Non-ventilator hospital-acquired pneumonia (NV-HAP) is common and deadly. Guidelines recommend improving oral care and mobility performance to prevent NV-HAP but data on their impact are limited. We therefore evaluated associations between oral care and mobility performance with NV-HAP and mortality rates in a large hospital network.

Retrospective cohort study

144 acute care hospitals

Adults hospitalized for ≥4 days between May 2021 and July 2023

We extracted daily data on oral care performance (yes, no) and patient mobility (bed-bound, upright, walking) and used time-varying Cox proportional hazards models to evaluate associations between oral care and mobility performance with NV-HAP and in-hospital mortality risk, adjusting for patients’ demographics, comorbidities, hospital service, daily vital signs, and daily laboratory measures.

Among 1,744,811 hospitalizations (9.6 million hospital-days), median patient age was 68 (IQR 55–78) and 50.6% were female. Persistent oral care for ≥3 days was associated with 16% less NV-HAP (hazard ratio (HR) 0.84; 95% CI: 0.82–0.86) and 6% lower mortality (HR 0.94; 95% CI: 0.92–0.96), with stronger effects in the ICU than outside the ICU. Persistent walking for ≥3 days was associated with 18% less NV-HAP (HR 0.82; 95% CI: 0.79–0.85) and 80% lower hospital-mortality (HR 0.20; 95% CI: 0.19–0.21), with stronger effects outside the ICU than in the ICU.

In a large hospital network, both oral care and mobility were associated with lower risk of NV-HAP and hospital mortality, with differential effects inside and outside of the ICU. Prospective trials are needed to confirm these potential benefits.

Although current prescribing guidelines suggest continuation of psychotropic drugs in pregnant women, population-based evidence supporting their safety is limited.

This study aims to clarify the plausible causal links between maternal psychotropic drug exposures and obstetric complications.

This cohort study investigated all births by Hong Kong residents ≥18 years of age in public hospitals between 2004 and 2022. Birth episodes were classified according to whether they were unexposed to psychotropic drugs, exposed but discontinued before conception or exposed during pregnancy. Firth’s penalised logistic regression was employed in all analysis, and negative control analysis was conducted to assess causality. False discovery rate correction and sensitivity analyses were performed.

Among 587 419 births, 7182 episodes involved psychotropic prescriptions (antipsychotics, antidepressants, anticonvulsants, benzodiazepines) during pregnancy. In broad drug class analysis, all significant associations observed in the exposed group were also observed in negative control analysis (psychotropics discontinued before conception), suggesting that elevated risks could be attributed to unmeasured confounders. Nevertheless, in subclass analyses, certain psychotropic drugs showed increased risks of obstetric complications, i.e. significant associations between atypical antipsychotics and genito-urinary infection (odds ratio 2.70, 95% CI 1.46–4.83), and between valproate and low birth weight (odds ratio 1.68, 95% CI 1.16–2.37). These associations became non-significant in negative control analysis, and the high E-values (atypical antipsychotics and genito-urinary infection, 4.84; valproate and low birth weight, 2.75) suggested that the results were unlikely to have been driven by unmeasured confounders. Maternal diagnoses of schizophrenia and depression were independently associated with increased risk of obstetric complications, after controlling for the effects of psychotropics.

The population-based data and meticulous analyses did not support any clear causal link between broad-class psychotropic exposure during pregnancy and increased risk of obstetric/neonatal complications. However, some psychotropic subclasses may increase obstetric/neonatal complications. The limited number of episodes involving discontinuation of some psychotropic subclasses may have resulted in false negative findings in the negative control analysis.

Mental disorder may affect individual’s ability to operate the motor vehicle. Previous studies have found that patient’s negative emotions may trigger aggressive driving behaviors. Thus, efficiently evaluating the correlation between emotions and driving behaviors in individuals with mental disorders has been drawn emphasis.

To explore the related factors of fitness-to-drive of individuals with mental disorders, to determine the application value of traffic psychology scales in assessment for fitness-to-drive of individuals with mental disorders, and to help establish consummate and effective assessment systems.

One hundred individuals with mental disorders were enrolled as the patient group, and 100 healthy individuals were enrolled as the control group. Positive and Negative Syndrome Scale (PANSS) was used to assess the psychiatric symptoms of the patient group. Driver Profile of Mood States (DPOMS), Driver Anger Scale (DAS), and Driving Behavior Scale (DBS) were used to evaluate the performance during driving within two groups. T-test were used to compare the differences in each factor score of traffic psychology scales within two groups. Pearson’s correlation analysis was used to calculate the correlation between scores of PANSS and scores of traffic psychology scales of the patient group.

The patient group had significantly higher score of driving function deficit in DBS than the control group (t=2.48, P<0.05), but scores of hostile gestures, impolite driving, overly cautious behaviors in DBS and total score of DAS showed the opposite (P<0.05). Positive syndrome in PANSS was positively related to traffic congestion in DAS (r = 0.315, P < 0.05). Anger in DPOMS was positively related to driving function deficit (r = 0.488, P < 0.01) and hostile behaviors in DBS (r = 0.510, P < 0.01), whereas it was negatively related to overly cautious behaviors in DBS (r = -0.417, P < 0.05). Anxiety and depression were also related to some factors in DAS and DBS.

The study found the practical application value of DPOMS, DAS, and DBS in assessment for fitness-to-drive of individuals with mental disorders. Patient’s anger in specific traffic situations such as traffic congestion may be mainly related to their positive syndrome. Patient’s anger may be a trigger of aggressive driving behaviors, and other emotions such as anxiety and depression also play important roles. Patient’s aggressive driving behaviors may be attributed to the compounding of many negative emotions.

S. Wang: None Declared, X. Ling: None Declared, Q. Zhang: None Declared, H. Li Grant / Research support from: This study was supported by National Key R & D Program of China [grant number 2022YFC3302001], National Natural Science Foundation of China [grant number 81801881], Science and Technology Committee of Shanghai Municipality [grant numbers 20DZ1200300, 21DZ2270800, 19DZ2292700].

Patients with mental disorders often engage in extreme and unpredictable violent behaviors that seriously endanger the public security and stability of the society. Violence risk is commonly assessed by subjective judgement, which may lead to bias and uncertainty in the appraisal results. Existing expression recognition and analysis techniques have limitations in identifying the emotional states of patients with mental disorders.

The study aimed to explore the association between violent behaviors and facial expression in patients with mental disorders by machine learning algorithm, to evaluate the application value of facial expression analysis system in violence risk assessment of individuals with mental disorders.

Thirty-nine patients with mental disorders were enrolled and assessed by using Modified Overt Aggression Scale (MOAS), positive and negative syndrome scale (PANSS) and brief psychiatric rating scale (BPRS). An emotional arousal paradigm was performed and the intensity of baisc emotions and expression action units was recorded before, during and after the paradigm. The processed quantitative data was used to generate one-dimensional waveform maps and two-dimensional time-frequency maps and then quantized feature data were extracted. A machine learning model with high accuracy was trained using these feature data, which can accurately determine the violence risk states of patients and output the probability. All individuals participated voluntarily and provided informed consent. This study was approved by the ethics committee of the Academy of Forensic Science.

The intensity difference of sadness, surprise and fear in different time periods was statistically significant. The intensity of the left medial eyebrow lift action unit was found significantly different before and after the emotional arousal. The intensity of anger and disgust was positively correlated with the MOAS scores, PANSS scores and BPRS scores. The features of time-frequency diagrams of 5 expression action units (medial eyebrow raise, eyebrow lowering, slightly open lips, chin drop and eye closure) and 8 basic emotions were selected and then support vector machine was used for triple classification, which is a classifier that can well distinguish the three stages of non-violence risk period, violence risk period, and post-violence risk period. In the 4:1 training-testing grouping, the classification accuracy reaches 91.2%.

Featured expressive action units and various baisc emotions might be used to capture information associated with violent behaviors. The facial expression analysis system mentioned above can be used as an auxiliary tool to assess the potential risk of violence in patients with mental disorders.

X. Ling: None Declared, S. Wang: None Declared, X. Zhou: None Declared, N. Li: None Declared, W. Cai: None Declared, H. Li Grant / Research support from: This study was supported by National Key R & D Program of China [grant number 2022YFC3302001], National Natural Science Foundation of China [grant number 81801881], Science and Technology Committee of Shanghai Municipality [grant numbers 20DZ1200300, 21DZ2270800, 19DZ2292700].

Violence is a major global health concern among patients with schizophrenia. However, the triggers of violent behavior remain unclear. In previous studies, familial risk factors are believed to be associated with mental disorders and violence. The relationship between parental bonding or childhood adversity and psychopathologic behavior (such as violence) has rarely been evaluated.

The study aimed to explore the relationship between violent behavior and childhood experience and to determine the role of the early child-parent bond in violence risk in patients with schizophrenia.

The study enrolled 287 patients with schizophrenia and 100 healthy controls. Patients were divided into 3 groups: patients with homicidal history (Group A), patients with violent behavior and without homicidal history (Group B) and patients without violent behavior (Group C). Childhood trauma questionnaire (CTQ), parental bonding instrument (PBI) and modified overt aggression scale (MOAS) were used to explore the violent behavior and childhood experience. All individuals participated voluntarily and provided informed consent. This study was approved by the ethics committee of the Academy of Forensic Science.

The findings indicated the proportion of males to be higher in the patient groups than in the healthy controls, especially in the group with homicidal history. Patients had a significantly higher prevalence of sexual abuse, emotional abuse and emotional neglect than the healthy controls. The emotional abuse and emotional neglect were found to be positively and negatively related to MOAS scores. Maternal over protection was found to be negatively related to the MOAS scores. On the CTQ subscales, emotional neglect was significantly associated with violence risk (OR=1.13, 95% CI=1.04–1.22). On the PBI subscales, maternal and paternal care (0.84, 0.74–0.94 and 1.30, 1.13–1.49) and over protection (1.18, 1.07–1.29 and 0.87, 0.81-0.95) were found to be significantly associated with violence risk. Maternal and paternal over protection were significantly associated with homicide risk (0.87, 0.78-0.97 and 1.10, 1.01-1.20).

The schizophrenia patients with violence might suffer lower paternal care and emotional abuse during the childhood. In terms of violence in schizophrenia patients, paternal over protection and maternal care might be a protective factor and emotional neglect, maternal over protection and paternal care might be a risk factor. In terms of homicide in schizophrenia patients, paternal over protection might be a risk factor and maternal over protection might be a protective factor. Therefore, childhood trauma and parental care and over protection could be a potential reference indicator for assessing violence risk in patients with schizophrenia.

X. Ling: None Declared, S. Wang: None Declared, N. Li: None Declared, Q. Zhang: None Declared, H. Li Grant / Research support from: This study was supported by National Key R & D Program of China [grant number 2022YFC3302001], National Natural Science Foundation of China [grant number 81801881], Science and Technology Committee of Shanghai Municipality [grant numbers 20DZ1200300, 21DZ2270800, 19DZ2292700].

People with psychotic-like experiences (PLE) have slow movements and uncontrolled movements, which are indicative of transition to psychotic disorders afterwards. Earlier research has reported that rhythmic auditory stimulation (RAS) is a promising therapeutic technique for movement abnormalities in people in the psychosis continuum. However, the small sample size was a major limitation in earlier research and restricted result generalizability.

This study was to increase the sample size and examine if faster RAS induced faster movements and less uncontrolled movements at both hands in people with PLE.

A total of 55 right-handed people with PLE (age: 20.51±2.50 years; 28 females) and 55 age- and gender-matched right-handed healthy controls (age: 20.53±3.10 years; 24 females) were recruited. Participants used the index finger to perform the alternate touching task for each hand when the motion capture system recorded the movement procedure. They were required to follow each beat of RAS with the normal tempo (100% of the fastest movement tempo without RAS) and the fast tempo (110% of the fastest movement tempo), the order of which was counterbalanced, when performing the alternate touching task. Kinematic variables were calculated to reflect severity of slow movements and uncontrolled movements in participants.

Two-way analysis of variance showed no interaction between groups and RAS in right-hand and left-hand kinematic values. People with PLE had slow movements at both hands and uncontrolled movements at the right hand. Faster RAS induced faster movements and less uncontrolled movements at both hands in people with PLE.

The major contribution of this study was to use a relatively large sample size to demonstrate effectiveness of faster RAS on inducing faster movements and less uncontrolled movements at both hands in people with PLE and thus increase result generalizability. Given that movement abnormalities are initial signs in the psychosis continuum and risk factors of transition to psychotic disorders, when healthcare practitioners design early intervention for movement problems in people with PLE, incorporating RAS in therapy is suggested.

None Declared

Background: Lifestyle factors are linked to differences in brain aging and risk for Alzheimer’s disease, underscored by concepts like ‘cognitive reserve’ and ‘brain maintenance’. The Resilience Index (RI), a composite of 6 factors (cognitive reserve, physical and cognitive activities, social engagement, diet, and mindfulness) provides such a holistic measure.

This study aims to examine the association of RI scores with cognitive function and assess the mediating role of cortical atrophy.

Baseline data from 113 participants (aged 45+, 68% female) from the Healthy Brain Initiative were included. Life course resilience was estimated with the RI, cognitive performance with Cognivue®, and brain health using a machine learning derived Cortical Atrophy Score (CAS). Mediation analysis probed the relationship between RI, cognitive outcomes, and cortical atrophy.

In age and sex adjusted models, the RI was significantly associated with CAS (β= -0.25, p = 0.006) and Cognivue® scores (β= 0.32, p < 0.001). The RI-Cognivue® association was partially mediated by CAS (β= 0.07; 95% CI [0.02, 0.14]).

Findings revealed that the collective effect of early and late-life lifestyle resilience factors on cognition are partially explained by their association with less brain atrophy. These findings underscore the value of comprehensive lifestyle assessments in understanding the risk and progression of cognitive decline and Alzheimer’s disease in an aging population.

R. Ezzeddine: None Declared, D. Oshea: None Declared, S. Camacho: None Declared, L. Besser: None Declared, M. Tolea: None Declared, J. Galvin Employee of: Cognivue (Chief Scientific Officer of Cognivue). Cognivue devices are used for research conducted at the center., C. Galvin: None Declared, L. Wang: None Declared, G. Gibbs: None Declared

Schizophrenia is a severe psychiatric disorder affecting 50% of patients intermittently and 20% chronically, with high unemployment rates (80-90%) and reduced life expectancy. Although genetic and neurodevelopmental factors are established non-modifiable risk factors, knowledge gaps persist regarding prevention strategies, particularly the combined impact of modifiable risk factors.

The aim of this study is to identify the modifiable risk factors and to estimate their joint effect on Schizophrenia.

We conducted an exposure-wide association study (EWAS) using the UK Biobank cohort to systematically evaluate 206 potentially modifiable factors associated with schizophrenia risk. The study population comprised individuals without schizophrenia at baseline, with diagnoses determined using ICD-10 criteria. We employed Cox proportional hazard regression models with Bonferroni correction (significance threshold: P<1.91×10-4) to identify significant factors. The identified factors were categorized into six domains: lifestyle, local environment, medical history, physical measures, psychosocial factors, and socioeconomic status (SES). Domain-specific, weighed, and standardized scores were calculated based on coefficients from Cox models, adjusting for covariates. Scores were stratified into tertiles (favorable, intermediate, unfavorable) for risk assessment. Population attributable fractions (PAFs) were calculated to quantify prevention potential.

The study cohort included 498,351 participants (54.45% female; mean age: 56.55 years) followed for a mean duration of 14.37 years, during which 1,345 participants developed schizophrenia. We identified 86 significant modifiable factors, with disability (HR 6.23, 95% CI 5.48-7.07), depression (HR 5.06, 95% CI 4.93-5.20), and anxiety disorders (HR 3.69, 95% CI 3.12-4.36) showing the strongest associations. Our analyses suggested that transitioning unfavorable profiles to intermediate and favorable status (Estimation 1) could prevent 59.6% of schizophrenia cases, while shifting both intermediate and unfavorable profiles to favorable (Estimation 2) could prevent 90.4% of cases. In Estimation 2, the preventive potential was highest for SES (18.0%), followed by medical history (17.5%), lifestyle factors (17.0%), psychosocial factors (14.3%), physical measures (12.8%), and local environment (10.8%).

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This analysis identifies multiple modifiable risk factors for schizophrenia, demonstrating substantial prevention potential through multi-domain interventions. Socioeconomic, medical, and lifestyle factors emerge as key targets for prevention strategies. The consistency of associations across genetic risk strata suggests interventions could be beneficial regardless of genetic predisposition, informing targeted prevention strategies and public health policies.

None Declared

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.