Background: Whole-genome sequencing (WGS) is well established as a high-resolution method for measuring bacterial relatedness to better understand infection transmission in cases of healthcare-associated infections (HAIs). However, sequencing is still rarely used in HAI investigations due to a lack of access to computational analysis platforms with actionable turnaround times. Single-nucleotide polymorphism (SNP) analysis is typically used to determine bacterial relatedness. However, SNP-based methods often require a suite of bioinformatics tools that can be difficult to use and interpret without the expertise of a trained computational biologist. These obstacles become more significant in the case of prospective, real-time surveillance of HAIs, which can require the analysis of a large number of isolates. To enable the use of WGS for proactive determination of infection outbreaks, a rapid, automated method that can scale to large data sets is needed. Methods: Here, we demonstrate the capabilities of ksim, a novel automated algorithm to determine the clonality of bacterial samples using WGS. ksim measures the number of shared kmers (genomic subsequences of length k) between bacterial samples to determine their relatedness. ksim also filters out accessory genomic regions, such as plasmids, that can confound genetic relatedness estimates. We benchmarked the accuracy and speed of ksim relative to an SNP-based pipeline on simulated data sets (with sequencing reads generated in silico) and on 9 clinical-cluster data sets (6 publicly available and 3 real-time data sets from Massachusetts General Hospital [MGH]). We also used ksim to determine the relatedness of >5,000 historical clinical bacterial isolates from MGH, collected between 2015 and 2019. Results: ksim first preprocesses raw sequencing data to generate a common data structure, after which it computes the genomic distance between bacterial samples in ∼0.2 seconds in simple cases and in ∼4 seconds in complex cases when accessory genome filtering is required. In simulations across 5 species, ksim determined clonality (defined as <40 SNPs) with high accuracy (sensitivity, 99.7% and specificity, 99.6%). ksim performance on 9 clinical HAI data sets demonstrated its sensitivity (99.4%) and specificity (90.8%) compared to an SNP-based pipeline. ksim efficiently analyzed >5,000 clinical samples from MGH and found previously unidentified transmission clusters. Conclusions:ksim shows promise for rapid clonality determination in HAI outbreaks and has the potential to scale to tens of thousands of samples. This method could enable infection control teams to use WGS for prospective outbreak detection via an automated computational pipeline without the need for specialized computational biology training.

Funding: Day Zero Diagnostics and the NIH provided Funding: for this study.

Disclosures: Mohamad Sater reports salary from Day Zero Diagnostics.

Inappropriate dental antibiotic prescriptions to prevent infective endocarditis in the United States results in ∼$31 million in excess costs to the healthcare system and patients. This includes out-of-pocket costs ($20.5 million), drug costs ($2.69 million) and adverse event costs (eg, Clostridioides difficile and hypersensitivity) of $5.82 million (amoxicillin), $1.99 million (clindamycin), and $380,849 (cephalexin).

The government publishes 3 different public report surgical site infection (SSI) metrics, all called standardized infection ratios (SIRs), that impact perceived hospital quality. We conducted a non-random cross-sectional observational pilot study of 20 California hospitals that voluntarily submitted colon surgery and SSI data. Discordant SIR values, leading to contradictory conclusions, occurred in 35% of these hospitals.

Infect Control Hosp Epidemiol 2016;1–5

Performing patient care while wearing high-level personal protective equipment presents risks to healthcare providers. Our failure mode effects analysis identified 81 overall risks associated with providing hygienic care and linen change to a patient with continuous watery stool. Implementation of checklists and scheduled pauses could potentially mitigate 76.5% of all risks.

Infect Control Hosp Epidemiol 2016;37:867–871

We assessed susceptibility patterns to newer antimicrobial agents among clinical carbapenem-resistant Klebsiella pneumoniae (CRKP) isolates from patients in long-term acute-care hospitals (LTACHs) from 2014 to 2015. Meropenem-vaborbactam and imipenem-relebactam nonsusceptibility were observed among 9.9% and 9.1% of isolates, respectively. Nonsusceptibility to ceftazidime-avibactam (1.1%) and plazomicin (0.8%) were uncommon.

Time constraints have been suggested as a potential driver of antibiotic overuse for acute respiratory tract infections. In this cross-sectional analysis of national data from visits to offices and emergency departments, we identified no statistically significant association between antibiotic prescribing and the duration of visits for acute respiratory tract infections.

Exposure investigations are labor intensive and vulnerable to recall bias. We developed an algorithm to identify healthcare personnel (HCP) interactions from the electronic health record (EHR), and we evaluated its accuracy against conventional exposure investigations. The EHR algorithm identified every known transmission and used ranking to produce a manageable contact list.

Background: Hospital-acquired influenza (HA flu) lacks a consensus definition. However, it is known to be associated with increased inpatient morbidity and mortality. Objective: To describe the clinical course of HA flu in a cohort population. Methods: A retrospective cohort study was conducted at a tertiary-care adult and pediatric teaching hospital. Patients with HA flu during 3 seasons, 2016 through 2019, were identified from medical record information based on timing of the onset of signs and symptoms and positive virologic testing >72 hours after admission. Influenza infection was confirmed by multiplex respiratory PCR, influenza A/B PCR, or direct fluorescent antibody tests. Chart review was performed to abstract patient demographics and comorbidities, length of stay, testing, and timing to antiviral administration as well as diagnosis of pneumonia, coinfections, and 30-day mortality. Escalation of care during hospitalization was defined as a new requirement of supplemental oxygen, invasive or noninvasive ventilation, and transfer to an intensive care unit. Results: During the 3 flu seasons, 132 patients were identified with HA flu; 76 (58%) were women, 6 (4.6%) were aged <18 years, and 126 (95.4%) were adults. Annually, HA-flu patients accounted for 5%–7.8% of all patients hospitalized with laboratory-proven influenza. The median duration between hospitalization and positive flu test was 15 days, and the median length of stay after influenza diagnosis was 6 days. Antiviral treatment was received by 96% of the patients. In total, 41 patients (31%) showed radiographic evidence for pneumonia. Coinfection with either a viral or bacterial pathogen was identified in 25% of the cases. In addition, 26% of the patients experienced an escalation of care, and 20 patients (15%) were transferred to the intensive care unit after HA flu diagnosis. Furthermore, 4 deaths (3%) were attributed to influenza during their hospitalization. Conclusions: HA flu was a frequent cause for escalation in care and was associated with a mortality rate substantially higher than is typically seen in community-based populations with influenza. Coinfection was mostly related to bacteremia and pneumonia, yet not all pneumonias had an associated microbiological diagnosis other than influenza, and there was no significant association between coinfection and mortality. Future work should explore more precise definitions for HA flu as well as its complications.

Funding: None

Disclosures: None

In this meta-analysis, central venous catheter exposure (pooled odds ratio, 8.02; 95% confidence interval [CI], 2.19–29.31; P < .01) in neonates and length of stay (standardized mean difference, 0.65; 95% CI, 0.26–1.05; P = .01) in an adult population were associated with acquisition of waterborne healthcare-associated infections or colonization in ICUs. The quality of evidence was low.

A series of five successive cases of ultraviolet-induced erythroderma and keratoconjunctivitis, occurring over a one-month period and related to exposure to an improperly installed ultraviolet light are described. Although in this series, as well as others reviewed, the effects appeared self-limited, significant associated morbidity was observed.

Case-control studies (sometimes referred to as case-referent studies) have long been important in epidemiologic research. This technique has been instrumental in allowing researchers to discover the associations between cigarettes and lung cancer, thromboembolism and oral contraceptives, and stilbesterol and vaginal cancer, just to cite a few examples. The case-control method is also a very useful technique for studies in hospital epidemiology. This article will briefly review this technique, its advantages, and some of its potential pitfalls.