Comorbid obsessive–compulsive disorder (OCD) or obsessive–compulsive symptoms (OCS) are common in people with severe mental illness (SMI; including schizophrenia, bipolar disorder and schizoaffective disorder), with little known about associations with smoking.

To estimate the association between OCD/OCS and smoking status among people with SMI in a huge electronic database.

Using the Clinical Records Interactive Search (CRIS) platform for data of service users in the South London and Maudsley (SLaM) NHS Foundation Trust, tobacco smoking status was retrospectively detected through an algorithm of natural language processing technique, categorising into ‘current smoker’, ‘ex-smoker’ and ‘non-smoker’ by the clinical notes of SMI individuals during 2007–2015. A hierarchical assignment rule was applied following the order of ‘smoker’, ‘ex-smoker’ and then ‘non-smoker’ in an individual. Logistic regression was used to examine the association between smoking and OCS in people with SMI for univariable and multivariable analyses.

We identified 15 479 SMI individuals (56% male; mean age 41 years old), with 90.4% ever smoked. Among them, 2320 (15%) had OCS (without OCD), while 2174 (14%) had a clinical diagnosis of comorbid OCD. After adjusting for demographics and functional status as confounders, both SMI individuals with OCS only and an OCD diagnosis were significantly more likely to have ever smoked (adj. odds ratio 1.47, 95% CI 1.23, 1.76 and adj. odds ratio 1.33, 95% CI 1.11, 1.60, respectively) compared with those without OCD/OCS.

In this large-scale analysis of people with SMI, we found that individuals with OCS or OCD were more likely to have ever smoked.

Childhood maltreatment (CM) is related to structural alterations in adult limbic regions. However, the change in limbic structures remains unclear in adolescents from the general population since most reports stem from clinical samples. Additionally, large longitudinal neuroimaging studies in community adolescents reporting CM are scarce. Hence, we aimed to investigate the cross-sectional and longitudinal associations between CM and the structure and function of the extended limbic and reward systems throughout adolescence.

We analysed data of 634 community adolescents from the IMAGEN cohort at age 14, followed up at age 18. CM was inferred from the Childhood Trauma Questionnaire completed at age 18, yielding subgroups with CM (N = 105) or without CM (N = 529). Using 3-Tesla T1 MRI, we performed between-group voxel-wise analyses at ages 14 and 18 to investigate grey matter volumes (GMV). In addition, GMV were investigated longitudinally between ages 14 and 18. Finally, using functional MRI and the Monetary Incentive Delay task, we measured reward anticipation and feedback sensitivity between groups at ages 14 and 18.

Both at ages 14 and 18, adolescents reporting CM had lower GMV in the right insula, left orbitofrontal cortex, putamen, superior medial frontal gyrus, paracentral lobule, and other paralimbic regions, but no significant differences in reward response. Longitudinal analyses revealed no GMV difference between age groups.

CM was associated with GMV alterations persisting from early to late adolescence in the limbic regions in community individuals. Therefore, these findings further support the need for research on targeted preventive interventions for adolescents who have experienced CM.

Because of the complexity of Alzheimer’s Disease (AD) clinical presentations across bio-psycho-social domains of functioning, data-reduction approaches, such as latent profile analysis (LPA), can be useful for studying profiles rather than individual symptoms. Previous LPA research has resulted in more precise characterization and understanding of patients, better clarity regarding the probability and rate of disease progression, and an empirical approach to identifying those who might benefit most from early intervention. Whereas previous LPA research has revealed useful cognitive, neuropsychiatric, or functional subtypes of patients with AD, no study has identified patient profiles that span the domains of health and functioning and that also include motor and sensory functioning.

LPA was conducted with data from the Advancing Reliable Measurement in Alzheimer’s Disease and cognitive Aging study. Participants were 209 older adults with amnestic mild cognitive impairment (aMCI) or mild dementia of the Alzheimer’s type (DAT). LPA indicator variables were from the NIH Toolbox® and included cognitive, emotional, social, motor, and sensory domains of functioning.

The data were best modeled with a 4-profile solution. The latent profiles were most differentiated by indices of social and emotional functioning and least differentiated by motor and sensory function.

These multi-domain patient profiles support and extend previous findings on single-domain profiles and highlight the importance of social and emotional factors for understanding patient experiences of aMCI/DAT. Future research should investigate these profiles further to better understand risk and resilience factors, the stability of these profiles over time, and responses to intervention.

This systematic review and meta-analysis evaluates the prevalence of disruptive mood dysregulation disorders (DMDD) in community-based and clinical populations.

PubMed and PsychINFO databases were searched, using terms specific to DMDD, for studies of prevalence and comorbidity rates conducted in youths below 18.

Fourteen studies reporting data from 2013 to 2023 were included. The prevalence of DMDD in the community-based samples was 3.3% (95% confidence interval [CI], 1.4–6.0) and 21.9% (95% CI, 15.5–29.0) in the clinical population. The differences in the identification strategy of DMDD were associated with significant heterogeneity between studies in the community-based samples, with a prevalence of 0.82% (95% CI, 0.11–2.13) when all diagnosis criteria were considered. Anxiety, depressive disorders, and ADHD were the most frequent comorbidity present with DMDD. The association with other neurodevelopmental disorders remained poorly investigated.

Caution is required when interpreting these findings, considering the quality of the reviewed data and the level of unexplained heterogeneity among studies. This review stresses the importance of considering a strict adhesion to DMDD criteria when exploring its clinical correlates.

The timing of tracheostomy for intensive care unit patients is controversial, with conflicting findings on early versus late tracheostomy.

Patients undergoing tracheostomy from 2001through 2012 were identified from the Medical Information Mart for Intensive Care-III database. Early tracheostomy was defined as less than the 25th percentile of time from intensive care unit admission to tracheostomy (time to tracheostomy). Statistical analysis for tracheostomy timing on intensive care unit length of stay and mortality were conducted.

Of the 1,566 patients that were included, patients with early tracheostomy had shorter intensive care unit length of stay (27.32 vs 12.55 days, p < 0.001) and lower mortality (12.9 per cent vs 9.0 per cent, p = 0.039). Multivariate logistic regression analysis found an association between increasing time to tracheostomy and mortality (odds ratio: 1.029, 95 per cent confidence interval 1.007–1.051, p = 0.009).

Our analysis revealed that patients with early tracheostomy were more likely to have shorter intensive care unit lengths of stay and lower mortality. Our data suggest that early tracheostomy should be given strong consideration in appropriately selected patients.

Previous pandemics have had negative effects on mental health, but there are few data on children and adolescents who were receiving ongoing psychiatric treatment.

To study changes in emotions and clinical state, and their predictors, during the COVID-19 pandemic in France.

We administered (by interview) the baseline Youth Self-Report version of the CoRonavIruS Health Impact Survey v0.3 (CRISIS, French translation) to 123 adolescent patients and the Parent/Caregiver version to evaluate 99 child patients before and during the first ‘lockdown’. For 139 of these patients who received ongoing treatment in our centre, treating physicians retrospectively completed longitudinal global ratings for five time periods, masked to CRISIS ratings.

The main outcome measure was the sum of eight mood state items, which formed a single factor in each age group. Overall, this score improved for each age group during the first lockdown. Clinician ratings modestly supported this result in patients without intellectual disability or autism spectrum disorder. Improvement of mood states was significantly associated with perceived improvement in family relationships in both age groups.

Consistent with previous studies of clinical cohorts, our patients had diverse responses during the pandemic. Several factors may have contributed to the finding of improvement in some individuals during the first lockdown, including the degree of family support or conflict, stress reduction owing to isolation, limitations of the outcome measures and/or possible selection bias. Ongoing treatment may have had a protective effect. Clinically, during crises additional support may be needed by families who experience increased conflict or who care for children with intellectual disability.

Symptom clustering research provides a unique opportunity for understanding complex medical conditions. The objective of this study was to apply a variable-centered analytic approach to understand how symptoms may cluster together, within and across domains of functioning in mild cognitive impairment (MCI) and dementia, to better understand these conditions and potential etiological, prevention, and intervention considerations.

Cognitive, motor, sensory, emotional, and social measures from the NIH Toolbox were analyzed using exploratory factor analysis (EFA) from a dataset of 165 individuals with a research diagnosis of either amnestic MCI or dementia of the Alzheimer’s type.

The six-factor EFA solution described here primarily replicated the intended structure of the NIH Toolbox with a few deviations, notably sensory and motor scores loading onto factors with measures of cognition, emotional, and social health. These findings suggest the presence of cross-domain symptom clusters in these populations. In particular, negative affect, stress, loneliness, and pain formed one unique symptom cluster that bridged the NIH Toolbox domains of physical, social, and emotional health. Olfaction and dexterity formed a second unique cluster with measures of executive functioning, working memory, episodic memory, and processing speed. A third novel cluster was detected for mobility, strength, and vision, which was considered to reflect a physical functioning factor. Somewhat unexpectedly, the hearing test included did not load strongly onto any factor.

This research presents a preliminary effort to detect symptom clusters in amnestic MCI and dementia using an existing dataset of outcome measures from the NIH Toolbox.

Understanding the factors contributing to optimal cognitive function throughout the aging process is essential to better understand successful cognitive aging. Processing speed is an age sensitive cognitive domain that usually declines early in the aging process; however, this cognitive skill is essential for other cognitive tasks and everyday functioning. Evaluating brain network interactions in cognitively healthy older adults can help us understand how brain characteristics variations affect cognitive functioning. Functional connections among groups of brain areas give insight into the brain’s organization, and the cognitive effects of aging may relate to this large-scale organization. To follow-up on our prior work, we sought to replicate our findings regarding network segregation’s relationship with processing speed. In order to address possible influences of node location or network membership we replicated the analysis across 4 different node sets.

Data were acquired as part of a multi-center study of 85+ cognitively normal individuals, the McKnight Brain Aging Registry (MBAR). For this analysis, we included 146 community-dwelling, cognitively unimpaired older adults, ages 85-99, who had undergone structural and BOLD resting state MRI scans and a battery of neuropsychological tests. Exploratory factor analysis identified the processing speed factor of interest. We preprocessed BOLD scans using fmriprep, Ciftify, and XCPEngine algorithms. We used 4 different sets of connectivity-based parcellation: 1)MBAR data used to define nodes and Power (2011) atlas used to determine node network membership, 2) Younger adults data used to define nodes (Chan 2014) and Power (2011) atlas used to determine node network membership, 3) Older adults data from a different study (Han 2018) used to define nodes and Power (2011) atlas used to determine node network membership, and 4) MBAR data used to define nodes and MBAR data based community detection used to determine node network membership.

Segregation (balance of within-network and between-network connections) was measured within the association system and three wellcharacterized networks: Default Mode Network (DMN), Cingulo-Opercular Network (CON), and Fronto-Parietal Network (FPN). Correlation between processing speed and association system and networks was performed for all 4 node sets.

We replicated prior work and found the segregation of both the cortical association system, the segregation of FPN and DMN had a consistent relationship with processing speed across all node sets (association system range of correlations: r=.294 to .342, FPN: r=.254 to .272, DMN: r=.263 to .273). Additionally, compared to parcellations created with older adults, the parcellation created based on younger individuals showed attenuated and less robust findings as those with older adults (association system r=.263, FPN r=.255, DMN r=.263).

This study shows that network segregation of the oldest-old brain is closely linked with processing speed and this relationship is replicable across different node sets created with varied datasets. This work adds to the growing body of knowledge about age-related dedifferentiation by demonstrating replicability and consistency of the finding that as essential cognitive skill, processing speed, is associated with differentiated functional networks even in very old individuals experiencing successful cognitive aging.

The COVID-19 pandemic was associated with increased rates of hospital-acquired infections. During the early months of the pandemic, we observed high rates of hospital-acquired bloodstream infections (HA-BSIs) among COVID-19 patients, prompting the implementation of intensified prevention measures.

To assess the prevalence of HA-BSI among mechanically ventilated COVID-19 patients, identify risk factors, and evaluate the effect of prevention measures.

We conducted a retrospective matched case-control study in adult medical step-up units between March 1, 2020, and March 31, 2021. We matched mechanically ventilated COVID-19 patients with ventilated non-COVID-19 patients based on age group and length of stay before ventilation. In response to the high rates of HA-BSI among COVID-19 patients, a comprehensive infection control intervention was implemented.

A total of 136 COVID-19 patients were matched with 136 non-COVID-19 patients. No significant differences were observed in pre-hospitalization characteristics. The central venous catheter utilization ratio was higher in COVID-19 patients (83.6%) versus 35.6% in the control group (p < 0.001). During pre-intervention, 35.2% (32/91) of COVID-19 patients developed HA-BSI, compared to 17.8% (13/73) in the control group (p < 0.001). Following the intervention, no significant difference was observed between the groups (17.8% (8/45) versus 15.9% (10 /63), p = 0.79). In a multivariate analysis, HA-BSI was associated with low body mass index (OR 0.9 (95% CI 0.9–1.0), p = 0.015)) and presence of temporary dialysis catheter (OR 2.7 (95% CI 1.0–7.3), p = 0.05)).

Mechanically ventilated COVID-19 patients were at higher risk for developing HA-BSI compared to non-COVID-19 patients. Intensified prevention measures were associated with decreased rates of HA-BSI.

Despite the increasing rates of carbapenem-resistant Acinetobacter baumannii (CRAB) carriage among hospitalized patients in endemic settings, the role of active surveillance cultures and cohorting is still debated. We sought to determine the long-term effect of a multifaceted infection-control intervention on the incidence of CRAB in an endemic setting.

A prospective, quasi-experimental study was performed at a 670-bed, acute-care hospital. The study consisted of 4 phases. In phase I, basic infection control measures were used. In phase II, CRAB carriers were cohorted in a single ward with dedicated nursing and enhanced environmental cleaning. In phase III large-scale screening in high-risk units was implemented. Phase IV comprised a 15-month follow-up period.

During the baseline period, the mean incidence rate (IDR) of CRAB was 44 per 100,000 patient days (95% CI, 37.7–54.1). No significant decrease was observed during phase II (IDR, 40.8 per 100,000 patient days; 95% CI, 30.0–56.7; P = .97). During phase III, despite high compliance with control measures, ongoing transmission in several wards was observed and the mean IDR was 53.9 per 100,000 patient days (95% CI, 40.5–72.2; P = .55). In phase IV, following the implementation of large-scale screening, a significant decrease in the mean IDR was observed (25.8 per 100,000 patient days; 95% CI, 19.9–33.5; P = .03). An overall reduction of CRAB rate was observed between phase I and phase IV (rate ratio, 0.6; 95% CI, 0.4–0.9; P < .001).

The comprehensive intervention that included intensified control measures with routine active screening cultures was effective in reducing the incidence of CRAB in an endemic hospital setting.