BACKGROUND:Evidence is limited on the comparative safety of antibiotic regimens for treatment of community-acquired pneumonia (CAP). We compared the risk of adverse drug events (ADEs) associated with antibiotic regimens for CAP treatment among otherwise healthy, nonelderly adults. METHODS:We conducted an active-comparator new-user cohort study (2007-2019) of commercially insured adults aged 18-64 years diagnosed with outpatient CAP, evaluated via chest X-ray, and dispensed a same-day CAP-related oral antibiotic regimen. ADE follow-up duration ranged from 2 to 90 days (eg, renal failure [14 days]). We estimated risk differences [RDs] per 1000 treatment episodes and risk ratios using propensity score-weighted Kaplan-Meier functions. Ankle/knee sprain and influenza vaccination were considered as negative control outcomes. RESULTS:Of 145 137 otherwise healthy CAP patients without comorbidities, 52% received narrow-spectrum regimens (44% macrolide, 8% doxycycline) and 48% received broad-spectrum regimens (39% fluoroquinolone, 7% β-lactam, 3% β-lactam + macrolide). Compared with macrolide monotherapy, each broad-spectrum antibiotic regimen was associated with increased risk of several ADEs (eg, β-lactam: nausea/vomiting/abdominal pain [RD per 1000, 3.20; 95% CI, 0.99-5.73]; non-Clostridioides difficile diarrhea [RD per 1000, 4.61; 95% CI, 2.47-6.82]; vulvovaginal candidiasis/vaginitis [RD per 1000, 3.57; 95% CI, 0.87, 6.88]). Narrow-spectrum antibiotic regimens largely conferred similar risk of ADEs. We generally observed similar risks of each negative control outcome, indicating minimal confounding. CONCLUSIONS:Broad-spectrum antibiotics were associated with increased risk of ADEs among otherwise healthy adults treated for CAP in the outpatient setting. Antimicrobial stewardship is needed to promote judicious use of broad-spectrum antibiotics and ultimately decrease antibiotic-related ADEs.

Background:Antimicrobial resistance (AMR) is a growing public health threat, and we currently lack accurate measures to track and trend this resistance. We developed the antibiotic resistance index (ARI) that aggregates resistance of Gram-negative bacilli (GNB) into a single metric which can be tracked across healthcare settings and over time. Methods:Culture data were collected from adult patients who met the CDC adult sepsis event criteria across 10 Barnes-Jewish HealthCare (BJC) hospitals between January 2018 and December 2023. An antibiotic's effective spectrum (AES) was calculated as the ratio of susceptible GNB to all identified GNB. The ARI was calculated as the sum of the AES to which the isolate was resistant. Using the 20 most common GNB and 15 most common anti-GNB antibiotics routinely tested in antibiograms, we calculated the ARI for each BJC hospital during the study years. Results:18,854 GNB cultured from 12,803 patients meeting CDC adult sepsis event criteria were included. AES varied between 0.15 for ampicillin and 0.94 for amikacin. A. calcoaceticus-baumannii complex had the highest ARI of 6.64 (IQR 4.00-9.28). Median hospital-level ARI fluctuated between 2.12 (IQR 0.40-3.83) in 2018 to 2.20 (IQR 0.34-3.86) in 2023. The ARI trajectories over time varied by medical center. Conclusion:ARI aggregates AMR in GNB and may facilitate monitoring across locations and over time. ARI and antibiotic effective spectra redefine narrow and broad spectrum of activity and offer a starting point for antibiotic utilization metrics.

Importance:Hospital-onset bacteremia and fungemia (HOB) are common and potentially preventable complications of hospital care. Objective:To assess whether nonindividual patient features, which summarize interactions with other patients and health care workers (HCWs), can contribute to predictive and causal machine learning models for HOB. Design, Setting, and Participants:This prognostic study included adult patients admitted to Barnes-Jewish Hospital, an academic hospital in St Louis, Missouri, in 2021. Analyses were developed between October 2023 and August 2024 and in April 2025. Exposure:Individual patient features were extracted from electronic health records and used to engineer nonpatient features, including interactions with HCWs and direct or indirect (consecutive room occupancy) patient contact. Main Outcomes and Measures:HOB was defined as a positive blood culture after the third day of hospitalization. Patients who were hospitalized for more than 3 days were considered at risk for the outcome. We developed 3 gradient boosting models: 2 predictive (with patient features only and with both patient and nonpatient features to predict the occurrence of HOB) and 1 causal to test the association of nonpatient features and HOB. Predictive performance is reported using area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUPRC), and the results of the causal model are reported as difference in average effects. Sensitivity analyses separated intensive care unit-onset and ward-onset HOB and included a methicillin-resistant Staphylococcus aureus-specific model to adjust for colonization pressure. Results:Among the 52 442 patients, 34 855 (66.5%) had admissions longer than 72 hours and were included for analysis; of these, 556 (1.6%) developed HOB. The median age for the included patients was 60 (IQR, 44-70) years, 50.5% were female, and obesity was the most frequent comorbidity (25.0%). Nonpatient features, such as a prior occupant of the same room receiving antipseudomonal beta-lactams and the mean number of HCWs per day for the 7 days preceding HOB, improved the model's performance (AUROC, 0.88 [95% CI, 0.88-0.89]; AUPRC, 0.20 [95% CI, 0.20-0.22]) compared with the patient-only model (AUROC, 0.85 [95% CI, 0.85-0.86]; AUPRC, 0.13 [95% CI, 0.12-0.14]) (P < .001). These 2 features were also associated with a higher likelihood of HOB in the causal gradient boosting model. Conclusions and Relevance:These findings suggest that nonindividual patient features may contribute to a comprehensive analysis of HOB when integrated with individual patient features in a machine learning model.

Background Urinary tract infections (UTI) affect approximately 250 million people annually worldwide. Patients often experience a cycle of antimicrobial treatment and recurrent UTI (rUTI) that is thought to be facilitated by a gut reservoir of uropathogenic Escherichia coli (UPEC). Methods 125 patients with UTI caused by an antibiotic-resistant organism (ARO) were enrolled from July 2016 to May 2019 in a longitudinal, multi -center cohort study. Multivariate statistical models were used to assess the relationship between uropathogen colonization and recurrent UTI (rUTI), controlling for clinical characteristics. 644 stool samples and 895 UPEC isolates were interrogated for taxonomic composition, antimicrobial resistance genes, and phenotypic resistance. Cohort UTI gut microbiome pro fi les were compared against published healthy and UTI reference microbiomes, as well as assessed within-cohort for timepoint- and recurrence-speci fi c differences. Findings Risk of rUTI was not independently associated with clinical characteristics. The UTI gut microbiome was distinct from healthy reference microbiomes in both taxonomic composition and antimicrobial resistance gene (ARG) burden, with 11 differentially abundant taxa at the genus level. rUTI and non-rUTI gut microbiomes in the cohort did not generally differ, but gut microbiomes from urinary tract colonized patients were elevated in E. coli abundance 7 - 14 days post-antimicrobial treatment. Corresponding UPEC gut isolates from urinary tract colonizing lineages showed elevated phenotypic resistance against 11 of 23 tested drugs compared to noncolonizing lineages. Interpretation The gut microbiome is implicated in UPEC urinary tract colonization during rUTI, serving as an ARGenriched reservoir for UPEC. UPEC can asymptomatically colonize the gut and urinary tract, and post-antimicrobial blooms of gut E. coli among urinary tract colonized patients suggest that cross -habitat migration of UPEC is an important mechanism of rUTI. Thus, treatment duration and UPEC populations in both the urinary and gastrointestinal tract should be considered in treating rUTI and developing novel therapeutics. Copyright (c) 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY -NC -ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Copyright (c) 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY -NC -ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Importance:The results of prediction models that stratify patients with sepsis and risk of resistant gram-negative bacilli (GNB) infections inform treatment guidelines. However, these models do not extrapolate well across hospitals. Objective:To assess whether patient case mix and local prevalence rates of resistance contributed to the variable performance of a general risk stratification GNB sepsis model for community-onset and hospital-onset sepsis across hospitals. Design, Setting, and Participants:This was a retrospective cohort study conducted from January 2016 and October 2021. Adult patients with sepsis at 10 acute-care hospitals in rural and urban areas across Missouri and Illinois were included. Inclusion criteria were blood cultures indicating sepsis, having received 4 days of antibiotic treatment, and having organ dysfunction (vasopressor use, mechanical ventilation, increased creatinine or bilirubin levels, and thrombocytopenia). Analyses were completed in April 2024. Exposure:The model included demographic characteristics, comorbidities, vital signs, laboratory values, procedures, and medications administered. Main Outcomes and Measures:Culture results were stratified for ceftriaxone-susceptible GNB (SS), ceftriaxone-resistant but cefepime-susceptible GNB (RS), and ceftriaxone- and cefepime-resistant GNB (RR). Negative cultures and other pathogens were labeled SS. Deep learning models were developed separately for community-onset (patient presented with sepsis) and hospital-onset (sepsis developed ≥48 hours after admission) sepsis. The models were tested across hospitals and patient subgroups. Models were assessed using area under the receiver operating characteristic curve (AUROC) and area under precision recall curve (AUPRC). Results:A total of 39 893 patients with 85 238 sepsis episodes (43 207 [50.7%] community onset; 42 031 [48.3%] hospital onset) were included. Median (IQR) age was 65 (54-74) years, 21 241 patients (53.2%) were male, and 18 830 (47.2%) had a previous episode of sepsis. RS contributed to 3.9% (1667 episodes) and 5.7% (2389 episodes) of community-onset and hospital-onset sepsis episodes, respectively, and RR contributed to 1.8% (796 episodes) and 3.9% (1626 episodes), respectively. Previous infections and exposure to antibiotics were associated with the risk of resistant GNB. For example, in community-onset sepsis, 375 RR episodes (47.1%), 420 RS episodes (25.2%) and 3483 of 40 744 (8.5%) SS episodes were among patients with resistance to antimicrobial drugs (P < .001). The AUROC and AUPRC results varied across hospitals and patient subgroups for both community-onset and hospital-onset sepsis. AUPRC values correlated with the prevalence rates of resistant GNB (R = 0.79; P = .001). Conclusions and Relevance:In this cohort study of 39 893 patients with sepsis, variable model performance was associated with prevalence rates of antimicrobial resistance rather than patient case mix. This variability suggests caution is needed when using generalized models for predicting resistant GNB etiologies in sepsis.

Objective: To measure SARS-CoV-2 anti-nucleocapsid (anti-N) antibody seropositivity among healthcare personnel (HCP) without a history of COVID-19 and to identify HCP characteristics associated with seropositivity.Design: Prospective cohort study from September 22, 2020, to March 3, 2022.Setting: A tertiary care academic medical center.Participants: 727 HCP without prior positive SARS-CoV-2 PCR testing were enrolled; 559 HCP successfully completed follow-up.Methods: At enrollment and follow-up 1-6 months later, HCP underwent SARS-CoV-2 anti-N testing and were surveyed on demographics, employment information, vaccination status, and COVID-19 symptoms and exposures.Results: Of 727 HCP enrolled, 27 (3.7%) had a positive SARS-CoV-2 anti-N test at enrollment. Seropositive HCPs were more likely to have a household exposure to COVID-19 in the past 30 days (OR 7.92, 95% CI 2.44-25.73), to have had an illness thought to be COVID-19 (4.31, 1.94-9.57), or to work with COVID-19 patients more than half the time (2.09, 0.94-4.77). Among 559 HCP who followed-up, 52 (9.3%) had a positive SARS-CoV-2 anti-N antibody test result. Seropositivity at follow-up was associated with community/household exposures to COVID-19 within the past 30 days (9.50, 5.02-17.96; 2.90, 1.31-6.44), having an illness thought to be COVID-19 (8.24, 4.44-15.29), and working with COVID-19 patients more than half the time (1.50, 0.80-2.78).Conclusions: Among HCP without prior positive SARS-CoV-2 testing, SARS-CoV-2 anti-N seropositivity was comparable to that of the general population and was associated with COVID-19 symptomatology and both occupational and non-occupational exposures to COVID-19.

Background:Sepsis is a major cause of morbidity and mortality worldwide. When selecting empiric antibiotics for sepsis, clinicians are encouraged to use local resistance rates, but their impact on individual outcomes is unknown. Improved methods to predict outcomes are needed to optimize treatment selection and improve antibiotic stewardship.Methods:We expanded on a previously developed theoretical model to estimate the excess risk of death in gram-negative bacilli (GNB) sepsis due to discordant antibiotics using 3 factors: the prevalence of GNB in sepsis, the rate of antibiotic resistance in GNB, and the mortality difference between discordant and concordant antibiotic treatments. We focused on ceftriaxone, cefepime, and meropenem as the anti-GNB treatment backbone in sepsis, pneumonia, and urinary tract infections. We analyzed both publicly available data and data from a large urban hospital.Results:Publicly available data were weighted toward culture-positive cases. Excess risk of death with discordant antibiotics was highest in septic shock and pneumonia. In septic shock, excess risk of death was 4.53% (95% confidence interval [CI], 4.04%-5.01%), 0.6% (95% CI, .55%-.66%), and 0.19% (95% CI, .16%-.21%) when considering resistance to ceftriaxone, cefepime, and meropenem, respectively. Results were similar in pneumonia. Local data, which included culture-negative cases, showed an excess risk of death in septic shock of 0.75% (95% CI, .57%-.93%) for treatment with discordant antibiotics in ceftriaxone-resistant infections and 0.18% (95% CI, .16%-.21%) for cefepime-resistant infections.Conclusions:Estimating the excess risk of death for specific sepsis phenotypes in the context of local resistance rates, rather than relying on population resistance data, may be more informative in deciding empiric antibiotics in GNB infections.

Contact tracing is a powerful tool for mitigating the spread of COVID-19 during the pandemic. Front-line healthcare workers are particularly at high risk of infection in hospital units. This paper presents ContAct TraCing for Hospitals (CATCH), an automated contact tracing system designed specifically for healthcare workers in hospital environments. CATCH employs distributed embedded devices placed throughout a hospital unit to detect close contacts among healthcare workers wearing Bluetooth Low Energy (BLE) beacons. We first identify a set of distinct contact tracing scenarios based on the diverse environmental characteristics of a real-world intensive care unit (ICU) and the different working patterns of healthcare workers in different spaces within the unit. We then develop a suite of novel contact tracing methods tailored for each scenario. CATCH has been deployed and evaluated in the ICU of a major medical center, demonstrating superior accuracy in contact tracing over existing approaches through a wide range of experiments. Furthermore, the real-world case study highlights the effectiveness and efficiency of CATCH compared to standard contact tracing practices.

Background SARS-CoV-2 vaccines are effective at reducing symptomatic and asymptomatic COVID-19. Limited studies have compared symptoms, threshold cycle (Ct) values from reverse transcription (RT)-PCR testing, and serological testing results between previously vaccinated vs unvaccinated populations with SARS-CoV-2 infection. Methods Healthcare personnel (HCP) with a positive SARS-CoV-2 RT-PCR test within the previous 14 to 28 days completed surveys including questions about demographics, medical conditions, social factors, and symptoms of COVID-19. Ct values were observed, and serological testing was performed for anti-nucleocapsid (anti-N) and anti-Spike (anti-S) antibodies at enrollment and 40 to 90 days later. Serological results were compared to HCP with no known SARS-CoV-2 infection and negative anti-N testing. Results There were 104 unvaccinated/not fully vaccinated and 77 vaccinated HCP with 2 doses of an mRNA vaccine at time of infection. No differences in type or duration of symptoms were reported (P = 0.45). The median (interquartile range [IQR]) Ct was 21.4 (17.6-24.6) and 21.5 (18.1-24.6) for the unvaccinated and vaccinated HCP, respectively. Higher anti-N IgG was observed in unvaccinated HCP (5.08 S/CO, 3.08-6.92) than vaccinated (3.61 signal to cutoff ratio [S/CO], 2.16-5.05). Anti-S IgG was highest among vaccinated HCP with infection (34 285 aribitrary units [AU]/mL, 17 672-61 775), followed by vaccinated HCP with no prior infection (1452 AU/mL, 791-2943), then unvaccinated HCP with infection (829 AU/mL, 290-1555). Anti-S IgG decreased 1.56% (0.9%-1.79%) per day in unvaccinated and 0.38% (0.03%-0.94%) in vaccinated HCP. Conclusions Vaccinated HCP infected with SARS-CoV-2 reported comparable symptoms and had similar Ct values relative to unvaccinated. However, vaccinated HCP had increased and prolonged anti-S and decreased anti-N response relative to unvaccinated.

Background: Healthcare personnel (HCP) working in non–acute-care facilities are at high risk of COVID-19. We sought to determine SARS-CoV-2 seroprevalence, and analyzed behaviors and activities related to COVID-19 acquisition in this cohort. Methods: Between May and June 2021, HCP were enrolled at a skilled nursing facility and a memory care facility in St. Louis, Missouri. Data regarding demographics, prior SARS-CoV-2 testing, symptoms consistent with COVID-19 in the previous 6 months, COVID-19 vaccination, personal protective equipment (PPE) use, and COVID-19 exposures were collected via survey. Blood specimens were obtained to determine SARS-CoV-2 nucleocapsid IgG antibody seroprevalence (Abbott Laboratories). Study protocol was approved by the Washington University Institutional Review Board. Results: The survey was completed by 74 HCP. 82% of participants were female, and 31% reported >10 years of healthcare experience. The overall SARS-CoV-2 seropositivity rate was 8.9% (5 HCP). Of the surveyed HCP, 50% reported symptoms concerning for COVID-19 in the prior 6 months. Headache (38%), fatigue (35%) and fever (27%) were the most common self-reported symptoms. Among symptomatic HCP, only 35% sought medical care for these symptoms. All HCP reported having taken at least 1 COVID-19 test prior to study enrollment. Of note, 18.9% (14 HCP) had a self-reported prior positive SARS-CoV-2 PCR test, of whom 9 HCP were seronegative. All seronegative HCP with a self-reported history of COVID-19 reported infection >3 months before study participation. Completion of a primary COVID-19 vaccination series was reported by 86% of HCP. Known exposure to COVID-19 at work was reported by 28% of HCP. When asked about PPE at the time of workplace exposure, N95 mask use was reported by 81%, gloves by 57%, gowns by 33%, face shields by 29% and surgical masks by 14%. Known specific exposure to COVID-19 outside work was reported by 31% of HCP. Conclusions: One year after the initial COVID-19 pandemic impacted the St. Louis region, HCP at non–acute-care facilities had a SARS-CoV-2 seroprevalence of 8.9%. Similar frequency of exposures were reported from both the workplace and community, with high rates of PPE use at the workplace. HCP in such settings remain at high risk of COVID-19 exposure from workplace and community exposures. Ongoing efforts are needed to maintain PPE use to prevent SARS-CoV-2 transmission within non–acute-care facilities, and continue access to timely COVID-19 screening for HCP.Disclosure: None

Objectives: Aminoglycosides and & beta;-lactams have been recommended for treatment of sepsis/septic shock despite a lack of mortality benefit. Previous studies have examined resistance emergence for the same bacterial isolate using old dosing regimens and during a narrow follow-up window. We hypothesised that combination regimens employing aminoglycosides will decrease the cumulative incidence of infections due to multidrug-resistant (MDR) Gram-negative bacilli (GNB) compared with & beta;-lactams alone.Methods: All adult patients admitted to Barnes Jewish Hospital between 2010 and 2017 with a diagnosis of sepsis/septic shock were included in this retrospective cohort study. Patients were divided into two treatment groups, with and without aminoglycosides. Patient demographics, severity of presentation, administered antibiotics, follow-up cultures with susceptibility results for a period of 4-60 days, and mortality were extracted. After propensity score matching, a Fine-Gray subdistribution proportional hazards model summarised the estimated incidence of subsequent infections with MDR-GNB in the presence of all-cause death as a competing risk.Results: A total of 10 212 septic patients were included, with 1996 (19.5%) treated with at least two antimicrobials including one aminoglycoside. After propensity score matching, the cumulative incidence of MDR-GNB infections between 4-60 days was lower in the combination group (incidence at 60 days 0.073, 95% CI 0.062-0.085) versus patients not receiving aminoglycosides (0.116, 95% CI 0.102-0.130). Patients aged & LE;65 years and with haematological malignancies had a larger treatment effect in subgroup analyses.Conclusion: Addition of aminoglycosides to & beta;-lactams may protect against subsequent infections due to MDR-GNB in patients with sepsis/septic shock.& COPY; 2023 Published by Elsevier Ltd.

To improve contact tracing for healthcare workers, we built and configured a Bluetooth low-energy system. We predicted close contacts with great accuracy and provided an additional contact yield of 14.8%. This system would decrease the effective reproduction number by 56% and would unnecessarily quarantine 0.74% of employees weekly.

Abstract Objective: To determine the prevalence of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) IgG nucleocapsid (N) antibodies among healthcare personnel (HCP) with no prior history of COVID-19 and to identify factors associated with seropositivity. Design: Prospective cohort study. Setting: An academic, tertiary-care hospital in St. Louis, Missouri. Participants: The study included 400 HCP aged ≥18 years who potentially worked with coronavirus disease 2019 (COVID-19) patients and had no known history of COVID-19; 309 of these HCP also completed a follow-up visit 70–160 days after enrollment. Enrollment visits took place between September and December 2020. Follow-up visits took place between December 2020 and April 2021. Methods: At each study visit, participants underwent SARS-CoV-2 IgG N-antibody testing using the Abbott SARS-CoV-2 IgG assay and completed a survey providing information about demographics, job characteristics, comorbidities, symptoms, and potential SARS-CoV-2 exposures. Results: Participants were predominately women (64%) and white (79%), with median age of 34.5 years (interquartile range [IQR], 30–45). Among the 400 HCP, 18 (4.5%) were seropositive for IgG N-antibodies at enrollment. Also, 34 (11.0%) of 309 were seropositive at follow-up. HCP who reported having a household contact with COVID-19 had greater likelihood of seropositivity at both enrollment and at follow-up. Conclusions: In this cohort of HCP during the first wave of the COVID-19 pandemic, ∼1 in 20 had serological evidence of prior, undocumented SARS-CoV-2 infection at enrollment. Having a household contact with COVID-19 was associated with seropositivity.

BACKGROUND:A greater proportion of patients with surgical risk factors are undergoing immediate breast reconstruction after mastectomy, resulting in the need for better risk prediction to inform decisions about the procedure. The objective of this study was to leverage clinical data to restructure a previously developed risk model to predict serious infectious and noninfectious wound complications after mastectomy alone and mastectomy plus immediate reconstruction for use during a surgical consultation. METHODS:The study established a cohort of women age 21 years or older treated with mastectomy from 1 July 2010 to 31 December 2015 using electronic health records from two hospitals. Serious infectious and non-infectious wound complications, defined as surgical-site infection, dehiscence, tissue necrosis, fat necrosis requiring hospitalization, or surgical treatment, were identified within 180 days after surgery. Risk factors for serious wound complications were determined using modified Poisson regression, with discrimination and calibration measures. Bootstrap validation was performed to correct for overfitting. RESULTS:Among 2159 mastectomy procedures, 1410 (65.3%) included immediate implant or flap reconstruction. Serious wound complications were identified after 237 (16.8%) mastectomy-plus-reconstruction and 30 (4.0%) mastectomy-only procedures. Independent risk factors for serious wound complications included immediate reconstruction, bilateral mastectomy, higher body mass index, depression, and smoking. The optimism-corrected C statistic of the risk prediction model was 0.735. CONCLUSIONS:Immediate reconstruction, bilateral mastectomy, obesity, depression, and smoking were significant risk factors for serious wound complications in this population of women undergoing mastectomy. Our risk prediction model can be used to counsel women before surgery concerning their individual risk of serious wound complications after mastectomy.

Large-scale genomic studies have identified within-host adaptation as a hallmark of bacterial infections. However, the impact of physiological, metabolic, and immunological differences between distinct niches on the pathoadaptation of opportunistic pathogens remains elusive. Here, we profile the within-host adaptation and evolutionary trajectories of 976 isolates representing 119 lineages of uropathogenic Escherichia coli (UPEC) sampled longitudinally from both the gastrointestinal and urinary tracts of 123 patients with urinary tract infections. We show that lineages persisting in both niches within a patient exhibit increased allelic diversity. Habitat-specific selection results in niche-specific adaptive mutations and genes, putatively mediating fitness in either environment. Within-lineage inter-habitat genomic plasticity mediated by mobile genetic elements (MGEs) provides the opportunistic pathogen with a mechanism to adapt to the physiological conditions of either habitat, and reduced MGE richness is associated with recurrence in gut-adapted UPEC lineages. Collectively, our results establish niche-specific adaptation as a driver of UPEC within-host evolution.

Abstract In this prospective, longitudinal study, we examined the risk factors for severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection among a cohort of chronic hemodialysis (HD) patients and healthcare personnel (HCPs) over a 6-month period. The risk of SARS-CoV-2 infection among HD patients and HCPs was consistently associated with a household member having SARS-CoV-2 infection.

Abstract Objective: Patients on dialysis are at high risk for severe COVID-19 and associated morbidity and mortality. We examined the humoral response to SARS-CoV-2 mRNA vaccine BNT162b2 in a maintenance dialysis population. Design: Single-center cohort study. Setting and participants: Adult maintenance dialysis patients at 3 outpatient dialysis units of a large academic center. Methods: Participants were vaccinated with 2 doses of BNT162b2, 3 weeks apart. We assessed anti–SARS-CoV-2 spike antibodies (anti-S) ∼4–7 weeks after the second dose and evaluated risk factors associated with insufficient response. Definitions of antibody response are as follows: nonresponse (anti-S level, <50 AU/mL), low response (anti-S level, 50–839 AU/mL), and sufficient response (anti-S level, ≥840 AU/mL). Results: Among the 173 participants who received 2 vaccine doses, the median age was 60 years (range, 28–88), 53.2% were men, 85% were of Black race, 86% were on in-center hemodialysis and 14% were on peritoneal dialysis. Also, 7 participants (4%) had no response, 27 (15.6%) had a low response, and 139 (80.3%) had a sufficient antibody response. In multivariable analysis, factors significantly associated with insufficient antibody response included end-stage renal disease comorbidity index score ≥5 and absence of prior hepatitis B vaccination response. Conclusions: Although most of our study participants seroconverted after 2 doses of BNT162b2, 20% of our cohort did not achieve sufficient humoral response. Our findings demonstrate the urgent need for a more effective vaccine strategy in this high-risk patient population and highlight the importance of ongoing preventative measures until protective immunity is achieved.

Objective: To identify characteristics associated with positive severe acute respiratory coronavirus virus 2 (SARS-CoV-2) polymerase chain reaction (PCR) tests in healthcare personnel. Design: Retrospective cohort study. Setting: A multihospital healthcare system. Participants: Employees who reported SARS-CoV-2 exposures and/or symptoms of coronavirus disease 2019 (COVID-19) between March 30, 2020, and September 20, 2020, and were subsequently referred for SARS-CoV-2 PCR testing. Methods: Data from exposure and/or symptom reports were linked to the corresponding SARS-CoV-2 PCR test result. Employee demographic characteristics, occupational characteristics, SARS-CoV-2 exposure history, and symptoms were evaluated as potential risk factors for having a positive SARS-CoV-2 PCR test. Results: Among 6,289 employees who received SARS-CoV-2 PCR testing, 873 (14%) had a positive test. Independent risk factors for a positive PCR included: working in a patient care area (relative risk [RR], 1.82; 95% confidence interval [CI], 1.37-2.40), having a known SARS-CoV-2 exposure (RR, 1.20; 95% CI, 1.04-1.37), reporting a community versus an occupational exposure (RR, 1.87; 95% CI, 1.49-2.34), and having an infected household contact (RR, 2.47; 95% CI, 2.11-2.89). Nearly all HCP (99%) reported symptoms. Symptoms associated with a positive PCR in a multivariable analysis included loss of sense of smell (RR, 2.60; 95% CI, 2.09-3.24) or taste (RR, 1.75; 95% CI, 1.40-2.20), cough (RR, 1.95; 95% CI, 1.40-2.20), fever, and muscle aches. Conclusions: In this cohort of >6,000 healthcare system and academic medical center employees early in the pandemic, community exposures, and particularly household exposures, were associated with greater risk of SARS-CoV-2 infection than occupational exposures. This work highlights the importance of COVID-19 prevention in the community and in healthcare settings to prevent COVID-19.

Immunocompromised adults can have prolonged acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive RT-PCR results, long after the initial diagnosis of coronavirus disease 2019 (COVID-19). This study aimed to determine if SARS-CoV-2 virus can be recovered in viral cell culture from immunocompromised adults with persistently positive SARS-CoV-2 RT-PCR tests. We obtained 20 remnant SARS-CoV-2 PCR positive nasopharyngeal swabs from 20 immunocompromised adults with a positive RT-PCR test ≥14 days after the initial positive test. The patients' 2nd test samples underwent SARS-CoV-2 antigen testing, and culture with Vero-hACE2-TMPRSS2 cells. Viral RNA and cultivable virus were recovered from the cultured cells after qRT-PCR and plaque assays. Of 20 patients, 10 (50%) had a solid organ transplant and 5 (25%) had a hematologic malignancy. For most patients, RT-PCR Ct values increased over time. There were 2 patients with positive viral cell cultures; one patient had chronic lymphocytic leukemia treated with venetoclax and obinutuzumab who had a low viral titer of 27 PFU/mL. The second patient had marginal zone lymphoma treated with bendamustine and rituximab who had a high viral titer of 2 x 106 PFU/mL. Most samples collected ≥7 days after an initial positive SARS-CoV-2 RT-PCR had negative viral cell cultures. The 2 patients with positive viral cell cultures had hematologic malignancies treated with chemotherapy and B cell depleting therapy. One patient had a high concentration titer of cultivable virus. Further data are needed to determine risk factors for persistent viral shedding and methods to prevent SARS-CoV-2 transmission from immunocompromised hosts.

Abstract Background COVID-19 rapidly evolved into a global pandemic. Contact tracing with isolation and quarantine contribute to epidemic control but they are time consuming, costly and may be incomplete. We set out to assess the usability and performance characteristics of Bluetooth Low-Energy (BLE) wireless technology for indoor localization applied to contact tracing in healthcare settings. Methods Consented healthcare workers (HCW) from 2 designated COVID-19 wards (one intensive care unit (ICU) and one medical ward) were equipped with coin-sized BLE- emitting beacons. The signal was captured by small embedded computers (anchors) placed at designated locations, time-stamped and transmitted to an edge server via secure Wi-Fi where data were stored and real time contact algorithms were run (Fig.1). We developed experiments mimicking clinical scenarios and tested indoor localization during observed clinical activity for 6 months. We constructed our algorithms based on room structure (e.g. open spaces vs computer rooms) and activity characteristics (e.g. rounding in a large group vs 2 healthcare workers sitting together). We used 1) radio fingerprint localization where an initial virtual radio map was developed, 2) semantic localization which carries additional information such as proximity to a computer to define indirect transmission via fomites, and 3) clustering contact tracing to identify individuals rounding together. Close contact was defined as per the CDC guidelines. Fig. 1System configuration Results Consent rate was 43.3% with 187 HCW enrolled in the study. Consent rate was higher in the ICU and among attendings. All participants were compliant with wearing the beacons for the duration of the study. The performance characteristics for contact tracing using fingerprinting methods were AUROC 0.93, AUPRC 0.96, sensitivity 0.9, specificity 0.77 with F1 score of 0.89 and overall accuracy of 0.85. The clustering contact tracing registered a sensitivity of 0.86, specificity 0.89, F1 score 0.91 and accuracy 0.87. Computation time necessary to generate a list of close contacts as per specified criteria was less than 30 minutes. Conclusion We have developed and tested a reliable and accurate, low-cost and easily deployable system based on BLE technology to improve contact tracing among healthcare workers. Disclosures M Cristina Vazquez Guillamet, MD, AUPH: Stocks/Bonds|BNGO: Stocks/Bonds|OCGN: Stocks/Bonds|SESN: Stocks/Bonds.