Depression is an independent risk factor for cardiovascular disease (CVD), but it is unknown if successful depression treatment reduces CVD risk.

Using eIMPACT trial data, we examined the effect of modernized collaborative care for depression on indicators of CVD risk. A total of 216 primary care patients with depression and elevated CVD risk were randomized to 12 months of the eIMPACT intervention (internet cognitive-behavioral therapy [CBT], telephonic CBT, and select antidepressant medications) or usual primary care. CVD-relevant health behaviors (self-reported CVD prevention medication adherence, sedentary behavior, and sleep quality) and traditional CVD risk factors (blood pressure and lipid fractions) were assessed over 12 months. Incident CVD events were tracked over four years using a statewide health information exchange.

The intervention group exhibited greater improvement in depressive symptoms (p < 0.01) and sleep quality (p < 0.01) than the usual care group, but there was no intervention effect on systolic blood pressure (p = 0.36), low-density lipoprotein cholesterol (p = 0.38), high-density lipoprotein cholesterol (p = 0.79), triglycerides (p = 0.76), CVD prevention medication adherence (p = 0.64), or sedentary behavior (p = 0.57). There was an intervention effect on diastolic blood pressure that favored the usual care group (p = 0.02). The likelihood of an incident CVD event did not differ between the intervention (13/107, 12.1%) and usual care (9/109, 8.3%) groups (p = 0.39).

Successful depression treatment alone is not sufficient to lower the heightened CVD risk of people with depression. Alternative approaches are needed.

ClinicalTrials.gov Identifier: NCT02458690

To synthesize evidence and identify gaps in the literature on environmental cleaning and disinfection in the operating room based on a human factors and systems engineering approach guided by the Systems Engineering Initiative for Patient Safety (SEIPS) model.

A systematic scoping review.

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched 4 databases (ie, PubMed, EMBASE, OVID, CINAHL) for empirical studies on operating-room cleaning and disinfection. Studies were categorized based on their objectives and designs and were coded using the SEIPS model. The quality of randomized controlled trials and quasi-experimental studies with a nonequivalent groups design was assessed using version 2 of the Cochrane risk-of-bias tool for randomized trials.

In total, 40 studies were reviewed and categorized into 3 groups: observational studies examining the effectiveness of operating-room cleaning and disinfections (11 studies), observational study assessing compliance with operating-room cleaning and disinfection (1 study), and interventional studies to improve operating-room cleaning and disinfection (28 studies). The SEIPS-based analysis only identified 3 observational studies examining individual work-system components influencing the effectiveness of operating-room cleaning and disinfection. Furthermore, most interventional studies addressed single work-system components, including tools and technologies (20 studies), tasks (3 studies), and organization (3 studies). Only 2 studies implemented interventions targeting multiple work-system components.

The existing literature shows suboptimal compliance and inconsistent effectiveness of operating-room cleaning and disinfection. Improvement efforts have been largely focused on cleaning and disinfection tools and technologies and staff monitoring and training. Future research is needed (1) to systematically examine work-system factors influencing operating-room cleaning and disinfection and (2) to redesign the entire work system to optimize operating-room cleaning and disinfection.

Evaluate the association between provider-ordered viral testing and antibiotic treatment practices among children discharged from an ED or hospitalized with an acute respiratory infection (ARI).

Active, prospective ARI surveillance study from November 2017 to February 2020.

Pediatric hospital and emergency department in Nashville, Tennessee.

Children 30 days to 17 years old seeking medical care for fever and/or respiratory symptoms.

Antibiotics prescribed during the child’s ED visit or administered during hospitalization were categorized into (1) None administered; (2) Narrow-spectrum; and (3) Broad-spectrum. Setting-specific models were built using unconditional polytomous logistic regression with robust sandwich estimators to estimate the adjusted odds ratios and 95% confidence intervals between provider-ordered viral testing (ie, tested versus not tested) and viral test result (ie, positive test versus not tested and negative test versus not tested) and three-level antibiotic administration.

4,107 children were enrolled and tested, of which 2,616 (64%) were seen in the ED and 1,491 (36%) were hospitalized. In the ED, children who received a provider-ordered viral test had 25% decreased odds (aOR: 0.75; 95% CI: 0.54, 0.98) of receiving a narrow-spectrum antibiotic during their visit than those without testing. In the inpatient setting, children with a negative provider-ordered viral test had 57% increased odds (aOR: 1.57; 95% CI: 1.01, 2.44) of being administered a broad-spectrum antibiotic compared to children without testing.

In our study, the impact of provider-ordered viral testing on antibiotic practices differed by setting. Additional studies evaluating the influence of viral testing on antibiotic stewardship and antibiotic prescribing practices are needed.

To compare the agreement and cost of two recall methods for estimating children’s minimum dietary diversity (MDD).

We assessed child’s dietary intake on two consecutive days: an observation on day one, followed by two recall methods (list-based recall and multiple-pass recall) administered in random order by different enumerators at two different times on day two. We compared the estimated MDD prevalence using survey-weighted linear probability models following a two one-sided test equivalence testing approach. We also estimated the cost-effectiveness of the two methods.

Cambodia (Kampong Thom, Siem Reap, Battambang, and Pursat provinces) and Zambia (Chipata, Katete, Lundazi, Nyimba, and Petauke districts).

Children aged 6–23 months: 636 in Cambodia and 608 in Zambia.

MDD estimations from both recall methods were equivalent to the observation in Cambodia but not in Zambia. Both methods were equivalent to the observation in capturing most food groups. Both methods were highly sensitive although the multiple-pass method accurately classified a higher proportion of children meeting MDD than the list-based method in both countries. Both methods were highly specific in Cambodia but moderately so in Zambia. Cost-effectiveness was better for the list-based recall method in both countries.

The two recall methods estimated MDD and most other infant and young child feeding indicators equivalently in Cambodia but not in Zambia, compared to the observation. The list-based method produced slightly more accurate estimates of MDD at the population level, took less time to administer and was less costly to implement.

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.

Previous evidence on antidepressant medication and cardiovascular disease (CVD) among patients with posttraumatic stress disorder (PTSD) has been inconclusive. We estimated the association between antidepressant medication and CVD by applying a marginal structural model.

We analyzed medical utilization records of 27 170 people with PTSD without prior major cardiovascular events in the Korean National Health Insurance Database (NHID). PTSD and CVD were defined in accordance with the recorded ICD-10 diagnostic codes. We acquired information on antidepressant use from the NHID and categorized them by medication type. A composite major adverse cardiovascular events (MACE) outcome was defined as coronary artery disease with revascularization, ischaemic stroke, and/or haemorrhagic stroke. We used inverse probability of treatment weighting to estimate the parameters of a marginal structural discrete-time survival analysis regression model, comparing the resulting estimates to those derived from traditional time-fixed and time-varying Cox proportional hazards regression. We calculated cumulative daily defined doses to test for a dose–response relationship.

People exposed to antidepressants showed a higher hazard of MACE [hazard ratio (HR) 1.34, 95% confidence interval (CI) 1.18–1.53]. The estimated effects were strongest for selective serotonin reuptake inhibitors (HR 1.24, 95% CI 1.08–1.44) and TCAs (HR 1.33, 95% CI 1.13–1.56). Exposure to serotonin-norepinephrine reuptake inhibitors did not appear to increase the risk of MACE. People exposed to higher doses of antidepressants showed higher risk of MACE.

In a national cohort of people with PTSD, exposure to antidepressant medications increased the risk of MACE in a dose–response fashion.

The COVID-19 pandemic has significantly impacted mental health services, with the literature reporting an increase in the incidence of psychiatric admissions.

The aim of this study was to assess the impact of the pandemic on clinical presentations, characteristics of admission and incidents occurring in three acute inpatient mental health facilities in the UK.

This was a retrospective study comparing data from the first and third UK lockdown to the five years prior to the pandemic. Data was acquired from electronic clinical records and addressed two acute psychiatric inpatient wards and one psychiatric intensive care unit. Key outcomes of comparison were clinical presentations, number of admissions, length of hospital stay, number of incidents and characteristics of incidents.

Compared to the previous 5 years, a higher number of incidents characterized by violence and aggression were reported during the first (56.8% vs 44.3%, x2=16.56, df=1, p<0.001) and third lockdown (100.0% vs 86.2%, x2=36.40, df=1, p<0.001). An increase in non-psychotic disorders was observed in the first lockdown (20.0% vs 13.1%, x2=4.76, df=1, p=0.029), whilst increased first episode psychosis (19.7% vs 11.3%, x2=8.1, df=1, p=0.004) and schizophrenia spectrum disorders (74.4% vs 57.2%, x2= 7.6, df=1, p=0.006) were diagnosed during the third lockdown. There were no significant changes in the diagnosis of mood disorders in both lockdowns compared to previously. The median length of inpatient stay significantly reduced during the first lockdown (28 days vs 36 days, x2= 7.66, df=1, p=0.006).

Increased inpatient incidents may be explained by the impact of the pandemic on staffing levels and resources, combined with increased emotional distress amongst patients in the face of uncertainty. The pandemic may have increased substance misuse potentially linked with the increased incidence of first episode psychosis.

S. Bonaccorso: None Declared, O. Ajnakina: None Declared, A. Ricciardi: None Declared, S. Ouabbou: None Declared, J. Wilson: None Declared, C. Theleritis: None Declared, M. Badhan: None Declared, A. Metastasio: None Declared, N. Stewart: None Declared, M. Barczyck: None Declared, F. Johansson: None Declared, T. Tharmaraja: None Declared, F. Schifano Speakers bureau of: Prof. Fabrizio Schifano is a member of the European Medical Agency