Pulmonary atresia with intact ventricular septum is a rare congenital cardiac lesion with significant anatomical heterogeneity. Surgical planning of borderline cases remains challenging and is primarily based on echocardiography. The aim was to identify echocardiographic parameters that correlate with surgical outcome and to develop a discriminatory calculator.

Retrospective review of all pulmonary atresia with intact ventricular septum cases at a statewide tertiary paediatric cardiac centre was performed between 2004 and 2020. Demographic, clinical, and echocardiographic data were collected. Logistic regression was used to develop a discriminatory tool for prediction of biventricular repair.

Forty patients were included. Overall mortality was 27.5% (n = 11) and confined to patients managed as univentricular (11 vs 0, p = 0.027). Patients who underwent univentricular palliation were more likely to have an associated coronary artery abnormality (17 vs 3, p = 0.001). Fifteen surviving patients (51.7%) achieved biventricular circulation while 14 (48.3%) required one-and-a-half or univentricular palliation. Nineteen patients (47.5%) underwent percutaneous pulmonary valve perforation. No patients without tricuspid regurgitation achieved biventricular repair. The combination of tricuspid valve/mitral valve annulus dimension ratio and right ventricle/left ventricle length ratio identified biventricular management with a sensitivity of 93% and specificity of 96%. An online calculator has been made available.

Pulmonary atresia with intact ventricular septum is a challenging condition with significant early and interstage morbidity and mortality risk. Patient outcomes were comparable to internationally reported data. Right ventricle/left ventricle length and tricuspid valve/mitral valve annulus dimension ratios identified a biventricular pathway with a high level of sensitivity and specificity. Absent tricuspid regurgitation was associated with a univentricular outcome.

Cognitive therapy for PTSD (CT-PTSD) is an efficacious treatment for children and adolescents with post-traumatic stress disorder (PTSD) following single incident trauma, but there is a lack of evidence relating to this approach for youth with PTSD following exposure to multiple traumatic experiences.

To assess the safety, acceptability and feasibility of CT-PTSD for youth following multiple trauma, and obtain a preliminary estimate of its pre–post effect size.

Nine children and adolescents (aged 8–17 years) with multiple-trauma PTSD were recruited to a case series of CT-PTSD. Participants completed a structured interview and mental health questionnaires at baseline, post-treatment and 6-month follow-up, and measures of treatment credibility, therapeutic alliance, and mechanisms proposed to underpin treatment response. A developmentally adjusted algorithm for diagnosing PTSD was used.

No safety concerns or adverse effects were recorded. Suicidal ideation reduced following treatment. No participants withdrew from treatment or from the study. CT-PTSD was rated as highly credible. Participants reported strong working alliances with their therapists. Data completion was good at post-treatment (n=8), but modest at 6-month follow-up (n=6). Only two participants met criteria for PTSD (developmentally adjusted algorithm) at post-treatment. A large within-subjects treatment effect was observed post-treatment and at follow up for PTSD severity (using self-report questionnaire measures; ds>1.65) and general functioning (CGAS; ds<1.23). Participants showed reduced anxiety and depression symptoms at post-treatment and follow-up (RCADS-C; ds>.57).

These findings suggest that CT-PTSD is a safe, acceptable and feasible treatment for children with multiple-trauma PTSD, which warrants further evaluation.

The identification of predictors of treatment response is crucial for improving treatment outcome for children with anxiety disorders. Machine learning methods provide opportunities to identify combinations of factors that contribute to risk prediction models.

A machine learning approach was applied to predict anxiety disorder remission in a large sample of 2114 anxious youth (5–18 years). Potential predictors included demographic, clinical, parental, and treatment variables with data obtained pre-treatment, post-treatment, and at least one follow-up.

All machine learning models performed similarly for remission outcomes, with AUC between 0.67 and 0.69. There was significant alignment between the factors that contributed to the models predicting two target outcomes: remission of all anxiety disorders and the primary anxiety disorder. Children who were older, had multiple anxiety disorders, comorbid depression, comorbid externalising disorders, received group treatment and therapy delivered by a more experienced therapist, and who had a parent with higher anxiety and depression symptoms, were more likely than other children to still meet criteria for anxiety disorders at the completion of therapy. In both models, the absence of a social anxiety disorder and being treated by a therapist with less experience contributed to the model predicting a higher likelihood of remission.

These findings underscore the utility of prediction models that may indicate which children are more likely to remit or are more at risk of non-remission following CBT for childhood anxiety.

This study examined the power of theory-derived models to account for the development of PTSD, Complex PTSD (CPTSD), depression, and anxiety in children and adolescents who had experienced a single-event trauma.

Children (n = 234, aged 8–17 years) recruited from local Emergency Departments were assessed at two and nine weeks post-trauma. Data obtained from self-report questionnaires completed by the child, telephone interviews with parents, and hospital data were used to develop four predictive models of risk factors for PTSD, CPTSD, depression, and Generalized Anxiety Disorder (GAD). ICD-11 proposed diagnostic criteria were used to generate measures for CPTSD and PTSD to assess for risk factors and identify the sample prevalence of these disorders.

At nine weeks post-trauma, 64% did not meet criteria for any disorder, 23.5% met criteria for PTSD, and 5.2% met criteria for CPTSD. 23.9% and 10.7% had developed clinically significant symptoms of depression and GAD, respectively. A cognitive model was the most powerful predictive model, a psychosocial model was weak, and subjective markers of event severity were more powerful than objective measures.

Youth exposed to single-incident trauma may develop different forms of psychopathology, and PTSD and CPTSD are frequently experienced alongside other conditions. The cognitive model of PTSD shows utility in identifying predictors of PTSD, CPTSD, depression, and GAD, particularly the role of trauma-related negative appraisals. This supports the application of cognitive interventions which focus upon re-appraising trauma-related beliefs in youth.

Over 2.7 million people have an opioid use disorder (OUD). Opioid-related deaths have steadily increased over the last decade. Although emergency department (ED)-based medication for OUD (MOUD) has been successful in initiating treatment for patients, there still is a need for improved access. This study describes the development of a prehospital MOUD program.

An interdisciplinary team expanded a MOUD program into the prehospital setting through the local city fire department Quick Response Team (QRT) to identify patients appropriate for MOUD treatment. The QRT consisted of a paramedic, social worker, and police officer. This team visited eligible patients (i.e., history of an opioid overdose and received prehospital care the previous week). The implementation team developed a prehospital MOUD protocol and a two-hour training course for QRT personnel. Implementation also required a signed contract between local hospitals and the fire department. A drug license was necessary for the QRT vehicle to carry buprenorphine/naloxone, and a process to restock the vehicle was created. Pamphlets were created to provide to patients. A clinical algorithm was created for substance use disorder (SUD) care coordinators to provide a transition of care for patients. Metrics to evaluate the program included the number of patients seen, the number enrolled in an MOUD program, and the number of naloxone kits dispensed. Data were entered into iPads designated for the QRT and uploaded into the Research Electronic Data Capture (REDCap) program.

Over the six-month pilot, the QRT made 348 visits. Of these, the QRT successfully contacted 83 individuals, and no individuals elected to be evaluated for new MOUD treatment. Nine fatal opioid overdoses occurred during the study period. A total of 55 naloxone kits were distributed, and all patients received MOUD information pamphlets.

A prehospital MOUD program can be established to expand access to early treatment and continuity of care for patients with OUD. The program was well-received by the local city fire department and QRT. There is a plan to expand the prehospital MOUD program to other local fire departments with QRTs.

Specialist forensic community teams for people with intellectual disability and/or autism have been developed, but little is known about their extent and delivery.

To describe specialist forensic community teams for people with intellectual disability and/or autism across the UK.

An online survey was sent to representatives of each UK Trust/Health Board providing adult mental health and/or intellectual disability services. Questions covered the availability, structure and activities of specialist community forensic services. Quantitative data were summarised and associations between access to specialist forensic teams and care were tested with Chi-squared tests. Thematic analysis of free-text survey responses was used to understand the challenges of providing community forensic mental health services for this group.

A total of 49 out of 78 (63%) eligible Trusts/Health Boards responded, of which 25 (51%) had access to a specialist forensic community team. Teams operated either as part of a single Trust/Board (n = 13) or over a larger regional footprint (n = 12). The availability of specialist forensic community teams was associated with better access to offence-related interventions (χ2 = 15.1002, P < 0.005) and co-production of patient care plans (χ2 = 7.8726, P = 0.005). Respondents reported a wide variation in availability, expertise and perceived quality of community services. The availability of secure and generic in-patient beds, commissioning and legal barriers were also significant challenges in providing appropriate care.

Coverage of specialist community forensic teams is not universal. There are indications that such teams are associated with improved care processes, but further work is needed to establish longer-term outcomes and the optimal model of care.