Transcranial direct current stimulation (tDCS) shows promise for treating depression, but heterogeneous findings from randomised controlled trials (RCTs) – likely due to patient characteristics and methodological differences – limit clear conclusions about its efficacy.

This individual patient data meta-analysis (IPD-MA) aims to evaluate the efficacy of tDCS for depression and explore moderators of clinical depression improvement.

Databases (PubMed, Embase, Web of Science, Cochrane Library) were searched up to 1 February 2025 for RCTs comparing active versus sham tDCS in acute depressive episodes. The outcomes were Hedges’ g for continuous measures of depressive symptoms, odds ratio for response and remission rates and analyses of individual/methodological moderators of clinical improvement. Acceptability was assessed via dropout rates. Heterogeneity was quantified using the I² statistic. Publication and risk of bias were evaluated with Egger’s test and Cochrane Risk of Bias Tool, respectively.

Of 29 eligible RCTs, 18 data-sets provided IPD, totalling 1246 included in the IPD-MA (651 active, 595 sham; mean age 43.2, 63.4% female). Most studies (90%) had low risk of bias. Active tDCS showed small but statistically significant effects on depression improvement (Hedges’ d = 0.24, 95% CI = 0.11–0.35) and response rates (odds ratio 1.33, 95% CI = 1.04–1.72), with low-to-moderate heterogeneity. No significant difference in remission rates (odds ratio 1.30, 95% CI = 0.98–1.74) and dropout rates (12.7% active, 11.3% sham) were observed between groups. Only sample size significantly moderated clinical improvement, with larger trials showing smaller between-group differences.

In this IPD data-set, tDCS showed modest efficacy for depression. Future research should clarify its mechanisms, considering non-specific placebo effects.

Artificial intelligence (AI) has the potential to enhance clinical decision-making, including in infectious diseases. By improving antimicrobial resistance prediction and optimizing antibiotic prescriptions, these technologies may support treatment strategies and address critical gaps in healthcare. This study evaluates the effectiveness of AI in guiding appropriate antibiotic prescriptions for infectious diseases through a systematic literature review.

We conducted a systematic review of studies evaluating AI (machine learning or large language models) used for guidance on prescribing appropriate antibiotics in infectious disease cases. Searches were performed in PubMed, CINAHL, Embase, Scopus, Web of Science, and Google Scholar for articles published up to October 25, 2024. Inclusion criteria focused on studies assessing the performance of AI in clinical practice, with outcomes related to antimicrobial management and decision-making.

Seventeen studies used machine learning as part of clinical decision support systems (CDSS). They improved prediction of antimicrobial resistance and optimized antimicrobial use. Six studies focused on large language models to guide antimicrobial therapy; they had higher prescribing error rates, patient safety risks, and needed precise prompts to ensure accurate responses.

AI, particularly machine learning integrated into CDSS, holds promise in enhancing clinical decision-making and improving antimicrobial management. However, large language models currently lack the reliability required for complex clinical applications. The indispensable role of infectious disease specialists remains critical for ensuring accurate, personalized, and safe treatment strategies. Rigorous validation and regular updates are essential before the successful integration of AI into clinical practice.

The amygdala is a subcortical limbic structure consisting of histologically and functionally distinct subregions. New automated structural magnetic resonance imaging (MRI) segmentation tools facilitate the in vivo study of individual amygdala nuclei in clinical populations such as patients with anorexia nervosa (AN) who show symptoms indicative of limbic dysregulation. This study is the first to investigate amygdala nuclei volumes in AN, their relationships with leptin, a key indicator of AN-related neuroendocrine alterations, and further clinical measures.

T1-weighted MRI scans were subsegmented and multi-stage quality controlled using FreeSurfer. Left/right hemispheric amygdala nuclei volumes were cross-sectionally compared between females with AN (n = 168, 12–29 years) and age-matched healthy females (n = 168) applying general linear models. Associations with plasma leptin, body mass index (BMI), illness duration, and psychiatric symptoms were analyzed via robust linear regression.

Globally, most amygdala nuclei volumes in both hemispheres were reduced in AN v. healthy control participants. Importantly, four specific nuclei (accessory basal, cortical, medial nuclei, corticoamygdaloid transition in the rostral-medial amygdala) showed greater volumetric reduction even relative to reductions of whole amygdala and total subcortical gray matter volumes, whereas basal, lateral, and paralaminar nuclei were less reduced. All rostral-medially clustered nuclei were positively associated with leptin in AN independent of BMI. Amygdala nuclei volumes were not associated with illness duration or psychiatric symptom severity in AN.

In AN, amygdala nuclei are altered to different degrees. Severe volume loss in rostral-medially clustered nuclei, collectively involved in olfactory/food-related reward processing, may represent a structural correlate of AN-related symptoms. Hypoleptinemia might be linked to rostral-medial amygdala alterations.

Patients admitted to the hospital may unknowingly carry severe acute respiratory coronavirus virus 2 (SARS-CoV-2), and hospitals have implemented SARS-CoV-2 admission screening. However, because SARS-CoV-2 reverse-transcription polymerase chain reaction (RT-PCR) assays may remain positive for months after infection, positive results may represent active or past infection. We determined the prevalence and infectiousness of patients who were admitted for reasons unrelated to COVID-19 but tested positive for SARS-CoV-2 on admission screening.

We conducted an observational study at the University of Iowa Hospitals & Clinics from July 7 to October 25, 2020. All patients admitted without suspicion of COVID-19 were included, and medical records of those with a positive admission screening test were reviewed. Infectiousness was determined using patient history, PCR cycle threshold (Ct) value, and serology.

In total, 5,913 patients were screened and admitted for reasons unrelated to COVID-19. Of these, 101 had positive admission RT-PCR results; 36 of these patients were excluded because they had respiratory signs/symptoms on admission on chart review. Also, 65 patients (1.1%) did not have respiratory symptoms. Finally, 55 patients had Ct values available and were included in this analysis. The median age of the final cohort was 56 years and 51% were male. Our assessment revealed that 23 patients (42%) were likely infectious. The median duration of in-hospital isolation was 5 days for those likely infectious and 2 days for those deemed noninfectious.

SARS-CoV-2 was infrequent among patients admitted for reasons unrelated to COVID-19. An assessment of the likelihood of infectiousness using clinical history, RT-PCR Ct values, and serology may help in making the determination to discontinue isolation and conserve resources.

The First Episode Rapid Early Intervention for Eating Disorders (FREED) service model is associated with significant reductions in wait times and improved clinical outcomes for emerging adults with recent-onset eating disorders. An understanding of how FREED is implemented is a necessary precondition to enable an attribution of these findings to key components of the model, namely the wait-time targets and care package.

This study evaluated fidelity to the FREED service model during the multicentre FREED-Up study.

Participants were 259 emerging adults (aged 16–25 years) with an eating disorder of <3 years duration, offered treatment through the FREED care pathway. Patient journey records documented patient care from screening to end of treatment. Adherence to wait-time targets (engagement call within 48 h, assessment within 2 weeks, treatment within 4 weeks) and care package, and differences in adherence across diagnosis and treatment group were examined.

There were significant increases (16–40%) in adherence to the wait-time targets following the introduction of FREED, irrespective of diagnosis. Receiving FREED under optimal conditions also increased adherence to the targets. Care package use differed by component and diagnosis. The most used care package activities were psychoeducation and dietary change. Attention to transitions was less well used.

This study provides an indication of adherence levels to key components of the FREED model. These adherence rates can tentatively be considered as clinically meaningful thresholds. Results highlight aspects of the model and its implementation that warrant future examination.

(i) To examine demographic and health characteristics of women of reproductive age on a vegan diet in Australia and compare these to the general population; (ii) to identify sources and intake of vitamin B12 and compare intake to current recommendations and (iii) examine associations between participant characteristics and adequacy of vitamin B12 intake.

In this cross-sectional study, data were collected via an online survey. Demographic and health characteristics of women on a vegan diet were compared with women in the general population (using Australian Bureau of Statistics data). Intake of vitamin B12 was estimated using a FFQ and estimation of supplemental intake.

Australia.

Participants (n 1530) were women aged 18–44 years who had been on a vegan diet for at least 6 months.

While BMI, smoking habits and intakes of fruit and vegetables compared favourably with the general population, 26 % of respondents had estimated intakes of vitamin B12 below recommendations. Analyses of relationships between vitamin B12 intake and participant characteristics revealed that the strongest predictor of intake was supplementation (P < 0·001); however, 25 % had not supplemented with vitamin B12 in the past 3 months.

The vitamin B12 intakes of a substantial proportion of Australian women of reproductive age consuming a vegan diet do not meet the recommended intake, which could adversely affect their health, and, if they are pregnant or lactating, that of their infants too. There is a need for further research in this area to identify effective strategies to address this situation.

Little is known about the everyday experiences of individuals transitioning from acute to outpatient psychiatric care, an important period of risk for mood symptom relapse. This study used ecological momentary assessment (EMA) to examine whether specific daily experiences were related to momentary affective states following discharge from a partial hospitalization program (PHP).

A sample of 114 adults (Mage = 36 years old, 52% female, 83% White) completed four brief EMA surveys every day for 2 weeks assessing intensity/type of stressful events and social contact, as well as positive/negative affect (PA/NA). Half of participants reported therapeutic skills use.

Stress severity ratings prospectively predicted increased NA. NA predicted spending less time with close relationships. However, interacting with close relationships predicted increased positive affect (PA). Finally, PA predicted spending time with more people. The use of two skills (behavioral activation and interpersonal effectiveness) was concurrently, but not prospectively, associated with improved affect.

Examining daily experiences of individuals discharging from partial hospitalization provides important information about factors that may influence affective states during the transition from acute to outpatient care. Findings from this study can be used to help prepare patients for discharge and develop interventions for the post-acute period.