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High-quality evidence from prospective longitudinal studies in humans is essential to testing hypotheses related to the developmental origins of health and disease. In this paper, the authors draw upon their own experiences leading birth cohorts with longitudinal follow-up into adulthood to describe specific challenges and lessons learned. Challenges are substantial and grow over time. Long-term funding is essential for study operations and critical to retaining study staff, who develop relationships with participants and hold important institutional knowledge and technical skill sets. To maintain contact, we recommend that cohorts apply multiple strategies for tracking and obtain as much high-quality contact information as possible before the child’s 18th birthday. To maximize engagement, we suggest that cohorts offer flexibility in visit timing, length, location, frequency, and type. Data collection may entail multiple modalities, even at a single collection timepoint, including measures that are self-reported, research-measured, and administrative with a mix of remote and in-person collection. Many topics highly relevant for adolescent and young adult health and well-being are considered to be private in nature, and their assessment requires sensitivity. To motivate ongoing participation, cohorts must work to understand participant barriers and motivators, share scientific findings, and provide appropriate compensation for participation. It is essential for cohorts to strive for broad representation including individuals from higher risk populations, not only among the participants but also the staff. Successful longitudinal follow-up of a study population ultimately requires flexibility, adaptability, appropriate incentives, and opportunities for feedback from participants.
Posttraumatic stress symptoms (PTSS) are common following traumatic stress exposure (TSE). Identification of individuals with PTSS risk in the early aftermath of TSE is important to enable targeted administration of preventive interventions. In this study, we used baseline survey data from two prospective cohort studies to identify the most influential predictors of substantial PTSS.
Self-identifying black and white American women and men (n = 1546) presenting to one of 16 emergency departments (EDs) within 24 h of motor vehicle collision (MVC) TSE were enrolled. Individuals with substantial PTSS (⩾33, Impact of Events Scale – Revised) 6 months after MVC were identified via follow-up questionnaire. Sociodemographic, pain, general health, event, and psychological/cognitive characteristics were collected in the ED and used in prediction modeling. Ensemble learning methods and Monte Carlo cross-validation were used for feature selection and to determine prediction accuracy. External validation was performed on a hold-out sample (30% of total sample).
Twenty-five percent (n = 394) of individuals reported PTSS 6 months following MVC. Regularized linear regression was the top performing learning method. The top 30 factors together showed good reliability in predicting PTSS in the external sample (Area under the curve = 0.79 ± 0.002). Top predictors included acute pain severity, recovery expectations, socioeconomic status, self-reported race, and psychological symptoms.
These analyses add to a growing literature indicating that influential predictors of PTSS can be identified and risk for future PTSS estimated from characteristics easily available/assessable at the time of ED presentation following TSE.
To describe national trends in testing and detection of carbapenemases
produced by carbapenem-resistant Enterobacterales (CRE) and associate
testing with culture and facility characteristics.
Retrospective cohort study.
Department of Veterans’ Affairs medical centers (VAMCs).
Patients seen at VAMCs between 2013 and 2018 with cultures positive for CRE,
defined by national VA guidelines.
Microbiology and clinical data were extracted from national VA data sets.
Carbapenemase testing was summarized using descriptive statistics.
Characteristics associated with carbapenemase testing were assessed with
Of 5,778 standard cultures that grew CRE, 1,905 (33.0%) had evidence of
molecular or phenotypic carbapenemase testing and 1,603 (84.1%) of these had
carbapenemases detected. Among these cultures confirmed as
carbapenemase-producing CRE, 1,053 (65.7%) had molecular testing for
≥1 gene. Almost all testing included KPC (n = 1,047, 99.4%), with KPC
detected in 914 of 1,047 (87.3%) cultures. Testing and detection of other
enzymes was less frequent. Carbapenemase testing increased over the study
period from 23.5% of CRE cultures in 2013 to 58.9% in 2018. The South US
Census region (38.6%) and the Northeast (37.2%) region had the highest
proportion of CRE cultures with carbapenemase testing. High complexity (vs
low) and urban (vs rural) facilities were significantly associated with
carbapenemase testing (P < .0001).
Between 2013 and 2018, carbapenemase testing and detection increased in the
VA, largely reflecting increased testing and detection of KPC. Surveillance
of other carbapenemases is important due to global spread and increasing
antibiotic resistance. Efforts supporting the expansion of carbapenemase
testing to low-complexity, rural healthcare facilities and standardization
of reporting of carbapenemase testing are needed.
Deficits in visuospatial attention, known as neglect, are common following brain injury, but underdiagnosed and poorly treated, resulting in long-term cognitive disability. In clinical settings, neglect is often assessed using simple pen-and-paper tests. While convenient, these cannot characterise the full spectrum of neglect. This protocol reports a research programme that compares traditional neglect assessments with a novel virtual reality attention assessment platform: The Attention Atlas (AA).
The AA was codesigned by researchers and clinicians to meet the clinical need for improved neglect assessment. The AA uses a visual search paradigm to map the attended space in three dimensions and seeks to identify the optimal parameters that best distinguish neglect from non-neglect, and the spectrum of neglect, by providing near-time feedback to clinicians on system-level behavioural performance. A series of experiments will address procedural, scientific, patient, and clinical feasibility domains.
Analyses focuses on descriptive measures of reaction time, accuracy data for target localisation, and histogram-based raycast attentional mapping analysis; which measures the individual’s orientation in space, and inter- and intra-individual variation of visuospatial attention. We will compare neglect and control data using parametric between-subjects analyses. We present example individual-level results produced in near-time during visual search.
The development and validation of the AA is part of a new generation of translational neuroscience that exploits the latest advances in technology and brain science, including technology repurposed from the consumer gaming market. This approach to rehabilitation has the potential for highly accurate, highly engaging, personalised care.
Although there has been significant research on the relationship between alcohol consumption and demographic and psychological influences, this does not consider the effect of social influence among older drinkers and if these effects differ between men and women. One aspect of social influence is social capital. The aim of this paper is to examine whether relational and cognitive social capital are associated with higher or lower risk of alcohol use among adults aged 50 years or older and to assess the extent to which this relationship differs between men and women. To investigate this, data were collected from a cross-sectional questionnaire survey of adults over the age of 50 in the United Kingdom who were recruited from general practitioners. The sample consisted of 9,984 individuals whose mean age was 63.87 years. From these data, we developed proxy measures of social capital and associate these with the respondent's level of alcohol consumption as measured on the Alcohol Use Disorders Identification Test (AUDIT-10) scale. In the sample, just over 20 per cent reported an increasing risk or dependency on alcohol. Using two expressions of social capital – relational (social relationships) and cognitive (knowledge acquisition and understanding) – we found that greater levels of both are associated with a reduced risk of higher drinking risk. Being female had no significant effect when combined with relational capital but did have a significant effect when combined with cognitive capital. It is argued that interventions to enhance social relations among older people and education to help understand alcohol risks would be helpful to protect older people from the damaging effects of excessive alcohol consumption.
A comparison of computer-extracted and facility-reported counts of hospitalized coronavirus disease 2019 (COVID-19) patients for public health reporting at 36 hospitals revealed 42% of days with matching counts between the data sources. Miscategorization of suspect cases was a primary driver of discordance. Clear reporting definitions and data validation facilitate emerging disease surveillance.
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.