Background: Black, Asian and Minority Ethnic (BAME) people continue to present later to specialist care centres and services for memory problems. This poses significant concerns due to implications for poorer treatment outcomes and higher treatment cost among this population. While diverse interventions to support improved help seeking for dementia have been proffered for other BAME communities, there is a paucity of research involving the Black African and Caribbean community. Furthermore, whilst community health professionals like the doctors and community nurses have been involved in such interventions, no previous research has considered the role of the community pharmacist. This research explored opportunities for community pharmacists to support improved help seeking for dementia among the Black African and Caribbean population.

Methods: This research was a multi-stage project involving surveys and interviews with community pharmacists and Black Africans and Caribbeans as participants.

Results: Knowledge, attitude and beliefs around dementia and it’s causes appeared to be major barriers to help seeking among the Black African and Caribbean population. For example, beliefs that dementia is caused by ‘the spirits’ and dementia is a repercussion for past wrongdoing and therefore not amenable to medical intervention. The community pharmacists believe they are well positioned to spot initial signs of dementia among their clients and are therefore willing to offer help seeking support to this population.

Conclusions: To offer intervention for timely help-seeking for dementia, a culturally tailored dementia education for the Black African and Caribbean population should be considered. In addition, training on the impact of cultural beliefs on help seeking for dementia should be considered for the communitypharmacists.

Background: Detecting healthcare-associated transmission and outbreaks often relies on reactive whole-genome sequencing (WGS), which occurs after the suspected transmission has occurred. Additionally, reactive WGS frequently misidentifies transmission and misses transmission when it has occurred. We initiated weekly real-time WGS to detect bacterial transmission and direct infection prevention interventions. We describe our experience after 1 year of real-time WGS surveillance at the University of Pittsburgh Medical Center–Presbyterian Hospital, a large, tertiary-care facility. Methods: Weekly WGS surveillance was performed from November 1, 2021, to October 31, 2022. Cultured isolates of select bacterial pathogens from patients who were hospitalized for ≥3 days or had a recent healthcare exposure in the prior 30 days were collected and sequenced. Isolates that were ≤15 single-nucleotide polymorphisms (SNPs) were considered genetically related clusters except for Clostridioides difficile (≤2 SNPs). Genetically related clusters were investigated for epidemiological links and interventions to interrupt transmission were implemented at the discretion of the infection prevention team. We analyzed subsequent infections that occurred within an outbreak after an intervention was in place. Results: In total, 1,909 isolates were sequenced. Of 1,633 unique patient isolates clustered by sequence type, 74 clusters were identified comprising 210 (12.9%) patient isolates (Table 1). The median time from culture date to sequencing was 14 days (IQR, 5.25). The median cluster size was 2 (IQR, 1) (Table 2). Overall, 118 patient isolates (56.2%) had an epidemiological link to a prior isolate, indicating potential transmission. Of 74 clusters, 66 (89.2%) received infection prevention interventions after notification based upon epidemiological data. The infection prevention team performed 69 total interventions, which included unit education (n = 28), hand hygiene observations (n = 16), enhanced cleaning (n = 16), environmental cultures or removal of endoscope (n = 7), and enhanced microbiology surveillance (n = 2). The 59 subsequent infections after infection prevention notification included 17 (28.8%) with no clear epidemiological link, and 41 (69.5%) with an epidemiological link either to a new transmission route (n = 37) or the same route prior to infection prevention intervention (n = 4). Only 1 (1.7%) subsequent infection within a cluster occurred after an infection prevention intervention from the same potential route, which was a suspected unit-based transmission of vancomycin-resistant Enterococcus faecium. Conclusions: Real-time WGS was effective at detecting genetically related clusters, finding potential sources, and halting further transmission after interventions by the infection prevention team. Quick turnaround times from patient culture to sequencing and analysis were vital for successful WGS surveillance. Real-time WGS surveillance has the potential to substantially shift the infection prevention paradigm for outbreak detection.

Disclosure: None

Background: Traditional infection prevention (IP) methods for outbreak detection often rely on geotemporal clustering confined to single locations. We recently developed the Enhanced Detection System for Healthcare-Associated Transmission (EDS-HAT), which combines whole-genome sequencing (WGS) surveillance and machine learning of the electronic health record (EHR). Our retrospective research findings show potential transmissions averted and cost savings using EDS-HAT in real time. Here, we describe the process and initial findings from EDS-HAT real-time implementation. Methods: Real-time whole-genome sequencing surveillance began on November 1, 2021. Patient cultures positive for select bacterial pathogens who were hospitalized for ≥3 days or had a recent healthcare exposure in the prior 30-days were collected. Isolates were deemed genetically related if ≤15 single-nucleotide polymorphisms (SNPs) were identified for all organisms except Clostridioides difficile (≤2 SNPs). Clusters were manually investigated by both research and IP teams, and interventions were performed by the IP team. Data on collection, analysis, notification, and intervention dates were gathered. Results: As of January 11, 2022, 413 isolates had undergone whole-genome sequencing. Among them, 18 unique patient isolates were genetically related to ≥1 other isolate, comprising 7 clusters (range, 2–6 patients). Notable findings include a Pseudomonas aeruginosa cluster possibly related to a shared bronchoscope, a pseudo-outbreak of Serratia marcescens related to autopsy blood culture practice, and a cluster of vancomycin-resistant Enterococcus faecium on a shared transplant unit. Only 1 cluster of 2 isolates of Klebsiella pneumoniae had no known possible transmission routes. The median turnaround time from patient’s culture date to IP notification was 19 days (range, 13–28), with noted delays over the winter holiday. Concusions: Real-time WGS can identify small clusters including potentially interruptible transmission routes. Rapid turnaround time, coordination between clinical and genomic laboratories, and a robust IP team are key factors in implementing a WGS surveillance program. Real-time WGS surveillance has the potential to reduce costs for hospitals, improve patient safety, and save lives.

Funding: None

Disclosures: None

Age- and sex-based BMI cut-offs are used to define overweight and obesity, but the relationship between BMI and body composition has not been very well studied in children or compared between children of different ethnic groups. Body size and composition in childhood are also influenced by size at birth. Our aim was to compare body size and composition at 2 years in children with different ethnicity and size at birth. We prospectively followed a multi-ethnic cohort of 300 children born with risk factors for neonatal hypoglycaemia (infants of diabetics, large or small at birth or late preterm) to 2 years corrected age. Complete data on weight, height and head circumference and body composition using bioelectrical impedance 24±1 months corrected age were available in 209 children. At birth, compared with European children, Chinese, Indian and other ethnicity children were lighter, and Indian children had smaller head circumferences, but birth lengths were similar in all ethnic groups. At 2 years, Pacific children were heavier and had higher BMI z scores, and Indian children had smaller head circumferences and lower BMI z scores than those from other ethnic groups. However, fat mass and fat-free mass indices were similar in all groups. At median BMI, fat mass:fat-free mass ratio was 23 % lower in Pacific than in Indian children (0·22 v. 0·27, P=0·03). BMI is not a good indicator of adiposity in this multi-ethnic cohort of 2-year-old New Zealand children.