Advances in medicine have led to an improvement in life expectancy, thus increasing the population of older individuals within the criminal justice system. This study investigates the determinants of risk formulation, care plan, and disposition among older adult forensic patients (OAFP) in Ontario, Canada.

This retrospective analysis utilized the Ontario Review Board database, focusing on 161 OAFP, aged 55 years and older. Hierarchical regression was used to analyze the relationship between changes in risk and six blocks of variables: sociodemographic characteristics (Block 1), circumstances during the index offense (Block 2), current clinical profile (Block 3), past psychiatric history and behavioral patterns (Block 4), criminal history and legal status (Block 5), and recent violent events (Block 6).

The median age of patients was 61 years (IQR 58–67), with 83.4% being male. Schizophrenia was the most common diagnosis (68.3%), and 9.3% had neurocognitive disorders. The model with six blocks of factors explained 92% of the variability in risk change. Models 2 (blocks 1 and 2) and 4 (blocks 1–4) were statistically significant, explaining 34% (p = 0.010) and 22% (p = 0.018) of the variance in the change in risk of threat to public safety, respectively. OAFP with a significant risk to public safety were more likely to be inpatients and less likely intoxicated during their index offense.

Resources, policies, and a supervised model of care to curtail behavioral risks are relevant to the care of OAFP. Innovative risk management models for OAFP are indicated.

Posttraumatic stress disorder (PTSD) has been associated with advanced epigenetic age cross-sectionally, but the association between these variables over time is unclear. This study conducted meta-analyses to test whether new-onset PTSD diagnosis and changes in PTSD symptom severity over time were associated with changes in two metrics of epigenetic aging over two time points.

We conducted meta-analyses of the association between change in PTSD diagnosis and symptom severity and change in epigenetic age acceleration/deceleration (age-adjusted DNA methylation age residuals as per the Horvath and GrimAge metrics) using data from 7 military and civilian cohorts participating in the Psychiatric Genomics Consortium PTSD Epigenetics Workgroup (total N = 1,367).

Meta-analysis revealed that the interaction between Time 1 (T1) Horvath age residuals and new-onset PTSD over time was significantly associated with Horvath age residuals at T2 (meta β = 0.16, meta p = 0.02, p-adj = 0.03). The interaction between T1 Horvath age residuals and changes in PTSD symptom severity over time was significantly related to Horvath age residuals at T2 (meta β = 0.24, meta p = 0.05). No associations were observed for GrimAge residuals.

Results indicated that individuals who developed new-onset PTSD or showed increased PTSD symptom severity over time evidenced greater epigenetic age acceleration at follow-up than would be expected based on baseline age acceleration. This suggests that PTSD may accelerate biological aging over time and highlights the need for intervention studies to determine if PTSD treatment has a beneficial effect on the aging methylome.

Peripheral inflammatory markers, including serum interleukin 6 (IL-6), are associated with depression, but less is known about how these markers associate with depression at different stages of the life course.

We examined the associations between serum IL-6 levels at baseline and subsequent depression symptom trajectories in two longitudinal cohorts: ALSPAC (age 10–28 years; N = 4,835) and UK Biobank (39–86 years; N = 39,613) using multilevel growth curve modeling. Models were adjusted for sex, BMI, and socioeconomic factors. Depressive symptoms were measured using the Short Moods and Feelings Questionnaire in ALSPAC (max time points = 11) and the Patient Health Questionnaire-2 in UK Biobank (max time points = 8).

Higher baseline IL-6 was associated with worse depression symptom trajectories in both cohorts (largest effect size: 0.046 [ALSPAC, age 16 years]). These associations were stronger in the younger ALSPAC cohort, where additionally higher IL-6 levels at age 9 years was associated with worse depression symptoms trajectories in females compared to males. Weaker sex differences were observed in the older cohort, UK Biobank. However, statistically significant associations (pFDR <0.05) were of smaller effect sizes, typical of large cohort studies.

These findings suggest that systemic inflammation may influence the severity and course of depressive symptoms across the life course, which is apparent regardless of age and differences in measures and number of time points between these large, population-based cohorts.

Accurate diagnosis of bipolar disorder (BPD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A depressive episode often precedes the first manic episode, making it difficult to distinguish BPD from unipolar major depressive disorder (MDD).

We use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores (PRS) that may aid early differential diagnosis.

Based on individual genotypes from case–control cohorts of BPD and MDD shared through the Psychiatric Genomics Consortium, we compile case–case–control cohorts, applying a careful quality control procedure. In a resulting cohort of 51 149 individuals (15 532 BPD patients, 12 920 MDD patients and 22 697 controls), we perform a variety of GWAS and PRS analyses.

Although our GWAS is not well powered to identify genome-wide significant loci, we find significant chip heritability and demonstrate the ability of the resulting PRS to distinguish BPD from MDD, including BPD cases with depressive onset (BPD-D). We replicate our PRS findings in an independent Danish cohort (iPSYCH 2015, N = 25 966). We observe strong genetic correlation between our case–case GWAS and that of case–control BPD.

We find that MDD and BPD, including BPD-D are genetically distinct. Our findings support that controls, MDD and BPD patients primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BPD and, importantly, BPD-D from MDD.

The relationship between psychosis and violence is often construed focusing on a narrow panel of factors; however, recent evidence suggests violence might be linked to a complex interplay of biopsychosocial factors among forensic psychiatric patients with psychosis (FPPP). This review describes violence incidents in FPPP, the factors associated with violence, and relevant implications.

This review was conducted following the preferred reporting items for systematic reviews and meta-analyses guideline. Databases, including CINAHL, EMBASE, Medline/PubMed, PsycINFO, and Web of Science, were searched for eligible studies that examined violence among adult FPPP. Screening of reports and data extraction were completed by at least two independent reviewers.

Across the 29 included studies, violence was consistently related to prior contact with psychiatric services, active psychotic symptoms, impulsivity, adverse experiences, and low social support. However, FPPP who reported violence varied in most other biopsychosocial domains, suggesting the underlying combinatorial effects of multiple risk factors for violence rather than individual factors. Variability in violence was addressed by stratifying FPPP into subgroups using composite/aggregate of identifiable factors (including gender, onset/course of illness, system-related, and other biopsychosocial factors) to identify FPPP with similar risk profiles.

There are multiple explanatory pathways to violence in FPPP. Recent studies identify subgroups with underlying similarities or risk profiles for violence. There is a need for future prospective studies to replicate the clinical utility of stratifying FPPP into subgroups and integrate emerging evidence using recent advancements in technology and data mining to improve risk assessment, prediction, and management.

Our objective was to assess the predictive value of physiologic dead space fraction for mortality in patients undergoing the comprehensive stage 2 operation.

This was a single-centre retrospective observational study conducted at a quaternary free-standing children’s hospital specialising in hybrid palliation of single ventricle cardiac disease. 180 patients underwent the comprehensive stage 2 operation. 76 patients (42%) underwent early extubation, 59 (33%) standard extubation, and 45 (25%) delayed extubation. We measured time to extubation, post-operative outcomes, length of stay and utilised Fine gray models, Youden’s J statistic, cumulative incidence function, and logistic regression to analyse outcomes.

Delayed extubation group suffered significantly higher rates of mortality (31.1% vs. 6.8%), cardiac arrest (40.0% vs. 10.2%), stroke (37.8% vs. 11.9%), and need for catheter (28.9% vs. 5.1%) and surgical intervention (24.4% vs. 8.5%) (P < 0.001). Physiologic dead space fraction was significantly higher in the delayed extubation group and in non-survivors with a value of 0.3, which was found to be the discriminatory point by Youden’s J statistic. For a 0.1 unit increase in physiologic dead space fraction on post-operative day 1, the odds of a patient expiring increase by a factor of 2.26 (95% CI 1.41–3.97, p < 0.001) and by a factor of 3.79 (95% CI 1.65–11.7, p 0.01) on post-operative day 3.

Delayed extubation impacts morbidity and mortality in patients undergoing the comprehensive stage 2 operation. Increased physiologic dead space fraction in the first 60 hours after arrival to the ICU is associated with higher mortality.

Studies have shown an association between workplace safety climate scores and patient outcomes. This study aimed to investigate (1) performance of the hospital safety climate scale that was adapted to assess acute respiratory illness safety climate, (2) factors associated with safety climate scores, and (3) whether the safety scores were associated with following recommended droplet and contact precautions.

A survey of Canadian healthcare personnel participating in a cohort study of influenza during the 2010/2011–2013/2014 winter seasons. Factor analysis and structural equation modeling were used for analyses.

Of the 1359 participants eligible for inclusion, 88% were female and 52% were nurses. The adapted items loaded to the same factors as the original scale. Personnel working on higher risk wards, nurses, and younger staff rated their hospital’s safety climate lower than other staff. Following guidelines for droplet and contact precautions was positively associated with ratings of management support and absence of job hindrances.

The adapted tool can be used to assess hospital safety climates regarding respiratory pathogens. Management support and the absence of job hindrances are associated with hospital staff’s propensity and ability to follow precautions against the transmission of respiratory illnesses.

Diagnostic criteria for major depressive disorder allow for heterogeneous symptom profiles but genetic analysis of major depressive symptoms has the potential to identify clinical and etiological subtypes. There are several challenges to integrating symptom data from genetically informative cohorts, such as sample size differences between clinical and community cohorts and various patterns of missing data.

We conducted genome-wide association studies of major depressive symptoms in three cohorts that were enriched for participants with a diagnosis of depression (Psychiatric Genomics Consortium, Australian Genetics of Depression Study, Generation Scotland) and three community cohorts who were not recruited on the basis of diagnosis (Avon Longitudinal Study of Parents and Children, Estonian Biobank, and UK Biobank). We fit a series of confirmatory factor models with factors that accounted for how symptom data was sampled and then compared alternative models with different symptom factors.

The best fitting model had a distinct factor for Appetite/Weight symptoms and an additional measurement factor that accounted for the skip-structure in community cohorts (use of Depression and Anhedonia as gating symptoms).

The results show the importance of assessing the directionality of symptoms (such as hypersomnia versus insomnia) and of accounting for study and measurement design when meta-analyzing genetic association data.

Chemsex occurs primarily among gay, bisexual and other men who have sex with men (GBMSM), and there is evidence of a subgroup of users who carry out chemsex-related criminal offences and experience harm. Challenges with chemsex can present to various settings; there are concerns that harm is increasing, including at interfaces between health, social care and criminal justice systems. The UK response to date has lacked a coordinated approach. An expert reference group was convened to share chemsex knowledge, articulate priorities for research and pathway development, and foster collaborative working between agencies. It made three key recommendations: develop and increase training and awareness across all services; implement a coordinated research programme with the development of a common data-set and assessment tool to fully characterise population-level needs; develop a professional network to share information, provide professional support and act as a knowledge hub. There was support for a unified multi-agency strategy incorporating the priorities identified as overarching principles.