We developed a clinical care pathway for the detection and management of frailty for older adults living in long-term care (LTC) homes.

We utilized a modified Delphi with residents of LTC homes experiencing frailty, their caregivers, and care providers. The pathway was created using existing literature and input from key LTC experts.

Fifty-two panelists completed round one of the Delphi, and 55.8% of these respondents completed round two. Both rounds had high agreement and ratings. We added six new statements following analysis of round two, and 15 statements were modified/updated to reflect panelist feedback. The final pathway included 28 statements and promotes a resident-centered approach that highlights caregiver involvement and inter-professional teamwork to identify and manage frailty, as well as initiate palliative care earlier.

Implementing this pathway will allow health care providers to adopt screening measures and adapt care to a resident’s frailty severity.

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.

This study assessed compassion satisfaction, compassion fatigue, and burnout in health care providers from public health care institutions in Ecuador during the COVID-19 pandemic.

A cross-sectional survey was conducted in 2022, involving 111 different public health care institutions in 23 provinces in Ecuador, with 2873 participants recruited via convenience sampling. The survey instrument was the revised Stamm’s Professional Quality of Life Scale Version-5 tool, designed to measure self-reported compassion fatigue, work satisfaction, and burnout among providers. Kruskall-Wallis test assessed subscale score differences by gender, professional role, region, and health care facility level. Dunn’s test was then applied to determine whether groups differed from each other.

On average, health care providers from all facilities had a high rate of compassion satisfaction (84.9%). However, the majority presented moderate levels of burnout (57.1%), and moderate levels of secondary traumatic stress (59.6%). Higher burnout levels were observed in the Amazon regions compared to Coastal regions.

Despite high compassion satisfaction, most surveyed health care providers from Ecuador’s public health institutions experienced moderate burnout and secondary traumatic stress, with higher burnout levels in the Amazon region. Ecuador, similarly to other LMICs, requires mental health policy and legislation targeted to the mental health workforce and these needs. More research is needed on burnout factors among health care providers in resource-challenged low- and middle-income countries.

Patients discharged from emergency departments (ED) with antibiotics for common infections often receive unnecessarily prolonged durations, representing a target for transition of care (TOC) antimicrobial stewardship intervention.

This study aimed to evaluate the effectiveness of TOC pharmacists’ review on decreasing the duration of discharge oral antibiotics in patients discharged from the ED at an academic medical center. Pharmacist interventions were guided by an antibiotic duration of therapy guidance focused on respiratory, urinary, and skin infections developed and implemented by the antimicrobial stewardship program. Pharmacist interventions from January 27, 2023, to December 29, 2023, were analyzed to quantify the total number of antibiotic days saved and the percentage of provider acceptance.

The ED TOC pharmacists reviewed a total of 157 oral antibiotic prescriptions. 86.6% percent of the reviews required pharmacist interventions. The most common indications for the discharge antibiotics were urinary tract infections (50.0%) and skin infections (23.4%). The total number of antibiotic days saved was 155 days with the provider acceptance rate of 76.5%. In 21% of cases, providers did not count the antibiotic doses administered in the ED, contributing to unnecessarily prolonged duration. 10.2% of patients re-presented to the ED while 6.4% of patients were hospitalized within 30 days of index ED discharge.

The transitions of care pharmacist-led intervention was successful in optimizing the duration of discharge oral antibiotics in the ED utilizing prospective audit and feedback based on institutional guidance. The ED represents a high-yield setting for TOC-directed antimicrobial stewardship.

To understand caregivers’ perceptions about their children’s mealtime social experiences at school and how they believe these social experiences impact their children’s consumption of meals at school (both meals brought from home and school meals).

Qualitative data were originally collected as part of a larger mixed methods study using an embedded-QUAN dominant research design.

Semi-structured interviews were conducted with United States (U.S.) caregivers over ZoomTM in English and Spanish during the 2021–2022 school year. The interview guide contained 14 questions on caregivers’ perceptions about their children’s experiences with school meals.

Caregivers of students in elementary, middle and high schools in rural, suburban and urban communities in California (n 46) and Maine (n 20) were interviewed. Most (60·6 %) were caregivers of children who were eligible for free or reduced-price meals.

Caregivers reported that an important benefit of eating meals at school is their child’s opportunity to socialise with their peers. Caregivers also stated that their child’s favourite aspect of school lunch is socialising with friends. However, some caregivers reported the cafeteria environment caused their children to feel anxious and not eat. Other caregivers reported that their children sometimes skipped lunch and chose to socialise with friends rather than wait in long lunch lines.

Socialising during school meals is important to both caregivers and students. Policies such as increasing lunch period lengths and holding recess before lunch have been found to promote school meal consumption and could reinforce the positive social aspects of mealtime for students.

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.

Clinical high-risk for psychosis (CHR-P) states exhibit diverse clinical presentations, prompting a shift towards broader outcome assessments beyond psychosis manifestation. To elucidate more uniform clinical profiles and their trajectories, we investigated CHR-P profiles in a community sample.

Participants (N = 829; baseline age: 16–40 years) comprised individuals from a Swiss community sample who were followed up over roughly 3 years. latent class analysis was applied to CHR-P symptom data at baseline and follow-up, and classes were examined for demographic and clinical differences, as well as stability over time.

Similar three-class solutions were yielded for both time points. Class 1 was mainly characterized by subtle, subjectively experienced disturbances in mental processes, including thinking, speech and perception (basic symptoms [BSs]). Class 2 was characterized by subthreshold positive psychotic symptoms (i.e., mild delusions or hallucinations) indicative of an ultra-high risk for psychosis. Class 3, the largest group (comprising over 90% of participants), exhibited the lowest probability of experiencing any psychosis-related symptoms (CHR-P symptoms). Classes 1 and 2 included more participants with functional impairment and psychiatric morbidity. Class 3 participants had a low probability of having functional deficits or mental disorders at both time points, suggesting that Class 3 was the healthiest group and that their mental health and functioning remained stable throughout the study period. While 91% of Baseline Class 3 participants remained in their class over time, most Baseline Classes 1 (74%) and Class 2 (88%) participants moved to Follow-up Class 3.

Despite some temporal fluctuations, CHR-P symptoms within community samples cluster into distinct subgroups, reflecting varying levels of symptom severity and risk profiles. This clustering highlights the largely distinct nature of BSs and attenuated positive symptoms within the community. The association of Classes 1 and 2 with Axis-I disorders and functional deficits emphasizes the clinical significance of CHR-P symptoms. These findings highlight the need for personalized preventive measures targeting specific risk profiles in community-based populations.

The association between cannabis and psychosis is established, but the role of underlying genetics is unclear. We used data from the EU-GEI case-control study and UK Biobank to examine the independent and combined effect of heavy cannabis use and schizophrenia polygenic risk score (PRS) on risk for psychosis.

Genome-wide association study summary statistics from the Psychiatric Genomics Consortium and the Genomic Psychiatry Cohort were used to calculate schizophrenia and cannabis use disorder (CUD) PRS for 1098 participants from the EU-GEI study and 143600 from the UK Biobank. Both datasets had information on cannabis use.

In both samples, schizophrenia PRS and cannabis use independently increased risk of psychosis. Schizophrenia PRS was not associated with patterns of cannabis use in the EU-GEI cases or controls or UK Biobank cases. It was associated with lifetime and daily cannabis use among UK Biobank participants without psychosis, but the effect was substantially reduced when CUD PRS was included in the model. In the EU-GEI sample, regular users of high-potency cannabis had the highest odds of being a case independently of schizophrenia PRS (OR daily use high-potency cannabis adjusted for PRS = 5.09, 95% CI 3.08–8.43, p = 3.21 × 10−10). We found no evidence of interaction between schizophrenia PRS and patterns of cannabis use.

Regular use of high-potency cannabis remains a strong predictor of psychotic disorder independently of schizophrenia PRS, which does not seem to be associated with heavy cannabis use. These are important findings at a time of increasing use and potency of cannabis worldwide.

Clinical trials often struggle to recruit enough participants, with only 10% of eligible patients enrolling. This is concerning for conditions like stroke, where timely decision-making is crucial. Frontline clinicians typically screen patients manually, but this approach can be overwhelming and lead to many eligible patients being overlooked.

To address the problem of efficient and inclusive screening for trials, we developed a matching algorithm using imaging and clinical variables gathered as part of the AcT trial (NCT03889249) to automatically screen patients by matching these variables with the trials’ inclusion and exclusion criteria using rule-based logic. We then used the algorithm to identify patients who could have been enrolled in six trials: EASI-TOC (NCT04261478), CATIS-ICAD (NCT04142125), CONVINCE (NCT02898610), TEMPO-2 (NCT02398656), ESCAPE-MEVO (NCT05151172), and ENDOLOW (NCT04167527). To evaluate our algorithm, we compared our findings to the number of enrollments achieved without using a matching algorithm. The algorithm’s performance was validated by comparing results with ground truth from a manual review of two clinicians. The algorithm’s ability to reduce screening time was assessed by comparing it with the average time used by study clinicians.

The algorithm identified more potentially eligible study candidates than the number of participants enrolled. It also showed over 90% sensitivity and specificity for all trials, and reducing screening time by over 100-fold.

Automated matching algorithms can help clinicians quickly identify eligible patients and reduce resources needed for enrolment. Additionally, the algorithm can be modified for use in other trials and diseases.