Cholestasis characterised by conjugated hyperbilirubinemia is a marker of hepatobiliary dysfunction following neonatal cardiac surgery. We aimed to characterise the incidence of conjugated hyperbilirubinemia following neonatal heart surgery and examine the effect of conjugated hyperbilirubinemia on post-operative morbidity and mortality.

This was a retrospective study of all neonates who underwent surgery for congenital heart disease (CHD) at our institution between 1/1/2010 and 12/31/2020. Patient- and surgery-specific data were abstracted from local registry data and review of the medical record. Conjugated hyperbilirubinemia was defined as perioperative maximum conjugated bilirubin level > 1 mg/dL. The primary outcome was in-hospital mortality. Survival analysis was conducted using the Kaplan–Meier survival function.

Conjugated hyperbilirubinemia occurred in 8.5% of patients during the study period. Neonates with conjugated hyperbilirubinemia were more likely to be of younger gestational age, lower birth weight, and non-Caucasian race (all p < 0.001). Patients with conjugated hyperbilirubinemia were more likely to have chromosomal and non-cardiac anomalies and require ECMO pre-operatively. In-hospital mortality among patients with conjugated hyperbilirubinemia was increased compared to those without (odds ratio 5.4). Post-operative complications including mechanical circulatory support, reoperation, prolonged ventilator dependence, and multi-system organ failure were more common with conjugated hyperbilirubinemia (all p < 0.04). Patients with higher levels of conjugated bilirubin had worst intermediate-term survival, with patients in the highest conjugated bilirubin group (>10 mg/dL) having a 1-year survival of only 6%.

Conjugated hyperbilirubinemia is associated with post-operative complications and worse survival following neonatal heart surgery. Cholestasis is more common in patients with chromosomal abnormalities and non-cardiac anomalies, but the underlying mechanisms have not been delineated.

Data are scarce regarding the clinical factors associated with utilization of long-term care facilities among older adults with schizophrenia.

In this multicenter study, we sought to examine potential clinical differences between older adults with schizophrenia who are living in a long-term care facility and their community-dwelling counterparts.

We used data from the French Cohort of individuals with Schizophrenia Aged 55-years or more (CSA) study, a large multicenter sample of older adults with schizophrenia (N = 353).

We used data from the French Cohort of individuals with Schizophrenia Aged 55-years or more (CSA)study, a large multicenter sample of older adults with schizophrenia (N = 353).

Results from the multivariable binary logistic regression analysis including all variables that had a significant association in univariate analyses (i.e., p < 0.05) revealed that older age (Adjusted odds ratio (AOR) [95%CI]=1.08 [1.03–1.13]), depression (AOR [95%CI]=1.97 [1.06–3.64]), lower MMSE (AOR [95%CI]=0.94 [0.88–0.99]) and GAF scores (AOR [95%CI]=0.97 [0.95–0.99]), living in an area comprising more than 1000 inhabitants per km2 (AOR [95%CI]=2.81 [1.37–5.80]), having consulted a general practitioner in the past year (AOR [95%CI]=0.28 [0.0.14–0.56]), and a greater lifetime number of hospitalizations in a psychiatric department (AOR [95%CI]=2.30 [1.18–4.50]) were significantly and independently associated with long-term care utilization among older adults with schizophrenia . In the multivariable logistic regression model, the variance inflation factor (VIF) and tolerance values of each predictor variable were respectively lower than 2.5 and higher than 0.2, supporting that multicollinearity was not a concern in our analysis.

In a multicenter sample of 353 older adults with schizophrenia, we found that ong-term care utilization was significantly and independently associated with depression, lower cognitive and global functioning, greater lifetime number of hospitalizations in a psychiatric department, not having consulted a general practitioner in the past year, urbanicity and older age. Patients living in a long-term care facility appear to belong to a distinct group, marked by a more severe course of illness with higher level of depression and more severe cognitive deficits.

Despite its limitations, this study contributes to gain more specific knowledge about this specific understudied population. Our study highlights the need of early assessment and management of depression and cognitive deficits in this population and the importance of monitoring closely this vulnerable population.

None Declared

Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.

To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.

This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.

The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.

Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

We summarize some of the past year's most important findings within climate change-related research. New research has improved our understanding of Earth's sensitivity to carbon dioxide, finds that permafrost thaw could release more carbon emissions than expected and that the uptake of carbon in tropical ecosystems is weakening. Adverse impacts on human society include increasing water shortages and impacts on mental health. Options for solutions emerge from rethinking economic models, rights-based litigation, strengthened governance systems and a new social contract. The disruption caused by COVID-19 could be seized as an opportunity for positive change, directing economic stimulus towards sustainable investments.

A synthesis is made of ten fields within climate science where there have been significant advances since mid-2019, through an expert elicitation process with broad disciplinary scope. Findings include: (1) a better understanding of equilibrium climate sensitivity; (2) abrupt thaw as an accelerator of carbon release from permafrost; (3) changes to global and regional land carbon sinks; (4) impacts of climate change on water crises, including equity perspectives; (5) adverse effects on mental health from climate change; (6) immediate effects on climate of the COVID-19 pandemic and requirements for recovery packages to deliver on the Paris Agreement; (7) suggested long-term changes to governance and a social contract to address climate change, learning from the current pandemic, (8) updated positive cost–benefit ratio and new perspectives on the potential for green growth in the short- and long-term perspective; (9) urban electrification as a strategy to move towards low-carbon energy systems and (10) rights-based litigation as an increasingly important method to address climate change, with recent clarifications on the legal standing and representation of future generations.

Stronger permafrost thaw, COVID-19 effects and growing mental health impacts among highlights of latest climate science.

It is unclear whether olfactory deficits improve after remission in depressed patients. Therefore, we aimed to assess in drug-free patients the olfactory performance of patients with major depressive episodes (MDE) and its change after antidepressant treatment.

In the DEP-ARREST-CLIN study, 69 drug-free patients with a current MDE in the context of major depressive disorder (MDD) were assessed for their olfactory performances and depression severity, before and after 1 (M1) and 3 (M3) months of venlafaxine antidepressant treatment. They were compared to 32 age- and sex-matched healthy controls (HCs). Olfaction was assessed with a psychophysical test, the Sniffin’ Sticks test (Threshold: T score; Discrimination: D score; Identification: I score; total score: T + D + I = TDI score) and Pleasantness (pleasantness score: p score; neutral score: N score; unpleasantness score: U score).

As compared to HCs, depressed patients had lower TDI olfactory scores [mean (s.d.) 30.0(4.5) v. 33.3(4.2), p < 0.001], T scores [5.6(2.6) v. 7.4(2.6), p < 0.01], p scores [7.5(3.0) v. 9.8(2.8), p < 0.001)] and higher N scores [3.5(2.6) v. 2.1(1.8), p < 0.01]. T, p and N scores at baseline were independent from depression and anhedonia severity. After venlafaxine treatment, significant increases of T scores [M1: 7.0(2.6) and M3: 6.8(3.1), p < 0.01] and p scores [M1: 8.1(3.0) and M3: 8.4(3.3), p < 0.05] were evidenced, in remitters only (T: p < 0.01; P: p < 0.01). Olfaction improvement was mediated by depression improvement.

The olfactory signature of MDE is restored after venlafaxine treatment. This olfaction improvement is mediated by depression improvement.

To make pragmatic recommendations on best practices for the engagement of patients in emergency medicine (EM) research.

We created a panel of expert Canadian EM researchers, physicians, and a patient partner to develop our recommendations. We used mixed methods consisting of 1) a literature review; 2) a survey of Canadian EM researchers; 3) qualitative interviews with key informants; and 4) feedback during the 2017 Canadian Association of Emergency Physicians (CAEP) Academic Symposium.

We synthesized our literature review into categories including identification and engagement, patients’ roles, perceived benefits, harms, and barriers to patient engagement; 40/75 (53% response rate) invited researchers completed our survey. Among respondents, 58% had engaged patients in research, and 83% intended to engage patients in future research. However, 95% stated that they need further guidance to engage patients. Our qualitative interviews revealed barriers to patient engagement, including the need for training and patient partner recruitment.

Our panel recommends 1) an overarching positive recommendation to support patient engagement in EM research; 2) seven policy-level recommendations for CAEP to support the creation of a national patient council, to develop, adopt and adapt training material, guidelines, and tools for patient engagement, and to support increased patient engagement in EM research; and 3) nine pragmatic recommendations about engaging patients in the preparatory, execution, and translational phases of EM research.

Patient engagement can improve EM research by helping researchers select meaningful outcomes, increase social acceptability of studies, and design knowledge translation strategies that target patients’ needs.

Previous work has identified associations between psychotic experiences (PEs) and general medical conditions (GMCs), but their temporal direction remains unclear as does the extent to which they are independent of comorbid mental disorders.

In total, 28 002 adults in 16 countries from the WHO World Mental Health (WMH) Surveys were assessed for PEs, GMCs and 21 Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) mental disorders. Discrete-time survival analyses were used to estimate the associations between PEs and GMCs with various adjustments.

After adjustment for comorbid mental disorders, temporally prior PEs were significantly associated with subsequent onset of 8/12 GMCs (arthritis, back or neck pain, frequent or severe headache, other chronic pain, heart disease, high blood pressure, diabetes and peptic ulcer) with odds ratios (ORs) ranging from 1.3 [95% confidence interval (CI) 1.1–1.5] to 1.9 (95% CI 1.4–2.4). In contrast, only three GMCs (frequent or severe headache, other chronic pain and asthma) were significantly associated with subsequent onset of PEs after adjustment for comorbid GMCs and mental disorders, with ORs ranging from 1.5 (95% CI 1.2–1.9) to 1.7 (95% CI 1.2–2.4).

PEs were associated with the subsequent onset of a wide range of GMCs, independent of comorbid mental disorders. There were also associations between some medical conditions (particularly those involving chronic pain) and subsequent PEs. Although these findings will need to be confirmed in prospective studies, clinicians should be aware that psychotic symptoms may be risk markers for a wide range of adverse health outcomes. Whether PEs are causal risk factors will require further research.