Integrated Genomic and Social Network Analyses of SARS-CoV-2 Transmission in the Healthcare Setting.

BACKGROUND: Infection prevention (IP) measures are designed to mitigate the transmission of pathogens in healthcare. Using large-scale viral genomic and social network analyses, we determined if IP measures used during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic were adequate in protecting healthcare workers (HCWs) and patients from acquiring SARS-CoV-2. METHODS: We performed retrospective cross-sectional analyses of viral genomics from all available SARS-CoV-2 viral samples collected at UC San Diego Health and social network analysis using the electronic medical record to derive temporospatial overlap of infections among related viromes and supplemented with contact tracing data. The outcome measure was any instance of healthcare transmission, defined as cases with closely related viral genomes and epidemiological connection within the healthcare setting during the infection window. Between November 2020 through January 2022, 12 933 viral genomes were obtained from 35 666 patients and HCWs. RESULTS: Among 5112 SARS-CoV-2 viral samples sequenced from the second and third waves of SARS-CoV-2 (pre-Omicron), 291 pairs were derived from persons with a plausible healthcare overlap. Of these, 34 pairs (12%) were phylogenetically linked: 19 attributable to household and 14 to healthcare transmission. During the Omicron wave, 2106 contact pairs among 7821 sequences resulted in 120 (6%) related pairs among 32 clusters, of which 10 were consistent with healthcare transmission. Transmission was more likely to occur in shared spaces in the older hospital compared with the newer hospital (2.54 vs 0.63 transmission events per 1000 admissions, P < .001). CONCLUSIONS: IP strategies were effective at identifying and preventing healthcare SARS-CoV-2 transmission.

Climate change and resilience for antimicrobial stewardship and infection prevention.

PURPOSE OF REVIEW: This review covers recent research regarding the challenges posed by climate change within the areas of antimicrobial stewardship and infection prevention, and ways to build resiliency in these fields. RECENT FINDINGS: Infectious disease patterns are changing as microbes adapt to climate change and changing environmental factors. Capacity for testing and treating infectious diseases is challenged by newly emerging diseases, which exacerbate challenges to antimicrobial stewardship and infection prevention.Antimicrobial resistance is accelerated due to environmental factors including air pollution, plastic pollution, and chemicals used in food systems, which are all impacted by climate change.Climate change places infection prevention practices at risk in many ways including from major weather events, increased risk of epidemics, and societal disruptions causing conditions that can overwhelm health systems. Researchers are building resilience by advancing rapid diagnostics and disease modeling, and identifying highly reliable versus low efficiency interventions. SUMMARY: Climate change and associated major weather and socioeconomic events will place significant strain on healthcare facilities. Work being done to advance rapid diagnostics, build supply chain resilience, improve predictive disease modeling and surveillance, and identify high reliability versus low yield interventions will help build resiliency in antimicrobial stewardship and infection prevention for escalating challenges due to climate change.

Common antibiotics, azithromycin and amoxicillin, affect gut metagenomics within a household.

BACKGROUND: The microbiome of the human gut serves a role in a number of physiological processes, but can be altered through effects of age, diet, and disturbances such as antibiotics. Several studies have demonstrated that commonly used antibiotics can have sustained impacts on the diversity and the composition of the gut microbiome. The impact of the two most overused antibiotics, azithromycin, and amoxicillin, in the human microbiome has not been thoroughly described. In this study, we recruited a group of individuals and unrelated controls to decipher the effects of the commonly used antibiotics amoxicillin and azithromycin on their gut microbiomes. RESULTS: We characterized the gut microbiomes by metagenomic sequencing followed by characterization of the resulting microbial communities. We found that there were clear and sustained effects of the antibiotics on the gut microbial community with significant alterations in the representations of Bifidobacterium species in response to azithromycin (macrolide antibiotic). These results were supported by significant increases identified in putative antibiotic resistance genes associated with macrolide resistance. Importantly, we did not identify these trends in the unrelated control individuals. There were no significant changes observed in other members of the microbial community. CONCLUSIONS: As we continue to focus on the role that the gut microbiome plays and how disturbances induced by antibiotics might affect our overall health, elucidating members of the community most affected by their use is of critical importance to understanding the impacts of common antibiotics on those who take them. Clinical Trial Registration Number NCT05169255. This trial was retrospectively registered on 23-12-2021.

Examination of Medication Use Patterns by Age Group, Comorbidity, and Month in COVID-19 Positive Patients in a Large Statewide Health System During the Pandemic in 2020.

Background: Understanding medication use patterns for patients with COVID-19 will provide needed insight into the evolution of COVID-19 treatment over the course of the SARS-CoV-2 pandemic and aid clinical management considerations. Objectives: To systematically determine most frequently used medications among COVID-19 patients overall and by hospitalization status. Secondary objective was use measurement of medications considered potential therapeutic options. Methods: Retrospective cohort study was performed using data from the University of California COVID Research Data Set (UC CORDS) patients between March 10, 2020, and December 31, 2020. Main outcomes were percentages of patients prescribed medications, overall, by age group, and by comorbidity based on hospitalization status for COVID-19 patients. Use percentage by month of COVID-19 diagnosis was measured. Cumulative count of potential therapeutic options was measured over time. Results: Dataset included 22 896 unique patients with COVID-19 (mean [SD] age, 42.4 [20.4] years; 12 154 [53%] women). Most frequently used medications in patients overall were acetaminophen (21.2%), albuterol (14.9%), ondansetron (13.9%), and enoxaparin (10.8%). Dexamethasone use increased from fewer than 50 total hospitalized patients through April who had received the medication, to more than 500 patients by mid-August. Cumulative count of enoxaparin users was the largest throughout the study period. Conclusion and Relevance: In this retrospective cohort study, across age and comorbidity groups, predominant utilization was for supportive care therapy. Dexamethasone and remdesivir experienced large increases in use. Conversely, hydroxychloroquine and azithromycin use markedly dropped. Medication utilization rapidly shifted toward more evidence-concordant treatment of patients with COVID-19 as rigorous study findings emerged.

A Risk-Based Clinical Decision Support System for Patient-Specific Antimicrobial Therapy (iBiogram): Design and Retrospective Analysis.

BACKGROUND: There is a pressing need for digital tools that can leverage big data to help clinicians select effective antibiotic treatments in the absence of timely susceptibility data. Clinical presentation and local epidemiology can inform therapy selection to balance the risk of antimicrobial resistance and patient risk. However, data and clinical expertise must be appropriately integrated into clinical workflows. OBJECTIVE: The aim of this study is to leverage available data in electronic health records, to develop a data-driven, user-centered, clinical decision support system to navigate patient safety and population health. METHODS: We analyzed 5 years of susceptibility testing (1,078,510 isolates) and patient data (30,761 patients) across a large academic medical center. After curating the data according to the Clinical and Laboratory Standards Institute guidelines, we analyzed and visualized the impact of risk factors on clinical outcomes. On the basis of this data-driven understanding, we developed a probabilistic algorithm that maps these data to individual cases and implemented iBiogram, a prototype digital empiric antimicrobial clinical decision support system, which we evaluated against actual prescribing outcomes. RESULTS: We determined patient-specific factors across syndromes and contexts and identified relevant local patterns of antimicrobial resistance by clinical syndrome. Mortality and length of stay differed significantly depending on these factors and could be used to generate heuristic targets for an acceptable risk of underprescription. Combined with the developed remaining risk algorithm, these factors can be used to inform clinicians' reasoning. A retrospective comparison of the iBiogram-suggested therapies versus the actual prescription by physicians showed similar performance for low-risk diseases such as urinary tract infections, whereas iBiogram recognized risk and recommended more appropriate coverage in high mortality conditions such as sepsis. CONCLUSIONS: The application of such data-driven, patient-centered tools may guide empirical prescription for clinicians to balance morbidity and mortality with antimicrobial stewardship.

Public Health Role of Academic Medical Center in Community Outbreak of Hepatitis A, San Diego County, California, USA, 2016-2018.

During 2016-2018, San Diego County, California, USA, experienced one of the largest hepatitis A outbreaks in the United States in 2 decades. In close partnership with local healthcare systems, San Diego County Public Health led a public health response to the outbreak that focused on a 3-pronged strategy to vaccinate, sanitize, and educate. Healthcare systems administered nearly half of the vaccinations delivered in San Diego County. At University of California San Diego Health, the use of informatics tools assisted with the identification of at-risk populations and with vaccine delivery across outpatient and inpatient settings. In addition, acute care facilities helped prevent further disease transmission by delaying the discharge of patients with hepatitis A who were experiencing homelessness. We assessed the public health roles that acute care hospitals can play during a large community outbreak and the critical nature of ongoing collaboration between hospitals and public health systems in controlling such outbreaks.

Transcriptome analysis of bacteriophage communities in periodontal health and disease.

BACKGROUND: The role of viruses as members of the human microbiome has gained broader attention with the discovery that human body surfaces are inhabited by sizeable viral communities. The majority of the viruses identified in these communities have been bacteriophages that predate upon cellular microbiota rather than the human host. Phages have the capacity to lyse their hosts or provide them with selective advantages through lysogenic conversion, which could help determine the structure of co-existing bacterial communities. Because conditions such as periodontitis are associated with altered bacterial biota, phage mediated perturbations of bacterial communities have been hypothesized to play a role in promoting periodontal disease. Oral phage communities also differ significantly between periodontal health and disease, but the gene expression of oral phage communities has not been previously examined. RESULTS: Here, we provide the first report of gene expression profiles from the oral bacteriophage community using RNA sequencing, and find that oral phages are more highly expressed in subjects with relative periodontal health. While lysins were highly expressed, the high proportion of integrases expressed suggests that prophages may account for a considerable proportion of oral phage gene expression. Many of the transcriptome reads matched phages found in the oral cavities of the subjects studied, indicating that phages may account for a substantial proportion of oral gene expression. Reads homologous to siphoviruses that infect Firmicutes were amongst the most prevalent transcriptome reads identified in both periodontal health and disease. Some genes from the phage lytic module were significantly more highly expressed in subjects with periodontal disease, suggesting that periodontitis may favor the expression of some lytic phages. CONCLUSIONS: As we explore the contributions of viruses to the human microbiome, the data presented here suggest varying expression of bacteriophage communities in oral health and disease.

Characterization of bacteriophage communities and CRISPR profiles from dental plaque.

BACKGROUND: Dental plaque is home to a diverse and complex community of bacteria, but has generally been believed to be inhabited by relatively few viruses. We sampled the saliva and dental plaque from 4 healthy human subjects to determine whether plaque was populated by viral communities, and whether there were differences in viral communities specific to subject or sample type. RESULTS: We found that the plaque was inhabited by a community of bacteriophage whose membership was mostly subject-specific. There was a significant proportion of viral homologues shared between plaque and salivary viromes within each subject, suggesting that some oral viruses were present in both sites. We also characterized Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) in oral streptococci, as their profiles provide clues to the viruses that oral bacteria may be able to counteract. While there were some CRISPR spacers specific to each sample type, many more were shared across sites and were highly subject specific. Many CRISPR spacers matched viruses present in plaque, suggesting that the evolution of CRISPR loci may have been specific to plaque-derived viruses. CONCLUSIONS: Our findings of subject specificity to both plaque-derived viruses and CRISPR profiles suggest that human viral ecology may be highly personalized.

Conservation of streptococcal CRISPRs on human skin and saliva.

BACKGROUND: Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) are utilized by bacteria to resist encounters with their viruses. Human body surfaces have numerous bacteria that harbor CRISPRs, and their content can provide clues as to the types and features of viruses they may have encountered. RESULTS: We investigated the conservation of CRISPR content from streptococci on skin and saliva of human subjects over 8-weeks to determine whether similarities existed in the CRISPR spacer profiles and whether CRISPR spacers were a stable component of each biogeographic site. Most of the CRISPR sequences identified were unique, but a small proportion of spacers from the skin and saliva of each subject matched spacers derived from previously sequenced loci of S. thermophilus and other streptococci. There were significant proportions of CRISPR spacers conserved over the entire 8-week study period for all subjects, and salivary CRISPR spacers sampled in the mornings showed significantly higher levels of conservation than any other time of day. We also found substantial similarities in the spacer repertoires of the skin and saliva of each subject. Many skin-derived spacers matched salivary viruses, supporting that bacteria of the skin may encounter viruses with similar sequences to those found in the mouth. Despite the similarities between skin and salivary spacer repertoires, the variation present was distinct based on each subject and body site. CONCLUSIONS: The conservation of CRISPR spacers in the saliva and the skin of human subjects over the time period studied suggests a relative conservation of the bacteria harboring them.

Secondary peritonitis in a patient with cirrhosis involving Hyphopichia burtonii, an emerging fungal pathogen.

We present a case where Hyphopichia burtonii, a yeast, speciated from peritoneal fluid in a cirrhotic patient with secondary peritonitis. The patient, a man in his 60s with decompensated cirrhosis, was admitted for an upper gastrointestinal (GI) bleed. On admission, he was treated empirically for spontaneous bacterial peritonitis (SBP) but failed to improve with antibiotics. Serial paracenteses revealed polymicrobial peritonitis and rising peritoneal polymorphonuclear leukocytes (PMNs). These findings raised concerns for secondary peritonitis, prompting an abdominal computed tomography (CT) scan which revealed ischemic bowel. Among the peritoneal microbiota isolated, Hyphopichia burtonii predominated. Hyphopichia burtonii has only recently been reported as a human pathogen, previously it had only reported as a pathogen in bats[1,2].

Surgical wound classification in otolaryngology: A state-of-the-art review.

Objective: To describe the issues related to the assignment of surgical wound classification as it pertains to Otolaryngology-Head & Neck surgery, and to present a simple framework by which providers can assign wound classification. Data Sources: Literature review. Conclusion: Surgical wound classification in its current state is limited in its utility. It has recently been disregarded by major risk assessment models, likely due to inaccurate and inconsistent reporting by providers and operative staff. However, if data accuracy is improved, this metric may be useful to inform the risk of surgical site infection. In an era of quality-driven care and reimbursement, surgical wound classification may become an equally important indicator of quality.

Persistent neutrophilic meningitis in an immunocompetent patient after basilar skull fracture: case report.

BACKGROUND: Persistent neutrophilic meningitis is an unusual form of chronic meningitis that is defined as clinical meningitis with a neutrophilic pleocytosis that persists for greater than 7 days despite empiric antimicrobial therapy. Although numerous disease processes can cause this syndrome, the majority of cases are due to opportunistic pathogens infecting immunocompromised hosts. CASE PRESENTATION: A 47 year-old female presented after basilar skull fracture with persistent neutrophilic meningitis unresponsive to empiric broad-spectrum antibiotics. After more than weeks of intensive therapy, 4 hospitalizations and 3 relapses, Nocardia cyriacigeorgica was identified from cerebral spinal fluid. Induction therapy was begun with Ceftriaxone and trimethoprim-sulfamethoxazole (TMP-SMX) for 6 weeks followed by therapy with TMP-SMX and doxycycline for one year. The patient made a complete recovery without sequelae. CONCLUSIONS: Due to the difficulty in obtaining a microbiologic diagnosis, appropriate treatment in cases of persistent neutrophilic meningitis is often delayed leading to morbidity, This case highlights a number of the unique features of Nocardia meningitis and the importance of considering Nocardia infection as a cause of persistent neutrophilic meningitis even in immunocompetent patients.

The Impact of an Inpatient Nurse-Triggered Sepsis Alert on Antimicrobial Utilization.

INTRODUCTION: A nurse-triggered sepsis alert called "Code Sepsis" was implemented for early recognition and management of sepsis. The researchers analyzed its impact on antimicrobial use and identified factors associated with infection as source of Code Sepsis. METHODS: The medical records of hospitalized patients with Code Sepsis between January 1 and June 30, 2018, were reviewed. Patients were classified as "Infection" when probable or definitive infection was identified or "No Infection" when a probable or definitive noninfectious source was identified. Patients were categorized as "Escalation" with addition or change to broader-spectrum antimicrobials or "No Escalation" with no change or change to narrower-spectrum antimicrobials. Escalation was classified as "Indicated" with appropriate escalation or "Not Indicated" with inappropriate escalation. Logistic regression model was used to identify factors associated with Infection as Code Sepsis trigger. RESULTS: Code Sepsis was activated in 529 patients, with Escalation in 246 (46.5%) and No Escalation in 283 (53.5%) patients. Escalation was Indicated in 157 (63.8%) and Not Indicated in 89 (36.2%) patients. Infection was identified in 356 (67.3%) and No Infection in 173 (32.7%) patients. History of HIV (odds ratio [OR] = 2.75, p = 0.03), temperature > 38.3°C or < 36°C (OR = 2.63, p < 0.01), and respiratory rate > 20/minute (OR = 1.56, p = 0.02) were associated with Infection, while surgery within 3 days (OR = 0.30, p < 0.01) was associated with No Infection. CONCLUSION: One hospital system's Code Sepsis inadvertently identified patients without infections and led to antimicrobial overuse. By refocusing Code Sepsis on early recognition of severe sepsis and septic shock only, the organization hopes to optimize resource utilization and improve patient outcomes.

The Effect of Clostridioides difficile Diagnostic Stewardship Interventions on the Diagnosis of Hospital-Onset Clostridioides difficile Infections.

BACKGROUND: Public reporting of Clostridioides difficile infection (CDI) using laboratory-identified events has led some institutions to revert from molecular-based tests to less sensitive testing modalities. At one academic medical center, researchers chose to use nucleic acid amplification test alone in CDI diagnosis with institutional protocols aimed at diagnostic stewardship. METHODS: A single-center, quasi-experimental study was conducted to introduce and analyze the effects of various diagnostic stewardship interventions. In April 2017 an order report was created to inform providers of patients' recent bowel movements, laxative use, and prior Clostridioides difficile (CD) testing (Intervention 1). In November 2017 nursing staff were empowered to not send nondiarrheal stools for testing (Intervention 2). In February 2019, an interruptive alert was implemented to prevent testing that was not indicated (Intervention 3). CD testing rates and healthcare facility-onset CDI (HO-CDI) rates were compared before and after the interventions using one-way analysis of variance (ANOVA). RESULTS: At baseline, testing for CD after 3 days of admission was performed at mean ± standard deviation of 15.9 ± 1.7 tests/1,000 patient-days. After Intervention 1, it decreased to 12.1 ± 1.1 tests. This further decreased to 10.6 ± 0.8 after Intervention 2 and to 8.1 ± 0.1 after Intervention 3 (p < 0.001). HO-CDI cases per 10,000 patient-days declined from 12.7 ± 1.4 cases at baseline to 10.7 ± 1.2 after Intervention 1, to 8.7 ± 2.4 after Intervention 2, and to 5.8 ± 0.2 after Intervention 3 (p = 0.03). CONCLUSION: A multidisciplinary approach optimizing electronic health record support tools and leveraging nursing education can reduce both testing and HO-CDI rates while using the most sensitive testing modality.