Treatment of seriously ill patients is often complicated by prolonged or complex transfers between hospitals in sub-Saharan Africa. Difficulties or inefficiency in these transfers can lead to poor outcomes for patients. “On-call” triage systems have been utilized to facilitate communication between facilities and to avoid poor outcomes associated with patient transfer. This study attempts to examine the effects of a pilot study to implement such a system in Rwanda.

Data collection occurred prospectively in two stages, pre-intervention and intervention, in the emergency department (ED) at Kigali University Teaching Hospital (CHUK). All patients transferred during the pre-determined timeframe were enrolled. Data were collected by ED research staff via a standardized form. Statistical analysis was performed using STATA version 15.0. Differences in characteristics were assessed using χ2 or Fisher’s exact tests for categorical variables and independent sample t-tests for normally distributed continuous variables.

During the “on call” physician intervention, the indication for transfer was significantly more likely to be for critical care (P <.001), transfer times were faster (P <.001), patients were more likely to be displaying emergency signs (P <.001), and vital signs were more likely to be collected prior to transport (P <.001) when compared to the pre-interventional phase.

The “[Emergency Medicine] EM Doc On Call” intervention was associated with improved timely interhospital transfer and clinical documentation in Rwanda. While these data are not definitive due to multiple limitations, it is extremely promising and worthy of further study.

Researchers have identified genetic and neural risk factors for externalizing behaviors. However, it has not yet been determined if genetic liability is conferred in part through associations with more proximal neurophysiological risk markers.

Participants from the Collaborative Study on the Genetics of Alcoholism, a large, family-based study of alcohol use disorders were genotyped and polygenic scores for externalizing (EXT PGS) were calculated. Associations with target P3 amplitude from a visual oddball task (P3) and broad endorsement of externalizing behaviors (indexed via self-report of alcohol and cannabis use, and antisocial behavior) were assessed in participants of European (EA; N = 2851) and African ancestry (AA; N = 1402). Analyses were also stratified by age (adolescents, age 12–17 and young adults, age 18–32).

The EXT PGS was significantly associated with higher levels of externalizing behaviors among EA adolescents and young adults as well as AA young adults. P3 was inversely associated with externalizing behaviors among EA young adults. EXT PGS was not significantly associated with P3 amplitude and therefore, there was no evidence that P3 amplitude indirectly accounted for the association between EXT PGS and externalizing behaviors.

Both the EXT PGS and P3 amplitude were significantly associated with externalizing behaviors among EA young adults. However, these associations with externalizing behaviors appear to be independent of each other, suggesting that they may index different facets of externalizing.

Current psychiatric diagnoses, although heritable, have not been clearly mapped onto distinct underlying pathogenic processes. The same symptoms often occur in multiple disorders, and a substantial proportion of both genetic and environmental risk factors are shared across disorders. However, the relationship between shared symptoms and shared genetic liability is still poorly understood.

Well-characterised, cross-disorder samples are needed to investigate this matter, but few currently exist. Our aim is to develop procedures to purposely curate and aggregate genotypic and phenotypic data in psychiatric research.

As part of the Cardiff MRC Mental Health Data Pathfinder initiative, we have curated and harmonised phenotypic and genetic information from 15 studies to create a new data repository, DRAGON-Data. To date, DRAGON-Data includes over 45 000 individuals: adults and children with neurodevelopmental or psychiatric diagnoses, affected probands within collected families and individuals who carry a known neurodevelopmental risk copy number variant.

We have processed the available phenotype information to derive core variables that can be reliably analysed across groups. In addition, all data-sets with genotype information have undergone rigorous quality control, imputation, copy number variant calling and polygenic score generation.

DRAGON-Data combines genetic and non-genetic information, and is available as a resource for research across traditional psychiatric diagnostic categories. Algorithms and pipelines used for data harmonisation are currently publicly available for the scientific community, and an appropriate data-sharing protocol will be developed as part of ongoing projects (DATAMIND) in partnership with Health Data Research UK.

To examine if smaller size at birth, an indicator of growth restriction in utero, is associated with lower cognition in late life, and whether this may be mediated by impaired early life brain development and/or adverse cardiometabolic programming.

Longitudinal follow-up of a birth cohort.

CSI Holdsworth Memorial Hospital (HMH), Mysore South India.

721 men and women (55–80 years) whose size at birth was recorded at HMH. Approximately 20 years earlier, a subset (n = 522) of them had assessments for cardiometabolic disorders in mid-life.

Standardized measurement of cognitive function, depression, sociodemographic, and lifestyle factors; blood tests and assessments for cardiometabolic disorders

Participants who were heavier at birth had higher composite cognitive scores (0.12 SD per SD birth weight [95% CI 0.05, 0.19] p = 0.001) in late life. Other lifecourse factors independently positively related to cognition were maternal educational level and participants’ own educational level, adult leg length, body mass index, and socioeconomic position, and negatively were diabetes in mid-life and current depression and stroke. The association of birth weight with cognition was independent cardiometabolic risk factors and was attenuated after adjustment for all lifecourse factors (0.08 SD per SD birth weight [95% CI −0.01, 0.18] p = 0.07).

The findings are consistent with positive effects of early life environmental factors (better fetal growth, education, and childhood socioeconomic status) on brain development resulting in greater long-term cognitive function. The results do not support a pathway linking poorer fetal development with reduced late life cognitive function through cardiometabolic programming.

To develop a semi-quantitative FFQ and to evaluate its validity and reproducibility for the assessment of total dietary intake of Kenyan urban adult population, given its non-existence in Kenya.

The current study adopted a cross-sectional design. A culture-sensitive semi-quantitative FFQ was developed and its validity was tested relative to three non-consecutive 24-h recalls (24hR). Reproducibility was tested by the test–retest method, with a 3-week interval. Spearman’s correlation coefficients and intra-class correlation coefficients were calculated for several macro- and micronutrients. Cross-classification into quartiles and Bland and Altman plots were analysed.

Nairobi county (Dagoreti South and Starehe constituencies).

A convenient sample was recruited in three different clusters in Nairobi.

A culture-sensitive 123-food-item semi-quantitative FFQ showed higher nutrient intakes compared with the 24hR (total energy median 12543·632 v. 8501·888 kJ, P < 0·001). Energy-adjusted and deattenuated Spearman’s correlations for macronutrients ranged between 0·21 (total fat) and 0·47 (protein). The agreement in the same quartile varied from 28 % (protein) to 41 % (carbohydrates). Including adjacent quartiles, the range increased: 76 % (protein and fat) to 81 % (carbohydrates). The extreme disagreement was low. The first FFQ application resulted in higher mean values for all nutrients compared with the second FFQ (total energy median 12459·952 v. 10485·104 kJ, P < 0·001). Energy-adjusted correlations for macronutrients ranged from 0·28 (carbohydrates) to 0·61 (protein). Intra-class correlation coefficients for macronutrients were moderate, between 0·6 and 0·7.

The developed semi-quantitative FFQ was shown to be a valid and reproducible tool for ranking urban adult Kenyans according to their dietary intake.

Studies suggest that alcohol consumption and alcohol use disorders have distinct genetic backgrounds.

We examined whether polygenic risk scores (PRS) for consumption and problem subscales of the Alcohol Use Disorders Identification Test (AUDIT-C, AUDIT-P) in the UK Biobank (UKB; N = 121 630) correlate with alcohol outcomes in four independent samples: an ascertained cohort, the Collaborative Study on the Genetics of Alcoholism (COGA; N = 6850), and population-based cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC; N = 5911), Generation Scotland (GS; N = 17 461), and an independent subset of UKB (N = 245 947). Regression models and survival analyses tested whether the PRS were associated with the alcohol-related outcomes.

In COGA, AUDIT-P PRS was associated with alcohol dependence, AUD symptom count, maximum drinks (R2 = 0.47–0.68%, p = 2.0 × 10−8–1.0 × 10−10), and increased likelihood of onset of alcohol dependence (hazard ratio = 1.15, p = 4.7 × 10−8); AUDIT-C PRS was not an independent predictor of any phenotype. In ALSPAC, the AUDIT-C PRS was associated with alcohol dependence (R2 = 0.96%, p = 4.8 × 10−6). In GS, AUDIT-C PRS was a better predictor of weekly alcohol use (R2 = 0.27%, p = 5.5 × 10−11), while AUDIT-P PRS was more associated with problem drinking (R2 = 0.40%, p = 9.0 × 10−7). Lastly, AUDIT-P PRS was associated with ICD-based alcohol-related disorders in the UKB subset (R2 = 0.18%, p < 2.0 × 10−16).

AUDIT-P PRS was associated with a range of alcohol-related phenotypes across population-based and ascertained cohorts, while AUDIT-C PRS showed less utility in the ascertained cohort. We show that AUDIT-P is genetically correlated with both use and misuse and demonstrate the influence of ascertainment schemes on PRS analyses.

To examine the relationship between unit-wide Clostridium difficile infection (CDI) susceptibility and inpatient mobility and to create contagion centrality as a new predictive measure of CDI.

Retrospective cohort study.

A mobility network was constructed using 2 years of patient electronic health record data for a 739-bed hospital (n = 72,636 admissions). Network centrality measures were calculated for each hospital unit (node) providing clinical context for each in terms of patient transfers between units (ie, edges). Daily unit-wide CDI susceptibility scores were calculated using logistic regression and were compared to network centrality measures to determine the relationship between unit CDI susceptibility and patient mobility.

Closeness centrality was a statistically significant measure associated with unit susceptibility (P < .05), highlighting the importance of incoming patient mobility in CDI prevention at the unit level. Contagion centrality (CC) was calculated using inpatient transfer rates, unit-wide susceptibility of CDI, and current hospital CDI infections. The contagion centrality measure was statistically significant (P < .05) with our outcome of hospital-onset CDI cases, and it captured the additional opportunities for transmission associated with inpatient transfers. We have used this analysis to create easily interpretable clinical tools showing this relationship as well as the risk of hospital-onset CDI in real time, and these tools can be implemented in hospital EHR systems.

Quantifying and visualizing the combination of inpatient transfers, unit-wide risk, and current infections help identify hospital units at risk of developing a CDI outbreak and, thus, provide clinicians and infection prevention staff with advanced warning and specific location data to inform prevention efforts.