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Background: Traditional hospital outbreak-detection methods are typically limited to select multidrug-resistant pathogens in a single unit, which can miss transmission of many medically important healthcare-transmissible pathogens. Whole-genome sequencing (WGS) enables comprehensive genomic resolution for accurate identification of clonal transmission. Previously, lack of scalability limited the use of WGS for hospital surveillance. Methods: We conducted prospective surveillance of select bacteria from all inpatient clinical cultures plus all bacteria from clinical cultures from ICUs and oncology units at the University of California Irvine (UCI) Clinical Microbiology Laboratory from September 2021 to February 2022. Due to pandemic stressors, this pilot test was a prelude to a real-time demonstration project. Its goal was to demonstrate the efficiency and scalability of the WGS platform when receiving samples monthly and analyzing results quarterly without the intent for real-time response. Bacterial isolates slated for discard were collected weekly and sent monthly to Day Zero Diagnostics for sequencing. In total, 1,036 samples from 926 patients were analyzed for genomic relatedness, a scalable and automated analysis pipeline already in use for rapid (days) characterization of genomic-relatedness in small and large sets of isolates. Mapping and SNP calling was performed against high-quality, best-match reference genomes. Sets of samples with pairwise distance of 2 persons with genomically related isolates and were denoted as “clusters.” Separately, we also investigated within-patient diversity by quantifying the genomic relatedness of isolates collected from individual patients. Results: Isolates represented 28 distinct species. We identified 10 Escherichia coli clusters (range, 2–4 patients; median, 2 patients), 2 Klebsiella pneumoniae clusters (range, 2–4 patients), and 1 Enterococcus faecium cluster (3 patients). All but 1 involved genomically matched isolates from multiple hospital locations. There were 4 Escherichia coli ST131 clusters spanning 4 months, including 1 with 4 patients across 3 different hospital locations. At a species level, there were distinct differences between the observed SNP distances between samples isolated from the same versus different patients (Fig. 1). All identified clusters had not been flagged by routine outbreak detection methods used by the UCI infection prevention program. Conclusions: Comprehensive WGS-based surveillance of hospital clinical isolates identified multiple potential transmission events between patients not in the same unit at the time cultures were taken. Combining WGS detection and real-time epidemiologic investigation may identify new avenues of transmission risk and could provide early warnings of clonal transmission to prevent larger outbreaks. High-volume surveillance of hospital isolates can also provide species- and context-specific clonality.
Financial support: This study was funded by Day Zero Diagnostics.
To investigate the source in an outbreak of carbapenem-resistant Acinetobacter baumannii (CRA) in a general hospital due to contamination of a laundry evaporative cooler and the laundry environment using multilocus sequence typing (MLST).
For CRA culture, clinical samples were collected from infected patients and close contacts, and environmental sampling was performed in patient surroundings and laundry facilities. MLST was used for the molecular typing of representative CRA isolates. Bacterial isolates with identical sequence types were considered epidemiologically linked and attributable to the same source. OXA genes in Acinetobacter baumannii were detected using polymerase chain reaction (PCR).
In total, 58 patients were affected in this outbreak. The mean patient age was 75.3, and 50% were female. The most common diagnoses at admission were skin and soft-tissue infection (n = 12, 20.7%) and pneumonia (n = 12, 20.7%). OXA-23 was positive in 64.7% of isolates. A CRA isolate from the evaporative cooler in the laundry was identical to that of 11 patients across 3 wards, belonging to ST345. Isolates from 3 laundry linen racks were identical to those of 7 patients from 3 wards, classified as ST1145. Isolates found on another linen rack and a pajama shelf were identical to isolates from 3 other patients from 2 wards, belonging to ST2207. There was no significant difference between sequence type distributions of clinical and environmental isolates (P = .12), indicating high likelihood of CRA originating from the same source.
MLST confirmed that contamination of the laundry evaporative cooler and surrounding environment caused a polyclonal CRA hospital outbreak. Hospital laundry is an important area for infection control and outbreak investigations of CRA.
This audit covered 3 hospitals in Glasgow City which has 1221 beds providing inpatient healthcare for the north east region of the city. To improve the referral process,we aimed to verify adherence to existing referral pathway and adequacy of information provided by referrals. Referral characteristics including referral indication, intervention and outcomes were accounted for to identify area interest that may help improve the referral process.
Our referral pathway involves completion of a Microsoft Word referral template subsequently sent electronically to an internal electronic mail.
Referrals in a 2 month period were included in the audit. Each referral was reviewed for adherence to the referral template, adequacy of provided information and referral indications. Intervention in the form of staff input, Mental Health Act status, psychotropic medication prescribed and given diagnosis was ascertained via staff electronic entry records.
139 referrals were included. 114 referrals (82%) adhered to the referral template. 72 referrals (52%) contained adequate information. Common referral indications were delirium (23%), agitation (20%), low mood (18%) and cognitive decline queries (18%). Staff input ranged from psychiatrist input (46%), liaison nurses (40%), clinical psychology (1%) and shared input (13%). 16 referrals (12%) resulted in subsequent detention under the Mental Health Act. Psychotropic medications prior to liaison assessment included antidepressants (49%), antipsychotics (29%) and benzodiazepines (16%). Liaison assessment resulted in increase use of antipsychotic (55%) and reduction of antidepressants (29%) and benzodiazepines (10%), Delirium (34%), dementia (21%), Mood & Anxiety related disorders (18%) and Query of Cognitive Impairment (14%) were recorded as the most discussed diagnosis.
Referrals with inadequate details affect the service's ability to efficiently assess for clinical urgency and matching of appropriate interventions to suit clinical needs. The percentage difference in delirium between referral indication and diagnosis highlights that delirium can be under-recognised, resulting in potentially delayed treatment. Identifying common given diagnosis and differences in psychotropic medication prescribing pattern points to the need for training and support of acute medical ward staff in utilising therapeutics for management of acute mental health disorder.
A pending electronic referral pathway with mandatory entries and linked relevant online resources can encourage early recognition of acute mental health disorder and prompt early management including the use of appropriate therapeutics. An additional feature allowing direct referrals by acute ward staff to community mental health team would support continuity of care for discharged patients needing ongoing mental health assessment.