Social unrest tied to racism negatively impacted half of NIH-funded extramural researchers underrepresented (UR) in science. UR early-career scientists encounter more challenges in their research careers, but the impact of social unrest due to systemic racism in this group is unclear. We used mixed methods to describe the impact of social unrest due to systemic racism on mentoring relationships, research, and psychological well-being in UR post-doctoral fellows and early-career faculty.

This is a cross-sectional analysis of data collected in September 2021–January 2022 from 144 UR early-career researchers from 25 academic medical centers in the Building Up Trial. The primary outcomes were agreement on five-point Likert scales with social unrest impact statements (e.g., “I experienced psychological distress due to events of social unrest regarding systemic racism”). Thematic analysis was conducted on responses to one open-ended question assessing how social unrest regarding systemic racism affected participants.

Most participants were female (80%), non-Hispanic Black (35%), or Hispanic (40%). Over half of participants (57%) experienced psychological distress as a result of social unrest due to systemic racism. Participants described direct and indirect discrimination and isolation from other persons of color at their institutions. Twice as many participants felt their mentoring relationships were positively (21%) versus negatively (11%) impacted by social unrest due to systemic racism.

Experiences with racial bias and discrimination impact the career and well-being of UR early-career researchers. Mentoring relationships and institutional support play an important role in buffering the negative impact of racial injustice for this population.

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.

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.

Informal carers play an essential role in the care of individuals with Parkinson’s disease (PD). This role, however, is often fraught with difficulties, including emotional, physical, and financial. Coping styles and relationship quality have been hypothesized to influence the impact of stressors. The aim of this study is to examine the relationship between carers’ coping style, relationship quality, and carer burden.

Cross-sectional.

Thirty-nine PD patient carer dyads were included in the study.

Participants completed self-rated questionnaires including the Dyadic Adjustment Scale, Zarit Burden Interview, and Brief Coping Orientation to Problems Experienced Inventory.

Correlational analyses found significant and positive correlation between carer burden and all three coping styles (problem-focused, emotion-focused, and dysfunctional). There was also a moderate association between carers’ perceived relationship quality and satisfaction and carer burden. Regression analyses found that carer’s gender, severity of PD, relationship quality, emotion-focused, and dysfunctional coping styles did not predict carer burden. Conversely, problem-focused coping style predicted carer burden.

The results highlight that there is no perfect way to react and care for a loved one and serves as important information for practitioners who design and implement interventions.

The aim of this study was to identify any relationship between hearing loss and mild cognitive impairment.

This was a systematic review and meta-analysis of randomised controlled trials conducted using Medline and the Cochrane Library up to 24 June 2020. Prospective, cohort and cross-sectional, and observational studies that reported on the relationship between mild cognitive impairment and hearing loss were included.

A total of 34 studies reporting data on 48 017 participants were included. Twenty-three studies observed a significant association between hearing loss and mild cognitive impairment. The pooled risk ratio across all studies of prevalence of mild cognitive impairment in people with hearing loss was 1.44 (random-effects; 95 per cent CI = 1.27–1.64; p < 0.00001; I2 = 0 per cent). Significantly more people with mild cognitive impairment had peripheral hearing loss compared with those without (risk ratio, 1.40 random-effects; 95 per cent CI = 1.10–1.77; p = 0.005; I2 = 0 per cent). When the incidence was studied, significantly more people with peripheral hearing loss had mild cognitive impairment compared with those without (risk ratio = 2.06 random-effects; 95 per cent CI = 1.35–3.15; p = 0.0008; I2 = 97 per cent); however; a high level of statistical heterogeneity was evident.

Most of the studies included in this systematic review observed a significant association between hearing loss and mild cognitive impairment.

To determine the frequency and predictors of antibiotic escalation in response to the inpatient sepsis screen at our institution.

Retrospective cohort study.

Two affiliated academic medical centers in Los Angeles, California.

Hospitalized patients aged 18 years and older who had their first positive sepsis screen between January 1, 2019, and December 31, 2019, on acute-care wards.

We described the rate and etiology of antibiotic escalation, and we conducted multivariable regression analyses of predictors of antibiotic escalation.

Of the 576 cases with a positive sepsis screen, antibiotic escalation occurred in 131 cases (22.7%). New infection was the most documented etiology of escalation, with 76 cases (13.2%), followed by known pre-existing infection, with 26 cases (4.5%). Antibiotics were continued past 3 days in 17 cases (3.0%) in which new or existing infection was not apparent. Abnormal temperature (adjusted odds ratio [aOR], 3.00; 95% confidence interval [CI], 1.91–4.70) and abnormal lactate (aOR, 2.04; 95% CI, 1.28–3.27) were significant predictors of antibiotic escalation. The patient already being on antibiotics (aOR, 0.54; 95% CI, 0.34–0.89) and the positive screen occurred during a nursing shift change (aOR, 0.36; 95% CI, 0.22–0.57) were negative predictors. Pneumonia was the most documented new infection, but only 19 (50%) of 38 pneumonia cases met full clinical diagnostic criteria.

Inpatient sepsis screening led to a new infectious diagnosis in 13.2% of all positive sepsis screens, and the risk of prolonged antibiotic exposure without a clear infectious source was low. Pneumonia diagnostics and lactate testing are potential targets for future stewardship efforts.

Discrepancies exist in reports of social cognition deficits in individuals with premanifest Huntington’s disease (HD); however, the reason for this variability has not been investigated. The aims of this study were to (1) evaluate group- and individual-level social cognitive performance and (2) examine intra-individual variability (dispersion) across social cognitive domains in individuals with premanifest HD.

Theory of mind (ToM), social perception, empathy, and social connectedness were evaluated in 35 individuals with premanifest HD and 29 healthy controls. Cut-off values beneath the median and 1.5 × the interquartile range below the 25th percentile (P25 – 1.5 × IQR) of healthy controls for each variable were established for a profiling method. Dispersion between social cognitive domains was also calculated.

Compared to healthy controls, individuals with premanifest HD performed worse on all social cognitive domains except empathy. Application of the profiling method revealed a large proportion of people with premanifest HD fell below healthy control median values across ToM (>80%), social perception (>57%), empathy (>54%), and social behaviour (>40%), with a percentage of these individuals displaying more pronounced impairments in empathy (20%) and ToM (22%). Social cognition dispersion did not differ between groups. No significant correlations were found between social cognitive domains and mood, sleep, and neurocognitive outcomes.

Significant group-level social cognition deficits were observed in the premanifest HD cohort. However, our profiling method showed that only a small percentage of these individuals experienced marked difficulties in social cognition, indicating the importance of individual-level assessments, particularly regarding future personalised treatments.