Patients with remitted psychosis wish to reduce antipsychotic doses yet facing increased risks of relapse. Examining dose-tapering processes may provide insights to re-evaluate the risk-to-benefit balance. We aimed to depict and subgroup tapering trajectories, and explore factors associated with different dose-reduction patterns.

A 2-year open-label randomized prospective comparative trial from August 2017 to September 2022 in Taiwan. Patients with a history of schizophrenia-related psychotic disorders under stable medications and symptoms were eligible, randomizing a proportion to conduct guided dose reduction. We depicted the trajectories of individual patients and named subgroups based on dose-tapering patterns. Predictors of baseline characteristics for designated subgroups were examined by logistic regression analysis; changes in outcomes were compared by paired t-test.

Fifty-one patients undergoing guided dose reduction, 18 (35.3%) reduced 4 steps consecutively (sequential reducers, SR), 14 (27.5%) reduced 1 to 3 steps (modest reducers, MR), 3 (5.9%) re-escalated to previous level (alert reducers, AR), 7 (13.7%) returned to baseline level (baseline returners, BR), 6 (11.7%) relapsed (failed reducers, FR) and 3 (5.9%) withdrew without relapse (early exits, EE). Patients with a history of relapse assumed a conservative dose-tapering pace; only the SR subgroup exhibited significant improvements in functioning and quality of life while failing to identify variables for predicting who would become SR or FR.

Guided dose reduction comprises dynamic processes with differences between individual trajectories. The proposed naming of dose-tapering patterns/subgroups provides a framework depicting patients undergoing dose-tapering. Longer-term observation and more flexible tapering approaches are anticipated to reveal favorable outcomes.

Excessive and persistent fear of clusters of holes, also known as trypophobia, has been suggested to reflect cortical hyperexcitability and may be associated with mental health risks. No study, however, has yet examined these associations in representative epidemiological samples.

To examine the prevalence of trypophobia in a population-representative youth sample, its association with mental health and functioning, and its interaction with external stress.

A total of 2065 young people were consecutively recruited from a household-based epidemiological youth mental health study in Hong Kong. Trypophobia, symptoms of anxiety, depression and stress, and exposure to personal stressors were assessed. Logistic regression was used to assess the relationships between trypophobia and mental health. Potential additive and interaction effects of trypophobia and high stress exposure on mental health were also tested.

The prevalence of trypophobia was 17.6%. Trypophobia was significantly associated with severe symptoms of anxiety (odds ratio (OR) = 1.83, 95% CI = 1.32–2.53), depression (OR = 1.78, 95% CI = 1.24–2.56) and stress (OR = 1.68, 95% CI = 1.11–2.53), even when accounting for sociodemographic factors, personal and family psychiatric history, resilience and stress exposure. Dose–response relationships were observed, and trypophobia significantly potentiated the effects of stress exposure on symptom outcomes, particularly for depressive symptoms. Those with trypophobia also showed significantly poorer functioning across domains and poorer health-related quality of life.

Screening for trypophobia in young people may facilitate early risk detection and intervention, particularly among those with recent stress exposure. Nevertheless, the generally small effect sizes suggest that other factors have more prominent roles in determining recent mental health outcomes in population-based samples; these should be explored in future work.

Clinical trials provide the “gold standard” evidence for advancing the practice of medicine, even as they evolve to integrate real-world data sources. Modern clinical trials are increasingly incorporating real-world data sources – data not intended for research and often collected in free-living contexts. We refer to trials that incorporate real-world data sources as real-world trials. Such trials may have the potential to enhance the generalizability of findings, facilitate pragmatic study designs, and evaluate real-world effectiveness. However, key differences in the design, conduct, and implementation of real-world vs traditional trials have ramifications in data management that can threaten their desired rigor.

Three examples of real-world trials that leverage different types of data sources – wearables, medical devices, and electronic health records are described. Key insights applicable to all three trials in their relationship to Data and Safety Monitoring Boards (DSMBs) are derived.

Insight and recommendations are given on four topic areas: A. Charge of the DSMB; B. Composition of the DSMB; C. Pre-launch Activities; and D. Post-launch Activities. We recommend stronger and additional focus on data integrity.

Clinical trials can benefit from incorporating real-world data sources, potentially increasing the generalizability of findings and overall trial scale and efficiency. The data, however, present a level of informatic complexity that relies heavily on a robust data science infrastructure. The nature of monitoring the data and safety must evolve to adapt to new trial scenarios to protect the rigor of clinical trials.

Despite replicated cross-sectional evidence of aberrant levels of peripheral inflammatory markers in individuals with major depressive disorder (MDD), there is limited literature on associations between inflammatory tone and response to sequential pharmacotherapies.

To assess associations between plasma levels of pro-inflammatory markers and treatment response to escitalopram and adjunctive aripiprazole in adults with MDD.

In a 16-week open-label clinical trial, 211 participants with MDD were treated with escitalopram 10– 20 mg daily for 8 weeks. Responders continued on escitalopram while non-responders received adjunctive aripiprazole 2–10 mg daily for 8 weeks. Plasma levels of pro-inflammatory markers – C-reactive protein, Interleukin (IL)-1β, IL-6, IL-17, Interferon gamma (IFN)-Γ, Tumour Necrosis Factor (TNF)-α, and Chemokine C–C motif ligand-2 (CCL-2) - measured at baseline, and after 2, 8 and 16 weeks were included in logistic regression analyses to assess associations between inflammatory markers and treatment response.

Pre-treatment levels of IFN-Γ and CCL-2 were significantly higher in escitalopram non-responders compared to responders. Pre-treatment IFN-Γ and CCL-2 levels were significantly associated with a lower of odds of response to escitalopram at 8 weeks. Increases in CCL-2 levels from weeks 8 to 16 in escitalopram non-responders were significantly associated with higher odds of non-response to adjunctive aripiprazole at week 16.

Pre-treatment levels of IFN-Γ and CCL-2 were predictive of response to escitalopram. Increasing levels of these pro-inflammatory markers may predict non-response to adjunctive aripiprazole. These findings require validation in independent clinical populations.

None Declared

Most mental disorders, when examined individually, are associated with an increased risk of cardiometabolic complications. However, these associations might be attributed to a general liability toward psychopathology or confounded by unmeasured familial factors.

To examine whether the associations between psychiatric diagnoses and increased risk of cardiometabolic complications are attributable to a general liability toward psychopathology, or confounded by unmeasured familial factors.

We conducted a cohort study in Sweden and identified all individuals and their siblings born in Sweden 1955-1962 with follow-up through 2013. After excluding individuals who died or emigrated before 1987, the final sample consisted 672 823 individuals. We extracted ICD-coded diagnoses (recorded 1973-1987) for ten psychiatric conditions and criminal convictions when participants were aged 18-25 years, and ICD-coded diagnoses (recorded 1987-2013) for five cardiometabolic complications (obesity, hypertensive diseases, hyperlipidemia, type 2 diabetes mellitus, and cardiovascular diseases) when the participants were 51-58 years old. Logistic regression models were used to estimate the bivariate associations between psychiatric conditions or criminal convictions and cardiometabolic complications in individuals. A general factor model was used to identify general, internalizing, externalizing, and psychotic factors based on the psychiatric conditions and criminal convictions. We then regressed the cardiometabolic complications on the latent general factor and three uncorrelated specific factors within a structural equation modeling framework in individuals and across sibling pairs.

Each psychiatric conditions significantly increased the risk of cardiometabolic complications; however, most of these associations were attributable to the general factor of psychopathology, rather than to specific psychiatric conditions. There were no or only small associations between individuals’ general psychopathology and their siblings’ cardiometabolic complications, suggesting that the associations were not attributable to genetic or environmental confounding factors shared within families. The same pattern was evident for the specific internalizing and psychotic factors.

Individuals with mental disorders in early life had an increased long term risk of cardiometabolic complications, which appeared attributable to a general liability toward psychopathology. Sibling analyses suggested that the elevated risk could not be attributed to confounds shared within families.This highlights the importance of transdiagnostic and lifestyle based interventions to reduce the risk of cardiometabolic complications, particularly in patients with several mental disorders.

None Declared

With persistent incidence, incomplete vaccination rates, confounding respiratory illnesses, and few therapeutic interventions available, COVID-19 continues to be a burden on the pediatric population. During a surge, it is difficult for hospitals to direct limited healthcare resources effectively. While the overwhelming majority of pediatric infections are mild, there have been life-threatening exceptions that illuminated the need to proactively identify pediatric patients at risk of severe COVID-19 and other respiratory infectious diseases. However, a nationwide capability for developing validated computational tools to identify pediatric patients at risk using real-world data does not exist.

HHS ASPR BARDA sought, through the power of competition in a challenge, to create computational models to address two clinically important questions using the National COVID Cohort Collaborative: (1) Of pediatric patients who test positive for COVID-19 in an outpatient setting, who are at risk for hospitalization? (2) Of pediatric patients who test positive for COVID-19 and are hospitalized, who are at risk for needing mechanical ventilation or cardiovascular interventions?

This challenge was the first, multi-agency, coordinated computational challenge carried out by the federal government as a response to a public health emergency. Fifty-five computational models were evaluated across both tasks and two winners and three honorable mentions were selected.

This challenge serves as a framework for how the government, research communities, and large data repositories can be brought together to source solutions when resources are strapped during a pandemic.

There is limited literature on associations between inflammatory tone and response to sequential pharmacotherapies in major depressive disorder (MDD).

In a 16-week open-label clinical trial, 211 participants with MDD were treated with escitalopram 10–20 mg daily for 8 weeks. Responders continued escitalopram while non-responders received adjunctive aripiprazole 2–10 mg daily for 8 weeks. Plasma levels of pro-inflammatory markers—C-reactive protein, interleukin (IL)-1β, IL-6, IL-17, interferon-gamma (IFN)-Γ, tumor necrosis factor (TNF)-α, and Chemokine C–C motif ligand-2 (CCL-2)—measured at baseline, and after 2, 8 and 16 weeks were included in logistic regression analyzes to assess associations between inflammatory markers and treatment response.

Pre-treatment IFN-Γ and CCL-2 levels were significantly associated with a lower of odds of response to escitalopram at 8 weeks. Increases in CCL-2 levels from weeks 8 to 16 in escitalopram non-responders were significantly associated with higher odds of non-response to adjunctive aripiprazole at week 16.

Higher pre-treatment levels of IFN-Γ and CCL-2 were associated with non-response to escitalopram. Increasing levels of these pro-inflammatory markers may be associated with non-response to adjunctive aripiprazole. These findings require validation in independent clinical populations.

This paper used data from the Apathy in Dementia Methylphenidate Trial 2 (NCT02346201) to conduct a planned cost consequence analysis to investigate whether treatment of apathy with methylphenidate is economically attractive.

A total of 167 patients with clinically significant apathy randomized to either methylphenidate or placebo were included. The Resource Utilization in Dementia Lite instrument assessed resource utilization for the past 30 days and the EuroQol five dimension five level questionnaire assessed health utility at baseline, 3 months, and 6 months. Resources were converted to costs using standard sources and reported in 2021 USD. A repeated measures analysis of variance compared change in costs and utility over time between the treatment and placebo groups. A binary logistic regression was used to assess cost predictors.

Costs were not significantly different between groups whether the cost of methylphenidate was excluded (F(2,330) = 0.626, ηp2 = 0.004, p = 0.535) or included (F(2,330) = 0.629, ηp2 = 0.004, p = 0.534). Utility improved with methylphenidate treatment as there was a group by time interaction (F(2,330) = 7.525, ηp2 = 0.044, p < 0.001).

Results from this study indicated that there was no evidence for a difference in resource utilization costs between methylphenidate and placebo treatment. However, utility improved significantly over the 6-month follow-up period. These results can aid in decision-making to improve quality of life in patients with Alzheimer’s disease while considering the burden on the healthcare system.

Patients with remitted psychosis face a dilemma between the wish to discontinue antipsychotics and the risk of relapse. We test if an operationalized guided-dose-reduction algorithm can help reach a lower effective dose without increased risks of relapse.

A 2-year open-label randomized prospective comparative cohort trial from Aug 2017 to Sep 2022. Patients with a history of schizophrenia-related psychotic disorders under stable medications and symptoms were eligible, randomized 2:1 into guided dose reduction group (GDR) v. maintenance treatment group (MT1), together with a group of naturalistic maintenance controls (MT2). We observed if the relapse rates would be different between 3 groups, to what extent the dose could be reduced, and if GDR patients could have improved functioning and quality of life.

A total of 96 patients, comprised 51, 24, and 21 patients in GDR, MT1, and MT2 groups, respectively. During follow-up, 14 patients (14.6%) relapsed, including 6, 4, and 4 from GDR, MT1, and MT2, statistically no difference between groups. In total, 74.5% of GDR patients could stay well under a lower dose, including 18 patients (35.3%) conducting 4 consecutive dose-tapering and staying well after reducing 58.5% of their baseline dose. The GDR group exhibited improved clinical outcomes and endorsed better quality of life.

GDR is a feasible approach as the majority of patients had a chance to taper antipsychotics to certain extents. Still, 25.5% of GDR patients could not successfully decrease any dose, including 11.8% experienced relapse, a risk comparable to their maintenance counterparts.

To report the processes used to design and implement an assessment tool to inform funding decisions for competing health innovations in a tertiary hospital.

We designed an assessment tool for health innovation proposals with three components: “value to the institution,” “novelty,” and “potential for adoption and scaling.” The “value to the institution” component consisted of twelve weighted value attributes identified from the host institution’s annual report; weights were allocated based on a survey of the hospital’s leaders. The second and third components consisted of open-ended questions on “novelty” and “barriers to implementation” to support further dialogue. Purposive literature review was performed independently by two researchers for each assessment. The assessment tool was piloted during an institutional health innovation funding cycle.

We used 17 days to evaluate ten proposals. The completed assessments were shared with an independent group of panellists, who selected five projects for funding. Proposals with the lowest scores for “value to the institution” had less perceived impact on the patient-related value attributes of “access,” “patient centeredness,” “health outcomes,” “prevention,” and “safety.” Similar innovations were reported in literature in seven proposals; potential barriers to implementation were identified in six proposals. We included a worked example to illustrate the assessment process.

We developed an assessment tool that is aligned with local institutional priorities. Our tool can augment the decision-making process when funding health innovation projects. The tool can be adapted by others facing similar challenges of trying to choose the best health innovations to fund.

It is unknown if the COVID-19 pandemic and public health measures had an immediate impact on stroke subtypes and etiologies in patients not infected with COVID-19. We aimed to evaluate if the proportion of non-COVID-19-related stroke subtypes (ischemic vs. hemorrhagic) and etiologies (cardioembolic, atherosclerosis, small vessel disease, and others) during the pandemic’s first wave were different from prepandemic.

For this retrospective cohort study, we included patients without COVID-19 with ischemic or hemorrhagic stroke at two large Canadian stroke centers between March–May 2019 (prepandemic cohort) and March–May 2020 (pandemic cohort). Proportions of stroke subtypes and etiologies were compared between cohorts using chi-square tests.

The prepandemic cohort consisted of 234 stroke patients and the pandemic cohort of 207 stroke patients. There were no major differences in baseline characteristics. The proportions of ischemic versus hemorrhagic stroke were similar (ischemic stroke: 77% prepandemic vs. 75% pandemic; hemorrhagic stroke:12% prepandemic vs. 14% pandemic; p > 0.05). There were no differences in etiologies, except for a decreased proportion of ischemic stroke due to atherosclerosis in the pandemic cohort (26% prepandemic vs. 15% pandemic; difference: 10.6%, 95%CI: 1.4-19.7; p = 0.03). Notably, during the pandemic, the cause of ischemic stroke was more often unknown because of incomplete work-up (13.3% prepandemic vs. 28.2% pandemic, difference: 14.9%, 95%-CI: 5.7–24.2; p = <0.01).

In this study, the pandemic had no clear effect on stroke subtypes and etiologies suggesting a limited impact of the pandemic on stroke triggers. However, the shift from atherosclerosis toward other causes warrants further exploration.

The transition from residency to paediatric cardiology fellowship is challenging due to the new knowledge and technical skills required. Online learning can be an effective didactic modality that can be widely accessed by trainees. We sought to evaluate the effectiveness of a paediatric cardiology Fellowship Online Preparatory Course prior to the start of fellowship.

The Online Preparatory Course contained 18 online learning modules covering basic concepts in anatomy, auscultation, echocardiography, catheterisation, cardiovascular intensive care, electrophysiology, pulmonary hypertension, heart failure, and cardiac surgery. Each online learning module included an instructional video with pre-and post-video tests. Participants completed pre- and post-Online Preparatory Course knowledge-based exams and surveys. Pre- and post-Online Preparatory Course survey and knowledge-based examination results were compared via Wilcoxon sign and paired t-tests.

151 incoming paediatric cardiology fellows from programmes across the USA participated in the 3 months prior to starting fellowship training between 2017 and 2019. There was significant improvement between pre- and post-video test scores for all 18 online learning modules. There was also significant improvement between pre- and post-Online Preparatory Course exam scores (PRE 43.6 ± 11% versus POST 60.3 ± 10%, p < 0.001). Comparing pre- and post-Online Preparatory Course surveys, there was a statistically significant improvement in the participants’ comfort level in 35 of 36 (97%) assessment areas. Nearly all participants (98%) agreed or strongly agreed that the Online Preparatory Course was a valuable learning experience and helped alleviate some anxieties (77% agreed or strongly agreed) related to starting fellowship.

An Online Preparatory Course prior to starting fellowship can provide a foundation of knowledge, decrease anxiety, and serve as an effective educational springboard for paediatric cardiology fellows.