiologic classification algorithms had moderate concordance with EIP classification of onset location. Misclassification of CDI onset location using Medicare algorithms may bias findings of claims-based CDI studies.

To compare rates of clinical response in children with Clostridioides difficile infection (CDI) treated with metronidazole vs vancomycin.

Retrospective cohort study was performed as a secondary analysis of a previously established prospective cohort of hospitalized children with CDI. For 187 participants 2–17 years of age who were treated with metronidazole and/or vancomycin, the primary outcome of clinical response (defined as resolution of diarrhea within 5 days of treatment initiation) was identified retrospectively. Baseline variables associated with the primary outcome were included in a logistic regression propensity score model estimating the likelihood of receiving metronidazole vs vancomycin. Logistic regression using inverse probability of treatment weighting (IPTW) was used to estimate the effect of treatment on clinical response.

One hundred seven subjects received metronidazole and 80 subjects received vancomycin as primary treatment. There was no univariable association between treatment group and clinical response; 78.30% (N = 83) of the metronidazole treatment group and 78.75% (N = 63) of the vancomycin group achieved clinical response (P = 0.941). After adjustment using propensity scores with IPTW, the odds of a clinical response for participants who received metronidazole was 0.554 (95% CI: 0.272, 1.131) times the odds of those who received vancomycin (P = 0.105).

In this observational cohort study of pediatric inpatients with CDI, the rate of resolution of diarrhea after 5 days of treatment did not differ among children who received metronidazole vs vancomycin.

Paediatric patients with heart failure requiring ventricular assist devices are at heightened risk of neurologic injury and psychosocial adjustment challenges, resulting in a need for neurodevelopmental and psychosocial support following device placement. Through a descriptive survey developed in collaboration by the Advanced Cardiac Therapies Improving Outcomes Network and the Cardiac Neurodevelopmental Outcome Collaborative, the present study aimed to characterise current neurodevelopmental and psychosocial care practices for paediatric patients with ventricular assist devices.

Members of both learning networks developed a 25-item electronic survey assessing neurodevelopmental and psychosocial care practices specific to paediatric ventricular assist device patients. The survey was sent to Advanced Cardiac Therapies Improving Outcomes Network site primary investigators and co-primary investigators via email.

Of the 63 eligible sites contacted, responses were received from 24 unique North and South American cardiology centres. Access to neurodevelopmental providers, referral practices, and family neurodevelopmental education varied across sites. Inpatient neurodevelopmental care consults were available at many centres, as were inpatient family support services. Over half of heart centres had outpatient neurodevelopmental testing and individual psychotherapy services available to patients with ventricular assist devices, though few centres had outpatient group psychotherapy (12.5%) or parent support groups (16.7%) available. Barriers to inpatient and outpatient neurodevelopmental care included limited access to neurodevelopmental providers and parent/provider focus on the child’s medical status.

Paediatric patients with ventricular assist devices often have access to neurodevelopmental providers in the inpatient setting, though supports vary by centre. Strengthening family neurodevelopmental education, referral processes, and family-centred psychosocial services may improve current neurodevelopmental/psychosocial care for paediatric ventricular assist device patients.

To examine feasibility, acceptability, and preliminary effectiveness of a novel group-based telemedicine psychoeducation programme aimed at supporting psychological well-being among adolescents with Fontan-palliated CHD.

A 5-week telemedicine psychoeducation group-based programme (WE BEAT) was developed for adolescents (N = 20; 13–18 years) with Fontan-palliated CHD aimed at improving resiliency and psychological well-being. Outcome measures included surveys of resilience (Connor–Davidson Resilience Scale), benefit finding (Benefit/Burden Scale for Children), depression, anxiety, peer relationships, and life satisfaction (National Institutes of Health Patient-Reported Outcomes Measurement Information System scales). Within-subject changes in these outcomes were compared pre- to post-intervention using Cohen’s d effect size. In addition, acceptability in the form of satisfaction measures and qualitative feedback was assessed.

Among eligible patients reached, 68% expressed interest in study participation. Of those consented, 77% have been scheduled for a group programme to date with 87% programme completion. Twenty adolescents (mean age 16.1 ± SD 1.6 years) participated across five WE BEAT group cohorts (range: 3–6 participants per group). The majority (80%) attended 4–5 sessions in the 5-session programme, and the median programme rating was a 9 out of 10 (10 = most favourable rating). Following WE BEAT participation, resiliency (d = 0.44) and perceptions of purpose in life increased (d = 0.26), while depressive symptoms reduced (d = 0.36). No other changes in assessed outcome measures were noted.

These findings provide preliminary support that a group-based, telemedicine delivered psychoeducation programme to support psychological well-being among adolescents with CHD is feasible, acceptable, and effective. Future directions include examining intervention effects across diverse centres, populations, and implementation methods.

Past studies indicate daily increases in estrogen across the menstrual cycle protect against binge-eating (BE) phenotypes (e.g. emotional eating), whereas increases in progesterone enhance risk. Two previous studies from our laboratory suggest these associations could be due to differential genomic effects of estrogen and progesterone. However, these prior studies were unable to directly model effects of daily changes in hormones on etiologic risk, instead relying on menstrual cycle phase or mean hormone levels. The current study used newly modified twin models to examine, for the first time, the effects of daily changes in estradiol and progesterone on genetic/environmental influences on emotional eating in our archival twin sample assessed across 45 consecutive days.

Participants included 468 female twins from the Michigan State University Twin Registry. Daily emotional eating was assessed with the Dutch Eating Behavior Questionnaire, and daily saliva samples were assayed for ovarian hormone levels. Modified genotype × environment interaction models examined daily changes in genetic/environmental effects across hormone levels.

Findings revealed differential effects of daily changes in hormones on etiologic risk, with increasing genetic influences across progesterone levels, and increasing shared environmental influences at the highest estradiol levels. Results were consistent across primary analyses examining all study days and sensitivity analyses within menstrual cycle phases.

Findings are significant in being the first to identify changes in etiologic risk for BE symptoms across daily hormone levels and highlighting novel mechanisms (e.g. hormone threshold effects, regulation of conserved genes) that may contribute to the etiology of BE.

Diagnostic criteria for major depressive disorder allow for heterogeneous symptom profiles but genetic analysis of major depressive symptoms has the potential to identify clinical and etiological subtypes. There are several challenges to integrating symptom data from genetically informative cohorts, such as sample size differences between clinical and community cohorts and various patterns of missing data.

We conducted genome-wide association studies of major depressive symptoms in three cohorts that were enriched for participants with a diagnosis of depression (Psychiatric Genomics Consortium, Australian Genetics of Depression Study, Generation Scotland) and three community cohorts who were not recruited on the basis of diagnosis (Avon Longitudinal Study of Parents and Children, Estonian Biobank, and UK Biobank). We fit a series of confirmatory factor models with factors that accounted for how symptom data was sampled and then compared alternative models with different symptom factors.

The best fitting model had a distinct factor for Appetite/Weight symptoms and an additional measurement factor that accounted for the skip-structure in community cohorts (use of Depression and Anhedonia as gating symptoms).

The results show the importance of assessing the directionality of symptoms (such as hypersomnia versus insomnia) and of accounting for study and measurement design when meta-analyzing genetic association data.

Military Servicemembers and Veterans are at elevated risk for suicide, but rarely self-identify to their leaders or clinicians regarding their experience of suicidal thoughts. We developed an algorithm to identify posts containing suicide-related content on a military-specific social media platform.

Publicly-shared social media posts (n = 8449) from a military-specific social media platform were reviewed and labeled by our team for the presence/absence of suicidal thoughts and behaviors and used to train several machine learning models to identify such posts.

The best performing model was a deep learning (RoBERTa) model that incorporated post text and metadata and detected the presence of suicidal posts with relatively high sensitivity (0.85), specificity (0.96), precision (0.64), F1 score (0.73), and an area under the precision-recall curve of 0.84. Compared to non-suicidal posts, suicidal posts were more likely to contain explicit mentions of suicide, descriptions of risk factors (e.g. depression, PTSD) and help-seeking, and first-person singular pronouns.

Our results demonstrate the feasibility and potential promise of using social media posts to identify at-risk Servicemembers and Veterans. Future work will use this approach to deliver targeted interventions to social media users at risk for suicide.

Migration is a well-established risk factor for psychotic disorders, and migrant language has been proposed as a novel factor that may improve our understanding of this relationship. Our objective was to explore the association between indicators of linguistic distance and the risk of psychotic disorders among first-generation migrant groups.

Using linked health administrative data, we constructed a retrospective cohort of first-generation migrants to Ontario over a 20-year period (1992–2011). Linguistic distance of the first language was categorized using several approaches, including language family classifications, estimated acquisition time, syntax-based distance scores, and lexical-based distance scores. Incident cases of non-affective psychotic disorder were identified over a 5- to 25-year period. We used Poisson regression to estimate incidence rate ratios (IRR) for each language variable, after adjustment for knowledge of English at arrival and other factors.

Our cohort included 1 863 803 first-generation migrants. Migrants whose first language was in a different language family than English had higher rates of psychotic disorders (IRR = 1.08, 95% CI 1.01–1.16), relative to those whose first language was English. Similarly, migrants in the highest quintile of linguistic distance based on lexical similarity had an elevated risk of psychotic disorder (IRR = 1.15, 95% CI 1.06–1.24). Adjustment for knowledge of English at arrival had minimal effect on observed estimates.

We found some evidence that linguistic factors that impair comprehension may play a role in the excess risk of psychosis among migrant groups; however, the magnitude of effect is small and unlikely to fully explain the elevated rates of psychotic disorder across migrant groups.

The study of psychological well-being and related resilient outcomes is of increasing focus in cardiovascular research. Despite the critical importance of psychological well-being and related resilient outcomes in promoting optimal cardiac health, there have been very few psychological interventions directed towards children with heart disease. This paper describes the development and theoretical framework of the WE BEAT Wellbeing Education Program, a group-based psychoeducation and coping skills training intervention designed to improve psychological well-being and resilience in adolescents with paediatric heart disease.

Program development was informed by patient and family needs and input gathered via large, international survey methods as well as qualitative investigation, a theoretical framework, and related resilience intervention research.

An overview of the WE BEAT intervention components and structure of the programme is provided.

The WE BEAT Wellbeing Education Program was developed as one of the first resiliency-focused interventions in paediatric heart disease with an overall objective to foster positive psychological well-being and resilient outcomes through a health promotion and prevention lens in an accessible format while providing access to safe, peer-to-peer community building. Feasibility pilot results are forthcoming. Future directions include mobile app-based delivery and larger-scale efficacy and implementation trials.