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.

Patients with unbalanced common atrioventricular canal can be difficult to manage. Surgical planning often depends on pre-operative echocardiographic measurements. We aimed to determine the added utility of cardiac MRI in predicting successful biventricular repair in common atrioventricular canal.

We conducted a retrospective cohort study of children with common atrioventricular canal who underwent MRI prior to repair. Associations between MRI and echocardiographic measures and surgical outcome were tested using logistic regression, and models were compared using area under the receiver operator characteristic curve.

We included 28 patients (median age at MRI: 5.2 months). The optimal MRI model included the novel end-diastolic volume index (using the ratio of left ventricular end-diastolic volume to total end-diastolic volume) and the left ventricle–right ventricle angle in diastole (area under the curve 0.83, p = 0.041). End-diastolic volume index ≤ 0.18 and left ventricle–right ventricle angle in diastole ≤ 72° yield a sensitivity of 83% and specificity of 81% for successful biventricular repair. The optimal multimodality model included the end-diastolic volume index and the echocardiographic atrioventricular valve index with an area under the curve of 0.87 (p = 0.026).

Cardiac MRI can successfully predict successful biventricular repair in patients with unbalanced common atrioventricular canal utilising the end-diastolic volume index alone or in combination with the MRI left ventricle–right ventricle angle in diastole or the echocardiographic atrioventricular valve index. A prospective cardiac MRI study is warranted to better define the multimodality characteristic predictive of successful biventricular surgery.

Reward processing has been proposed to underpin the atypical social feature of autism spectrum disorder (ASD). However, previous neuroimaging studies have yielded inconsistent results regarding the specificity of atypicalities for social reward processing in ASD.

Utilising a large sample, we aimed to assess reward processing in response to reward type (social, monetary) and reward phase (anticipation, delivery) in ASD.

Functional magnetic resonance imaging during social and monetary reward anticipation and delivery was performed in 212 individuals with ASD (7.6–30.6 years of age) and 181 typically developing participants (7.6–30.8 years of age).

Across social and monetary reward anticipation, whole-brain analyses showed hypoactivation of the right ventral striatum in participants with ASD compared with typically developing participants. Further, region of interest analysis across both reward types yielded ASD-related hypoactivation in both the left and right ventral striatum. Across delivery of social and monetary reward, hyperactivation of the ventral striatum in individuals with ASD did not survive correction for multiple comparisons. Dimensional analyses of autism and attention-deficit hyperactivity disorder (ADHD) scores were not significant. In categorical analyses, post hoc comparisons showed that ASD effects were most pronounced in participants with ASD without co-occurring ADHD.

Our results do not support current theories linking atypical social interaction in ASD to specific alterations in social reward processing. Instead, they point towards a generalised hypoactivity of ventral striatum in ASD during anticipation of both social and monetary rewards. We suggest this indicates attenuated reward seeking in ASD independent of social content and that elevated ADHD symptoms may attenuate altered reward seeking in ASD.

To evaluate the construct validity of the NIH Toolbox Cognitive Battery (NIH TB-CB) in the healthy oldest-old (85+ years old).

Our sample from the McKnight Brain Aging Registry consists of 179 individuals, 85 to 99 years of age, screened for memory, neurological, and psychiatric disorders. Using previous research methods on a sample of 85 + y/o adults, we conducted confirmatory factor analyses on models of NIH TB-CB and same domain standard neuropsychological measures. We hypothesized the five-factor model (Reading, Vocabulary, Memory, Working Memory, and Executive/Speed) would have the best fit, consistent with younger populations. We assessed confirmatory and discriminant validity. We also evaluated demographic and computer use predictors of NIH TB-CB composite scores.

Findings suggest the six-factor model (Vocabulary, Reading, Memory, Working Memory, Executive, and Speed) had a better fit than alternative models. NIH TB-CB tests had good convergent and discriminant validity, though tests in the executive functioning domain had high inter-correlations with other cognitive domains. Computer use was strongly associated with higher NIH TB-CB overall and fluid cognition composite scores.

The NIH TB-CB is a valid assessment for the oldest-old samples, with relatively weak validity in the domain of executive functioning. Computer use’s impact on composite scores could be due to the executive demands of learning to use a tablet. Strong relationships of executive function with other cognitive domains could be due to cognitive dedifferentiation. Overall, the NIH TB-CB could be useful for testing cognition in the oldest-old and the impact of aging on cognition in older populations.

Cognitive therapy and behavioural activation are both widely applied and effective psychotherapies for depression, but it is unclear which works best for whom. Individual participant data (IPD) meta-analysis allows for examining moderators at the participant level and can provide more precise effect estimates than conventional meta-analysis, which is based on study-level data.

This article describes the protocol for a systematic review and IPD meta-analysis that aims to compare the efficacy of cognitive therapy and behavioural activation for adults with depression, and to explore moderators of treatment effect. (PROSPERO: CRD42022341602)

Systematic literature searches will be conducted in PubMed, PsycINFO, EMBASE and the Cochrane Library, to identify randomised clinical trials comparing cognitive therapy and behavioural activation for adult acute-phase depression. Investigators of these trials will be invited to share their participant-level data. One-stage IPD meta-analyses will be conducted with mixed-effects models to assess treatment effects and to examine various available demographic, clinical and psychological participant characteristics as potential moderators. The primary outcome measure will be depressive symptom level at treatment completion. Secondary outcomes will include post-treatment anxiety, interpersonal functioning and quality of life, as well as follow-up outcomes.

To the best of our knowledge, this will be the first IPD meta-analysis concerning cognitive therapy versus behavioural activation for adult depression. This study has the potential to enhance our knowledge of depression treatment by using state-of-the-art statistical techniques to compare the efficacy of two widely used psychotherapies, and by shedding more light on which of these treatments might work best for whom.

Autism and autistic traits are risk factors for suicidal behaviour.

To explore the prevalence of autism (diagnosed and undiagnosed) in those who died by suicide, and identify risk factors for suicide in this group.

Stage 1: 372 coroners’ inquest records, covering the period 1 January 2014 to 31 December 2017 from two regions of England, were analysed for evidence that the person who died had diagnosed autism or undiagnosed possible autism (elevated autistic traits), and identified risk markers. Stage 2: 29 follow-up interviews with the next of kin of those who died gathered further evidence of autism and autistic traits using validated autism screening and diagnostic tools.

Stage 1: evidence of autism (10.8%) was significantly higher in those who died by suicide than the 1.1% prevalence expected in the UK general alive population (odds ratio (OR) = 11.08, 95% CI 3.92–31.31). Stage 2: 5 (17.2%) of the follow-up sample had evidence of autism identified from the coroners’ records in stage 1. We identified evidence of undiagnosed possible autism in an additional 7 (24.1%) individuals, giving a total of 12 (41.4%); significantly higher than expected in the general alive population (1.1%) (OR = 19.76, 95% CI 2.36–165.84). Characteristics of those who died were largely similar regardless of evidence of autism, with groups experiencing a comparably high number of multiple risk markers before they died.

Elevated autistic traits are significantly over-represented in those who die by suicide.

Food insecurity is associated with numerous adverse health outcomes. The US Veterans Health Administration (VHA) began universal food insecurity screening in 2017. This study examined prevalence and correlates of food insecurity among Veterans screened.

Retrospective cross-sectional study using VHA administrative data. Multivariable logistic regression models were estimated to identify sociodemographic and medical characteristics associated with a positive food insecurity screen.

All US Veterans Administration (VA) medical centres (n 161).

All Veterans were screened for food insecurity since screening initiation (July 2017–December 2018).

Of 3 304 702 Veterans screened for food insecurity, 44 298 were positive on their initial screen (1·3 % of men; 2·0 % of women). Food insecurity was associated with identifying as non-Hispanic Black or Hispanic. Veterans who were non-married/partnered, low-income Veterans without VA disability-related compensation and those with housing instability had higher odds of food insecurity, as did Veterans with a BMI < 18·5, diabetes, depression and post-traumatic stress disorder. Prior military sexual trauma (MST) was associated with food insecurity among both men and women. Women screening positive, however, were eight times more likely than men to have experienced MST (48·9 % v. 5·9 %).

Food insecurity was associated with medical and trauma-related comorbidities as well as unmet social needs including housing instability. Additionally, Veterans of colour and women were at higher risk for food insecurity. Findings can inform development of tailored interventions to address food insecurity such as more frequent screening among high-risk populations, onsite support applying for federal food assistance programs and formal partnerships with community-based resources.

Coronavirus disease 2019 (COVID-19) vaccination effectiveness in healthcare personnel (HCP) has been established. However, questions remain regarding its performance in high-risk healthcare occupations and work locations. We describe the effect of a COVID-19 HCP vaccination campaign on SARS-CoV-2 infection by timing of vaccination, job type, and work location.

We conducted a retrospective review of COVID-19 vaccination acceptance, incidence of postvaccination COVID-19, hospitalization, and mortality among 16,156 faculty, students, and staff at a large academic medical center. Data were collected 8 weeks prior to the start of phase 1a vaccination of frontline employees and ended 11 weeks after campaign onset.

The COVID-19 incidence rate among HCP at our institution decreased from 3.2% during the 8 weeks prior to the start of vaccinations to 0.38% by 4 weeks after campaign initiation. COVID-19 risk was reduced among individuals who received a single vaccination (hazard ratio [HR], 0.52; 95% confidence interval [CI], 0.40–0.68; P < .0001) and was further reduced with 2 doses of vaccine (HR, 0.17; 95% CI, 0.09–0.32; P < .0001). By 2 weeks after the second dose, the observed case positivity rate was 0.04%. Among phase 1a HCP, we observed a lower risk of COVID-19 among physicians and a trend toward higher risk for respiratory therapists independent of vaccination status. Rates of infection were similar in a subgroup of nurses when examined by work location.

Our findings show the real-world effectiveness of COVID-19 vaccination in HCP. Despite these encouraging results, unvaccinated HCP remain at an elevated risk of infection, highlighting the need for targeted outreach to combat vaccine hesitancy.

The objectives of this study were (1) to develop and validate a simulation model to estimate daily probabilities of healthcare-associated infections (HAIs), length of stay (LOS), and mortality using time varying patient- and unit-level factors including staffing adequacy and (2) to examine whether HAI incidence varies with staffing adequacy.

The study was conducted at 2 tertiary- and quaternary-care hospitals, a pediatric acute care hospital, and a community hospital within a single New York City healthcare network.

All patients discharged from 2012 through 2016 (N = 562,435).

We developed a non-Markovian simulation to estimate daily conditional probabilities of bloodstream, urinary tract, surgical site, and Clostridioides difficile infection, pneumonia, length of stay, and mortality. Staffing adequacy was modeled based on total nurse staffing (care supply) and the Nursing Intensity of Care Index (care demand). We compared model performance with logistic regression, and we generated case studies to illustrate daily changes in infection risk. We also described infection incidence by unit-level staffing and patient care demand on the day of infection.

Most model estimates fell within 95% confidence intervals of actual outcomes. The predictive power of the simulation model exceeded that of logistic regression (area under the curve [AUC], 0.852 and 0.816, respectively). HAI incidence was greatest when staffing was lowest and nursing care intensity was highest.

This model has potential clinical utility for identifying modifiable conditions in real time, such as low staffing coupled with high care demand.