Bicuspid aortic valve is considered to have a multifactorial origin. Some research suggests a defect in neural crest cell signalling may increase the risk of developing bicuspid aortic valve, and also impact on the proximal conduction system.

To examine electrocardiographic parameters in unselected newborns from the general population diagnosed with bicuspid aortic valve within 30 days after birth.

This is a substudy of the Copenhagen Baby Heart Study; a multicentre, prospective, population-based cohort study with prenatal inclusion. Cardiac examination, including transthoracic echocardiography and electrocardiography, were obtained within 30 days after birth. Newborns diagnosed with bicuspid aortic valve were matched 1:4 with newborns with structurally normal hearts based on age, sex, gestational age, weight, and length at examination.

A total of 127 newborns with bicuspid aortic valve (84 boys, median age 11 days) and 508 controls (336 boys, median age 11 days) were included. Newborns with bicuspid aortic valve had a significantly longer PR-interval (100 vs 96 ms, p = 0.011) and QRS duration (56 vs 54 ms, p = 0.042), and a significantly lower R-wave amplitude in V6 (759 vs 906 µV, p = 0.047) compared to controls. However, when correcting for multiple testing none of the results were significant.

Newborns from the general population with bicuspid aortic valve demonstrated a slightly longer PR-interval, a longer QRS duration, and a lower maximum R-wave amplitude in V6 than matched controls, although non-significant after correcting for multiple testing. This may represent early signs of conduction abnormalities, but longitudinal follow-up will provide further clarification.

It remains unclear which individuals with subthreshold depression benefit most from psychological intervention, and what long-term effects this has on symptom deterioration, response and remission.

To synthesise psychological intervention benefits in adults with subthreshold depression up to 2 years, and explore participant-level effect-modifiers.

Randomised trials comparing psychological intervention with inactive control were identified via systematic search. Authors were contacted to obtain individual participant data (IPD), analysed using Bayesian one-stage meta-analysis. Treatment–covariate interactions were added to examine moderators. Hierarchical-additive models were used to explore treatment benefits conditional on baseline Patient Health Questionnaire 9 (PHQ-9) values.

IPD of 10 671 individuals (50 studies) could be included. We found significant effects on depressive symptom severity up to 12 months (standardised mean-difference [s.m.d.] = −0.48 to −0.27). Effects could not be ascertained up to 24 months (s.m.d. = −0.18). Similar findings emerged for 50% symptom reduction (relative risk = 1.27–2.79), reliable improvement (relative risk = 1.38–3.17), deterioration (relative risk = 0.67–0.54) and close-to-symptom-free status (relative risk = 1.41–2.80). Among participant-level moderators, only initial depression and anxiety severity were highly credible (P > 0.99). Predicted treatment benefits decreased with lower symptom severity but remained minimally important even for very mild symptoms (s.m.d. = −0.33 for PHQ-9 = 5).

Psychological intervention reduces the symptom burden in individuals with subthreshold depression up to 1 year, and protects against symptom deterioration. Benefits up to 2 years are less certain. We find strong support for intervention in subthreshold depression, particularly with PHQ-9 scores ≥ 10. For very mild symptoms, scalable treatments could be an attractive option.

Both impulsivity and compulsivity have been identified as risk factors for problematic use of the internet (PUI). Yet little is known about the relationship between impulsivity, compulsivity and individual PUI symptoms, limiting a more precise understanding of mechanisms underlying PUI.

The current study is the first to use network analysis to (a) examine the unique association among impulsivity, compulsivity and PUI symptoms, and (b) identify the most influential drivers in relation to the PUI symptom community.

We estimated a Gaussian graphical model consisting of five facets of impulsivity, compulsivity and individual PUI symptoms among 370 Australian adults (51.1% female, mean age = 29.8, s.d. = 11.1). Network structure and bridge expected influence were examined to elucidate differential associations among impulsivity, compulsivity and PUI symptoms, as well as identify influential nodes bridging impulsivity, compulsivity and PUI symptoms.

Results revealed that four facets of impulsivity (i.e. negative urgency, positive urgency, lack of premeditation and lack of perseverance) and compulsivity were related to different PUI symptoms. Further, compulsivity and negative urgency were the most influential nodes in relation to the PUI symptom community due to their highest bridge expected influence.

The current findings delineate distinct relationships across impulsivity, compulsivity and PUI, which offer insights into potential mechanistic pathways and targets for future interventions in this space. To realise this potential, future studies are needed to replicate the identified network structure in different populations and determine the directionality of the relationships among impulsivity, compulsivity and PUI symptoms.

Surveillance of non–ventilator-associated hospital-acquired pneumonia (NV-HAP) is complicated by subjectivity and variability in diagnosing pneumonia. We compared a fully automatable surveillance definition using routine electronic health record data to manual determinations of NV-HAP according to surveillance criteria and clinical diagnoses.

We retrospectively applied an electronic surveillance definition for NV-HAP to all adults admitted to Veterans’ Affairs (VA) hospitals from January 1, 2015, to November 30, 2020. We randomly selected 250 hospitalizations meeting NV-HAP surveillance criteria for independent review by 2 clinicians and calculated the percent of hospitalizations with (1) clinical deterioration, (2) CDC National Healthcare Safety Network (CDC-NHSN) criteria, (3) NV-HAP according to a reviewer, (4) NV-HAP according to a treating clinician, (5) pneumonia diagnosis in discharge summary; and (6) discharge diagnosis codes for HAP. We assessed interrater reliability by calculating simple agreement and the Cohen κ (kappa).

Among 3.1 million hospitalizations, 14,023 met NV-HAP electronic surveillance criteria. Among reviewed cases, 98% had a confirmed clinical deterioration; 67% met CDC-NHSN criteria; 71% had NV-HAP according to a reviewer; 60% had NV-HAP according to a treating clinician; 49% had a discharge summary diagnosis of pneumonia; and 82% had NV-HAP according to any definition according to at least 1 reviewer. Only 8% had diagnosis codes for HAP. Interrater agreement was 75% (κ = 0.50) for CDC-NHSN criteria and 78% (κ = 0.55) for reviewer diagnosis of NV-HAP.

Electronic NV-HAP surveillance criteria correlated moderately with existing manual surveillance criteria. Reviewer variability for all manual assessments was high. Electronic surveillance using clinical data may therefore allow for more consistent and efficient surveillance with similar accuracy compared to manual assessments or diagnosis codes.

In 2019 there were 1,760 patients in Denmark’s hospitals who experienced cardiac arrest (IHCA patients = In Hospital Cardiac Arrest patients). Of these patients about 70% survived. There is only limited knowledge about the mental and cognitive state of cardiac arrest survivors. However, it seems, that cardiac arrest survivors, perform mentally and cognitively worse compared to the background population. The mental and cognitive difficulties can lead to reduced quality of life for both those affected and their relatives.

Because the above-mentioned area has limited knowledge, further studies are needed to shed more light into the problem.

To find out if the patients can be included in the study, the patient journals will be studied. After that there will be performed an interview-survey-based study, in which IHCA patients’ possible symptoms of depression, anxiety, PTSD and suicide risk, the patients’ quality of life and any cognitive disorder, shortly after and three months after cardiac arrest, will be examined. The study will also, if possible, focus on the patients’ relatives and on the eventual difficulties they may experience in the aftermath of a relative surviving a cardiac arrest. The above-mentioned will be done using already existing relevant psychiatric and neuropsychological examination tools. In relation to the patients’ relatives, however, a separate survey tool, that has been developed, will be used.

It is an ongoing study. Results are expected in 2023.

In the long run the study hopefully can contribute to establishing relevant help, counseling and rehabilitation for the patients and relatives affected.

No significant relationships.

Biomarkers in CSF could provide etiological clues and diagnostic tools for psychotic disorders. However, an overview of all CSF findings in individuals with psychotic disorders compared to healthy controls is lacking.

To analyse CSF findings from individuals with psychotic disorders compared to healthy controls.

PubMed, EMBASE, Cochrane Library, Web of Science, ClinicalTrials.gov, and PsycINFO were searched November 3rd, 2021. Case-control studies including patients with non-affective, psychotic disorder compared to healthy controls measuring at least one biomarker in CSF are included. Standardized Mean Differences (SMD) and random-effects analyses were used.

141 studies, covering 192 biomarkers, were included. 161 biomarkers have not previously been included in meta-analyses. Most markers measured showed no significant differences, including the dopamine metabolites HVA and DOPAC. Patients with psychotic disorders showed increased CSF levels of noradrenaline (SMD, 0.53; 95% CI, 0.15-0.90), MHPG (SMD, 0.30; 95% CI, 0.05-0.55), 5-HIAA (SMD, 0.11; 95 % CI, 0.01-0.21), kynurenic acid (SMD, 1.58; 95% CI, 0.26-2.91), kynurenine (SMD, 1.00; 95% CI, 0.58-1.42), IL-6 (SMD, 0.58; 95% CI, 0.39-0.77), IL-8 (SMD, 0.47; 95% CI, 0.18-0.77), anandamide (SMD, 0.78; 95% CI, 0.53-1.02), albumin ratio (SMD, 0.53; 95% CI, 0.10-0.96), total protein (SMD, 0.31; 95% CI, 0.14-0.48), and glucose (SMD, 0.57; 95% CI, 0.08-1.06). Neurotensin (SMD, -0.67; 95% CI, -0.89 to -0.46) and GABA (SMD, -0.29; 95% CI, -0.50 to -0.09) were decreased.

These findings suggest that dysregulation of the immune and adrenergic system and blood-brain barrier dysfunction might play a role in the pathophysiology of psychotic disorders.

No significant relationships.

The COVID-19 pandemic has affected mental health globally, but the impact on referrals and admissions to mental health services remains understudied.

To assess patterns in psychiatric admissions, referrals, and suicidal behavior before and during the COVID-19 pandemic in Denmark.

Utilizing hospital and Emergency Medical Services (EMS) health records covering 46% of the Danish population, we compared psychiatric in-patients, referrals to mental health services and suicidal behavior in years prior to the COVID-19 pandemic to levels during the first lockdown (March 11 – May 17, 2020), inter-lockdown period (May 18 – December 15, 2020), and second lockdown (December 16, 2020 – February 28, 2021) using negative binomial models.

The rate of psychiatric in-patients declined compared to pre-pandemic levels (RR = 0.95, 95% CI = 0.94 – 0.96, p < 0.01). Referrals were not significantly different (RR = 1.01, 95% CI = 0.92 – 1.10, p = 0.91) during the pandemic; neither was suicidal behavior among hospital contacts (RR = 1.04, 95% CI = 0.94 – 1.14, p = 0.48) nor EMS contacts (RR = 1.08, 95% CI = 1.00 – 1.18, p = 0.06). In the age group <18, an increase in the rate of psychiatric in-patients (RR = 1.11, 95% CI = 1.07 – 1.15, p < 0.01) was observed during the pandemic; however, this did not exceed the pre-pandemic, upwards trend in psychiatric hospitalizations in the age group <18 (p = 0.78).

The pandemic was associated with a decrease in psychiatric hospitalizations. No significant change was observed in referrals and suicidal behavior.

No significant relationships.

There is emerging evidence of heterogeneity within treatment-resistance schizophrenia (TRS), with some people not responding to antipsychotic treatment from illness onset and a smaller group becoming treatment-resistant after an initial response period. It has been suggested that these groups have different aetiologies. Few studies have investigated socio-demographic and clinical differences between early and late onset of TRS.

This study aims to investigate socio-demographic and clinical correlates of late-onset of TRS.

Using data from the electronic health records of the South London and Maudsley, we identified a cohort of people with TRS. Regression analyses were conducted to identify correlates of the length of treatment to TRS. Analysed predictors include gender, age, ethnicity, positive symptoms severity, problems with activities of daily living, psychiatric comorbidities, involuntary hospitalisation and treatment with long-acting injectable antipsychotics.

We observed a continuum of the length of treatment until TRS presentation. Having severe hallucinations and delusions at treatment start was associated shorter duration of treatment until the presentation of TRS.

Our findings do not support a clear cut categorisation between early and late TRS, based on length of treatment until treatment resistance onset. More severe positive symptoms predict earlier onset of treatment resistance.

DFdF, GKS, EF and IR have received research funding from Janssen and H. Lundbeck A/S. RDH and HS have received research funding from Roche, Pfizer, Janssen and Lundbeck. SES is employed on a grant held by Cardiff University from Takeda Pharmaceutical Comp