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.

Depressive symptomatology has long been shown to be associated with the onset of dementia, though the exact form and directionality of this association remains unclear. While much research has gone into confirming this link, there has been little investigation into the effects of depression on dementia progression after diagnosis. The aim of this study is to investigate the relationship between depressive symptomatology and cognitive and behavioural decline over the following year.

In a Rural and Remote Memory Clinic, 375 patients consecutively diagnosed with mild cognitive impairment (MCI), Alzheimer’s Disease (AD), or non-AD dementia completed the Center for Epidemiological Studies Depression Scale (CES-D) at first visit and one-year follow-up to assess depressive symptomatology. The same cohort were evaluated for cognitive and behavioural decline through the completion of five clinical tests performed at the first visit and at one-year follow-up. Cognitive decline was assessed using the Mini Mental Status Exam (MMSE) and the Clinical Dementia Rating Scale (CDR). Neuropsychiatric symptoms were assessed using two subsets of data from the Neuropsychiatric Inventory (NPI severity and distress), both of which are completed by the patients’ caregivers. Functional decline was assessed using the Functional Activities Questionnaire (FAQ). In both cognitive and functional decline, data were analyzed with linear regression analysis in the population subgroups of All Type Dementia (ATD, which includes MCI for this study) (N=375), Alzheimer’s type dementia (N=187), and Mild Cognitive Impairment (N=74).

In this study, we observed no correlation between CES-D scores at baseline and cognitive or functional decline over one year. However, we observed a significant positive correlation between changes in CES-D scores and NPI-severity scores over one year in patients with ATD (likely the most reliable observation from this study due to larger statistical power) and in the MCI subgroup, but not in the AD subgroup. This relationship may be attributable to a relationship between depression and neuropsychiatric symptoms in general, or to the fact that a person with dementia who exhibits more depressive symptomatology appears more impaired and causes greater distress in their caregivers, despite stability in the objective measures of their cognitive and functional status. This finding may indicate that intervention for depression is needed to alleviated caregiver burden when managing dementia patients.

Increasingly severe depressive symptomatology may exacerbate neuropsychiatric symptomatology but did not correlate with cognitive and functional decline in patients with dementia. More studies are needed to help delineate the relationship between depression and dementia progression.

Engaging patients, caregivers, and other stakeholders to help guide the research process is a cornerstone of patient-centered research. Lived expertise may help ensure the relevance of research questions, promote practices that are satisfactory to research participants, improve transparency, and assist with disseminating findings.

Traditionally engagement has been conducted face-to-face in the local communities in which research operates. Decentralized platform trials pose new challenges for the practice of engagement. We used a remote model for stakeholder engagement, relying on Zoom meetings and blog communications.

Here we describe the approach used for research partnership with patients, caregivers, and clinicians in the planning and oversight of the ACTIV-6 trial and the impact of this work. We also present suggestions for future remote engagement.

The ACTIV-6 experience may inform proposed strategies for future engagement in decentralized trials.

Lumateperone (LUMA) is an FDA-approved antipsychotic to treat schizophrenia and depressive episodes associated with bipolar I or bipolar II disorder. An open-label study (Study 303) evaluated the safety and tolerability of LUMA in outpatients with stable schizophrenia who switched from previous antipsychotic (AP) treatment. This post hoc analysis of Study 303 investigated the safety and tolerability of LUMA stratified by previous AP in patients who switched to LUMA treatment for 6 weeks.

Adult outpatients (≥18 years) with stable schizophrenia were switched from previous AP to LUMA 42 mg once daily for 6 weeks followed by switching to another approved AP for 2 weeks follow-up. Post hoc analyses were stratified by most common previous AP: risperidone or paliperidone (RIS/PAL); quetiapine (QET); aripiprazole or brexpiprazole (ARI/BRE); olanzapine (OLA). Safety analyses included adverse events (AE), vital signs, and laboratory tests. Efficacy was assessed using the Positive and Negative Syndrome Scale (PANSS) and the Clinical Global Impressions-Severity (CGI-S) scale.

The safety population comprised 301 patients, of which 235 (78.1%) were previously treated with RIS/PAL (n=95), QET (n=60), ARI/BRE (n=43), or OLA (n=37). Rates of treatment-emergent AEs (TEAEs) while on LUMA were similar between previous AP groups (44.2%-55.8%). TEAEs with incidences of ≥5% in any AP group were dry mouth, somnolence, sedation, headache, diarrhea, cough, and insomnia. Most TEAEs were mild or moderate in severity for all groups. Rates of serious TEAEs were low and similar between groups (0%–7.0%).

Statistically significant (P<.05) decreases from baseline were observed in the OLA group that switched to LUMA in total cholesterol and low-density lipoprotein cholesterol with significant decreases thereafter on LUMA. Statistically significant decreases in prolactin levels were observed in both the RIS/PAL (P<.0001) and OLA (P<.05) groups. Patients switched from RIS/PAL to LUMA showed significant (P<.05) decreases for body mass index, waist circumference, and weight. At follow-up, 2 weeks after patients switched back from LUMA to another AP, none of the decreases in laboratory parameters or body morphology observed while on LUMA maintained significance.

Those switching from QET had significant improvements from baseline at Day 42 in PANSS Total score (mean change from baseline −3.47; 95% confidence interval [CI] −5.27, −1.68; P<.001) and CGI-S Total score (mean change from baseline −0.24; 95% CI, −0.38, −0.10; P<.01).

In outpatients with stable schizophrenia, LUMA 42 mg treatment was well tolerated in patients switching from a variety of previous APs. Patients switching from RIS/PAL or OLA to LUMA had significant improvements in cardiometabolic and prolactin parameters. These data further support the favorable safety, tolerability, and efficacy of LUMA in patients with schizophrenia.

Intra-Cellular Therapies, Inc.

Risk of suicide-related behaviors is elevated among military personnel transitioning to civilian life. An earlier report showed that high-risk U.S. Army soldiers could be identified shortly before this transition with a machine learning model that included predictors from administrative systems, self-report surveys, and geospatial data. Based on this result, a Veterans Affairs and Army initiative was launched to evaluate a suicide-prevention intervention for high-risk transitioning soldiers. To make targeting practical, though, a streamlined model and risk calculator were needed that used only a short series of self-report survey questions.

We revised the original model in a sample of n = 8335 observations from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS) who participated in one of three Army STARRS 2011–2014 baseline surveys while in service and in one or more subsequent panel surveys (LS1: 2016–2018, LS2: 2018–2019) after leaving service. We trained ensemble machine learning models with constrained numbers of item-level survey predictors in a 70% training sample. The outcome was self-reported post-transition suicide attempts (SA). The models were validated in the 30% test sample.

Twelve-month post-transition SA prevalence was 1.0% (s.e. = 0.1). The best constrained model, with only 17 predictors, had a test sample ROC-AUC of 0.85 (s.e. = 0.03). The 10–30% of respondents with the highest predicted risk included 44.9–92.5% of 12-month SAs.

An accurate SA risk calculator based on a short self-report survey can target transitioning soldiers shortly before leaving service for intervention to prevent post-transition SA.

In UK males, prostate cancer is the most common cancer, with over 47,500 diagnosed annually. Radiotherapy is a highly effective curative treatment but can be limited by dose to surrounding normal-tissues such as the rectum. Radiation to the rectum can be reduced by increasing the distance between prostate and rectum with a hydrogel spacer. Despite National Institute of Health and Care Excellence guidance, spacers are not widely funded in the UK. Limited funding has necessitated patient prioritization, without any existing consensus on method.

Studies have shown generally homogenous results in reduction of rectal toxicity across assessed subgroups, but the requirement to prioritize remains. One way of addressing the appropriate use of beneficial health technologies is the inclusion of end-user experts in decision-making. The study aim was to identify consensus among radiation oncologists on patient prioritization for rectal hydrogel spacers.

We conducted a Delphi study where six leading clinical oncologists and one urologist from across the UK experienced in using rectal hydrogel spacers participated in two rounds of online questionnaires and two virtual advisory board meetings.

The experts estimated that 83 percent of patients who could potentially benefit from a spacer were denied access. Overall, ten points of consensus were reached. Key ones concerning patient-access were:

• • Spacer use in eligible patients significantly reduces radiation dose to the rectum and toxicity-related adverse events.

• • Increased benefit is expected in patients on anticoagulation, with diabetes and with inflammatory bowel disease.

• • Increased benefit can be expected with ultra-hypofractionated radiotherapy, but radiotherapy modality is not a key consideration for patient selection.

• • Patients should have the opportunity to actively participate in the discussion regarding the use of a spacer.

Currently, not all patients who would benefit can access funding for hydrogel spacers. Consensus in this study indicates that appropriate health policy and funding mechanisms are warranted for patients, to provide equitable access to technologies improving quality of life.

Only a limited number of patients with major depressive disorder (MDD) respond to a first course of antidepressant medication (ADM). We investigated the feasibility of creating a baseline model to determine which of these would be among patients beginning ADM treatment in the US Veterans Health Administration (VHA).

A 2018–2020 national sample of n = 660 VHA patients receiving ADM treatment for MDD completed an extensive baseline self-report assessment near the beginning of treatment and a 3-month self-report follow-up assessment. Using baseline self-report data along with administrative and geospatial data, an ensemble machine learning method was used to develop a model for 3-month treatment response defined by the Quick Inventory of Depression Symptomatology Self-Report and a modified Sheehan Disability Scale. The model was developed in a 70% training sample and tested in the remaining 30% test sample.

In total, 35.7% of patients responded to treatment. The prediction model had an area under the ROC curve (s.e.) of 0.66 (0.04) in the test sample. A strong gradient in probability (s.e.) of treatment response was found across three subsamples of the test sample using training sample thresholds for high [45.6% (5.5)], intermediate [34.5% (7.6)], and low [11.1% (4.9)] probabilities of response. Baseline symptom severity, comorbidity, treatment characteristics (expectations, history, and aspects of current treatment), and protective/resilience factors were the most important predictors.

Although these results are promising, parallel models to predict response to alternative treatments based on data collected before initiating treatment would be needed for such models to help guide treatment selection.

To examine differences in surgical practices between salaried and fee-for-service (FFS) surgeons for two common degenerative spine conditions. Surgeons may offer different treatments for similar conditions on the basis of their compensation mechanism.

The study assessed the practices of 63 spine surgeons across eight Canadian provinces (39 FFS surgeons and 24 salaried) who performed surgery for two lumbar conditions: stable spinal stenosis and degenerative spondylolisthesis. The study included a multicenter, ambispective review of consecutive spine surgery patients enrolled in the Canadian Spine Outcomes and Research Network registry between October 2012 and July 2018. The primary outcome was the difference in type of procedures performed between the two groups. Secondary study variables included surgical characteristics, baseline patient factors, and patient-reported outcome.

For stable spinal stenosis (n = 2234), salaried surgeons performed statistically fewer uninstrumented fusion (p < 0.05) than FFS surgeons. For degenerative spondylolisthesis (n = 1292), salaried surgeons performed significantly more instrumentation plus interbody fusions (p < 0.05). There were no statistical differences in patient-reported outcomes between the two groups.

Surgeon compensation was associated with different approaches to stable lumbar spinal stenosis and degenerative lumbar spondylolisthesis. Salaried surgeons chose a more conservative approach to spinal stenosis and a more aggressive approach to degenerative spondylolisthesis, which highlights that remuneration is likely a minor determinant in the differences in practice of spinal surgery in Canada. Further research is needed to further elucidate which variables, other than patient demographics and financial incentives, influence surgical decision-making.

Fewer than half of patients with major depressive disorder (MDD) respond to psychotherapy. Pre-emptively informing patients of their likelihood of responding could be useful as part of a patient-centered treatment decision-support plan.

This prospective observational study examined a national sample of 807 patients beginning psychotherapy for MDD at the Veterans Health Administration. Patients completed a self-report survey at baseline and 3-months follow-up (data collected 2018–2020). We developed a machine learning (ML) model to predict psychotherapy response at 3 months using baseline survey, administrative, and geospatial variables in a 70% training sample. Model performance was then evaluated in the 30% test sample.

32.0% of patients responded to treatment after 3 months. The best ML model had an AUC (SE) of 0.652 (0.038) in the test sample. Among the one-third of patients ranked by the model as most likely to respond, 50.0% in the test sample responded to psychotherapy. In comparison, among the remaining two-thirds of patients, <25% responded to psychotherapy. The model selected 43 predictors, of which nearly all were self-report variables.

Patients with MDD could pre-emptively be informed of their likelihood of responding to psychotherapy using a prediction tool based on self-report data. This tool could meaningfully help patients and providers in shared decision-making, although parallel information about the likelihood of responding to alternative treatments would be needed to inform decision-making across multiple treatments.

Obesity increases the risk of post-operative arrhythmias in adults undergoing cardiac surgery, but little is known regarding the impact of obesity on post-operative arrhythmias after CHD surgery.

Patients undergoing CHD surgery from 2007 to 2019 were prospectively enrolled in the parent study. Telemetry was assessed daily, with documentation of all arrhythmias. Patients aged 2–20 years were categorised by body mass index percentile for age and sex (underweight <5, normal 5–85, overweight 85–95, and obese >95). Patients aged >20 years were categorised using absolute body mass index. We investigated the impact of body mass index category on arrhythmias using univariate and multivariate analysis.

There were 1250 operative cases: 12% underweight, 65% normal weight, 12% overweight, and 11% obese. Post-operative arrhythmias were observed in 38%. Body mass index was significantly higher in those with arrhythmias (18.8 versus 17.8, p = 0.003). There was a linear relationship between body mass index category and incidence of arrhythmias: underweight 33%, normal 38%, overweight 42%, and obese 45% (p = 0.017 for trend). In multivariate analysis, body mass index category was independently associated with post-operative arrhythmias (p = 0.021), with odds ratio 1.64 in obese patients as compared to normal-weight patients (p = 0.036). In addition, aortic cross-clamp time (OR 1.007, p = 0.002) and maximal vasoactive–inotropic score in the first 48 hours (OR 1.03, p = 0.04) were associated with post-operative arrhythmias.

Body mass index is independently associated with incidence of post-operative arrhythmias in children after CHD surgery.