Targeting the glutamatergic system is posited as a potentially novel therapeutic strategy for psychotic disorders. While studies in subjects indicate that antipsychotic medication reduces brain glutamatergic measures, they were unable to disambiguate clinical changes from drug effects.

To address this, we investigated the effects of a dopamine D2 receptor partial agonist (aripiprazole) and a dopamine D2 receptor antagonist (amisulpride) on glutamatergic metabolites in the anterior cingulate cortex (ACC), striatum and thalamus in healthy controls.

A double-blind, within-subject, cross-over, placebo-controlled study design with two arms (n = 25 per arm) was conducted. Healthy volunteers received either aripiprazole (up to 10 mg/day) for 7 days or amisulpride (up to 400 mg/day) and a corresponding period of placebo treatment in a pseudo-randomised order. Magnetic resonance spectroscopy (1H-MRS) was used to measure glutamatergic metabolite levels and was carried out at three different time points: baseline, after 1 week of drug and after 1 week of placebo. Values were analysed as a combined measure across the ACC, striatum and thalamus.

Aripiprazole significantly increased glutamate + glutamine (Glx) levels compared with placebo (β = 0.55, 95% CI [0.15, 0.95], P = 0.007). At baseline, the mean Glx level was 8.14 institutional units (s.d. = 2.15); following aripiprazole treatment, the mean Glx level was 8.16 institutional units (s.d. = 2.40) compared with 7.61 institutional units (s.d. = 2.36) for placebo. This effect remained significant after adjusting for plasma parent and active metabolite drug levels. There was an observed increase with amisulpride that did not reach statistical significance.

One week of aripiprazole administration in healthy participants altered brain Glx levels as compared with placebo administration. These findings provide novel insights into the relationship between antipsychotic treatment and brain metabolites in a healthy participant cohort.

Patients with posttraumatic stress disorder (PTSD) exhibit smaller regional brain volumes in commonly reported regions including the amygdala and hippocampus, regions associated with fear and memory processing. In the current study, we have conducted a voxel-based morphometry (VBM) meta-analysis using whole-brain statistical maps with neuroimaging data from the ENIGMA-PGC PTSD working group.

T1-weighted structural neuroimaging scans from 36 cohorts (PTSD n = 1309; controls n = 2198) were processed using a standardized VBM pipeline (ENIGMA-VBM tool). We meta-analyzed the resulting statistical maps for voxel-wise differences in gray matter (GM) and white matter (WM) volumes between PTSD patients and controls, performed subgroup analyses considering the trauma exposure of the controls, and examined associations between regional brain volumes and clinical variables including PTSD (CAPS-4/5, PCL-5) and depression severity (BDI-II, PHQ-9).

PTSD patients exhibited smaller GM volumes across the frontal and temporal lobes, and cerebellum, with the most significant effect in the left cerebellum (Hedges’ g = 0.22, pcorrected = .001), and smaller cerebellar WM volume (peak Hedges’ g = 0.14, pcorrected = .008). We observed similar regional differences when comparing patients to trauma-exposed controls, suggesting these structural abnormalities may be specific to PTSD. Regression analyses revealed PTSD severity was negatively associated with GM volumes within the cerebellum (pcorrected = .003), while depression severity was negatively associated with GM volumes within the cerebellum and superior frontal gyrus in patients (pcorrected = .001).

PTSD patients exhibited widespread, regional differences in brain volumes where greater regional deficits appeared to reflect more severe symptoms. Our findings add to the growing literature implicating the cerebellum in PTSD psychopathology.

Physical health checks in primary care for people with severe mental illness ((SMI) defined as schizophrenia, bipolar disorders and non-organic psychosis) aim to reduce health inequalities. Patients who decline or are deemed unsuitable for screening are removed from the denominator used to calculate incentivisation, termed exception reporting.

To describe the prevalence of, and patient characteristics associated with, exception reporting in patients with SMI.

We identified adult patients with SMI from the UK Clinical Practice Research Datalink (CPRD), registered with a general practice between 2004 and 2018. We calculated the annual prevalence of exception reporting and investigated patient characteristics associated with exception reporting, using logistic regression.

Of 193 850 patients with SMI, 27.7% were exception reported from physical health checks at least once. Exception reporting owing to non-response or declining screening increased over the study period. Patients of Asian or Black ethnicity (Asian: odds ratio 0.72, 95% CI 0.65–0.80; Black: odds ratio 0.86, 95% CI 0.76–0.97; compared with White) and women (odds ratio 0.90, 95% CI 0.88–0.92) had a reduced odds of being exception reported, whereas patients diagnosed with ‘other psychoses’ (odds ratio 1.19, 95% CI 1.15–1.23; compared with bipolar disorder) had increased odds. Younger patients and those diagnosed with schizophrenia were more likely to be exception reported owing to informed dissent.

Exception reporting was common in people with SMI. Interventions are required to improve accessibility and uptake of physical health checks to improve physical health in people with SMI.

Evaluate impact of COVID-19 prevention training with video-based feedback on nursing home (NH) staff safety behaviors.

Public health intervention

Twelve NHs in Orange County, California, 6/2020-4/2022

NHs received direct-to-staff COVID-19 prevention training and weekly feedback reports with video montages about hand hygiene, mask-wearing, and mask/face-touching. One-hour periods of recorded streaming video from common areas (breakroom, hallway, nursing station, entryway) were sampled randomly across days of the week and nursing shifts for safe behavior. Multivariable models assessed the intervention impact.

Video auditing encompassed 182,803 staff opportunities for safe behavior. Hand hygiene errors improved from first (67.0%) to last (35.7%) months of the intervention, decreasing 7.6% per month (OR = 0.92, 95% CI = 0.92–0.93, P < 0.001); masking errors improved from first (10.3 %) to last (6.6%) months of the intervention, decreasing 2.3% per month (OR = 0.98, 95% CI = 0.97–0.99, P < 0.001); face/mask touching improved from first (30.0%) to last (10.6%) months of the intervention, decreasing 2.5% per month (OR = 0.98, 95% CI = 0.97–0.98, P < 0.001). Hand hygiene errors were most common in entryways and on weekends, with similar rates across shifts. Masking errors and face/mask touching errors were most common in breakrooms, with the latter occurring most commonly during the day (7A.M.–3P.M.) shift, with similar rates across weekdays/weekends. Error reductions were seen across camera locations, days of the week, and nursing shifts, suggesting a widespread benefit within participating NHs.

Direct-to-staff training with video-based feedback was temporally associated with improved hand hygiene, masking, and face/mask-touching behaviors among NH staff during the COVID-19 pandemic.

Decentralized research has many advantages; however, little is known about the representativeness of a source population in decentralized studies. We recruited participants aged 18-64 years from four states from June to December 2022 for a prospective cohort study to assess viral epidemiology. Our aim was to determine the association between age, gender, race/ethnicity, rurality, and socioeconomic status (SES) on study participation in a decentralized prospective cohort study.

We consented 9,286 participants from 231,099 (4.0%) adults with the mean age of 45.6 years (±12.0). We used an electronic decentralized approach for recruitment. Consented participants were more likely to be non-Hispanic White, female, older, urban residents, have more health conditions, and possessed higher socioeconomic status (SES) compared to those non-consented.

We observed an interaction between SES and race-ethnicity on the odds of consent (P = 0.006). Specifically, SES did not affect non-Hispanic white participation rates(OR 1.24 95% CI 1.16 – 1.32] for the highest SES quartile compared to those with the lowest SES quartile) as much as it did participants combined across the other races (OR 1.73; 95% CI 1.45 – 2.98])

The relationship between SES and consent rates might be disproportionately greater in historically disadvantaged groups, compared to non-Hispanic White. It suggests that instead of focusing on enrollment of specific minority groups in research, there is value in future research exploring and addressing the diversity of barriers to trials within minority groups. Our study highlights that decentralized studies need to address social determinants of health, especially in under-resourced populations.

Hallucinations are common and distressing symptoms in Parkinson’s disease (PD). Treatment response in clinical trials is measured using validated questionnaires, including the Scale for Assessment of Positive Symptoms-Hallucinations (SAPS-H) and University of Miami PD Hallucinations Questionnaire (UM-PDHQ). The minimum clinically important difference (MCID) has not been determined for either scale. This study aimed to estimate a range of MCIDs for SAPS-H and UM-PDHQ using both consensus-based and statistical approaches.

A Delphi survey was used to seek opinions of researchers, clinicians, and people with lived experience. We defined consensus as agreement ≥75%. Statistical approaches used blinded data from the first 100 PD participants in the Trial for Ondansetron as Parkinson’s Hallucinations Treatment (TOP HAT, NCT04167813). The distribution-based approach defined the MCID as 0.5 of the standard deviation of change in scores from baseline at 12 weeks. The anchor-based approach defined the MCID as the average change in scores corresponding to a 1-point improvement in clinical global impression-severity scale (CGI-S).

Fifty-one researchers and clinicians contributed to three rounds of the Delphi survey and reached consensus that the MCID was 2 points on both scales. Sixteen experts with lived experience reached the same consensus. Distribution-defined MCIDs were 2.6 points for SAPS-H and 1.3 points for UM-PDHQ, whereas anchor-based MCIDs were 2.1 and 1.3 points, respectively.

We used triangulation from multiple methodologies to derive the range of MCID estimates for the two rating scales, which was between 2 and 2.7 points for SAPS-H and 1.3 and 2 points for UM-PDHQ.

Sudden cardiac death is a significant concern among patients with congenital heart disease (CHD). We assessed the risk of remote sudden cardiac death after congenital heart surgery.

Patients undergoing congenital heart surgery before 21 years of age between 1982 and 2003 in the Pediatric Cardiac Care Consortium registry were linked to National Death Index data through 2019. Sudden cardiac death was defined as death associated with a cardiac arrest or ventricular fibrillation diagnosis code. Standardised mortality ratios relative to the general population were calculated using Centers for Disease Control and Prevention data.

Among 30,566 patients discharged after their initial surgery, 2,718 deaths occurred over a median period of 23 years (IQR 19–27). Of 463 (17%) sudden cardiac deaths, the median age was 1.7 years (IQR 0.5–16.5). The mean incidence was 7 per 10,000 person-years (95% CI: 0.64–0.77), ranging from 2.7 for left-to-right shunt lesions to 37 for single-ventricle physiology. Cardiac comorbidities including heart failure (13.6%) and arrhythmias (7.1%) were more frequent among sudden cardiac death patients. Standard mortality ratios for sudden cardiac death were elevated across all CHD types, ranging from 8.0 (95% CI: 6.3–9.6) for left-to-right shunts to 107.7 (95% CI: 88.9–126.5) for single-ventricle physiology.

Sudden cardiac death risk is higher post-congenital heart surgery compared to the general population. Even patients with mild CHD are at risk, highlighting the need for long-term follow-up for all patients. Heart failure and arrhythmia prevalence suggest potential therapeutic targets to reduce sudden cardiac death risk.

Antibiograms monitor antibiotic resistance trends and help guide empiric antibiotic treatment. A statewide pediatric antibiogram can help inform stewardship efforts.

Annual pediatric antibiograms for the five children’s hospitals in Georgia from 2014–2023 were collected. All sites used the Clinical and Laboratory Standards Institute guidelines for antibiogram development. Antibiogram data were combined, and the most common bacteria were included: Staphylococcus aureus, Streptococcus pneumoniae, Enterococcus faecalis, Escherichia coli, Klebsiella pneumoniae, Enterobacter cloacae complex and Pseudomonas aeruginosa. Interhospital differences were compared for methicillin-susceptible S. aureus (MSSA), methicillin-resistant S. aureus (MRSA), E. coli and K. pneumoniae. The combined data from 2014 and 2023 were compared to demonstrate antibiotic susceptibility changes over time.

Data in 2023 for MSSA and MRSA showed clindamycin susceptibility was 78% and 82%, respectively. S. pneumoniae susceptibility to amoxicillin/clavulanate was 96%. E. faecalis resistance to ampicillin and vancomycin was rare. For all included gram-negative bacteria, susceptibility remained high to 3rd generation cephalosporins (90%–92%) and meropenem (95%–99%). From 2014 to 2023, the rate of MRSA decreased from 49% to 33.5%. S. pneumoniae susceptibility to amoxicillin/clavulanate and clindamycin significantly increased. For E. coli, there was a significant decrease in susceptibility for cefazolin (90% to 84%), ceftriaxone (95% to 92%), and meropenem (100% to 99%). There were nonsignificant decreases in susceptibility for K. pneumoniae.

Over the past 10 years, MRSA rates decreased, S. pneumoniae antibiotic susceptibility increased, and gram-negative bacilli susceptibility was stable to slightly decreased. Georgia antibiogram data support the recommended antibiotic treatment for common pediatric infections.

Machine learning (ML) has developed classifiers differentiating patient groups despite concerns regarding diagnostic reliability. An alternative strategy, used here, is to develop a functional classifier (hyperplane) (e.g. distinguishing the neural responses to received reward v. received punishment in typically developing (TD) adolescents) and then determine the functional integrity of the response (reward response distance from the hyperplane) in adolescents with externalizing and internalizing conditions and its associations with symptom clusters.

Two hundred and ninety nine adolescents (mean age = 15.07 ± 2.30 years, 117 females) were divided into three groups: a training sample of TD adolescents where the Support Vector Machine (SVM) algorithm was applied (N = 65; 32 females), and two test groups– an independent sample of TD adolescents (N = 39; 14 females) and adolescents with a psychiatric diagnosis (major depressive disorder (MDD), generalized anxiety disorder (GAD), attention deficit hyperactivity disorder (ADHD) & conduct disorder (CD); N = 195, 71 females).

SVM ML analysis identified a hyperplane with accuracy = 80.77%, sensitivity = 78.38% and specificity = 88.99% that implicated feature neural regions associated with reward v. punishment (e.g. nucleus accumbens v. anterior insula cortices). Adolescents with externalizing diagnoses were significantly less likely to show a normative and significantly more likely to show a deficient reward response than the TD samples. Deficient reward response was associated with elevated CD, MDD, and ADHD symptoms.

Distinguishing the response to reward relative to punishment in TD adolescents via ML indicated notable disruptions in this response in patients with CD and ADHD and associations between reward responsiveness and CD, MDD, and ADHD symptom severity.