Electronic Health Record (EHR) data are critical for advancing translational research and AI technologies. The ENACT network offers access to structured EHR data across 57 CTSA hubs. However, substantial information is contained in clinical narratives, requiring natural language processing (NLP) for research. The ENACT NLP Working Group was formed to make NLP-derived clinical information accessible and queryable across the network.

We established the ENACT NLP Working Group with 13 sites selected based on criteria including clinical notes access, IT infrastructure, NLP expertise, and institutional support. We divided sites into five focus groups targeting clinical tasks within disease contexts. Each focus group consisted of two development sites and two validation sites. We extended the ENACT ontology to standardize NLP-derived data and conducted multisite evaluations using the Open Health Natural Language Processing (OHNLP) Toolkit.

The working group achieved 100% site retention and deployed NLP infrastructure across all sites. We developed and validated NLP algorithms for rare disease phenotyping, social determinants of health, opioid use disorder, sleep phenotyping, and delirium phenotyping. Performance varied across sites (F1 scores 0.53–0.96), highlighting data heterogeneity impacts. We extended the ENACT common data model and ontology to incorporate NLP-derived data while maintaining Shared Health Research Informatics NEtwork (SHRINE) compatibility.

This demonstrates feasibility of deploying NLP infrastructure across large, federated networks. The focus group approach proved more practical than general-purpose approaches. Key lessons include the challenge of data heterogeneity and importance of collaborative governance. This work also provides a foundation that other networks can build on to implement NLP capabilities for translational research.

Surgical pulmonary valve replacement is commonly required to palliate patients with CHD affecting the right ventricular outflow tract; however, concerns remain about mid- and long-term durability. Post-operative short-term anticoagulation has been hypothesised to improve valve durability.

This is a single-centre, retrospective study of paediatric patients who underwent surgical pulmonary valve replacement and received a direct oral anticoagulant in addition to aspirin post heart valve insertion. The primary objective was a composite safety score consisting of clinically relevant non-major bleeding, major bleeding, bleeding-related readmission, and medication discontinuation.

The study analysed 34 patients with a median age 14 years (Interquartile range (IQR): 11, 15) and weight 45 kg (IQR: 35, 55). Ten patients met the composite endpoint (10/34, 29%), with 4 patients experiencing major bleeding (4/34, 12%), 6 experiencing clinically relevant non-major bleeding (6/34, 18%), and 3 patients being readmitted within 90 days of surgical pulmonary valve replacement for bleeding (3/29, 8.8%) resulting in 10 patients discontinuing medication early (10/34, 29%). Lower weight was identified as a significant risk factor for adverse event development (p = 0.04).

We observed a higher overall bleeding rate, driven predominately by clinically relevant non-major bleeding events, than other studies using short-term anticoagulation after surgical pulmonary valve replacement. Additional studies should be aimed at evaluating the dosing and safety of direct oral anticoagulants in children in the post-operative period.

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.

Duchenne muscular dystrophy is a devastating neuromuscular disorder characterized by the loss of dystrophin, inevitably leading to cardiomyopathy. Despite publications on prophylaxis and treatment with cardiac medications to mitigate cardiomyopathy progression, gaps remain in the specifics of medication initiation and optimization.

This document is an expert opinion statement, addressing a critical gap in cardiac care for Duchenne muscular dystrophy. It provides thorough recommendations for the initiation and titration of cardiac medications based on disease progression and patient response. Recommendations are derived from the expertise of the Advance Cardiac Therapies Improving Outcomes Network and are informed by established guidelines from the American Heart Association, American College of Cardiology, and Duchenne Muscular Dystrophy Care Considerations. These expert-derived recommendations aim to navigate the complexities of Duchenne muscular dystrophy-related cardiac care.

Comprehensive recommendations for initiation, titration, and optimization of critical cardiac medications are provided to address Duchenne muscular dystrophy-associated cardiomyopathy.

The management of Duchenne muscular dystrophy requires a multidisciplinary approach. However, the diversity of healthcare providers involved in Duchenne muscular dystrophy can result in variations in cardiac care, complicating treatment standardization and patient outcomes. The aim of this report is to provide a roadmap for managing Duchenne muscular dystrophy-associated cardiomyopathy, by elucidating timing and dosage nuances crucial for optimal therapeutic efficacy, ultimately improving cardiac outcomes, and improving the quality of life for individuals with Duchenne muscular dystrophy.

This document seeks to establish a standardized framework for cardiac care in Duchenne muscular dystrophy, aiming to improve cardiac prognosis.

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.

Incidence of first-episode psychosis (FEP) varies substantially across geographic regions. Phenotypes of subclinical psychosis (SP), such as psychotic-like experiences (PLEs) and schizotypy, present several similarities with psychosis. We aimed to examine whether SP measures varied across different sites and whether this variation was comparable with FEP incidence within the same areas. We further examined contribution of environmental and genetic factors to SP.

We used data from 1497 controls recruited in 16 different sites across 6 countries. Factor scores for several psychopathological dimensions of schizotypy and PLEs were obtained using multidimensional item response theory models. Variation of these scores was assessed using multi-level regression analysis to estimate individual and between-sites variance adjusting for age, sex, education, migrant, employment and relational status, childhood adversity, and cannabis use. In the final model we added local FEP incidence as a second-level variable. Association with genetic liability was examined separately.

Schizotypy showed a large between-sites variation with up to 15% of variance attributable to site-level characteristics. Adding local FEP incidence to the model considerably reduced the between-sites unexplained schizotypy variance. PLEs did not show as much variation. Overall, SP was associated with younger age, migrant, unmarried, unemployed and less educated individuals, cannabis use, and childhood adversity. Both phenotypes were associated with genetic liability to schizophrenia.

Schizotypy showed substantial between-sites variation, being more represented in areas where FEP incidence is higher. This supports the hypothesis that shared contextual factors shape the between-sites variation of psychosis across the spectrum.

Precariously housed individuals are exposed to multiple adverse factors negatively impacting neurocognitive functioning. Additionally, this population is subjected to poor life outcomes, such as impaired psychosocial functioning. Neurocognitive functioning plays an important role in psychosocial functioning and may be especially critical for precariously housed individuals who face numerous barriers in their daily lives. However, few studies have explicitly examined the cognitive determinants of functional outcomes in this population. Cognitive intraindividual variability (IIV) involves the study of within-person differences in neurocognitive functioning and has been used as marker of frontal system pathology. Increased IIV has been associated with worse cognitive performance, cognitive decline, and poorer everyday functioning. Hence, IIV may add to the predictive utility of commonly used neuropsychological measures and may serve as an emergent predictor of poor outcomes in at-risk populations. The objective of the current study was to examine IIV as a unique index of the neurocognitive contributions to functional outcomes within a large sample of precariously housed individuals. It was hypothesized that greater IIV would be associated with poorer current (i.e., baseline) and long-term (i.e., up to 12 years) psychosocial functioning.

Four hundred and thirty-seven adults were recruited from single-room occupancy hotels located in the Downtown Eastside of Vancouver, Canada (Mage = 44 years, 78% male) between November 2008 and November 2021. Baseline neurocognitive functioning was assessed at study enrolment. Scores from the Social and Occupational Functioning Assessment Scale (SOFAS), the Role Functioning Scale (RFS), the physical component score (PCS) and the mental component score (MCS) of the 36-Item Short Form Survey Instrument were obtained at participants’ baseline assessments and at their last available follow-up assessment to represent baseline and long-term psychosocial functioning, respectively. Using an established formula, an index of IIV was derived using a battery of standardized tests that broadly assessed verbal learning and memory, sustained attention, mental flexibility, and cognitive control. A series of multiple linear regressions were conducted to predict baseline and long-term social and role functioning (average across SOFAS and RFS scores), and PCS and MCS scores from IIV. In each of the models, we also included common predictors of functioning, including a global cognitive composite score, age, and years of education.

The IIV index and the global composite score did not explain a significant proportion of the variance in baseline and long-term social and role functioning (p > .05). However, IIV was a significant predictor of baseline (B = -3.84, p = .021) and long-term (B = -3.58, p = .037) PCS scores, but not MCS scores (p > .05). The global composite score did not predict baseline or long-term PCS scores.

IIV significantly predicted baseline and long-term physical functioning, but not mental functioning or social and role functioning, suggesting that IIV may be a sensitive marker for limitations in everyday functioning due to physical health problems in precariously housed individuals. Critically, the present study is the first to show that IIV may be a useful index for predicting poor long-term health-related outcomes in this population compared to traditional neuropsychological measures.

Childhood adversity and cannabis use are considered independent risk factors for psychosis, but whether different patterns of cannabis use may be acting as mediator between adversity and psychotic disorders has not yet been explored. The aim of this study is to examine whether cannabis use mediates the relationship between childhood adversity and psychosis.

Data were utilised on 881 first-episode psychosis patients and 1231 controls from the European network of national schizophrenia networks studying Gene–Environment Interactions (EU-GEI) study. Detailed history of cannabis use was collected with the Cannabis Experience Questionnaire. The Childhood Experience of Care and Abuse Questionnaire was used to assess exposure to household discord, sexual, physical or emotional abuse and bullying in two periods: early (0–11 years), and late (12–17 years). A path decomposition method was used to analyse whether the association between childhood adversity and psychosis was mediated by (1) lifetime cannabis use, (2) cannabis potency and (3) frequency of use.

The association between household discord and psychosis was partially mediated by lifetime use of cannabis (indirect effect coef. 0.078, s.e. 0.022, 17%), its potency (indirect effect coef. 0.059, s.e. 0.018, 14%) and by frequency (indirect effect coef. 0.117, s.e. 0.038, 29%). Similar findings were obtained when analyses were restricted to early exposure to household discord.

Harmful patterns of cannabis use mediated the association between specific childhood adversities, like household discord, with later psychosis. Children exposed to particularly challenging environments in their household could benefit from psychosocial interventions aimed at preventing cannabis misuse.

The internet serves an increasingly critical role in how older adults manage their personal health. Electronic patient portals, for example, provide a centralized platform for older adults to access lab results, manage prescriptions and appointments, and communicate with providers. This study examined whether neurocognition mediates the effect of older age on electronic patient portal navigation.

Forty-nine younger (18–35 years) and 35 older adults (50–75 years) completed the Test of Online Health Records Navigation (TOHRN), which is an experimenter-controlled website on which participants were asked to log-in, review laboratory results, read provider messages, and schedule an appointment. Participants also completed a neuropsychological battery, self-report questionnaires, and measures of health literacy and functional capacity.

Mediation analyses revealed a significant indirect effect of older age on lower TOHRN accuracy, which was fully mediated by the total cognitive composite.

Findings indicate that neurocognition may help explain some of the variance in age-related difficulties navigating electronic patient health portals. Future studies might examine the possible benefits of both structural (e.g., human factors web design enhancement) and individual (e.g., training and compensation) cognitive supports to improve the navigability of electronic patient health portals for older adults.

Child maltreatment (CM) and migrant status are independently associated with psychosis. We examined prevalence of CM by migrant status and tested whether migrant status moderated the association between CM and first-episode psychosis (FEP). We further explored whether differences in CM exposure contributed to variations in the incidence rates of FEP by migrant status.

We included FEP patients aged 18–64 years in 14 European sites and recruited controls representative of the local populations. Migrant status was operationalized according to generation (first/further) and region of origin (Western/non-Western countries). The reference population was composed by individuals of host country's ethnicity. CM was assessed with Childhood Trauma Questionnaire. Prevalence ratios of CM were estimated using Poisson regression. We examined the moderation effect of migrant status on the odds of FEP by CM fitting adjusted logistic regressions with interaction terms. Finally, we calculated the population attributable fractions (PAFs) for CM by migrant status.

We examined 849 FEP cases and 1142 controls. CM prevalence was higher among migrants, their descendants and migrants of non-Western heritage. Migrant status, classified by generation (likelihood test ratio:χ2 = 11.3, p = 0.004) or by region of origin (likelihood test ratio:χ2 = 11.4, p = 0.003), attenuated the association between CM and FEP. PAFs for CM were higher among all migrant groups compared with the reference populations.

The higher exposure to CM, despite a smaller effect on the odds of FEP, accounted for a greater proportion of incident FEP cases among migrants. Policies aimed at reducing CM should consider the increased vulnerability of specific subpopulations.

Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.

To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.

This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.

The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.

Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

In response to the 2014–2016 West Africa Ebola virus disease (EVD) epidemic, the Centers for Disease Control and Prevention (CDC) designated 56 US hospitals as Ebola treatment centers (ETCs) with high-level isolation capabilities. We sought to determine the ongoing sustainability of ETCs and to identify how ETC capabilities have affected hospital, local, and regional coronavirus disease 2019 (COVID-19) readiness and response.

An electronic survey included both qualitative and quantitative questions and was structured into 2 sections: operational sustainability and role in the COVID-19 response.

The survey was distributed to site representatives from the 56 originally designated ETCs, and 37 (66%) responded.

Data were coded and analyzed using descriptive statistics.

Of the 37 responding ETCs, 33 (89%) reported that they were still operating, and 4 had decommissioned. ETCs that maintain high-level isolation capabilities incurred a mean of $234,367 in expenses per year. All but 1 ETC reported that existing capabilities (eg, trained staff, infrastructure) before COVID-19 positively affected their hospital, local, and regional COVID-19 readiness and response (eg, ETC trained staff, donated supplies, and shared developed protocols).

Existing high-level isolation capabilities and expertise developed following the 2014–2016 EVD epidemic were leveraged by ETCs to assist hospital-wide readiness for COVID-19 and to support responses by other local and regional hospitals However, ETCs face continued challenges in sustaining those capabilities for high-consequence infectious diseases.

Schizophrenia (SZ), bipolar disorder (BD) and depression (D) run in families. This susceptibility is partly due to hundreds or thousands of common genetic variants, each conferring a fractional risk. The cumulative effects of the associated variants can be summarised as a polygenic risk score (PRS). Using data from the EUropean Network of national schizophrenia networks studying Gene-Environment Interactions (EU-GEI) first episode case–control study, we aimed to test whether PRSs for three major psychiatric disorders (SZ, BD, D) and for intelligent quotient (IQ) as a neurodevelopmental proxy, can discriminate affective psychosis (AP) from schizophrenia-spectrum disorder (SSD).

Participants (842 cases, 1284 controls) from 16 European EU-GEI sites were successfully genotyped following standard quality control procedures. The sample was stratified based on genomic ancestry and analyses were done only on the subsample representing the European population (573 cases, 1005 controls). Using PRS for SZ, BD, D, and IQ built from the latest available summary statistics, we performed simple or multinomial logistic regression models adjusted for 10 principal components for the different clinical comparisons.

In case–control comparisons PRS-SZ, PRS-BD and PRS-D distributed differentially across psychotic subcategories. In case–case comparisons, both PRS-SZ [odds ratio (OR) = 0.7, 95% confidence interval (CI) 0.54–0.92] and PRS-D (OR = 1.31, 95% CI 1.06–1.61) differentiated AP from SSD; and within AP categories, only PRS-SZ differentiated BD from psychotic depression (OR = 2.14, 95% CI 1.23–3.74).

Combining PRS for severe psychiatric disorders in prediction models for psychosis phenotypes can increase discriminative ability and improve our understanding of these phenotypes. Our results point towards the potential usefulness of PRSs in specific populations such as high-risk or early psychosis phases.

The COVID-19 pandemic exacerbated gender disparities in some academic disciplines. This study examined the association of the pandemic with gender authorship disparities in clinical neuropsychology (CN) journals.

Author bylines of 1,018 initial manuscript submissions to four major CN journals from March 15 through September 15 of both 2019 and 2020 were coded for binary gender. Additionally, authorship of 40 articles published on pandemic-related topics (COVID-19, teleneuropsychology) across nine CN journals were coded for binary gender.

Initial submissions to these four CN journals increased during the pandemic (+27.2%), with comparable increases in total number of authors coded as either women (+23.0%) or men (+25.4%). Neither the average percentage of women on manuscript bylines nor the proportion of women who were lead and/or corresponding authors differed significantly across time. Moreover, the representation of women as authors of pandemic-related articles did not differ from expected frequencies in the field.

Findings suggest that representation of women as authors of peer-reviewed manuscript submissions to some CN journals did not change during the initial months of the COVID-19 pandemic. Future studies might examine how risk and protective factors may have influenced individual differences in scientific productivity during the pandemic.

A history of childhood adversity is associated with psychotic disorder, with an increase in risk according to the number of exposures. However, it is not known why only some exposed individuals go on to develop psychosis. One possibility is pre-existing polygenic vulnerability. Here, we investigated, in the largest sample of first-episode psychosis (FEP) cases to date, whether childhood adversity and high polygenic risk scores for schizophrenia (SZ-PRS) combine synergistically to increase the risk of psychosis, over and above the effect of each alone.

We assigned a schizophrenia-polygenic risk score (SZ-PRS), calculated from the Psychiatric Genomics Consortium (PGC2), to all participants in a sample of 384 FEP patients and 690 controls from the case–control component of the EU-GEI study. Only participants of European ancestry were included in the study. A history of childhood adversity was collected using the Childhood Trauma Questionnaire (CTQ). Synergistic effects were estimated using the interaction contrast ratio (ICR) [odds ratio (OR)exposure and PRS − ORexposure − ORPRS + 1] with adjustment for potential confounders.

There was some evidence that the combined effect of childhood adversities and polygenic risk was greater than the sum of each alone, as indicated by an ICR greater than zero [i.e. ICR 1.28, 95% confidence interval (CI) −1.29 to 3.85]. Examining subtypes of childhood adversities, the strongest synergetic effect was observed for physical abuse (ICR 6.25, 95% CI −6.25 to 20.88).

Our findings suggest possible synergistic effects of genetic liability and childhood adversity experiences in the onset of FEP, but larger samples are needed to increase precision of estimates.