Patients with stroke or transient ischemic attack (TIA) are at high early risk of mortality and morbidity. Current risk prediction tools focus on patients after hospital discharge but not on those surviving to outpatient follow-up. We examined whether demographic and medical history data could predict 1-year stroke recurrence and mortality, among those discharged alive and event-free for 90 days after stroke and 1 day after TIA.

Data were obtained from the Ontario Stroke Registry (13,848 stroke and 13,059 TIA patients) and linked to administrative databases. Two-thirds of each cohort were used for model derivation and one-third for validation. Multivariable regression models were used to predict stroke recurrence and all-cause mortality.

There were 238 (2.71%) recurrent strokes in the ischemic stroke and 298 (3.44%) in the TIA cohorts at one year. Increasing age and previous stroke/TIA were associated with an increased risk of recurrent stroke in both cohorts. A higher modified Rankin Scale and diabetes were associated with an increased risk of recurrent stroke in the stroke cohort and heart failure, smoking and discharge location in the TIA cohort. Time-dependent areas under the curve were modest, 0.59 (0.54–0.64) and 0.59 (0.55–0.64) for the stroke and TIA validation cohorts, respectively. C-statistics from derivation and validation cohorts for mortality ranged from 0.74–0.78.

The predictive accuracy of the models was quite low after accounting for several risk factors. Additional risk factors associated with stroke recurrence for people seen in outpatient stroke clinics, and innovative approaches to individualized secondary prevention are needed.

Species of the Burkholderia (B.) cepacia complex (Bcc) have been implicated in multiple nosocomial outbreaks linked to contaminated water-based products, including liquid soaps, mouthwash, and other non-alcoholic aqueous solutions.

We describe two substantial healthcare-associated outbreaks of Bcc (B. cepacia and B. contaminans) in the United Kingdom and Ireland associated with contaminated products. We highlight the challenges during investigation and mitigation, and provide recommendations.

A multidisciplinary, multi-stakeholder investigation across both outbreaks was adopted, involving interviews, trawling questionnaires, and targeted product sampling.

There were 153 and 66 confirmed cases in the B. cepacia and B. contaminans outbreaks, respectively. Cases predominantly comprised hospitalized individuals, and 70% of isolates were recovered from an invasive site. The outbreak strain of B. cepacia was isolated from non-sterile ultrasound gel. An analytical study suggested the B. contaminans cluster was also linked to ultrasound gel; however, a disinfectant wipe product was subsequently identified as the source (0–3 single nucleotide polymorphism differences between case and wipe isolates).

The affected disinfectant wipes were withdrawn. The ultrasound gel was not recalled but health system procurement was suspended, rapid clinical guidance was produced and a National Patient Safety Alert was issued. Inter-organizational partnership was required to mitigate risks.

Identifying the source of outbreaks associated with contaminated products can be challenging, requiring complex multi-stakeholder interventions. We recommend a low threshold for investigation of Bcc clusters, adopting a multidisciplinary approach to investigation and mitigation, implementing interventions focusing on practice, and prompt product removal to protect patients.

Previous results show that women who suffered from perinatal depression (PND) have a higher risk of suicidal behavior. However, clinical tools for predicting suicidal behavior among patients with PND are lacking.

To develop a prediction model for suicidal behavior after PND using machine learning.

Leveraging nationwide Swedish register data, we included 57,848 women with PND diagnosed during 2001-2018 and identified 2,303 events of suicidal behavior up to 5 years after PND diagnosis. Based on our previous association studies, 16 predictors containing information on demographics and pregnancy characteristics were included after multiple imputation. The sample was randomly split into 80% as a training set and 20% for testing. Classification and Regression Tree (CART), Random Forest (RF), Naïve Bayes (NB) and Logistic regression (LR) were used to establish prediction models with area under the curve (AUC) assessed for prediction performance. 10-fold cross-validation was used to evaluate the algorithms on unseen data.

In the prediction models, the CART yielded the best performance for suicidal behavior within 5 years after PND diagnosis (AUC 0.78, 95% CI 0.76-0.81). The population that scored highest (17%) in CART model had 84% risk of suicidal behavior. LR also had a comparable performance (AUC 0.78, 95% CI 0.76-0.81), whereas RF (AUC 0.74, 95% CI 0.72-0.76) and NB (AUC 0.70, 95% CI 0.68-0.72) had relatively poor performance. Notably, suicide history was a main contributor in all four models. Other predictors like household income, gestational age and education level were also important indicators of suicidal behavior risk.

The machine learning models have promising prediction performance for suicidal behavior after PND. Yet, further improvement is needed before clinical implementation.

None Declared

The quality of news reports about suicide can influence suicide rates. Although many researchers have aimed to assess the general safety of news reporting in terms of adherence to responsible media guidelines, none have focused on major US cable networks, a key source of public information in North America and beyond.

To characterise and compare suicide-related reporting by major US cable television news networks across the ideological spectrum.

We searched a news archive (Factiva) for suicide-related transcripts from ‘the big three’ US cable television news networks (CNN, Fox News and MSNBC) over an 11-year inclusion interval (2012–2022). We included and coded segments with a major focus on suicide (death, attempt and/or thoughts) for general content, putatively harmful and protective characteristics and overarching narratives. We used chi-square tests to compare these variables across networks.

We identified 612 unique suicide-related segments (CNN, 398; Fox News, 119; MSNBC, 95). Across all networks, these segments tended to focus on suicide death (72–89%) and presented stories about specific individuals (61–87%). Multiple putatively harmful characteristics were evident in segments across networks, including mention of a suicide method (42–52%) – with hanging (15–30%) and firearm use (12–20%) the most commonly mentioned – and stigmatising language (39–43%). Only 15 segments (2%) presented a story of survival.

Coverage of suicide stories by major US cable news networks was often inconsistent with responsible reporting guidelines. Further engagement with networks and journalists is thus warranted.

Transcranial direct current stimulation (tDCS) is a promising treatment for major depressive disorder (MDD). This study evaluated its antidepressant and cognitive effects as a safe, effective, home-based therapy for MDD.

This double-blind, sham-controlled, randomized trial divided participants into low-intensity (1 mA, n = 47), high-intensity (2 mA, n = 49), and sham (n = 45) groups, receiving 42 daily tDCS sessions, including weekends and holidays, targeting the dorsolateral prefrontal cortex for 30 minutes. Assessments were conducted at baseline and weeks 2, 4, and 6. The primary outcome was cognitive improvement assessed by changes in total accuracy on the 2-back test from baseline to week 6. Secondary outcomes included changes in depressive symptoms (HAM-D), anxiety (HAM-A), and quality of life (QLES). Adverse events were monitored. This trial was registered with ClinicalTrials.gov (NCT04709952).

In the tDCS study, of 141 participants (102 [72.3%] women; mean age 35.7 years, standard deviation 12.7), 95 completed the trial. Mean changes in the total accuracy scores from baseline to week 6 were compared across the three groups using an F-test. Linear mixed-effects models examined the interaction of group and time. Results showed no significant differences among groups in cognitive or depressive outcomes at week 6. Active groups experienced more mild adverse events compared to sham but had similar rates of severe adverse events and dropout.

Home-based tDCS for MDD demonstrated no evidence of effectiveness but was safe and well-tolerated. Further research is needed to address the technical limitations, evaluate broader cognitive functions, and extend durations to evaluate its therapeutic potential.

The depression, obstructive sleep apnea and cognitive impairment (DOC) screen assesses three post-stroke comorbidities, but additional information may be gained from the time to complete the screen. Cognitive screening completion time is rarely used as an outcome measure.

To assess DOC screen completion time as a predictor of cognitive impairment in stroke/transient ischemic attack clinics.

Consecutive English-speaking stroke prevention clinic patients consented to undergo screening and neuropsychological testing (n = 437). DOC screen scores and times were compared to scores on the NINDS-CSC battery using multiple linear regression (controlling for age, sex, education and stroke severity) and receiver operating characteristic (ROC) curve analysis.

Completion time for the DOC screen was 3.8 ± 1.3 minutes. After accounting for covariates, the completion time was a significant predictor of the speed of processing (p = 0.002, 95% CI: −0.016 to −0.004), verbal fluency (p < 0.001, CI: −0.012 to −0.006) and executive function (p = 0.004, CI: −0.006 to −0.001), but not memory. Completion time above 5.5 minutes was associated with a high likelihood of impairment on executive and speed of processing tasks (likelihood ratios 3.9–5.2).

DOC screen completion time is easy to collect in routine care. People needing over 5.5 minutes to be screened likely have deficits in executive functioning and speed of processing – areas commonly impaired, but challenging to screen for, after stroke. DOC screen time provides a simple, feasible approach to assess these under-identified cognitive impairments.

Although behavioral mechanisms in the association among depression, anxiety, and cancer are plausible, few studies have empirically studied mediation by health behaviors. We aimed to examine the mediating role of several health behaviors in the associations among depression, anxiety, and the incidence of various cancer types (overall, breast, prostate, lung, colorectal, smoking-related, and alcohol-related cancers).

Two-stage individual participant data meta-analyses were performed based on 18 cohorts within the Psychosocial Factors and Cancer Incidence consortium that had a measure of depression or anxiety (N = 319 613, cancer incidence = 25 803). Health behaviors included smoking, physical inactivity, alcohol use, body mass index (BMI), sedentary behavior, and sleep duration and quality. In stage one, path-specific regression estimates were obtained in each cohort. In stage two, cohort-specific estimates were pooled using random-effects multivariate meta-analysis, and natural indirect effects (i.e. mediating effects) were calculated as hazard ratios (HRs).

Smoking (HRs range 1.04–1.10) and physical inactivity (HRs range 1.01–1.02) significantly mediated the associations among depression, anxiety, and lung cancer. Smoking was also a mediator for smoking-related cancers (HRs range 1.03–1.06). There was mediation by health behaviors, especially smoking, physical inactivity, alcohol use, and a higher BMI, in the associations among depression, anxiety, and overall cancer or other types of cancer, but effects were small (HRs generally below 1.01).

Smoking constitutes a mediating pathway linking depression and anxiety to lung cancer and smoking-related cancers. Our findings underline the importance of smoking cessation interventions for persons with depression or anxiety.

Screen time in infancy is linked to changes in social-emotional development but the pathway underlying this association remains unknown. We aim to provide mechanistic insights into this association using brain network topology and to examine the potential role of parent–child reading in mitigating the effects of screen time.

We examined the association of screen time on brain network topology using linear regression analysis and tested if the network topology mediated the association between screen time and later socio-emotional competence. Lastly, we tested if parent–child reading time was a moderator of the link between screen time and brain network topology.

Infant screen time was significantly associated with the emotion processing-cognitive control network integration (p = 0.005). This network integration also significantly mediated the association between screen time and both measures of socio-emotional competence (BRIEF-2 Emotion Regulation Index, p = 0.04; SEARS total score, p = 0.04). Parent–child reading time significantly moderated the association between screen time and emotion processing-cognitive control network integration (β = −0.640, p = 0.005).

Our study identified emotion processing-cognitive control network integration as a plausible biological pathway linking screen time in infancy and later socio-emotional competence. We also provided novel evidence for the role of parent–child reading in moderating the association between screen time and topological brain restructuring in early childhood.

Neurocognitive impairment and quality of life are two important long-term challenges for patients with complex CHD. The impact of re-interventions during adolescence and young adulthood on neurocognition and quality of life is not well understood.

In this prospective longitudinal multi-institutional study, patients 13–30 years old with severe CHD referred for surgical or transcatheter pulmonary valve replacement were enrolled. Clinical characteristics were collected, and executive function and quality of life were assessed prior to the planned pulmonary re-intervention. These results were compared to normative data and were compared between treatment strategies.

Among 68 patients enrolled from 2016 to 2020, a nearly equal proportion were referred for surgical and transcatheter pulmonary valve replacement (53% versus 47%). Tetralogy of Fallot was the most common diagnosis (59%) and pulmonary re-intervention indications included stenosis (25%), insufficiency (40%), and mixed disease (35%). There were no substantial differences between patients referred for surgical and transcatheter therapy. Executive functioning deficits were evident in 19–31% of patients and quality of life was universally lower compared to normative sample data. However, measures of executive function and quality of life did not differ between the surgical and transcatheter patients.

In this patient group, impairments in neurocognitive function and quality of life are common and can be significant. Given similar baseline characteristics, comparing changes in neurocognitive outcomes and quality of life after surgical versus transcatheter pulmonary valve replacement will offer unique insights into how treatment approaches impact these important long-term patient outcomes.